SlideShare una empresa de Scribd logo
1 de 15
Descargar para leer sin conexión
Remote sensing based yield
model and application to major
exporting countries
B. Franch1,2, E. Vermote3, Sergii Skakun2,3, Jean-Claude Roger2,3,
I. Becker-Reshef2, C. Justice2,3
1 Global Change Unit, Image Processing Laboratory, Universitat de Valencia,
Paterna, 46980 Valencia, Spain
2 Department of Geographical Sciences, University of Maryland,
College Park MD 20742, United States
3 NASA Goddard Space Flight Center, 8800 Greenbelt Road,
Greenbelt, MD 20771, United States
befranch@umd.edu
Land Climate Data Record
Multi instrument/Multi sensor Science Quality Data Records used to
quantify trends and changes
Why do we use coarse resolution?
Emphasis on data consistency
Coarse (250m) Moderate (30m) Fine (5m)
Problems when working with coarse spatial
resolution data
Basis: Strong correlation between NDVI Peak and yield
Tucker 1980, Hatfield 1983, Benedetti 1993, Doraiswamy 1995, Rasmussen 1997, Mika 2002
Becker-Reshef I, Vermote E, Lindeman M, Justice C. 2010. In Remote Sensing of Environment, 114, 1312–1323.
Previous remote sensing methods
(Becker-Reshef et al., 2010)
USA (MODIS) USA (AVHRR)
Franch, B., Vermote, E., Roger, J.C., Murphy, E., Becker-Reshef, I., Justice, C., Claverie, M., Nagol, J., Csiszar, I., Meyer, D., Baret, F.,
Masuoka, E., Wolfe, R. and Devadiga, S., (2017) A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to
wheat yield monitoring, Remote Sensing, 9, 296
Improvement of the method
The NDVI peak occurs around
1 month prior to the harvest
(earliest forecast using this
method)
Inclusion of an additional
parameter (the Growing Degree
Days, GDD) to improve the
timeliness of the prediction
YIELD MONITORING
Franch, B., E. F. Vermote, I. Becker-Reshef, M. Claverie, J. Huang, J. Zhang, C. Justice and J. A. Sobrino, 2015. Remote Sensing of Environment
Tbase = 0 °C
Improvement of the method
The NDVI peak occurs around
1 month prior to the harvest
(earliest forecast using this
method)
Inclusion of an additional
parameter (the Growing Degree
Days, GDD) to improve the
timeliness of the prediction
YIELD MONITORING
Franch, B., E. F. Vermote, I. Becker-Reshef, M. Claverie, J. Huang, J. Zhang, C. Justice and J. A. Sobrino, 2015. Remote Sensing of Environment
Tbase = 0 °CReliable estimation (10% error) between 1-
1.5 month prior to the peak NDVI (meaning
2-2.5 months prior to harvest)
USA
For each AU and a given date, the total DVI signal from each
pixel can be written as:
𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖 = 𝐷𝐷𝐷𝐷𝐷𝐷𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 − 𝐷𝐷𝐷𝐷𝐷𝐷𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 � 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑖𝑖 + 𝐷𝐷𝐷𝐷𝐷𝐷𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
DVIwheat : DVI signal from the wheat
DVIothers: DVI from other surfaces within the pixel
Wpct: percentage of wheat within the pixel or wheat purity
MODIS 1km RGB (2/21/2017)
Harper county (Kansas)
2017 wheat mask (from CDL)
Harper county (Kansas)
Franch, B., Vermote, E. F., Skakun, S., Roger, J. C., Becker-Reshef, I., Murphy, E., & Justice, C. (2019). Remote sensing based yield monitoring:
Application to winter wheat in United States and Ukraine. International Journal of Applied Earth Observation and Geoinformation, 76, 112-127.
100%
0%
New method
Calibration equations
For each AU, a separate linear regression was built with different combinations
of regressors
Seasonal Peak Peak length
Input parameters
Evaporative Fraction
(after the peak)
New method
US winter wheat validation
County level validation National level validation
Black dots: each
county and year
from 2001-2016
Red dots: each
county in 2017
Application to other countries
60% of the global
wheat exports in 2018
Yield forecasting
Working on adapting Franch et al. (2015) to the new method
County level validation National level validation
US corn validation
County level validation National level validation
US soybean validation
Conclusions
• A generic crop yield simple regression model has been developed
based on a the “wheat” DVI at the peak of the growing process, the
length of the peak and EF information.
• Can estimate yield for the main wheat exporting countries with an
accuracy
– 7% at national level
– 15% at sub-national level
• The new method shows high correlation with official statistics and
captures well extreme yield conditions (maximum and minimum).
Freezing and flooding is still a problem
• First results on yield forecasting show promising results
• The model is also applicable to other cereals (corn and soybean)

