Influential factors and classification of cultivated land ...

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Land Use Policy

journal homepage: www.elsevier.com/locate/landusepol

Influential factors and classification of cultivated land fragmentation, andimplications for future land consolidation: A case study of Jiangsu Provincein eastern China

Jing Liua,b, Xiaobin Jina,b,c,⁎, Weiyi Xua,b, Rui Suna,b, Bo Hana,b, Xuhong Yanga,b,c,Zhengming Gua,b, Cuilan Xud, Xueyan Suid, Yinkang Zhoua,b,c

a School of Geography and Ocean Science, Nanjing University, 163 Xianlin Avenue, Qixia District, Nanjing, 210023, Chinab Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Land and Resources, 163 Xianlin Avenue, Qixia District, Nanjing, 210023, ChinacNatural Resources Research Center, 163 Xianlin Avenue, Qixia District, Nanjing University, Nanjing, 210023, Chinad Jiangsu Province Land Development and Consolidation Center, 58 Shuiximen Street, Jianye District, Nanjing, 210024, China

A R T I C L E I N F O

Keywords:Cultivated land fragmentationRegional differentiationInfluential factorsClassificationLand consolidationJiangsu Province

A B S T R A C T

Cultivated land fragmentation (CLF) is one of the main obstacles hindering the development of agriculturalmodernization and mechanization. Systematically exploring the general distribution characteristics, influentialfactors and classification of CLF are of great significance for improving regional agricultural production capacity,promoting resource conservation and intensive use, and ensuring national food security, especially at the re-gional scale. In this study, we established a new conceptual index system using multivariable linear regression,geographical detectors, and magic cube model for CLF assessment as well as an analysis of the spatial differ-entiation characteristics, driving mechanism and management zoning trade-off of CLF in Jiangsu Province ineastern China based on multi-source data characterizing geographic, land-use and socio-economic information.The results showed that the connotation of CLF has spatial-scale characteristics due to the differences in func-tions positioning of cultivated land resources in macro-social security and micro-livelihood maintenance. At thenational/regional scale, CLF mainly covers the natural (resource), spatial and utilization attributes of cultivatedland. Based on this, the CLFI in Jiangsu presents a spatial pattern that gradually increases from north to south,with significant spatial differences. Besides, the CLFI within built-up areas is significantly higher than thatoutside built-up areas, and its fractal dimensions both within and outside the urban planning built-up areas showthe spatial pattern of "spatial distribution > resource endowment > convenience of utilization". Furthermore,average plot size, the proportion of industry and service industry, gross domestic product, slope, grain output,and plot distance from town are the dominant factors driving the spatial differentiation of CLF, with the in-fluence power (q) is 0.472, 0.204, 0.133, 0.129, 0.097 and 0.084, respectively. Location conditions and socio-economic activities have significant effects on the spatial differentiation of CLF within the built-up areas whilehighlighting the role of rural settlements outside urban built-up areas on CLF. Finally, we propose a two-levelzoning system for diminishing the CLF and optimizing the utilization of cultivated land resources in Jiangsubased on influencing factors and fragmentation characteristics. The findings of this study will assist the gov-ernment in developing appropriate regional context and land consolidation policies and coping strategies to CLFand food insecurity issues, and achieve sustainable development goals.

1. Introduction

More than half of the world's population (54%) currently lives inurban areas, and this proportion is expected to grow to 66% by 2050(Masini et al., 2018). The rising population expects 70% higher foodproduction (by the year 2050) and more sustainable land management

(Looga et al., 2018), which also implies that maximization of the pro-vision of products and services for human's increasing food demandsrequires more rational and effective utilization of the finite global landarea and natural resources.

Cultivated land fragmentation (CLF) is a common agrarian featureof many transition economies as well as developing countries (Niroula

https://doi.org/10.1016/j.landusepol.2019.104185Received 14 April 2019; Received in revised form 11 August 2019; Accepted 27 August 2019

⁎ Corresponding authors at: School of Geography and Ocean Science, Nanjing University, 163 Xianlin Avenue, Qixia District, Nanjing, 210023, China.E-mail addresses: [email protected] (J. Liu), [email protected] (X. Jin).

Land Use Policy 88 (2019) 104185

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and Thapa, 2007; Falco et al., 2010). CLF has become a critical factor inensuring food security and sustainability of land resources in East Asia(Qi and Dang, 2018), especially for China where per capita cultivatedland is only 0.08 ha, far below the global average of 0.20 ha per capita(Du et al., 2018; Jin et al., 2017). As a prominent feature in traditionalagricultural production in China, CLF not only enriches productiondiversification, reduces agricultural production risks, and increasesfarmers' income, but also causes a number of negative influences in-cluding reducing the efficiency of agricultural production, wasting theworkforce in rural areas and improving production costs (Falco et al.,2010), and then becomes a critical damper to China's agriculturalmodernization and scale development (Sun and Liu, 2010). Studieshave shown that China's CLF wastes about 3%–10% of the effectiveagricultural land area (Zhang et al., 1997), increases labor costs per tonof grain production by 115 yuan and reduces land productivity by15.3% (Bai et al., 2014). Meanwhile, the annual output of tuber cropsand wheat decreased by 9.8% and 6.5% respectively for each additionalplot (Wan and Cheng, 2001).

To further alleviate the negative influences of CLF, the Chinesegovernment has focused on CLF control and management in recentyears. The No.1 Document of the Central Committee put forward themacro-strategic plan of "accelerating the development of land circula-tion and actively developing moderate-scale management" in 2017,marking a new era of transformation and development of China's tra-ditional agricultural production into the scale, intensive and modernagriculture. As important land management and remediation instru-ment, land consolidation (LC) has been shown to effectively tackle theCLF problem and promote agricultural modernization in many coun-tries across the world (FAO, 2004; Hartvigsen, 2015). The dominantdiscourse is that fragmented land ownership and land use tend to beineffective and unwanted, and LC is then a solution to this quandary(Ntihinyurwa et al., 2019). Despite the close correlation between CLFand LC, little attention has been paid to the differences in regionalpatterns and directions of LC affected by regional differences of CLF andits influential factors, which thereby leading to the spatial mismatchbetween LC practices and characteristics of arable land resources tosome extent, especially at the regional scale. With the new goal ofarable land protection of "quantity-quality-ecology", the aims of the LCare shifting toward the integrated goals of increasing cropland, redu-cing fragmentation, improving agriculture infrastructure, promotingagricultural productivity, and improving environmental quality (Duet al., 2018). If this is the case, LC policies may focus on the regionalendowment difference and fragmentation of cultivated land resources,including characteristics of scale, spatial pattern, and infrastructureconditions. Therefore, based on the deep understanding of the char-acteristics of CLF's spatial pattern, further excavation of the drivingmechanism and influential factors of CLF will provide practical supportfor LC practices to inform the policy-makers of more locally-adaptivedecisions.

Previous studies on CLF primarily have three foci. One focus is toexplore the connotation of CLF in terms of conceptual design (Sundqvistand Lisa, 2006; de Vries, 2016) and classification (Sklenicka et al.,2014). The second focus is to discuss the effects of CLF from the per-spectives of the governance of the commons (Qi and Dang, 2018; Zanget al., 2019), productivity (Sundqvist and Lisa, 2006; Looga et al.,2018), and production diversification (Sichoongwe et al., 2014; Ciaianet al., 2018). The third focus is to analyze the driving factors of CLF interms of cultural tradition (Bizimana et al., 2004; Hartvigsen, 2014),physical conditions (Ntihinyurwa et al., 2019), socio-economic (Kingand Burton, 1982), and land distribution (Sklenicka et al., 2014;Jürgenson, 2016). Generally speaking, the previous studies haveshowed three characteristics: (1) research perspective focuses on dis-persed land owners and dispersed plot locations; (2) research methodsare mainly based on theoretical analysis or qualitative description; (3)research scales are mostly concentrated on middle- or micro- scalessuch as towns (Sun and Liu, 2010), villages (Ciaian et al., 2018; Zang

et al., 2019), farms and households (Looga et al., 2018; Ntihinyurwaet al., 2019). While these studies work together to recognize the char-acteristics of cultivated land resources and greatly expanded thebreadth and depth of this topic, there is still a great room for im-provement in the following aspects due to limitations in technicalmethods and data acquisition:

(1) The connotation of CLF needs to be improved. The social securityfunction of cultivated land resources on macro-scale and the live-lihood maintenance function on a micro-scale determine that thecharacteristics of CLF vary significantly in different spatial scales(e.g., national, regional or local scales, household levels). Currently,the connotation of CLF mainly focuses on land property rights of thefarm, household, or individual levels. However, little attention hasbeen paid to understanding the effects of natural, spatial, and uti-lization properties of cultivated land resources on fragmentation,especially in the context of the spatial scales.

(2) Indicators for assessing CLF are limited. Although CLF is mostlyunderstood as a high number of farmed plots or as a high number ofplot co-owners (Ciaian et al., 2018), it is a more complex phe-nomenon. It includes the size distribution and shape of land plots,the spatial distribution, and number of parcels, the distances be-tween plots and their uses or locations (Sundqvist and Lisa, 2006;Latruffe and Piet, 2014). Because the quantification of several di-mensions of CLF simultaneously is challenging (Ciaian et al., 2018),most studies measure CLF only based on one aspect (e.g., landscapepatterns, the number of plots or their average size) (Sichoongweet al., 2014), thereby the expansibility of CLF assessment is rela-tively weak.

(3) The spatial scale of CLF associated with practical guidance needs tobe further expanded. Currently, the research on CLF is mostly fo-cused on micro-scale constrained by data acquisition from house-holds surveys. Even if there are some individual case studies fo-cusing on CLF across regions or countries (Niroula and Thapa,2005; Hartvigsen, 2014), to the best of our knowledge a compara-tive study guiding the optimal utilization of cultivated land re-sources and LC practices through the comprehensive measurementof spatial differences and influencing mechanisms of CLF based onmulti-source data is still missing.

