Part 2: Mapped Data Analysis and Spatial Modeling Applying Map Analysis Techniques To Site-Specific Management Joseph K. Berry Berry & Associates 2000.

Part 2: Mapped Data Part 2: Mapped Data Analysis Analysis

and Spatial Modelingand Spatial Modeling

Applying Map Analysis Techniques Applying Map Analysis Techniques To Site-Specific Management To Site-Specific Management

Joseph K. BerryJoseph K. Berry

Berry & AssociatesBerry & Associates2000 South College, Suite 3002000 South College, Suite 300

Fort Collins, CO 80525Fort Collins, CO 80525

Email: Email: [email protected]@innovativegis.comWeb Site: Web Site: www.innovativegis.com/basiswww.innovativegis.com/basis

Collecting Remote Collecting Remote Sensing Data:Sensing Data:Proximal Sensing:Proximal Sensing:

• Film CamerasFilm Cameras• Video MappingVideo Mapping

Aerial Remote Sensing:Aerial Remote Sensing:• Film CamerasFilm Cameras• Video MappingVideo Mapping• ScannersScanners

Satellite Imaging:Satellite Imaging:• ScannersScanners

Utilizing Remote Sensing for PFUtilizing Remote Sensing for PF

((BerryBerry))

Normalized Density Normalized Density Vegetation Index Vegetation Index (NDVI)… plant vigor(NDVI)… plant vigor

A video camera is a A video camera is a broadband scanner broadband scanner

Demo of Video Mapping System

Geo-registrationGeo-registration is facilitated by GPS mapping is facilitated by GPS mapping ground features visible in the imageground features visible in the image

• IntersectionsIntersections• Well pivotsWell pivots

• Building cornersBuilding corners• Grain bins, etc.Grain bins, etc.

++

GPS Video SurveyGPS Video Survey ““Raw” Aerial ImageryRaw” Aerial Imagery

Dycam ImageDycam Image

(Preliminary study, Colorado State University, Soil and Crop Sciences )(Preliminary study, Colorado State University, Soil and Crop Sciences )

Geo-Registration of ImageryGeo-Registration of Imagery

Georegistered image/dataGeoregistered image/data== …”…”rubber-sheet” corrections rubber-sheet” corrections remove image geometric distortionsremove image geometric distortions

……in effect, it is like printing the in effect, it is like printing the image on a rubber sheet then image on a rubber sheet then

stretching the image to fit the GPS stretching the image to fit the GPS featuresfeatures

……inside Cessna, M-VMS, Dycam, inside Cessna, M-VMS, Dycam, 35mm, camcorder and battery35mm, camcorder and battery

(Preliminary study, Colorado State University, Soil and Crop Sciences )(Preliminary study, Colorado State University, Soil and Crop Sciences )

Geo-Registered ResultGeo-Registered Result

Belly-Belly-PortPort

M-VMSM-VMS

Camcorder Camcorder and batteryand battery

DycamDycam

……Electromagnetic SpectrumElectromagnetic Spectrum (Light (Light++))

……incoming light is incoming light is preferentially preferentially absorbed (reflected) absorbed (reflected) depending on plant depending on plant physiologyphysiology

SpeciesSpecies PhotosynthesisPhotosynthesis Water ContentWater Content

((BerryBerry))

Related Spatial Technologies (RS)Related Spatial Technologies (RS)

[1][1]

[2][2]

[3][3]

[4][4]

Linking NDVI to Nitrogen LevelsLinking NDVI to Nitrogen Levels

Nitrogen TreatmentNitrogen TreatmentNDVI NDVI

(Preliminary study, Wright, Red Hen Systems,)(Preliminary study, Wright, Red Hen Systems,)

……there appears to be a strong relationship between NDVI there appears to be a strong relationship between NDVI measurements from remotely sensed data and nitrogen measurements from remotely sensed data and nitrogen application levelsapplication levels

Delineating ZonesDelineating Zones

(Wright & Berry)(Wright & Berry)

Visible Visible differences in differences in an aerial an aerial image can be image can be used to used to delineate delineate portions of a portions of a field that field that have have consistent consistent texture and texture and color color (Management (Management Zones). Zones). The zones are The zones are assumed to assumed to have have consistent consistent levels for each levels for each of the field’s of the field’s driving driving variables variables (uniform (uniform conditions)conditions)