Más contenido relacionado

La actualidad más candente

Ciat crop modeling_18may11
Ciat crop modeling_18may11Ciat crop modeling_18may11
Ciat crop modeling_18may11
CIAT
 
U.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptx
U.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptxU.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptx
U.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptx
grssieee
 
Lwasa ews project poster2 1
Lwasa ews project poster2 1Lwasa ews project poster2 1
Lwasa ews project poster2 1
cenafrica
 
Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012
Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012
Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012
Decision and Policy Analysis Program
 

La actualidad más candente (20)

Ciat crop modeling_18may11
Ciat crop modeling_18may11Ciat crop modeling_18may11
Ciat crop modeling_18may11
 
Using empirical and mechanistic models to predict crop suitability and produc...
Using empirical and mechanistic models to predict crop suitability and produc...Using empirical and mechanistic models to predict crop suitability and produc...
Using empirical and mechanistic models to predict crop suitability and produc...
 
AKADEMIYA2063-Ecowas Regional Learning event: Food Crop Production during the...
AKADEMIYA2063-Ecowas Regional Learning event: Food Crop Production during the...AKADEMIYA2063-Ecowas Regional Learning event: Food Crop Production during the...
AKADEMIYA2063-Ecowas Regional Learning event: Food Crop Production during the...
 
Quantifying trends of rainfall and temperature extremes over Central Tanzania...
Quantifying trends of rainfall and temperature extremes over Central Tanzania...Quantifying trends of rainfall and temperature extremes over Central Tanzania...
Quantifying trends of rainfall and temperature extremes over Central Tanzania...
 
Highly Organised, Disruptive Big Data Science in CIAT
Highly Organised, Disruptive Big Data Science in CIATHighly Organised, Disruptive Big Data Science in CIAT
Highly Organised, Disruptive Big Data Science in CIAT
 
Julian R - Using the EcoCrop model and database to forecast impacts of cc
Julian R - Using the EcoCrop model and database to forecast impacts of ccJulian R - Using the EcoCrop model and database to forecast impacts of cc
Julian R - Using the EcoCrop model and database to forecast impacts of cc
 
Solar power
Solar powerSolar power
Solar power
 
U.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptx
U.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptxU.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptx
U.S.NationalAgriculturalLandCoverMonitoring_Mueller.pptx
 
Lwasa ews project poster2 1
Lwasa ews project poster2 1Lwasa ews project poster2 1
Lwasa ews project poster2 1
 
Collaborative evaluation opportunities in Africa RISING Phase II
Collaborative evaluation opportunities in Africa RISING Phase IICollaborative evaluation opportunities in Africa RISING Phase II
Collaborative evaluation opportunities in Africa RISING Phase II
 
Fer, Istem: Operational decision tools for climate change mitigation: a case ...
Fer, Istem: Operational decision tools for climate change mitigation: a case ...Fer, Istem: Operational decision tools for climate change mitigation: a case ...
Fer, Istem: Operational decision tools for climate change mitigation: a case ...
 
Monitoring and evaluation of Africa RISING: Results and achievements from Pha...
Monitoring and evaluation of Africa RISING: Results and achievements from Pha...Monitoring and evaluation of Africa RISING: Results and achievements from Pha...
Monitoring and evaluation of Africa RISING: Results and achievements from Pha...
 
Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012
Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012
Mer F - Use of climate predictions for impact studies, Nairobi Aug 2012
 
Food Security - How can remote sensing and GIS help?
Food Security - How can remote sensing and GIS help?Food Security - How can remote sensing and GIS help?
Food Security - How can remote sensing and GIS help?
 
Geospatial tools to guide targeting of technologies
Geospatial tools to guide targeting of technologiesGeospatial tools to guide targeting of technologies
Geospatial tools to guide targeting of technologies
 
Targeting inputs in appropriate landscapes and farming systems
Targeting inputs in appropriate landscapes and farming systemsTargeting inputs in appropriate landscapes and farming systems
Targeting inputs in appropriate landscapes and farming systems
 
12) Mitch Maguire
12) Mitch Maguire12) Mitch Maguire
12) Mitch Maguire
 
Extrapolation suitability for improved vegetable technologies in Babati Distr...
Extrapolation suitability for improved vegetable technologies in Babati Distr...Extrapolation suitability for improved vegetable technologies in Babati Distr...
Extrapolation suitability for improved vegetable technologies in Babati Distr...
 
Pan_European and pan-African Early Warning on Floods and Droughts: From the E...
Pan_European and pan-African Early Warning on Floods and Droughts: From the E...Pan_European and pan-African Early Warning on Floods and Droughts: From the E...
Pan_European and pan-African Early Warning on Floods and Droughts: From the E...
 
Malawi Policy Learning Event - Food Production Systems Disruption - April 28...
Malawi Policy Learning Event - Food Production Systems Disruption -  April 28...Malawi Policy Learning Event - Food Production Systems Disruption -  April 28...
Malawi Policy Learning Event - Food Production Systems Disruption - April 28...
 

Similar a Remote Sensing Based Yield Model and Application to Major Exporting Countries

Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.ppt
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.pptJianqiang Ren_Simulation of regional winter wheat yield by EPIC model.ppt
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.ppt
grssieee
 
MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...
MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...
MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...
grssieee
 
2856 IGARSS 2011- CHARMS.ppt
2856 IGARSS 2011- CHARMS.ppt2856 IGARSS 2011- CHARMS.ppt
2856 IGARSS 2011- CHARMS.ppt
grssieee
 
Operational Agriculture Monitoring System Using Remote Sensing
Operational Agriculture Monitoring System Using Remote SensingOperational Agriculture Monitoring System Using Remote Sensing
Operational Agriculture Monitoring System Using Remote Sensing
Mary Adel
 
Crow.IGARSS.talk.pptx
Crow.IGARSS.talk.pptxCrow.IGARSS.talk.pptx
Crow.IGARSS.talk.pptx
grssieee
 
PPT for report-Cambodai
PPT for report-CambodaiPPT for report-Cambodai
PPT for report-Cambodai
jayan_sri
 

Similar a Remote Sensing Based Yield Model and Application to Major Exporting Countries (20)

Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Sat...
Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Sat...Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Sat...
Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Sat...
 
Identification and Evaluation of Cercospora Leaf Spot of Sugar Beet by using ...
Identification and Evaluation of Cercospora Leaf Spot of Sugar Beet by using ...Identification and Evaluation of Cercospora Leaf Spot of Sugar Beet by using ...
Identification and Evaluation of Cercospora Leaf Spot of Sugar Beet by using ...
 
216-880-1-PB
216-880-1-PB216-880-1-PB
216-880-1-PB
 
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.ppt
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.pptJianqiang Ren_Simulation of regional winter wheat yield by EPIC model.ppt
Jianqiang Ren_Simulation of regional winter wheat yield by EPIC model.ppt
 
MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...
MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...
MONITORING VEGETATION WATER CONTENT BY USING OPTICAL VEGETATION INDEX AND MIC...
 
Google Earth Engine: Health Applications of Google’s Cloud Platform for Big E...
Google Earth Engine: Health Applications of Google’s Cloud Platform for Big E...Google Earth Engine: Health Applications of Google’s Cloud Platform for Big E...
Google Earth Engine: Health Applications of Google’s Cloud Platform for Big E...
 