To fill the gaps of existing CLF studies and the needs for sustainableLC practices, this paper presents an empirical case study of JiangsuProvince in eastern China. This study analyzes the spatial-scale char-acteristics of CLF from the perspective of spatial differences in func-tional positioning of cultivated land. Then, we construct a compre-hensive CLF evaluation index system, including natural, spatial, andutilization attributes of cultivated land resources. Next, based on Three-dimensional magic cube, Geographical detectors, and Multivariablelinear regression, the study analyzes the regional differences and in-fluential factors of CLF integrated with multi-source data that char-acterize geographic, land use, agricultural production, and socio-eco-nomic information. Finally, based on the above analysis, our studyproposes a zoning system for the management of CLF in JiangsuProvince based on the fusion of regional differences and influentialfactors of CLF to offer insights into CLF management and LC practicesimprovement.

The information derived from this analysis might not only be usedto support regional LC planning and policy-making, for example, toidentify the current cultivated land resources characteristics amongnatural, spatial and utilization attributes for tackling the problem ofCLF, but also has theoretical and practical significance for formulationof regional cultivated land utilization strategies to promote agriculturalmodernization and ensure food security.

J. Liu, et al. Land Use Policy 88 (2019) 104185

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2. Theoretical framework

2.1. Literature review

At present, there is no single commonly agreed definition of CLF(Ntihinyurwa et al., 2019). In this regard, Mcpherson (1982) definedCLF as a situation where household's land resources are divided amongseveral spatially separated plots; King and Burton (1982) characterizedCLF as a fundamental rural spatial problem whereby farms are poorlyorganized at different locations across space. Similarly, many authors(Sundqvist and Lisa, 2006; Hartvigsen, 2015; de Vries, 2016) con-sidered CLF as the scattering of farmland or farming household pos-sesses several non-contiguous land plots. Throughout the existing con-ceptual understanding of CLF, these conceptualizations focus howeveronly on dispersed land owners, the number of plots or dispersed plotlocations held by single owners without considering the variety in size,use, shape and other aspects of the respective plots (Demetriou et al.,2012; Ntihinyurwa et al., 2019). In fact, the forms and causes of CLFshould be linked with each of the characteristics of cultivated land,including the features of natural (resource) property, i.e., focusing onnatural endowment characteristics of cultivated land resources (such asits resource capacity, spatial distribution, soil qualities, size, patchnumbers and density, etc.); spatial property, i.e., emphasizing thelandscape pattern characteristics (such as the shapes of dispersed plots,their distance, agglomeration degree, and segmentation degree, etc.);utilization property, i.e., emphasizing the utilization conditions (such asits ownership, infrastructures construction, accessibility, etc.), andother aspects (King and Burton, 1982; Muchová, 2017). Since theircauses and effects on the utilization and management of cultivated landresources also vary from spatial-scale characteristics, which leads to thespatial-scale differences in CLF's management. However, most of theprevious studies ignore the impact of natural attribute, spatial pattern,and utilization attribute of arable land on CLF when analyzing thespatial forms and causes of CLF in general, which in turn leads to thedevelopment of broad and non-appropriate coping policies and strate-gies (Ntihinyurwa et al., 2019), especially at the national or regionallevels.

As for CLF measurement and its influential factors, CLF is re-presented by the number of plots and/or their average size in most ofthe researches mentioned above. However, these indices ignore criticalspatial variables such as plot shapes as well as non-spatial variables(Ciaian et al., 2018), for example, cultivated land production and uti-lization conditions, infrastructures construction and accessibility ofland parcels. Because they do not show all the information or dimen-sions related to CLF and may not capture all the constraints that CLFimposes on agricultural production system (Latruffe and Piet, 2014;Looga et al., 2018), and the influence mechanism of external (en-vironmental) factors other than the characteristics of cultivated land onCLF, in particular in terms of distance, socio-economic development,production and living conditions, land policies and land allocation,topography, and agricultural development. With the deepening of re-search endeavors, in addition to the above-mentioned sole variables,some scholars have gradually recognized the multi-dimensional struc-ture of CLF, and tried to characterize the information of CLF in distance,size, shape and dispersion of plots (Gonzalez et al., 2007), which wouldenrich the principles of CLF. However, those elaborate measures werenot tested on a regional scale or even a real sample of farms but insteadwere applied to a possible dataset (Latruffe and Piet, 2014).

CLF's measurement and its influence mechanism are the complexand vital issue (Looga et al., 2018), and have significant implications interms of food security, productivity improvement, rural development,agricultural modernization and sustainability of land resources (Qi andDang, 2018). In the context of the call to use resources and the en-vironment more efficiently and sustainably to attain the economies ofscale of cultivated land and promote sustainable development forhuman well-being, two questions arise: 1) what is the spatial-scale

characteristics of CLF from the perspective of spatial differences infunctional positioning of cultivated land? 2) how do we measure it?

2.2. Spatial-scale characteristics of CLF

Coping with this very complex issue needs a sound knowledge aboutthe level, forms, performances and causes of CLF along with all its ef-fects at different spatial scales, and the components of food security atboth national and household levels and their relationships(Ntihinyurwa et al., 2019). Because, the issue of CLF is connected to thedual attributes of resources and assets for social security and livelihoodmaintenance due to the spatial differences in functional orientation ofcultivated land, which has significant implications for resource utili-zation strategy and farmers' production choices both at national andhousehold levels.

Differences in the formation of cultivated land functions dominatedby top-down institutional supply and bottom-up market demands leadto its hierarchical and scale dependence (Song et al., 2014), to a certainextent, especially for different social groups (e.g., countries, states,governments, households, farmers, etc.). For the states or governments,cultivated land, as a precious and scarce natural resource, mainlypossesses the function of macro-social security, including maintainingsocial stability, ensuring food security, maintaining ecological securityand national economic contribution, etc.; while for households orfarmers, it serves as an essential asset for their survival and mainlyplays the role of micro-livelihood maintenance, such as basic livingsecurity, family economic contribution, and employment security.Therefore, the spatial hierarchy and scale differences of the cultivatedland function positioning (Jiang et al., 2011) determine that CLF is acomposite system (Fig. 1) that includes multi-scale (e,g., national scale,regional scale, household scale, etc.), multi-level (resource fragmenta-tion, spatial fragmentation, utilization fragmentation, ownership frag-mentation, etc.), multi-factor (resource endowments, spatial patterns,facilities construction, management and utilization, etc.), and then hasdifferences in guiding regional LC practices.

At the household/farmer scale, farmers are the basic productiondecision-making units to obtain agricultural products and improve in-come by working on cultivated land resources. Thus, the characteristicsof asset attributes, such as ownership status and economic output value,make cultivated land resources as the necessary material to accesseconomic benefits for farmers' survival and development. Farmers paymore attention to their livelihood maintenance function brought bycultivated land. Due to the diversification of farmers' production andlivelihood needs, the micro-scale of CLF is mainly characterized by theland ownership fragmentation in dispersed plots and the fragmentationof farmland utilization modes, which is mostly caused by institutionalrights factors such as land reforms, land policies, and economic pro-cesses (King and Burton, 1982; Bizimana et al., 2004). As such, CLFbased on micro-perspective can provide practical guidance for land usedecision-makers to inform field planning, facility layout, ownershipadjustment, and organization and implementation of LC projects.

At the national/regional scale, cultivated land resources, as an es-sential natural resource to promote agricultural development, play acrucial role in stabilizing grain production patterns, ensuring nationalfood security, and maintaining social stability, and possess multi-attri-butes of natural, spatial, and utilization (as noted in Section 2.1).However, the characteristics of natural property are more affected byfactors of topography, water, and soil matching patterns, and evennatural disasters, etc.; spatial property may be connected with the ele-ments such as spatial segmentation of linear features, e.g., rivers androads, and human activities; while utilization property may be mainlylinked with the level of regional socio-economic development and landuse patterns as well as facilities construction by the state. Based on this,the CLF at the regional scale mainly reflects the differences of resourceagglomeration, spatial distribution, and facilities construction, whichcan play a guiding role in deepening the understanding of locally


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problems in arable land utilization, implementing differentiated re-gional LC strategies, and identifying the key issues and solutions of LCaccordingly to diminish the CLF and realize the scale efficiency.

It is challenging to achieve scale management of cultivated land atthe household/farmer level under the constraints of scattered resources,large population, and scarce land resources. Because the resourcefragmentation of cultivated land is the basis for the ownership frag-mentation, and the ownership fragmentation is the further extension ofresource fragmentation. Therefore, as for the goal of promoting thedevelopment of large-scale and modern agriculture, it is urgent to givepriority to diminish the resource fragmentation at the national/regionalscale to further provide sufficient support for addressing the ownershipfragmentation at the household/farmer scale.

As a result, based on the above analysis, this study considers CLF atthe macro-scale as a situation where cultivated land in specific regionpossesses the comprehensive characteristics of insufficient resourcesendowment, spatial dispersion, and limited production and operation,which are mainly driven by the regional socio-economic development,production and living conditions, land distribution process, naturalenvironmental conditions, and agricultural development.

3. Materials and methods

3.1. Multidimensional evaluation of CLF

(1) Indicators for assessing CLF

Based on theoretical basis of land resources science, land economics,and landscape ecology (Liu, 2010; Li, 2015), our study proposes a newconceptual index system for CLF assessment at regional scale aiming atthe demands of "moderate-scale operation and intensive and efficientdevelopment" in national agricultural modernization developmentstrategy, with three dimensions of resource endowment, spatial dis-tribution, and convenience of utilization. The definitions and quanti-tative methods of the indexes are shown in Table 1.

(2) Calculating the CLF index

This study constructed the cultivated land fragmentation index(CLFI) with the standard value of "1-weighted linear sum of indicators"to consistent with evaluation meanings and experience and knowledge.The calculation method of CLFI is shown in formula 1.

∑ ∑= −= =( )CLFI I w w1

i

n

j

mij ij i1 1 (1)

Where, n denotes the number of dimensions; m represents the numberof indicators in dimension i; Wij represents the weight of the j-th in-dicator in i;Wi is the weight of dimension i; Iij is the normalized value ofthe indicator j in dimension i.