Mgt Zones vs. Map SurfacesMgt Zones vs. Map Surfaces …the …the

bottomlinebottomline ……both approaches “carve” a field into smaller pieces to both approaches “carve” a field into smaller pieces to better represent the unique conditions and patterns better represent the unique conditions and patterns occurring in the field. Zones pre-partitions it into occurring in the field. Zones pre-partitions it into relatively large, irregular areas that are assumed to be relatively large, irregular areas that are assumed to be homogenous—homogenous—discrete polygonsdiscrete polygons. Surfaces, on the other . Surfaces, on the other hand, process field samples for an estimate of each hand, process field samples for an estimate of each factor at grid cells throughout a uniform analysis grid—factor at grid cells throughout a uniform analysis grid—continuous gradientcontinuous gradient..

……relationships relationships among among Surfaces Surfaces (data (data layers) are layers) are easily easily investigatedinvestigated

No map analysis No map analysis is possible with is possible with Management ZonesManagement Zones ((BerryBerry))

Air Photo (Air Photo (soil soil colorcolor))

NIR (R)

Red (G)

Green (B)(Beyond our sight)(Beyond our sight) Color Infrared Color Infrared

P

K

ph

etc.etc.

RS Imagery as GIS Data LayersRS Imagery as GIS Data Layers

Remote sensing Remote sensing images are composed images are composed of numbersof numbers, just like , just like any other map in a any other map in a grid-based GIS…grid-based GIS…

““Mapematical Mapematical Processing”Processing”

1481485252

2626

4444

4343

257257

7.27.2

4646

3434

5757

312312

7.57.5

((BerryBerry))

A RS image is just a A RS image is just a ““shishkebab shishkebab of numbersof numbers” like ” like any other any other grid map grid map (raster)(raster)

ImageImage

The Precision Farming ProcessThe Precision Farming Process

5.00 10.00 15.00 20.00 25.00 30.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

Zone 3

Zone 2

Zone 1

As a combine moves through a field As a combine moves through a field 1)1) it uses GPS it uses GPS to check its location then to check its location then 2)2) checks the yield at that location to checks the yield at that location to 3)3) create a create a continuous map of the yieldcontinuous map of the yield variation every few feet. This variation every few feet. This map map 4)4) is combined is combined with soil, terrain and other with soil, terrain and other maps to derive amaps to derive a 5)5) “ “Prescription MapPrescription Map” that is ” that is used to adjustused to adjust fertilization levels every few fertilization levels every few feet in the fieldfeet in the field

(Cyber-Farmer, Circa 1990)(Cyber-Farmer, Circa 1990)

Variable Rate ApplicationVariable Rate Application

Prescription MapPrescription Map

Farm dBFarm dB

Map AnalysisMap Analysis

On-the-Fly On-the-Fly Yield MapYield Map

Steps 1)–3)Steps 1)–3)

Step 4)Step 4) Step 5)Step 5)

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Step 3:Step 3: Data AnalysisData AnalysisMap InsightsMap Insights (Univariate-- within a single map)(Univariate-- within a single map)

• Standard Normal Variable (SNV) MapsStandard Normal Variable (SNV) Maps• Coefficient of Variation (CoffVar) MapsCoefficient of Variation (CoffVar) Maps• Slope/Aspect (Spatial Derivative) MapsSlope/Aspect (Spatial Derivative) Maps

Relating MapsRelating Maps (Multivariate-- among maps)(Multivariate-- among maps)• Map Comparison Map Comparison

Difference Difference %Change%Change Difference TestsDifference Tests

• Corresponding Areas Corresponding Areas CoincidenceCoincidenceMap SimilarityMap SimilarityClusteringClustering

• Prescriptive StatisticsPrescriptive StatisticsRegressionRegressionTrend SurfacesTrend SurfacesSpatial Data MiningSpatial Data Mining

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A A histogramhistogram depicts the depicts the numerical numerical distributiondistribution

A A map map depicts the depicts the geographical geographical distributiondistribution ……the data the data

values link values link the two the two views—views—

Click Click anywhere on anywhere on the map and the map and the the histogram histogram interval is interval is highlighted; highlighted; click on a click on a histogram histogram interval and interval and the map the map locations are locations are highlightedhighlighted

Linking Data and Map Linking Data and Map DistributionsDistributions

(Berry)(Berry)

PreprocessingPreprocessing involves conversion of raw data into consistent involves conversion of raw data into consistent units that accurately represent field conditions.units that accurately represent field conditions.