Crop yield prediction using ridge regression.pdf
Crop yield prediction using ridge regression.pdfCrop yield prediction using ridge regression.pdf
Crop yield prediction using ridge regression.pdf
 
Precision Management - Nicole Rabe and Sarah Lepp - 12
Precision Management - Nicole Rabe and Sarah Lepp - 12Precision Management - Nicole Rabe and Sarah Lepp - 12
Precision Management - Nicole Rabe and Sarah Lepp - 12
 
remote sensing in agriculture
remote sensing in agricultureremote sensing in agriculture
remote sensing in agriculture
 
Drones in Agriculture | EquiAgra
Drones in Agriculture | EquiAgra Drones in Agriculture | EquiAgra
Drones in Agriculture | EquiAgra
 
Presentation adv gis 08 01-2014
Presentation adv gis 08 01-2014Presentation adv gis 08 01-2014
Presentation adv gis 08 01-2014
 
2856 IGARSS 2011- CHARMS.ppt
2856 IGARSS 2011- CHARMS.ppt2856 IGARSS 2011- CHARMS.ppt
2856 IGARSS 2011- CHARMS.ppt
 
Assessment of wheat crop coefficient using remote sensing techniques
Assessment of wheat crop coefficient using remote sensing techniquesAssessment of wheat crop coefficient using remote sensing techniques
Assessment of wheat crop coefficient using remote sensing techniques
 
Operational Agriculture Monitoring System Using Remote Sensing
Operational Agriculture Monitoring System Using Remote SensingOperational Agriculture Monitoring System Using Remote Sensing
Operational Agriculture Monitoring System Using Remote Sensing
 
Crow.IGARSS.talk.pptx
Crow.IGARSS.talk.pptxCrow.IGARSS.talk.pptx
Crow.IGARSS.talk.pptx
 
Recent advances on application of remote sensing in fruit production of imp...
Recent advances on  application of remote sensing  in fruit production of imp...Recent advances on  application of remote sensing  in fruit production of imp...
Recent advances on application of remote sensing in fruit production of imp...
 
DOCTORAL SEMINAR on remote sensing in Agriculture
DOCTORAL SEMINAR on remote sensing  in AgricultureDOCTORAL SEMINAR on remote sensing  in Agriculture
DOCTORAL SEMINAR on remote sensing in Agriculture
 
PPT for report-Cambodai
PPT for report-CambodaiPPT for report-Cambodai
PPT for report-Cambodai
 
Crowd sourcing rangeland vegetation conditions
Crowd sourcing rangeland vegetation conditionsCrowd sourcing rangeland vegetation conditions
Crowd sourcing rangeland vegetation conditions
 
Available data for crop modelling
Available data for crop modelling Available data for crop modelling
Available data for crop modelling
 

Más de International Food Policy Research Institute (IFPRI)

Más de International Food Policy Research Institute (IFPRI) (20)

Targeting in Development Projects: Approaches, challenges, and lessons learned
Targeting in Development Projects: Approaches, challenges, and lessons learnedTargeting in Development Projects: Approaches, challenges, and lessons learned
Targeting in Development Projects: Approaches, challenges, and lessons learned
 
Prevalence and Impact of Landmines on Ukrainian Agricultural Production
Prevalence and Impact of Landmines on Ukrainian Agricultural ProductionPrevalence and Impact of Landmines on Ukrainian Agricultural Production
Prevalence and Impact of Landmines on Ukrainian Agricultural Production
 
Global Markets and the War in Ukraine
Global Markets and  the War in UkraineGlobal Markets and  the War in Ukraine
Global Markets and the War in Ukraine
 
Impact of the Russian Military Invasion on Ukraine’s Agriculture and Trade
Impact of the Russian Military Invasion on Ukraine’s Agriculture and Trade Impact of the Russian Military Invasion on Ukraine’s Agriculture and Trade
Impact of the Russian Military Invasion on Ukraine’s Agriculture and Trade
 
Mapping cropland extent over a complex landscape: An assessment of the best a...
Mapping cropland extent over a complex landscape: An assessment of the best a...Mapping cropland extent over a complex landscape: An assessment of the best a...
Mapping cropland extent over a complex landscape: An assessment of the best a...
 