3.2. Analyzing the impact factors of CLF

(1) Influential factors of CLF and its basis

Cultivated land is a natural geography-socio-economic complex ofdynamic integration of topography, climate, hydrology, soil, plants aswell as human land-use behaviors and its impacts. As a result, culti-vated land utilization system (CLUS) is composed of endowment char-acteristics of cultivated land resources, regional natural environmentalconditions, and human socio-economic activities, where they interactand co-exist with each other to jointly promote the sustainable land useand serve social demands. Among them, as the critical productionfactors of CLUS, the endowment of cultivated land such as its scale andspatial distribution, is always linked to the volume of agriculture pro-duction and resource-supply capacity (Zhang et al., 2018) due to pro-viding the material basis and spatial carrier for human survival anddevelopment. In this process, the level of socio-economic development,production and living conditions, land distribution mechanism, andnatural environment characteristics are vital links and media of inter-action between resources endowment and CLUS external environment.Their spatial heterogeneity, to a certain extent, influences the ways ofutilization and development of cultivated land resources. CLF, as amultidimensional phenomenon in this interaction process, is

Fig. 1. Spatial-scale characteristics of CLF. The left and right blue circles respectively indicate the functional orientation of cultivated land at the national/regionalscale and the household/farmer scale. Gray arrows represent the dominant function of cultivated land resources for different social groups. Red arrows indicate themain contents of CLF at different spatial scales.


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highlighted with the mismatch between regional cultivated land re-sources and productivity development in terms of scale characteristics,spatial distribution patterns, etc. Its formation mechanism includes notonly the division of natural environmental factors, e.g., topography,rivers, but also human activities, e.g., land use, economic development.In summary, these factors can be broadly classified into five categoriesin view of CLUS and previous studies (Hartvigsen, 2014; Jürgenson,2016; Zang et al., 2019), namely, socio-economic development level,production and living conditions, land distribution process, naturalenvironmental conditions and agricultural development (Table 2).

(2) Multivariable linear regression

CLFI is used as the dependent variable and indicators in Table 2 asindependent variables. The general form of the multivariable linearregression equation is as follows:

= + + + + + + + +Y β β x β x β x β x β x u..... .....j j k k0 1 0 2 2 3 3 (2)

Where, Y is CLFI, the dependent variable; β0 is constant; k representsthe number of independent variables; βj represents the regressioncoefficient, and μ is a random error perturbation term subject to anormal distribution.

(3) Geographical detectors

A geographical detectors model (Wang et al., 2010) was im-plemented to analyze the impact magnitude of the major influencingfactors on CLFI, which was complementary to the multivariable linearregression method. Assuming that A={Ah, h=1, 2,…, L, where L is thefactor classification number} are the attributes associated with thegeographical stratum of a suspected CLFI, the power of the determinantA={Ah, h=1, 2, …, L} to CLFI is given by:

∑= −=

qnσ

n σ1 1

h

L

h h21

2

(3)

Where, nh is the number of samples in the sub-region h of the de-terminant Ah; n is the total number of samples of interest over the entireregion A; σ h

2 and σ2 indicate the dispersion variance of sub-region hand the entire region A, respectively. The range of q is [0,1]. A largervalue of q suggests more clear spatial differentiation of CLFI andstronger spatial determination of the independent variable xi to CLFI.

3.3. Trade-off judgment method for CLF zoning

First, we employ k-means clustering (Jain, 2010) to classify countiesinto several clusters to characterize CLF first-level zones based on thegeographic detection results of the major influencing factors on CLFI.Then, we use magic cube model (Ye et al., 2017) to construct the fra-mework for reflecting the spatial combination characteristics of CLFupon different dimensions, and finally, propose a two-level zoningsystem aiming at the management of CLF based on influencing factorsand fragmentation characteristics. More concretely, the three sides ofthe magic cube represent resource endowment (x), spatial distribution(y) and convenience of utilization (z) of cultivated land, respectively.We further divide x, y, and z into four grades (i.e., lowest, lower, higher,and highest with numbered 1, 2, 3, 4, respectively) by using "Mean±0.5× Standard Deviation" (Long et al., 2012). On this basis, 64 com-binations are merged by consulting relevant experts to minimizewithin-group variability and maximize its homogeneity, and the studyarea can be divided into several categories, such as the utilization ef-ficiency improvement zone, spatial intensive merging zone, facilityconstruction improvement zone, scale management and land circula-tion zone, resource allocation optimization zone, and comprehensiveimprovement zone. The conceptual model and classification standardsfor second-level zones of CLF are shown in Fig. 2 and Table 3,Ta

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Table 2Influential factors of CLF at regional scale.

Categories of influential factors Influential factors Variables' description Relationship with CLF

Socio-economic developmentlevel (SEDL)

Land use degree (x1) Reflecting the comprehensive status ofland resources utilization anddevelopment

With the improvement of SEDL, the expansion of construction landand the development of the transportation network will have somenegative impacts on the layout and shape of cultivated land

Gross domestic product(x2)

Reflecting the level of regional economicdevelopment

The proportion of industryand service industry (x3)

Reflecting the state of the regionalindustrial structure

Production and living conditions(PLC)

Plot distance from ruralsettlements (x4)

Indicating the interference degree ofcultivated land by human activities

PLC reflects the possibility of cultivated land being occupied byurban construction, the disturbance degree caused by humanactivities, the spatial segmentation degree of linear features and thesupport for large-scale and mechanized farming

Plot distance from town(x5)

Reflecting the possibility of cultivatedland being occupied by urbanconstruction

Plot distance from nearestwater system (x6)

Reflecting the chance of cultivated landbeing blocked or separated by linearfeatures

Average plot size (x7) Reflecting the support to agriculturalmechanization

Land distribution process (LDP) Per capita cultivated landarea (x8)

Reflecting the endowment status ofcultivated land resources

LDP, determined by factors such as cultivated land quality, size,distance, environment, and location, is closely linked with CLF

Cultivated land quality (x9) Reflecting the quality difference ofregional cultivated land resources

Natural environmentalconditions (NEC)

Slope (x10) Reflecting the surface steepness ofregional cultivated land resources

The slope is the essential elements reflecting the regional topographiccharacteristics, while water network density indicates the divisiondegree of cultivated land by rivers, lakes, etc. They are essentialnatural environmental factors for the formation of CLF

Water network density(x11)

Reflecting the division degree ofcultivated land by rivers, lakes, etc.

Agricultural development (AD) Grain output (x12) Reflecting the status of regionalagricultural development

AD reflects the utilization efficiency of cultivated land in a specificregion, and to some extent is affected by CLF

Food supply capacity (x13) Reflecting the value of local agriculturalproduction and the productiondiversification

Note: In the table, the calculation method of x1 refers to Zhuang and Liu (1997). For x12, “water network” includes rivers, canals, lakes, reservoirs, ponds, etc. Moredescription and calculation method of x14 can be found in Sun et al. (2017).

Fig. 2. The conceptual model of second-level zones of CLF based on spatial differences. The green, red, and blue solid lines represent x (resource endowment), y(spatial distribution) and z (convenience of utilization) of CLF, respectively. The red ellipses represent second-level zones of CLF while blue ellipses indicate thestatistical characteristics of the corresponding second-level zones in fractal dimension.


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respectively.

3.4. Overview of the research area

Jiangsu Province is situated in the Yangtze River Delta on thecoastal center of eastern China with an area of 107,000 km2 and a totalpopulation of approximately 79.763 million (Fig. 3). As an economic-ally developed region in eastern China, the gross domestic product(GDP) of the Jiangsu Province increased from 24.924 billion renminbi

(RMB) in 1978 to 8590.094 billion RMB in 2017 with a national landarea of 1.12% carrying a population of 5.78% and a total economicoutput of 10.4%. Nevertheless, the district also suffers from severe re-source shortage, with the per capita arable land area of only 0.057 hm2,which is only 60.96% of the average national level and approaching thewarning line of 0.053 hm2 established by Food and Agriculture Orga-nization of the United Nations.

Agriculture in Jiangsu will continue to develop as planned by"Opinions on Further Promoting Agricultural Supply-side Structural

Table 3The classification standards and characteristics for second-level zones of CLF based on influencing factors and spatial differences.

Second- level zoning Classification standards and the correspondingcombination of magic cube units

Essential characteristics of second-level zones and the main directions ofdiminishing CLF through LC

Utilization efficiency improvement zone(High values of x, y, and z)

(4,4,4) (4,4,3) (4,3,4) (4,3,3) (3,4,3) (3,4,4)(3,3,4) (3,3,3)

Possessing the conditions of resources and facilities for promoting large-scale management and modern agriculture development endowed withsuperior resources, concentrated spatial distribution, and convenientutilization. Attention should be paid to agricultural technologicalinnovation to improve the efficiency of cultivated land resources utilization

Spatial intensive merging zone (Higher x and zvalues while lower y value)

(4,1,4) (4,2,4) (4,1,3) (3,2,3) (3,2,4) (3,1,4)(3,1,3) (4,2,3) (2,1,4) (4,1,2) (4,2,2) (2,2,4)

Cultivated land resources have apparent advantages in scale andconvenience while its spatial layout is scattered and fragmented. It shouldfocus on the optimization of the spatial structure of cultivated landcombined with rural construction land consolidation to promote thecentralized and continuous distribution

Facility construction improvement zone(Higher x and y values while lower z value)

(4,4,1) (4,4,2) (4,3,1) (4,3,2) (3,4,1) (3,4,2)(3,3,1) (3,3,2) (4,2,1) (2,4,1)

Having great advantages in terms of resources scale and spatialagglomeration, but there are certain deficiencies in infrastructureconstruction and land accessibility. Attention should be paid to theimprovement of regional agricultural infrastructure construction toenhance conditions for production

Scale management and land circulation zone(Higher y and z values while lower x value)

(1,4,4) (1,4,3) (1,3,4) (1,3,3) (2,4,4) (2,4,3)(2,3,4) (2,3,3) (1,2,4) (1,4,2) (2,4,2)

Having great advantages in spatial agglomeration and convenientutilization, but there are certain deficiencies in the scale of resources.Attention should be paid to the market-oriented circulation of dispersedland plots and ownership adjustment to create conditions for promotinglarge-scale management

Resource allocation optimization zone(x, y, and z values are all medium)

(3,1,2) (3,2,1) (2,1,3) (2,3,1) (1,2,3) (1,3,2)(2,2,3) (3,2,2) (2,3,2)

Resources scale, spatial agglomeration, and utilization convenience ofcultivated land are all at a medium level, or two of the three dimensions areat a medium level, and the phenomenon of CLF is more serious.Differentiated LC strategies should be adopted to promote the optimalallocation of regional resource elements according to the characteristics ofCLF in different regions

Comprehensive improvement zone(Low values of x, y, and z)

(1,1,1) (1,1,2) (1,2,1) (1,2,2) (2,1,2) (2,2,1)(2,1,1) (2,2,2) (1,1,3) (1,1,4) (1,3,1) (1,4,1)(3,1,1) (4,1,1)

Resources scale, spatial agglomeration, and utilization convenience ofcultivated land are poor, or two of the three dimensions are poor, and thephenomenon of CLF is the most serious. Attention should be paid to theglobal planning and comprehensive improvement of production factorssuch as cultivated land, water systems, roads, and rural settlements

Fig. 3. Study area.