CalibrationCalibration - translates signals into measurements of - translates signals into measurements of crop production units, such crop production units, such as bushels per acre (measure of volume) or tons per as bushels per acre (measure of volume) or tons per hectare (measure of mass). hectare (measure of mass).

AdjustmentsAdjustments - “tweaking” the values… sort of like a - “tweaking” the values… sort of like a slight turn on that bathroomslight turn on that bathroom scale to alter the reading to what you know is your scale to alter the reading to what you know is your true weight. true weight.

CorrectionsCorrections - dramatically changes the measurement - dramatically changes the measurement values, such as after the massvalues, such as after the mass flow correction to GPS coordinates flow correction to GPS coordinates

Preprocessing and Map Preprocessing and Map NormalizationNormalization

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NormalizationNormalization involves standardization of a data set, usually for involves standardization of a data set, usually for comparison among different types of data. comparison among different types of data.

GoalGoal - Norm_GOAL = (mapValue / 250 ) * 100 - Norm_GOAL = (mapValue / 250 ) * 100

0-1000-100 - Norm_0-100 = ((mapValue – min) * 100) / (max – - Norm_0-100 = ((mapValue – min) * 100) / (max – min)min)

SNVSNV - Norm_SNV = ((mapValue - mean) / stdev) * 100 - Norm_SNV = ((mapValue - mean) / stdev) * 100

Since normalization Since normalization involves scalar involves scalar mathematics (constants), mathematics (constants), the pattern of the the pattern of the numeric distribution numeric distribution (histogram) and the (histogram) and the spatial distribution (map) spatial distribution (map) doesn’t changedoesn’t change

……same relative same relative distributionsdistributions

Preprocessing and Map Preprocessing and Map NormalizationNormalization

((BerryBerry))

Applying the MapCalc equation…Applying the MapCalc equation… Norm_GOAL = (Yield_Vol / 250 ) * 100Norm_GOAL = (Yield_Vol / 250 ) * 100……generates a standardized map based on a yield goal of generates a standardized map based on a yield goal of 250 bushels/acre. This map can be used in analysis with 250 bushels/acre. This map can be used in analysis with other goal-normalized maps, even from different cropsother goal-normalized maps, even from different crops

Assessing Localized Variation in Assessing Localized Variation in YieldYield

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Scan Yield_Volume Scan Yield_Volume Coffvar Coffvar Within 2 Within 2 For Yield_CoffvarFor Yield_Coffvar

Where,Where, Coffvar= Coffvar= Stdev/mean *100Stdev/mean *100

The “Scan” operation moves a The “Scan” operation moves a window around the yield map and window around the yield map and calculates the Coefficient of calculates the Coefficient of Variation with a 2-cell radius of Variation with a 2-cell radius of each locationeach location

……higher values indicate higher values indicate areas with more areas with more localized variabilitylocalized variability

Assessing Rate of Change in YieldAssessing Rate of Change in Yield

((BerryBerry))

Slope Slope 1997_Yield_Volume 1997_Yield_Volume Fitted Fitted For Yield_SlopeFor Yield_Slope

Where,Where, Slope= Rise/Run Slope= Rise/Run *100*100

The “Slope” operation moves a The “Slope” operation moves a window around the yield map and window around the yield map and calculates the inclination (rate of calculates the inclination (rate of change) in yield of neighboring change) in yield of neighboring cellscells

……higher values indicate higher values indicate areas with rapidly areas with rapidly changing productivitychanging productivity

UnivariateUnivariate analysis investigates relationships within a single map analysis investigates relationships within a single map

• SlopeSlope ~ rate of change (spatial derivative) of each surface element (grid cell) ~ rate of change (spatial derivative) of each surface element (grid cell)

• AspectAspect ~ orientation (direction) of each surface element ~ orientation (direction) of each surface element

