Remote Sensing FIGARO FINAL - Figaro Irrigation … of Remote sensing in irrigationmanagement • Calcultationof CropWaterRequirements(CWR) • Estimation crop coefficients (k c) from

FLEXIBLEANDPRECISEIRRIGATIONPLATFORMTOIMPROVEFARM‐SCALEWATERPRODUCTIVITY

FIGARO

RemotesensinginFIGARO

FinalMeeting,Brussels19/09/2016TechnicalUniversityofValencia

UseofRemote sensing inirrigation management

• Calcultation ofCropWater Requirements (CWR)• Estimationcropcoefficients(kc)fromremotelysensedvegetationindices(VI)

• Surfaceenergy balancemethods (SEB)

– Cropmonitoring• Cropmapping• Physiologycal parameters (Leaf Area Index,Biomass,GroundCover…)• Irrigation assesment (Seasonal Irrigation PerformanceIndex)

– Crop water stressdetection• CropWater StressIndex (CWSI‐Temperature)• PhotochemicalReflectanceIndex (PRI)• WaterDeficitIndex(WDI)

• CalcultationofCropWater Requirements (CWR)– Estimationcropcoefficients(kc)fromremotelysensedvegetationindices(VI)

; ; ;

Crop Kcb Parameter Reference

Vine (wine) Kc = 1.44*NDVI ‐ 0.10 Kc = 1.79*SAVI ‐ 0.08  

NDVI;SAVI Campos et al 2010

Vine(Table grape) Kc = 0.008 + 0.017*GC GC(%) Williams et al(2005)

Citrus Kc= 0.0283 + (0.0203 *GC) ‐ (0.00017*GC2)

GC(%) Castel (2000)

Potato Kc = 0.0504+1.085 SAVI SAVI Jayanthi et al (2007)

Cotton Kc = 1.49 NDVI ‐ 0.12 (early vegetative)Kc=2.80 NDVI ‐1.17 (Afterfull cover)

NDVI Hunsaker et al (2003)

Corn (Irrigated) Y = 1.317 NDVI + 0.023 NDVI Singh and Imak(2009)

Processing Tomato Kc = 0.126 + (0.0172)*GC‐(0.0000776*GC2)

GC(%) Hanson and May(2006)

Remote sensing inFIGARO

Ground cover is the physiologic parameter used by Aquacrop

• CalcultationofCropWater Requirements (CWR)– Estimationcropbasalcoefficients(kc)fromremotelysensedvegetationindices(VI)

• Advantages– Onlyfewbandsarerequired(visibleandNIR)– Easycomputation

• Drawbacks– Empiricalformulasarecalculatedwithlocaldata– Tousespecifickc acropmapisrequired– Novegetationstressisdetected– Spatialresolutioncannotbeaccurateenoughtocalculateparametersasgroundcoverfordiscontinuouscanopies

NDVI mapValencia region

Remote sensing inFIGARO

IrrrigationassessmentIrrrigationassessment

IrrrigationschedulingIrrrigationscheduling

RSinputsincrop models•Fao model

Ground cover is related with KcGround cover is related with Kc

Ground cover

Agroclimaticstations

Crop waterrequirements

(CWR)

Kcavg = 0.0283 + (0.0203 x GC) ‐ (0.00017 x GC2)Kcavg = 0.0283 + (0.0203 x GC) ‐ (0.00017 x GC2)

CropCoefficient

Water registered (V)

Seasonal IrrigationPerformance Index

SIPI=CWR/V

EstimatesET withoutcrop waterrestriction

Remote sensing inFIGARO

Remote sensing inFIGARO

Seasonal Irrigation PerformanceIndex.Picassentirrigation districtSIPI=CWR/V

SIPI 2014 SIPI 2015

Usedimagery

Remote sensing inFIGARO

• USed PNOA(National PlanofAerial Ortophoto,Spain)

Radiometric resolution:R,G,B,IR Spatial resolution:0.25m Temporalresolution:2years Datasetsavalaible:2006‐2008‐2010‐2012(July)

Rapideye Radiometric resolution

Spatial resolution:5m Temporalresolution:1‐5days

60mspatial resolution bands

• Usedimagery

Remote sensing inFIGARO

Sentinel 2(Images avaliable from January 2016)

10mspatial resolution bands

20mspatial resolution bands

10mSentinel 2 10 m

Band number Central wavelength

(nm)

Bandwidth(nm)

2 490 65

3 560 35

4 665 30

8 842 (NIR) 115

Band number Central wavelength

(nm)

Bandwidth(nm)

5 705 15

6 740 15

7 783 20

8a 865 (NIR) 20

11 1 610 90

12 2 190 180

Band number

Central wavelength

(nm)

Bandwidth(nm)

1 443 20

9 945 20

10 1 375 30

Useofdifferentspatialresolutionimages

Remote sensing inFIGARO

Ortophoto high spatial resolution, low temporal resolution.

RapidEyemedium spatial resolution, high temporal resolutionresolution.

Obtained from simultanous images in july 2012

• CalcultationofCropWater Requirements (CWR)

– Surfaceenergy balancemethod (SEB)

Amodelthatcalculatesthelatentheat(ET),asaresidualofthesurfaceenergybalance.Sensibleheat(H)iscalculatedusingtheradiometricsurfacetemperatureobtainedfromthethermalbandimagery

UseofRemote sensing inirrigation management

(Bastiaanssen et al 2002)

• Calcultation ofCropWater Requirements (CWR)

– Surfaceenergy blance methods (SEB)

• Advantages– Actualevapotranspirationiscalculated– Vegetationstresscanbedetected

• Drawbacks– Thermalbandneeded– ETinstantaneoushastobeextrapolated.– Platformsensorshasacoarsespatialresolutionforthermalband(Landsat8,30m)

UseofRemote sensing inirrigation management

ET mapcalculatedby SEBAL

Remote sensing inFIGARO

2013: 13 avalaible images out of 28

2015: 20 avalaible images out of 28

2014: 14 avalaible images out of 28

year 2014

Spanishcasestudy(citrus)Landsatimageswereused:Temporalresolution:16days

Two scenes overlap on the citrus pilot site (199‐33 and 198‐33) Images avalaible each 7 and 9 days

• Irrigation procedure– Each timeaLandsat 8image freeofclouds is avalaible,actualETis

estimated anddownscaled todaily values.

– ETFAO Vol‐1>1,it is assumed that crop is irrigated less than required– ETFAO Vol‐1<1 ,it is assumed that crop is irrigatedmorethan required

– ETSEBALETFAO‐1>1,actualETis higher than potential– ETSEBALETFAO‐1<1, actualETis lower than potential

Citrustestsite

Flexible and precIse irriGation plAtform to improve faRm scale water prOductivity Slide13

• Irrigation procedure

Citrustestsite

Flexible and precIse irriGation plAtform to improve faRm scale water prOductivity Slide14

22 plots were selected(0,3‐3,5 ha)

• SEBAL is amethodology that canbeused for irrigationscheduling atirrigation district level

• It is able todetect those plots that sufferwater stressdue toitestimates theactualevapotrasnpiration instead ofpotentialevapotrasnpiration

• Along with models based on the vegetation indices (Castel,2000)andvolume readings,it allows performwater stressmaps forlarge areas

• The disadvantges arethecloudy days andthesmall spatialresolution by now

Remote sensing inFIGARO

• Architecture

Remote sensing inFIGARO

U‐Manage

III Jornada sobre Gestión Eficiente del Agua de Riego 17

Rapid Eye Deimos Spot 7

Spot 6

Landsat 8Sentinel 2

Landsat 7