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Reform and Promoting Continuous Income Increase of Farmers" issuedby Jiangsu Provincial People's Government in 2017: Strengthen theinfrastructure construction of farmland, actively develop the moderate-scale operation of agriculture, and construct modern agricultural pro-duction and management system. This indicates that the regionalagricultural development will transform from the traditional agri-culture of improved variety, intensive cultivation, fine management,and more fertilizer to modern agriculture of green, ecological, efficient,and sustainable. Notably, in the context of comprehensively deepeningreforms to ensure food security and sustainable development, CLF is asevere obstacle existed in pushing forward scale management of farm-land and agricultural mechanization and adopting agricultural in-novations and new technologies. Hence, it is of great significance toanalyze the spatial disparities, influencing factors, and governanceapproaches of CLF to formulate state-regulated reasonable resourceutilization policies, improve LC modes and directions, and promote thetransformation and upgrading of agriculture.

3.5. Data sources and pre-processing

In the quantitative evaluation, the cultivated land plot is used as theresearch unit, and the research results are statistically analyzed at thetownship level (since townships are the most basic administrative unitsof LC strategy implementation) under the administrative division ofJiangsu Province in 2014, including 1389 sub-objects and 7.191 millionsub-plots. We assembled data that characterize geographic, land use,and socio-economic information (Table 4). Due to the differences indata sources and spatial accuracy, this paper processes all data on theArcGIS 10.2 software platform. The weights of indicators in Table 1 arecalculated by combining the entropy weight method and analytichierarchy process method (Shemshadi et al., 2011), which can addressthe limitations of over-reliance on evaluation data and subjective ar-bitrariness.

4. Results and analysis

4.1. Spatial differentiation characteristics of CLF

4.1.1. Spatial differentiation of provincial CLFAccording to the measurement model of CLFI, we calculated the

CLFI of Jiangsu, and divided it into four grades (i.e., lowest, lower,higher, and highest) by using natural break method. The CLFI inJiangsu Province presents a spatial pattern that gradually increasesfrom north to south (Fig. 4d). The average provincial CLFI is 0.408,while the average CLFI in northern, central, and southern Jiangsu is0.372, 0.430, and 0.456, respectively, revealing obvious regional dif-ferences of CLF. Judging from the quantity structure of each level oftownships, the CLFI in Jiangsu Province presents a "U-shaped" structure,and the proportion of towns with the highest and lowest grades of CLFIis 31.53% and 30.45%, respectively. In general, the resource endow-ment (RE) attribute of Jiangsu is high, with the average provincial RE is0.633, but the resource scale in southern and central Jiangsu is sig-nificantly lower than that in northern (Fig. 4a) with the average RE is0.569, 0.592, and 0.687, respectively. The spatial difference of spatialdistribution (SD) attribute is similar to that of RE (Fig. 4b), and culti-vated lands around Taihu Lake, such as Suzhou and Wuxi, and along the

Yangtze River in Nanjing, Zhenjiang and Changzhou are scattered andpoorly concentrated. The average value of the convenience of culti-vated land use in the province is 0.392, which indicates that the ac-cessibility of cultivated land and infrastructure construction are poor(Fig. 4c), and the proportion of the townships at lowest, lower, higher,and highest level is 29.30%, 18.86%, 20.45%, and 31.39%, respec-tively.

4.1.2. Characteristics of CLF and its fractal dimensions within and outsidethe urban planning built-up areas

We further analyze the regional differences of CLF and its fractaldimensions within and outside the urban planning built-up areas ofdifferent cities (Fig. 5), due to the differences in production and life-style, infrastructure construction, industrial structure characteristics,and intensity of human activities, which provides adequate support fordetermining locally strategies for arable land use. Fig. 5c shows theurban planning built-up areas of cities in Jiangsu Province.

In summary, the spatial differences of CLF and its fractal dimensionswithin and outside the urban planning built-up areas are significant.Overall, the CLFI in built-up areas is significantly higher than thatoutside built-up areas (Fig. 5d), indicating that the CLF in the built-uparea is more serious, which could be a result of a higher level of socio-economic development, that is, the segmentation, erosion and spatialcrowding effect on agricultural space caused by high-intensity humanactivities, perfect infrastructure construction, and intensive demandsfor land use within built-up areas. The average provincial CLFI withinthe urban planning built-up areas is 0.423, while the average CLFI insouthern, central, and northern Jiangsu is 0.458, 0.450, and 0.377,respectively, revealing a prominent regional difference. In terms offractal dimensions of CLF, the order of fractal dimensions both withinand outside the urban planning built-up areas are the following: spatialdistribution (SD)> resource endowment (RE)> convenience of utili-zation (CU) (Fig. 5a/b), which indicates that reducing the number ofland plots, promoting the centralized and continuous distribution ofarable land, and enhancing infrastructure construction to improveproduction conditions are still the critical contents of LC in the future.Specifically, the values of RE and SD outside the built-up areas aregenerally higher than that within the built-up areas, indicating that thescale of the cultivated land resources outside the built-up area and thespatial agglomeration are superior; while the spatial difference of CUcontradicts the RE and SD, and CU within the built-up areas is generallyhigher than that outside.

4.2. Influencing factors of CLF

4.2.1. General analysis of influencing factors of CLFCollinearity diagnostics were performed assessing the variance in-

flation factor (VIF) of each impact factor, and all calculated VIFs werebelow five indicating that there were no multiple collinearities amongfactors. In the initial analysis, significance tests were made on linearregression relationship among all variables in Table 2, and there areonly five variables, i.e., gross domestic product (x2), plot distance fromtown (x5), average plot size (x7), per capita cultivated land area (x8),and grain output (x12), passed the significant test at the 1% or 5% leveland the adjusted R2 of the multivariable linear regression analysis was0.460, which was significantly inconsistent with expectations.

Table 4Data sources and descriptions.

Data name Data source Time-series Resolution

Land Use/Land Cover Data Jiangsu Province Land Use Change Survey Database 2014 1:1,0000Socioeconomic Data Jiangsu Statistical Yearbook 2016 County/township levelsCultivated Land Quality Data Results of National Survey of Cultivated Land Quality 2010 1:10,0000DMSP/OLS Night Light Data http://www.noaa.gov/ 2013 1 km×1 kmDEM (ASTER GDEMV2) http://www.gscloud.cn/ 2009 30m×30m


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http://www.noaa.gov/

http://www.gscloud.cn/

Dependent and independent variables have been further processed withlogarithm to limit the broad range of data changes with the adjusted R2

is 0.622 and passed the significance tests of F-test and t-test. In parti-cular, some variables, i.e., land use degree (x1), plot distance fromnearest water system (x6), cultivated land quality (x9), and water net-work density (x11), are excluded from the modeling process due thatthey failed significance test in the t-test, while the other variables aresignificant at the 1% or 5% level. The multivariable linear regressionmodel is shown in formula 4, while the regression results are expressedin Table 5.

LnY=−0.709+ 0.044Lnx2+0.077Lnx3−0.016Lnx4−0.016Ln-x5−0.132Lnx7−0.034Ln8+0.016Lnx10−0.009Lnx12−0.039Lnx13 (4)

In the formula, the influential factors with larger regression coeffi-cients are average plot size (x7), the proportion of industry and serviceindustry (x3), gross domestic product (x2), food supply capacity (x13),per capita cultivated land area (x8) and slope (x10).

In addition, geographical detectors were used to identify the impactfactors in Table 2 (x1∼x13) on CLFI; the influence power (q) on CLF is:0.067, 0.133, 0.204, 0.032, 0.084, 0.011, 0.472, 0.059, 0.039, 0.097,0.003, 0.129 and 0.016, respectively. There is no significant differencein the effect of variables in Table 2 (x1∼x13) on CLF by the results of

multivariable linear regression and geographical detectors, whichshows that the modeling-based cause analysis results had good relia-bility and objectivity.

4.2.2. Identifying dominant factors for geographical differentiation of CLF

(1) The dominant factors of regional differentiation of CLF at the pro-vincial scale

We further ranked the absolute values of q and Beta in descendingorder to cross-validate the results of multivariable linear regression andgeographical detectors (Table 6). As indicated in Table 6, the results ofthe Beta analysis of the linear regression standardized coefficient fea-tured the importance of indicators with significantly positive and ne-gative correlations with CLFI. Among all measured indicators for CLFIin Jiangsu Province, the top six factors (ranked in descending order ofabsolute values of Beta) included average plot size (x7), the proportionof industry and service industry (x3), gross domestic product (x2), grainoutput (x12), slope (x10), and plot distance from town (x5) are basicallyconsistent with the results of influence power (q). These econometricresults fully indicate that these six indicators are the dominant factorsaffecting the geographical differentiation of the CLF in Jiangsu

Fig. 4. Spatial differentiation characteristics of CLF. The green shades indicate the lowest grade of CLF in the fractal dimension, and the red shades indicate thehighest grade. The difference between green to red characterizes the increasing trend of CLF in each fractal dimension.