The slope and aspect of an elevation surface (altitude derived from a surveyed points or The slope and aspect of an elevation surface (altitude derived from a surveyed points or rectified orthophotos) identifies terrain steepness and orientation; example uses include rectified orthophotos) identifies terrain steepness and orientation; example uses include road-building and water runoff modeling road-building and water runoff modeling The slope and aspect of a barometric surface (air pressure gradient derived from a set The slope and aspect of a barometric surface (air pressure gradient derived from a set weather station data) estimates wind speed and directionweather station data) estimates wind speed and directionThe slope and aspect of a thermal gradient in a lake (generated from remote sensing data The slope and aspect of a thermal gradient in a lake (generated from remote sensing data of surface temperature) identifies rate and direction of cooling from a thermal input of surface temperature) identifies rate and direction of cooling from a thermal input (nuclear powerplant ponds)(nuclear powerplant ponds)The slope and aspect of a total revenue surface (generated by summing the cash flow The slope and aspect of a total revenue surface (generated by summing the cash flow stream for each surface element) identifies a marginal revenue surface which shows the stream for each surface element) identifies a marginal revenue surface which shows the spatial distribution of relative cash flowspatial distribution of relative cash flowThe slope and aspect of a proximity surface determines the speed and direction of the The slope and aspect of a proximity surface determines the speed and direction of the optimal movement in traversing each surface element optimal movement in traversing each surface element ……what would the slope of a slopemap show? …the aspect of a slopemap?what would the slope of a slopemap show? …the aspect of a slopemap?

Analysis“Within” A SurfaceAnalysis“Within” A Surface

((BerryBerry))

UnivariateUnivariate analysis investigates relationships within a map surface analysis investigates relationships within a map surface

• Aggregation Aggregation ~ sum of the values for all or a portion of the surface elements ~ sum of the values for all or a portion of the surface elements (spatial integral); example uses include cut/fill calculations in road building and total (spatial integral); example uses include cut/fill calculations in road building and total yield estimates in precision farming yield estimates in precision farming

• Coefficient of VariationCoefficient of Variation ~ localized variation surrounding each surface ~ localized variation surrounding each surface element (surface roughness)element (surface roughness)

• Mathematical TranslationsMathematical Translations ~ scalar arithmetic, logarithmic, trigonometric ~ scalar arithmetic, logarithmic, trigonometric and logical operations; example use of taking the cosine of the zenith angle formed and logical operations; example use of taking the cosine of the zenith angle formed between the sun’s position and each elevation surface element to calculate insolation between the sun’s position and each elevation surface element to calculate insolation (sun energy at each location)(sun energy at each location)

• Statistical OperationsStatistical Operations ~ describe and characterize a surface ~ describe and characterize a surface

Descriptive statistics (min. max, range, median, mode, mean, skewness…)Descriptive statistics (min. max, range, median, mode, mean, skewness…) Similarity assessment (spatial autocorrelation)Similarity assessment (spatial autocorrelation) Predictive statistics (map generalization and interpolation)Predictive statistics (map generalization and interpolation) Accuracy assessment (residual analysis of how well a surface fits a data set)Accuracy assessment (residual analysis of how well a surface fits a data set)

• Other “Stuff”Other “Stuff” ~ standard Normal Variable Surface; pattern recognition filters ~ standard Normal Variable Surface; pattern recognition filters

Analysis“Within” A Surface Analysis“Within” A Surface ……

continuedcontinued

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Visual Analysis of 2D MapsVisual Analysis of 2D Maps

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Data Analysis Data Analysis (Visual comparison)(Visual comparison)

……so what do these maps tell you (so what do these maps tell you (Data AnalysisData Analysis)? )?

……what management actions should be taken and where (what management actions should be taken and where (Spatial Spatial ModelingModeling)?)?

Top-soil Phosphorous Bottom-soil Top-soil Phosphorous Bottom-soil Phosphorous Phosphorous

Mapped Data Analysis of Map SurfacesMapped Data Analysis of Map Surfaces

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Data Analysis Data Analysis (Map-ematical comparison)(Map-ematical comparison)

Top-soil PhosphorousTop-soil Phosphorous

Bottom-soil PhosphorousBottom-soil Phosphorous

Phosphorous DifferencePhosphorous Difference

……Top-Bottom values are subtracted for each location (Top-Bottom values are subtracted for each location (Map-Map-ematicsematics)?)?

Visualizing Difference Map (2D)Visualizing Difference Map (2D)

((BerryBerry))

Data Analysis Data Analysis (Difference map)(Difference map)

……add more Phosphorous just where it is needed (add more Phosphorous just where it is needed (Spatial Spatial ModelingModeling)?)?

((BerryBerry))

Data AnalysisData Analysis (visually comparing maps)(visually comparing maps)

What differences do you see? What differences do you see? …where …where did yield change significantly? …where did it did yield change significantly? …where did it

stay about the same? stay about the same?