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Province.

(2) Factors of regional differentiation of CLF within and outside theurban planning built-up areas

Influence power (q) of factors in Table 2 on CLF are calculated andranked as mentioned above, both within and outside the urban plan-ning built-up areas (Fig. 6). In general, the impact of factors on CLF isbasically consistent with the spatial detection results at the provincial

Fig. 5. The characteristics of CLF and its fractal dimensions within and outside the urban planning built-up areas of Jiangsu Province.

Table 5Results of multivariable linear regression.

Categories of influential factors Influential factors Unstandardized B Std. Error t Sig. VIF

SEDL x1 0.004 0.061 0.060 0.952 1.720x2 0.044*** 0.006 7.448 0.000 1.402x3 0.077*** 0.012 6.249 0.000 1.540

PLC x4 −0.016*** 0.005 −3.309 0.001 1.237x5 −0.016*** 0.004 −3.900 0.000 1.865x6 −0.001 0.004 −0.020 0.984 1.068x7 −0.132*** 0.006 −21.980 0.000 1.315

LDP x8 −0.034*** 0.006 −5.703 0.000 1.474x9 −0.008 0.039 −0.194 0.846 1.158

NEC x10 0.016*** 0.009 1.776 0.007 1.109x11 0.002 0.002 0.780 0.435 1.322

AD x12 −0.009** 0.005 −1.817 0.021 2.115x13 −0.039*** 0.007 −5.969 0.000 1.872

Constant −0.709*** 0.119 −5.939 0.000

Note: ***, ** denotes significance level at 1% and 5%, respectively.

Table 6Statistics of influencing factors on CLF in Jiangsu Province.

Influential factors x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13

Standardized Beta 0.002 0.320 0.350 −0.089 −0.137 0.000 −0.612 −0.046 −0.005 0.180 0.019 −0.093 −0.297Ranking of Beta 12 3 2 8 6 13 1 9 11 5 10 7 4Influence power q 0.067 0.133 0.204 0.032 0.084 0.011 0.472 0.059 0.039 0.097 0.003 0.129 0.016Ranking of q 7 3 2 10 6 12 1 8 9 5 13 4 11

Note: Ranking by the absolute values of Beta or q.


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scale, especially the top six factors have not changed significantly butwith slight changes in the ranking of individual factors. This indicatesthat the average plot size (x7), the proportion of industry and serviceindustry (x3), gross domestic product (x2), grain output (x12) and slope(x10) are still the dominant factors affecting the regional differentiationof CLF both within and outside the built-up areas, but for differentregions, the influence intensity of each factor is different. Specifically,within the built-up areas, the order of each factor (ranked in descendingorder of absolute values of q) is the following: average plot size (x7,q=0.427) > the proportion of industry and service industry (x3,q=0.240) > grain output (x12, q=0.168) > plot distance fromtown (x5, q=0.128) > gross domestic product (x2, q=0.122) >slope (x10, q=0.086), which indicates that location conditions andsocio-economic activities have significant effects on the geographicaldifferentiation of CLF within the built-up areas. In comparison, theorder of each factor outside the urban planning built-up areas is thefollowing: average plot size (x7, q=0.491) > the proportion of in-dustry and service industry (x3, q=0.188) > plot distance from ruralsettlements (x4, q=0.142) > gross domestic product (x2,q=0.125) > grain output (x12, q=0.084) > slope (x10, q=0.076),which highlights the important impact of rural settlements outsideurban built-up areas on CLF. Further analysis shows that the influencepower (q) of the same-ranking within the built-up areas is higher thanthat outside the built-up areas, indicating the mechanism of CLF inbuilt-up areas may be more complex. While production and livingconditions have a more significant impact on the CLF outside the built-up areas. The smaller average plot size is still the main obstacle existedin pushing forward scale management of farmland in the vast ruralareas. Meanwhile, the alternant distribution of rural settlements andcultivated land also has an important impact on the development ofCLF.

Further analysis of the mechanism of the dominant factors canprovide a reference for addressing the local obstacles of CLF. Thus, thetop six factors with the most significant influence of power (q) inTable 6 are analyzed to inform regional agricultural development andLC policies. Fig. 7 shows the spatial differentiation characteristics ofeach dominant factor.

(1) Average plot size is an important indicator reflecting the support ofcultivated land resources for large-scale and mechanized agri-cultural development. Generally, the larger the average plot size,the higher the appropriate degree of regional promotion of large-scale agricultural development, and the smaller the degree of CLF.From the perspective of geographical distribution, the average plotsize in Jiangsu Province is characterized by the spatial distributionpattern of smaller in the south and larger in the north (Fig. 7a)

while the CLFI shows that higher in the south and lower in the north(Fig. 4a). This contradictory spatial pattern indicates that there maybe a negative correlation between the average plot size and CLFI,and the result of multivariable linear regression demonstrate asignificant negative correlation between them with R=−0.738.Especially in Xuhuai plain areas, such as Xinyi, Donghai, andSuining, the endowment of cultivated land resources in these areasis superior, and the scale agriculture and modern agriculture de-velopment level is high, characterizing with a larger average plotsize (1.362 hm2) and a lower level of CLFI (the average value ofCLFI is 0.356); while in Ningzhenyang and Yili low mountain andhilly areas in southwest Jiangsu Province, such as Jurong, Lishui,and Liyang, the average plot size in these areas is smaller(0.472 hm2), and the average value of CLFI (0.466) is obviouslyhigher than that of other areas.

(2) The proportion of industry and service industry fully reflects thecharacteristics of regional industrial structure, and presents a gra-dual increase from north to south (Fig. 7b), which is basicallyconsistent with the spatial patterns of CLFI, that is, the higher theproportion of industry and service industry, the higher the CLFI,otherwise the lower the CLFI. Multivariable linear regression resultdemonstrates a significant positive correlation between them withR=0.147. The secondary and tertiary industries in the southernJiangsu have made outstanding contributions to the economic de-velopment of the province, especially in the areas along both sidesof Yangtze River and the areas around Taihu Lake. These regionsare horned as the pioneer demonstration areas of national moder-nization construction with the rapid development of advancedmanufacturing industry, modern service industry, and high-techindustries. However, regional urban construction has a significantcrowding effect on agriculture space to a certain extent, resulting ina relatively high degree of CLFI. By contraries, the northernJiangsu, such as Jinhu, Jianhu, and Guannan, is a post-economicdevelopment area in Jiangsu Province. The proportion of primaryindustry in these regions is 12.04% with a higher development levelof large-scale agriculture and agricultural mechanization, which farexceeds the provincial average (5.54%), and the CLFI is relativelylow (0.372).

(3) The gross domestic product reflects the overall level of regionalsocio-economic development. On the whole, the socio-economicdevelopment of Jiangsu Province generally presents a spatial dis-tribution pattern similar to that of the industrial structure. Thegross domestic product in southern is significantly higher than thatin central and northern Jiangsu (Fig. 7c), which is basically con-sistent with the spatial distribution trend of CLFI (Fig. 4d) whilecontrary to the spatial pattern of resource endowment (Fig. 4a) and

Fig. 6. Differences of factors leading to CLF within and outside urban planning built-up areas.


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spatial agglomeration (Fig. 4b) of cultivated land. In the meantime,multivariable linear regression result also shows that there is asignificant statistical positive correlation between gross domesticproduct and CLFI with R = 0.320, indicating that the higher thelevel of regional socio-economic development, the lower the scaleof cultivated land resources, the more dispersed the spatial dis-tribution and the higher the CLFI, on the contrary, the lower theCLFI.

(4) Agricultural development. As an essential element of agriculturaldevelopment, grain production is the fundamental guarantee for

economic growth and social stability. In terms of grain output, thereare significant regional differences in Jiangsu Province, and thegrain output in northern and central Jiangsu is significantly higherthan that in southern (Fig. 7d). The spatial distribution of grainoutput is contrary to the CLFI, indicating that the better the regionalagricultural development, the lower the CLFI. Further analysis findsthat the spatial distribution trend of grain production is similar tothat of resource endowment and spatial agglomeration of cultivatedland, especially in the Xuhuai plain and the Lixia river plain. Theseareas are essential bases for production, processing, and marketing

Fig. 7. Spatial distribution of the main factors influencing CLF in Jiangsu Province.


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of agricultural and sideline products throughout the province andthe country. The original superior agricultural production condi-tions characterized by the superior endowment of cultivated landresources, right scale conditions and spatial distribution of ag-glomeration, and the implementation of large-scale LC projects inthe regions have reduced the degree of CLF to a certain extent.

(5) Slope effectively reflects the topographical features of the area.Generally, the gentler the slope, the weaker the spatial division oncultivated land resources. It can be seen from Fig. 7e that the slopein Jiangsu Province shows remarkable spatial connectivity char-acteristics with a gradual increase from east to west and the slope ofthe western region is significantly higher than that in the centraland eastern areas. Especially in the low mountain and hilly areas ofsouthwest Jiangsu, e.g., Lishui, Jurong, Liyang, and Yixing. Thetopographic fluctuation in the region varies significantly due to thehigher land's slope. To a certain extent, the spatial separation ofcultivated land resources is more obvious, resulting in a relativelyhigh degree of CLF.

(6) Plot distance from town reflects the location of cultivated land re-sources, and the possibility of occupying on it by urban constructionland expansion to some extent. From Fig. 7f, plot distance fromtown in Jiangsu Province is gradually decreasing from north tosouth, which is contrary to the CLFI. In addition, the result ofmultivariable linear regression demonstrates a significant negativecorrelation between them with R=−0.319. In terms of spatialdistribution, the low-value areas of plot distance from town arebasically consistent with the spatial extent of the high-value areasof CLFI, especially in southern Jiangsu. These statistical resultsshow that the smaller the distance between cultivated land re-sources and towns, the more severe the interference of cultivatedland by human activities, and the higher the CLFI; otherwise, thelower the CLFI.

4.3. Zoning trade-off of CLF and implications for future land consolidation

4.3.1. Classification of CLF based on the major influencing factorsOn the basis of quantitative detection of the dominant influencing

factors of provincial CLF, geographical detectors are used to carry outmulti-level geographic detection at the county-level city, and thesamples are grouped into four clusters by k-means clustering (Jain,2010), which varied in different influential factors, hence revealingfour first-level zones (Table 7; Fig. 8). We named the four clusters basedon dominant categories of influential factors.

Socio-economic dominant influence area. This cluster is mainlyconcentrated in the rapid economic development of southern Jiangsuand the superior endowment of agricultural resources in northernJiangsu, including 39 counties. The average q of the SEDL on CLF in thecluster is 0.512, which is significantly higher than that of PLC (0.358),LDP (0.316), NEC (0.366) and AD (0.367). The level of regional socio-economic development is relatively high, especially in southernJiangsu. The CLF in the region is greatly influenced by social andeconomic factors such as industrial structure and land development

intensity. While promoting socio-economic development and improvingquality of life, rapid urbanization also has a special impact on CLF, dueto that rapid expansion of construction land has occupied arable landand the spatial separation by urban infrastructure construction, such ashigh-speed lines, highways, and railways, etc.

Production and living conditions dominant influence area. Thiscluster is greatly influenced by factors such as the plot distance fromrural settlements and towns, and the average plot size, with q of 0.424,0.382 and 0.449, respectively, which are significantly higher than SEDL(0.150), LDP (0.148), NEC (0.128) and AD (0.135). As the main pri-mary division of the CLF in Jiangsu Province, it is mainly concentratedin the central and eastern coastal areas of Jiangsu, including 49 coun-ties. These areas are dominated by plains with abundant arable landresources, concentrated spatial distribution and apparent advantages inagricultural production, and are essential commodity production basesfor rice, wheat, cotton, and vegetables in the province. Further analysisfinds that there are significant differences in the mechanism of thecounty-level objects located within or outside the urban built-up areas.Specifically, for the county-level objects within the urban built-up area,such as Nanjing, Suzhou, and Xuzhou, the q of the above three factorson the CLF is 0.378, 0.434 and 0.451, respectively; while the q outsidethe built-up areas is 0.425, 0.324 and 0.494, respectively, e.g., Sheyang,Hai'an, and Guanyun. These results fully indicate that the smalleraverage plot size is an important production factor affecting the re-gional differentiation of CLF in Jiangsu Province. In addition, plotdistance from towns and rural settlements has a significant impact onthe CLF within the built-up areas and outside, respectively. This alsoconfirms the spatial detection results of the dominant factors on CLF inSection 4.2.2.

Natural environmental conditions dominant influence area. Naturalenvironmental factors have a significant impact on the spatial differ-entiation of CLF, e.g., slope. This cluster includes 14 county-level ob-jects. Agricultural planting methods and structures are restricted tosome extent due that low mountains and hills dominate landforms inthis cluster, and their topography vary greatly. The average q of theslope on CLF is 0.624, which is significantly higher than that of SEDL(0.367), LDP (0.350), PLC (0.380) and AD (0.239).

Multi-factor comprehensive influence area. The q of SEDL, LDP,PLC, NEC, and AD on CLF is 0.733, 0.796, 0.739, 0.691, and 0.791,respectively. This cluster consists of 9 county-level objects, mainlydistributed in urban built-up areas and suburban areas with compleximpact mechanisms and numerous influencing factors. Therefore, giventhis cluster, the mechanism of CLF is more complicated, and it is moredifficult to address the problem of CLF accurately. It is more necessaryto adopt differential measures according to local conditions and sci-entific evaluation.

4.3.2. Zoning scheme for CLF management based on influencing factors andfragmentation characteristics, and suggestions for addressing CLF

The same types of first-level zones based on the major influencingfactors on CLF incorporate different sub-categories featuring differentcultivated land resource endowment, spatial distribution patterns,

Table 7Average influence power (q) for each influencing factor on CLFI within each first-level zone. The number of counties in each cluster is denoted by n.

Clusters SEDL PLC LDP NEC AD Name

x2 x3 x4 x5 x7 x8 x10 x12 x13

Ⅰ(n= 39) 0.487 0.537 0.328 0.302 0.443 0.316 0.363 0.363 0.370 Socio-economic dominant influence areaAverage q 0.512 0.358 0.316 0.363 0.367Ⅱ(n= 49) 0.152 0.147 0.424 0.382 0.449 0.148 0.128 0.164 0.105 Production and living conditions dominant influence areaAverage q 0.150 0.418 0.148 0.128 0.135Ⅲ (n= 14) 0.460 0.274 0.393 0.378 0.368 0.350 0.624 0.229 0.249 Natural environmental conditions dominant influence areaAverage q 0.367 0.380 0.350 0.624 0.239Ⅳ(n= 9) 0.753 0.713 0.674 0.759 0.785 0.796 0.691 0.792 0.789 Multi-factor comprehensive influence areaAverage q 0.733 0.739 0.796 0.691 0.791


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production, and utilization status. Therefore, we use the magic cubemodel to further identified 24 s-level zones (Fig. 9) that were associatedwith fractal dimensions of cultivated land utilization, aiming at pro-viding practical support for regional LC practices for diminishing CLF.

Utilization efficiency improvement zone. This type of areas accountsfor 24.76% of the total towns and is mainly distributed in the Xuhuaiplain and the western Lixia river plain. The average CLFI is 0.338,which is lower than the average level of provincial CLFI (0.408). Themean value of the resource, spatial, and utilization properties in thistype of areas is 0.704, 0.739, and 0.535, respectively. As a critical maingrain-producing area in Jiangsu Province, cultivated land area andgrain output in this region account for 30.22% and 32.38% of theprovince respectively, with rich in cultivated land resources, con-centrated spatial distribution and complete facilities. Therefore, LCpractices in this region should focus on further improving the utiliza-tion efficiency of cultivated land. In reality, the government couldfurther improve the quality of resource utilization by: (1) activelypromote the construction of high-standard basic farmland and com-modity grain bases; (2) appropriately adjust regional planting habitsand planting methods to create conditions for large-scale managementand mechanized farming; (3) actively highlight the promotion andapplication of modern new technologies in regional agricultural

planting and production. The organic, ecological, facility and resource-intensive agriculture should be actively developed.

Spatial intensive merging zone. This type of areas accounts for10.51% of the total towns, and mainly distributes in the areas aroundTaihu Lake. The average CLFI is 0.404, and the mean value of the re-source, spatial, and utilization properties in this type is 0.624, 0.332,and 0.516, respectively. The cultivated land resources in the regionhave better scale conditions and entire infrastructure, yet the scatteredand fragmented spatial layout. Rural settlements have a higher degreeof separation for cultivated land, and the average distance betweenthem is only 85.48m. Attention in LC should be paid to the spatialintegration of regional cultivated land resources by reducing thenumber of ridges and combining the dispersed plots to achieve thepurposes of lowering CLF and expanding the scale of cultivated land. Atthe same time, for the rural settlements with the scattered and dis-ordered spatial layout in the region, rural construction land con-solidation should be implemented to promote the centralization offarmers' residence and the centralized and continuous distribution ofarable land. Especially, the spatial structure and layout of rural settle-ments should be renovated and reconstructed, as well as the infra-structure construction.

Facility construction improvement zone. This type of areas accounts

Fig. 8. Classification of CLF in Jiangsu Province based on the major influencing factors on CLFI. The number of counties in each cluster is denoted by n. The petals ofdifferent colors in a, b, c, and d represent different categories of influential factors. The size of the petals represents the average q of the influencing factors on CLFupon different dimensions.


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for 21.81% of the total towns, and mainly distributes in some townshipsin the interior of central Jiangsu and the eastern coastal plain regions innorthern Jiangsu. The average CLFI is 0.386, while the mean value ofthe resource, spatial, and utilization properties in this type is 0.708,0.792, and 0.304, respectively. There are abundant arable land re-sources with concentrated spatial distribution in these areas, but withthe large potential for improvement in the construction of agriculturalinfrastructure. LC practices in this region should focus on improvingproduction and living conditions, including water conservancy facil-ities, production facilities, and farmland protection facilities. On theother hand, attention should also be paid to the spatial layout andplanning of production factors in the regional LC planning, such as fieldplanning, field road planning, field irrigation, and drainage systemplanning, and field protection forest planning.

Scale management and land circulation zone. This type of areasaccounts for 8.28% of the total towns, and mainly distributes in theplains along the Yangtze river and Lixia river. The average CLFI is0.405, while the mean value of the resource, spatial, and utilizationproperties in this type is 0.431, 0.747, and 0.530, respectively. Thespatial distribution of cultivated land in the region is concentrated, andthe agricultural infrastructure is well equipped, but there are certaindeficiencies in resources scale. The average plot size is only 0.621 hm2,which is significantly lower than the provincial average (0.943 hm2).LC practices in the region should focus on promoting moderate-scalemanagement of agricultural land and expanding its resources scale. Inpractice, our study suggests that: (1) expand the scale of cultivated landmanagement through the measures of leveling abandoned ditches andridges to meet the needs of irrigation, drainage and mechanizedfarming; (2) merge fragmented small fields and promote land owner-ship adjustment simultaneously to create conditions for moderate-scalemanagement of farmland and agricultural modernization.

Resource allocation optimization zone. This type of areas accountsfor 11.45% of the total towns with mean CLFI of 0.440, which presents

the spatial distribution characteristics along both sides of YangtzeRiver, around Taihu Lake and along the coast. However, there is a vastspatial difference in combination characteristics of fractal dimensionsof CLF, due to the vast regional differences in natural environmentcharacteristics, socio-economic development level, and production andliving conditions, etc. Accordingly, LC in this region should embracedifferentiated strategies to adapt to local conditions and promote theoptimal allocation of resource elements. For example, in plain areas, LCshould aim at expanding the resource scale of cultivated land to attainthe economies of scale, and pay more attention to address the problemsof small scale of cultivated land resources and scattered spatial layout;while in low mountains and hilly areas, LC should focus on improvingthe output efficiency of cultivated land through the agricultural infra-structure construction to enhance the convenience of cultivated landutilization.