((BerryBerry))

Data AnalysisData Analysis (comparing discrete maps)(comparing discrete maps)

((BerryBerry))

Data AnalysisData Analysis (discrete maps vs. continuous (discrete maps vs. continuous

surfaces)surfaces)

Discrete maps= intervals Continuous Discrete maps= intervals Continuous surfaces= values surfaces= values

Comparing Map SurfacesComparing Map Surfaces (Difference (Difference

map)map)

((BerryBerry))

……greengreen indicates indicates areas of increased areas of increased productionproduction

……yellowyellow indicates indicates minimal changeminimal change

……redred indicates indicates decreased productiondecreased production

1997_Yield_Volume1997_Yield_Volume- 1998_Yield_Volume- 1998_Yield_Volume

Yield_DiffYield_Diff

Map VariablesMap Variables… map values within … map values within an analysis grid can be an analysis grid can be mathematically and statistically mathematically and statistically analyzed analyzed

((BerryBerry))

Data AnalysisData Analysis (assessing spatial patterns)(assessing spatial patterns)

What What spatial spatial relationshirelationships do you ps do you see?see?

……do do relatively relatively high levels high levels of P often of P often occur with occur with high levels high levels of K and N?of K and N?……how often?how often?……where?where?

((BerryBerry))

Data AnalysisData Analysis (assessing spatial patterns)(assessing spatial patterns)

Data Clustering identifies of similar data Data Clustering identifies of similar data patterns– Management Zones patterns– Management Zones

……the “data shishkebab” for each grid location is the “data shishkebab” for each grid location is sent to a statistical algorithm that divides the data sent to a statistical algorithm that divides the data set into groups that are 1) as similar within each set into groups that are 1) as similar within each

group and 2) as different between groups as group and 2) as different between groups as possible possible

Investigating Surface Correlation Investigating Surface Correlation (predictive model)(predictive model)

Histogram/Map Histogram/Map ViewView

Data SpaceData Space (magnitude of values)(magnitude of values)

are linked toare linked to

Geographic SpaceGeographic Space (position of (position of values)values)

Histogram/Map Histogram/Map ViewView

Data SpaceData Space (joint magnitude of (joint magnitude of values)values)

are linked toare linked to

Geographic SpaceGeographic Space (position of (position of values)values)

(Berry)(Berry)

Investigating Surface Correlation Investigating Surface Correlation (error analysis)(error analysis)

(Berry)(Berry)

……a predicted surface is compared to actual data (% difference map) for an assessment of a predicted surface is compared to actual data (% difference map) for an assessment of overall performance and spatial pattern of errors. In this instance, the model is a good overall performance and spatial pattern of errors. In this instance, the model is a good predictor within the partitioned area but poor along the west and north edges.predictor within the partitioned area but poor along the west and north edges.

On-Farming TestingOn-Farming Testing — — Investigating the Effects of AlternativesInvestigating the Effects of Alternatives

((BerryBerry))

Data Analysis Data Analysis (establishing relationships)(establishing relationships)

Step 4:Step 4: Spatial Model Spatial Model

Knowledge-Based RelationshipsKnowledge-Based Relationships —— evaluates spatial relationships given input map dataevaluates spatial relationships given input map data

• Look-Up Table Look-Up Table If-Then RulesIf-Then Rules Expert SystemsExpert Systems

• Evaluating Functions Evaluating Functions EquationsEquations

• Optimization Techniques Optimization Techniques Linear ProgrammingLinear Programming Induction ModelingInduction Modeling Genetics ModelingGenetics Modeling TessellationTessellation

((BerryBerry))

Spatial Data MiningSpatial Data Mining ——new technology (CART) that is new technology (CART) that is based on large sample size, repetitive data grouping and data driven based on large sample size, repetitive data grouping and data driven to develop more accurate prediction equations than traditional to develop more accurate prediction equations than traditional statisticsstatistics

((BerryBerry))

……a new a new application of the application of the Spatial Spatial TechnologiesTechnologies

……that utilizes that utilizes spatial spatial relationships in a relationships in a field for site-field for site-specific specific managementmanagement

Precision Farming’s Big Precision Farming’s Big PicturePicture

So Where Are We in Precision So Where Are We in Precision Farming?Farming?