Comprehensive improvement zone. This type of areas accounts for23.18% of the total towns with mean CLFI of 0.491, which is con-centrated in the areas of along Yangtze River, e.g., Jurong, Yizheng andJiangyin, and the areas around Taihu Lake, e.g., Wujiang. The phe-nomenon of CLF is serious, which is characterized by the inadequateresources scale, dispersed spatial layout, and poor utilization con-venience of cultivated land, with the average values of 0.470, 0.357,and 0.342, respectively. Socio-economic factors are the dominant fac-tors affecting the regional differentiation of CLF, such as the high-in-tensity human activities and urban construction land expansion, ac-counting for 47.2%. Furthermore, the spatial distribution pattern ofarable land is also affected by the diverse topography and the scatteredrural settlements, and the average distance between the latter and plotsis only 77.59m. LC in this region should pay more attention to theglobal planning and overall improvement of production factors such asfarmland, water system, and roads. Such as, expanding the scale offarmland management by digging high and filling low in the same areaand leveling abandoned ditches and ridges; strengthening the

Fig. 9. The zoning scheme for CLF management in Jiangsu Province based on influencing factors and fragmentation characteristics. Among them, the first-class zonesfully reflect the impacts of dominant influencing factors on CLF, while the second-class zones highlight the combined characteristics of fractal dimensions of CLFwithin the same type of first-class zones and refine the spatial development directions of optimal utilization of cultivated land resources for CLF management and LCpractices improvement in Jiangsu Province.


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construction of agricultural infrastructure to promote the effective useof cultivated land resources; and implementing the rural constructionland consolidation to achieve the centralization of farmers' residenceand agricultural production scale.

5. Discussion and policy implications

5.1. The contribution of this study and the quantitative basis for academicdebate

5.1.1. Contribution of the analytical framework for interaction betweenCLF's spatial-scale characteristics and LC

Ensuring food security and promoting sustainable socio-economicdevelopment within a sustainable land use framework are still con-sidered the challenging policy targets owing to limited land space andcultivated land resources along with the rapid growth of population. Inthis case, improving agricultural technologies and policies through landmanagement tools including land consolidation are effective measuresto meet food demands (Hartvigsen, 2015; Du et al., 2018), especially forensuring food security at regional or national levels. This requires sta-keholders (e.g., national, local/provincial governments, ministries,council) to make a sound knowledge about the characteristics of cul-tivated land in the multi-dimensional aspects of the resource scale,spatial distribution and facilities allocation, and then make the mostrealistic decision-making of resources utilization and agriculture de-velopment planning. Unfortunately, prior to the lack of crucial knowl-edge and the literature gap about the above problems, the majority ofthe governmental programs to tackle CLF have emerged, including theFarm Land Use Consolidation (LUC) program (Ntihinyurwa et al., 2019)and the National Land Remediation Plan. The uniform agricultural landconsolidation models have caused a disconnect between the resourceutilization targets at larger scales and the cultivated land utilizationimprovements at smaller scales due to that they do not account for theregional differences in resource and environment utilization, and to acertain extent have damaged the local characteristics.

Therefore, expanding the spatial-scale characteristics of CLF fordifferent social groups and exploring its spatial differentiation char-acteristics, diversity mechanisms, and solutions on a larger spatial scalewill be conducive to human well-being. The analytical frameworkpresented in this study has the potential to make an important con-tribution to the existing literature as it enriches the connotation of CLFto a certain extent and expands its content and research scale. In termsof practical application, on the basis of scientifically measuring thespatial differentiation characteristics and its mechanisms, this studybrings in a new idea of considering both natural (resource) property,spatial property and utilization property of CLF when guiding or im-plementing the practice, planning and management of regional LC,which is of great significance to break the dilemma of CLF, improve theutilization efficiency of cultivated land resources and ensure nationalfood security. This work provides valuable reference and guidance forcultivated land use optimization and LC practices in China as well asother developing countries worldwide.

5.1.2. Smaller average plot size is indeed the primary cause of CLFFor a long time, there is agreement on the quantitative evaluation,

causes, and effects of CLF. It is generally believed that CLF is mainlycharacterized by dispersed plot locations. This conceptualization fo-cuses however on the landscape pattern characteristics of cultivatedland resources and considers that smaller average plot size is the typicalspatial form of CLF. However, this viewpoint is mainly derived fromqualitative experiences summarization, but few quantitative studiesverified it. With the deepening of research endeavors, academic circleshave aroused heated discussions about whether the average plot size isthe manifestation of CLF, or the influencing factor leading to its spatialdifferentiation, or both expression and cause. Scholars have been con-fronted with this debate for various reasons, e.g., data acquisition,

research methods, etc., and have made some efforts to address it.As noted above, this study attempts to break through the traditional

research idea of CLF, that is, average plot size is used to measure thedegree of regional CLF, and takes it as a factor to characterize regionalproduction and living conditions to explore its impact mechanism andintensity on spatial differentiation of CLF. The result shows that smalleraverage plot size is indeed the main factor affecting the spatial differ-entiation of CLF, whether based on the results of multivariable linearregression (the ranking of influence degree of the average plot size onCLF is 1 st with the absolute value of Beta is 0.624) or geographicaldetectors (also ranks 1 st with the absolute value of q is 0.472), whichprovides a quantitative basis for academic debate. Based on this, wehave reason to believe that the expansion of the average plot size candiminish the CLF, which has important implications for LC practices.

5.2. Policy implications of land consolidation and rural land use system inChina

Our research shows that CLF is the result of the comprehensive ef-fect of regional resource endowment and the rural land system (Section2.2). This enlightens us that reducing CLF requires not only strength-ening the systematic planning and top-level design of land consolida-tion planning at the macro-scale to further highlight the spatial guidingrole of planning, but also innovating the policies of effective utilizationand management of rural land resources at the micro-scale to createpolicy environment for the implementation of land consolidationplanning and the efficient utilization of cultivated land resources afterconsolidation.

5.2.1. Improving operation modes and structural system of landconsolidation in China5.2.1.1. CLF should be embedded in LC planning and decision-making topromote the optimal allocation of critical resources, especially at the regionalscale. State-regulated consolidation is often perceived as a criticalmeasure to tackle the CLF problem (Ciaian et al., 2018). LC planning,as the primary content of reasonable arrangement and classificationguidance of land consolidation activities, is an essential basis for thespatial allocation of critical resources, resources utilization, andregional agricultural development strategies. However, it mainlyfocuses on local natural environmental conditions and agriculturalproduction methods currently, such as topography, geomorphology,meteorology and hydrology, soil conditions, cropping systems,irrigation, and drainage methods, while paying little attention to theeffects of natural, spatial and utilization properties of cultivated landresources on fragmentation. Regional differences in resources size,spatial patterns, and facilities of cultivated land, to a certain extent,have caused the serious spatial mismatch among the consolidationmodes, the engineering measures and the characteristics of regionalcultivated land. Thus the benefits of LC need to be improved.

As the result of a combination of natural, economic, and socialfactors, CLF can intuitively reflect the human disturbance to cultivatedland resources, and provide reference and basis for coordinating therelationship among human activities, socio-economic development andcultivated land protection. Therefore, it is necessary to improve thenational LC planning system and incorporate the CLF into the planningand decision-making of policies to achieve higher quality and sustain-able of cultivated land utilization. Firstly, governments should regardthe region's CLF as the scientific basis of planning and improve its en-forcement to enhance the guidance of national resources utilization.Specifically, governments should be responsible for organizing the strictand comprehensive investigation of CLF yearly or at regular intervals toclarify the characteristics of the CLF, including the level, forms, causes,mechanisms along with all its effects, especially at the regional scales(e.g., administrative regions, states, provinces). On this basis, regionaldifferences in CLF should be taken as guidance for the allocation ofcritical resources, such as finances, markets, agricultural facilities and


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knowledge, and the decision-making of regional development strategiesduring the adjustment, revision or redesign of relevant planning. Sincethese administrative units have the authority, through policies, reg-ulations, and plans, to make the most efficient arable land use and LCstrategies that are most consistent with regional resources character-istics, e.g., financial support, projects arrangement and developmentstrategies.

5.2.1.2. Implementing rural land comprehensive consolidation project forrural revitalization and agricultural modernization. The importance oftraditional agriculture in China also means that rural areas play asignificant role in the country's sustainable development (Cheng et al.,2019). Facing the current rural decline in China (Long, 2014; Yanget al., 2015; Liu and Li, 2017; Liu, 2018a, b; Liu, 2019), such asdepopulation, non-agriculturalization of rural elements, hollowedvillages, deterioration of rural residential environment, andinefficiently used or abandoned farmland, etc., the Chinesegovernment proposed Rural Revitalization Strategy in 2017 aimed atrealizing agriculture and rural modernization. LC is an importantplatform for implementing the Rural Revitalization Strategy.However, CLF is the critical obstacle in the process of implementingRural Revitalization Strategy and promoting agriculturalmodernization. It is also the result of the interaction between thehuman-land relationship and the external environment in rural areasand is affected by various agricultural production factors such as roads,ditches, and settlements, etc. Against this background, thecomprehensive land consolidation projects covering fields, water,roads, forests, and villages should become the key content of ruralland consolidation in the new era to support rural revitalization andagricultural modernization. Based on our study, we suggest as follows:

(1) Fields: farmland improvement project (FIP). Under the strategicgoal of rural revitalization, the focus of the FIP should be to opti-mize the spatial layout of cultivated land and reduce the CLF bystrengthening the construction of high-standard basic farmland andimproving the quality of cultivated land, so as to create conditionsfor the construction of modern agricultural production and man-agement system.

(2) Water: farmland water conservancy project (FWCP). The goal ofFWCP should be to build a good irrigation and drainage system toenhance the disaster resistance of agricultural production, espe-cially in areas with scarce water resources. Specifically, it includesthe transformation and design of field branch canals, lateral canals,and bucket canals, the construction of irrigation wells, and thepromotion of water-saving irrigation instruments.

(3) Roads: rural and field road project (RFRP). The goal of RFRP is toimprove the transportability of agricultural products and materialsin rural areas, facilitate farmers' travel, and then provide infra-structure support for mechanized agriculture and modern ruralcommunities, including field roads, production roads, bridges, andrecreational trails, etc.

(4) Forests: farmland protection and eco-environmental protectionproject (FPEPP). The goal of FPAPP should be to build farmlandecosystem barriers through engineering and biological measures toenhance soil and water conservation capacity and improve the ruralecological environment. Among them, engineering measuresmainly include farmland shelterbelt networks engineering, bankslope protection engineering, ditch protection engineering, andecological engineering of slope surface, etc.; while biological mea-sures mainly include farmland shelterbelts, road protection forest,and forest belt for shore protection, etc.

(5) Villages: rural settlement optimization project (RSOP). The goal ofthe RSOP should be to rationally plan and orderly integrate therural residential space through strengthening municipal facilities(e.g., water supply, electricity, environmental sanitation, etc.),public service facilities (e.g., medical service, education, financial

institutions, etc.), and recreational facilities (e.g., landscapegreening, parks, etc.), etc., so as to improve the economical andintensive land use and reconstruct rural living space.

5.2.2. Innovative policies for effective utilization and management of ruralland resources5.2.2.1. Deepening the reform of rural land property rightssystem. Although LC can eliminate certain types of landfragmentation through the projects of farmland improvement andrural settlement optimization (Zhou et al., 2019), thus creatingconditions for modern agriculture, however, the fragmentation of theownership of cultivated land at the micro-scale is to some extent the keyfactor that restricts farmers' enthusiasm for production and inefficientof cultivated land utilization. Especially, the scattered and flower-arrangement ownership of land plots has further led to thefragmentation of farmland management. Meanwhile, promoting themodernization of agriculture and reconstructing the production andliving space of rural areas through LC are still faced with issues ofunsmooth transfer of land and imperfect development of rural landmarket caused by the ambiguous rural land property rights, incompletepower, and the vacancy of ownership subjects (Long et al., 2016; Liuet al., 2018). Furthermore, the lack of scientific and efficientmanagement system of land resources in rural areas has also led tothe parallel management of rural land by agriculture, forestry, animalhusbandry, and other departments, as well as a large number of landdisputes and conflicts of interests. In this context, there is an urgentneed to push forward the reform of rural land property rights system tocreate policy support for rural land consolidation (Long et al., 2016).China's rural land property rights system mainly includes thecontractual management right of agricultural land and the collectiveconstruction land use right. Accordingly, our study suggests as follows:

(1) Further clarify the subject of rural land property rights under theframework of collective ownership of rural land. Governmentsshould speed up the construction of laws and regulations for thedefinition of rural land property rights, and clarify the social groupof "collective ownership", such as villager committees, village col-lectives, village groups, or grass-roots governments, etc.

(2) Gradually establish a standardized and efficient mechanism for theseparation and parallel operation of land ownership, land con-tracting right and land management right (hereinafter referred to as"three rights"). Effective forms of collective ownership of rural landshould be explored constantly and the respective functions andoverall effectiveness of the "three rights" should be given full playthrough the implementation of collective ownership, stabilizationof farmers' contractual rights and liberalization of land manage-ment rights. In short, rural land property rights system reformshould focus on the protection of farmers' rights and interests andthe improvement of land use efficiency, by emphatically addressingthe finely divided and scattered land use pattern by land con-solidation adapted to local conditions (Liu et al., 2014a, 2018).

5.2.2.2. Promoting the transfer of rural land management rights. It is alsonecessary to recognize that rural transformation, which is characterizedby non-agriculture farmers, loss of young and middle-aged rural labors,and abandonment of farmland, determines that the fragmentation ofcultivated land management and the vacant and abandoned ruralhomestead will exist for a long time in China (Li et al., 2014; Long,2015; Yang et al., 2018). More seriously, the subjectivization of theaged, children, and female groups in rural areas makes it impossible toutilize the restored cultivated land effectively. In this case, the transferof contractual management right of agricultural land and collectiveconstruction land use right will have important impacts on thesustainable rural development and modern agriculture (Liu et al.,2014b, 2018). Consequently, the government could further stimulatethe transfer of rural land management rights by: (1) scientifically


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promoting the registration of rural collective land rights to lay thefoundation for the unified management system of urban and rural land(Liu et al., 2013), because clear land property right is the premise oforderly land transfer; (2) perfecting the relevant laws and regulationsand technical systems to standardize rural land transfer. To this end, thenational legislature should actively build a sound legal system of landtransfer based on extensive investigations to supervise the rural landtransfer according to law, and also provide the basis for resolving thedisputes. It should clearly stipulate various aspects of the rural landtransfer process, including the subject, scale, mode, price, time andduration, purpose, and division of powers and responsibilities; (3)developing and improving a unified rural land transfer market toactivate the contractual management right of agricultural land andthe rural collective construction land use right (mainly referred to ashomestead), including the inefficient utilization, abandoned, and idlerural residential land transfer market and the scattered, fragmentedagricultural land transfer market. The former focuses on theestablishment of rural homestead withdrawal with compensation, andmarket-oriented circulation mechanism, but it should be noted that thetransfer of rural collective construction land use rights into the marketmust be carried out under the premise of land use planning and land usecontrol (Liu et al., 2018); while the latter focuses on promoting thelarge-scale operation and industrialization of agricultural land bycultivating new-type agricultural management mainbody(e.g.,agricultural leading enterprises, farmer cooperatives, familyfarms, large and specialized family businesses, etc.) and adjusting theownership of fragmented fields (Long et al., 2016; Liu et al., 2019). Inaddition, the land administration department shall strengthen thesupervision and management of the transfer of land managementrights (Li et al., 2018) to protect the interests of farmers.

5.3. Limitations and future prospects

CLF is the result of dynamic processes driven by natural, economic,social, cultural, and institutional impacts. In addition to the five cate-gories of influential factors mentioned in Section 3.2, CLF is also subjectto local traditional culture, e.g., inheritance customs (Niroula andThapa, 2005), marriage, and dowry culture (Hartvigsen, 2014), etc.;institutional context, e.g., land market, land transactions, land con-tracting, management and use rights, and the duration and stability ofthese rights (Zang et al., 2019); and socio-economic changes, e.g., wars,population growth (Niroula and Thapa, 2007), etc. Particularly thetradition of land inheritance prevailing in many countries, that is, theEgalitarian principle applied in the distribution of land among house-hold heirs (Falco et al., 2010; Sklenicka et al., 2014), has made landfragmentation an on-going process, resulting in landholdings and landparcels getting smaller and smaller, and dispersed over successivegenerations (Mearns and Sinha, 1999). Although it is beyond the scopeof this paper to indulge in a full-scale discussion on the above issues dueto the limitations of data sources, they are also important factors af-fecting the CLF. Because these factors are based on fine-scale local datathat need to be sourced locally, without which it is challenging to re-search on a regional scale.

The above challenges imply that field surveys and interviews can beconducted in typical areas to quantitatively explore the mechanism ofCLF's regional differentiation under the interaction of natural, social,cultural, and institutional factors in further studies. Meanwhile, basedon the current understanding of the spatial pattern and influencingfactors of CLF, it is still necessary to further reveal the spatial-temporalevolution law and trend of CLF in a long time series and to improve theanalytical framework of CLF management that combines national/re-gional macro-scale with household/farmer micro-scale.

6. Conclusion

In this study, we employ multivariable linear regression,

geographical detectors and magic cube model to explore the spatialdifferentiation characteristics of regional CLF using three aspects: nat-ural (resource) property, spatial property and utilization property, andthe driving mechanism using multi-source data that characterize geo-graphic, land use and socio-economic information. After this, our studyfurther constructs the guiding zoning scheme for the management ofCLF in Jiangsu Province in eastern China, which offers insights intosustainable cultivated land utilization and LC practices.

The CLFI in Jiangsu shows a gradual increase from north to south,indicating the noticeable regional difference. The mean value of pro-vincial CLFI is 0.408, and the quantity structure of each level of thegrade of CLFI shows a "U-shaped" structure, which dominated bylowest- and highest-level, revealing greater polarization in CLF. TheCLFI in built-up areas is significantly higher than that outside built-upareas, and its fractal dimensions both within and outside the urbanplanning built-up areas show the spatial pattern of "spatial distribu-tion > resource endowment > convenience of utilization", which in-dicates that promoting the centralized and continuous distribution ofarable land, enhancing infrastructure construction, and improvingproduction conditions are still the critical contents of LC in the future.

The results of this study show that x7, x3, x2, x12, x10, and x5 are thedominant factors affecting the geographical differentiation of the CLF,with the influence power (q) is 0.472, 0.204, 0.133, 0.129, 0.097 and0.084, respectively. The spatial detection results of the impact factors ofCLF both within and outside the urban planning built-up areas arebasically consistent with these in provincial but with slight changes inthe ranking of individual factors, which indicates that the influenceintensity of each factor is different for different regions. In summary,location conditions and socio-economic activities have significant ef-fects on the spatial differentiation of CLF within the built-up areas,while highlighting the role of rural settlements outside urban built-upareas on CLF.

Finally, this study proposes a two-level zoning plan for optimizingthe utilization of cultivated land resources and diminishing the CLF inJiangsu based on influencing factors and fragmentation characteristics,which includes 4 first-level zones and 24 second-level zones. Each levelof zones features characteristics and relationships among different CLFin fractal dimensions and influencing factors. The proposal of trade-offzoning of CLF management can provide a feasible approach for LCspatial planning, optimal utilization of cultivated land resources andimplementation of land management policies in Jiangsu Province, aswell as a pathway to ensure food security and achieve sustainable de-velopment.

Acknowledgements

This work was supported by Nanjing University Innovation andCreative Program for PhD candidate (CXCY18-21) and National ScienceTechnology Support Plan Projects of China (2015BAD06B02).

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