((BerryBerry))

...Gaps in Our “Thinking”...Gaps in Our “Thinking”

• Limited ApproachLimited Approach – Mapping vs. Data Analysis; Tools vs. Mapping vs. Data Analysis; Tools vs. ScienceScience

• Science LinkScience Link – “Scientific “Scientific Method” Doctrine, The “Random” Method” Doctrine, The “Random” Thing, Appropriate Driving Variables, Thing, Appropriate Driving Variables, Correlation vs. Causation Correlation vs. Causation

• Market ConfusionMarket Confusion – Empirical Verification, Economic Empirical Verification, Economic Validation, Rationalization Validation, Rationalization (Productivity vs. Stewardship)(Productivity vs. Stewardship)

Underlying Issues In Precision Underlying Issues In Precision FarmingFarming

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The Environmental The Environmental Trump CardTrump Card

Characterizing SlopeCharacterizing SlopeA digital terrain surface is formed by A digital terrain surface is formed by assigning an elevation value to each assigning an elevation value to each cell in an analysis grid. The “slant” of cell in an analysis grid. The “slant” of the terrain at any location can be the terrain at any location can be calculated—calculated— inclination of a plane inclination of a plane fitted to the elevation values of the fitted to the elevation values of the immediate vicinity immediate vicinity

Micro Terrain AnalysisMicro Terrain Analysis (Slope and Flow)(Slope and Flow)

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Characterizing Surface FlowCharacterizing Surface FlowA map of surface flow is simulated by A map of surface flow is simulated by aggregating the “steepest downhill aggregating the “steepest downhill paths” from each cell— confluence paths” from each cell— confluence

Slope and Flow maps draped over vertically exaggerated terrain surface

Calibrating Slope and Flow Classes: Calibrating Slope and Flow Classes: Areas of Gentle, Moderate, and Areas of Gentle, Moderate, and Steep slopes are identified; areas of light, moderate and heavy flows are identifiedSteep slopes are identified; areas of light, moderate and heavy flows are identified

Micro Terrain AnalysisMicro Terrain Analysis (Slope and Flow)(Slope and Flow)

((BerryBerry))

Determining Erosion Potential: Determining Erosion Potential: The slope and flow classes are The slope and flow classes are combined into a single map identifying erosion potentialcombined into a single map identifying erosion potential

Micro Terrain AnalysisMicro Terrain Analysis (a simple erosion (a simple erosion model)model)

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(Berry)(Berry)

Effectively far away, though right near a stream …how can that be? …what about different soils? …what about roughness? …or time of year?

Micro Terrain AnalysisMicro Terrain Analysis (extending the (extending the erosion model)erosion model)

Simple Buffer

Precision Farming… an Precision Farming… an Oxymoron?Oxymoron?

What are your What are your thoughts…thoughts…

Are there spatial Are there spatial variations in variations in agricultural fields?agricultural fields?

Is our technology Is our technology able to “precisely” able to “precisely” measure the spatial measure the spatial variations?variations?

Can we derive and Can we derive and validate the spatial validate the spatial relationships in the relationships in the patterns?patterns?

Can we develop Can we develop and implement and implement spatially-based spatially-based management management actions?actions?

Are you burnt out yet?Are you burnt out yet?

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PF Case StudyPF Case Study (uses MapCalc (uses MapCalc Learner software)Learner software)

www.innovativegis.com/basis www.innovativegis.com/basis Online text and Case StudyOnline text and Case Study

More Information on PF Data More Information on PF Data AnalysisAnalysis

((BerryBerry))

www.agriculture.com/technology/www.agriculture.com/technology/

Online articles and active discussion forum on Online articles and active discussion forum on technologytechnology

……the MapCalc Learner CD the MapCalc Learner CD contains a copy of the Precision contains a copy of the Precision Farming Primer and the Farming Primer and the agriculture data set used in the agriculture data set used in the case Studycase Study

www.redhensystems.comwww.redhensystems.com

www.innovativegis.com/basis www.innovativegis.com/basis ……select Precision Farming Primer then click on select Precision Farming Primer then click on

Appendix EAppendix E

Online PowerPoint Slide SetOnline PowerPoint Slide Set

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……tuned for Internet Explorer 4.0+ and can have problems with some Netscape versionstuned for Internet Explorer 4.0+ and can have problems with some Netscape versionsView in “Medium Text” mode; size window to fit the slidesView in “Medium Text” mode; size window to fit the slides