Examples of remote sensing application in agriculture monitoring
Examples of remote sensing application in agriculture monitoringExamples of remote sensing application in agriculture monitoring
Examples of remote sensing application in agriculture monitoring
 
Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...
 
Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...
 
Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...
 
Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...
 
Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...Statistics from Space: Next-Generation Agricultural Production Information fo...
Statistics from Space: Next-Generation Agricultural Production Information fo...
 
Current ENSO and IOD Conditions, Forecasts, and the Potential Impacts
Current ENSO and IOD Conditions, Forecasts, and the Potential ImpactsCurrent ENSO and IOD Conditions, Forecasts, and the Potential Impacts
Current ENSO and IOD Conditions, Forecasts, and the Potential Impacts
 
The importance of Rice in Senegal
The importance of Rice in SenegalThe importance of Rice in Senegal
The importance of Rice in Senegal
 
Global Rice Market and Export Restriction
Global Rice Market and Export RestrictionGlobal Rice Market and Export Restriction
Global Rice Market and Export Restriction
 
Global Rice Market Situation and Outlook
Global Rice Market Situation and Outlook Global Rice Market Situation and Outlook
Global Rice Market Situation and Outlook
 
Rice prices at highest (nominal) level in 15 years
Rice prices at highest (nominal) level in 15 yearsRice prices at highest (nominal) level in 15 years
Rice prices at highest (nominal) level in 15 years
 
Book Launch: Political Economy and Policy Analysis (PEPA) Sourcebook
Book Launch:  Political Economy and Policy Analysis (PEPA) SourcebookBook Launch:  Political Economy and Policy Analysis (PEPA) Sourcebook
Book Launch: Political Economy and Policy Analysis (PEPA) Sourcebook
 
Shocks, Production, Exports and Market Prices: An Analysis of the Rice Sector...
Shocks, Production, Exports and Market Prices: An Analysis of the Rice Sector...Shocks, Production, Exports and Market Prices: An Analysis of the Rice Sector...
Shocks, Production, Exports and Market Prices: An Analysis of the Rice Sector...
 
Anticipatory cash for climate resilience
Anticipatory cash for climate resilienceAnticipatory cash for climate resilience
Anticipatory cash for climate resilience
 
2023 Global Report on Food Crises: Joint Analysis for Better Decisions
2023 Global Report on Food Crises: Joint Analysis for Better Decisions 2023 Global Report on Food Crises: Joint Analysis for Better Decisions
2023 Global Report on Food Crises: Joint Analysis for Better Decisions
 

Último

call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...
call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...
call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...
9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...
Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...
Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...
Chandigarh Call girls 9053900678 Call girls in Chandigarh
 
Call Girls in Sarita Vihar Delhi Just Call 👉👉9873777170 Independent Female ...
Call Girls in  Sarita Vihar Delhi Just Call 👉👉9873777170  Independent Female ...Call Girls in  Sarita Vihar Delhi Just Call 👉👉9873777170  Independent Female ...
Call Girls in Sarita Vihar Delhi Just Call 👉👉9873777170 Independent Female ...
adilkhan87451
 

Último (20)

call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...
call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...
call girls in Raghubir Nagar (DELHI) 🔝 >༒9953056974 🔝 genuine Escort Service ...
 
Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...
Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...
Russian🍌Dazzling Hottie Get☎️ 9053900678 ☎️call girl In Chandigarh By Chandig...
 
2024: The FAR, Federal Acquisition Regulations, Part 30
2024: The FAR, Federal Acquisition Regulations, Part 302024: The FAR, Federal Acquisition Regulations, Part 30
2024: The FAR, Federal Acquisition Regulations, Part 30
 
Call Girls in Sarita Vihar Delhi Just Call 👉👉9873777170 Independent Female ...
Call Girls in  Sarita Vihar Delhi Just Call 👉👉9873777170  Independent Female ...Call Girls in  Sarita Vihar Delhi Just Call 👉👉9873777170  Independent Female ...
Call Girls in Sarita Vihar Delhi Just Call 👉👉9873777170 Independent Female ...
 
A Press for the Planet: Journalism in the face of the Environmental Crisis
A Press for the Planet: Journalism in the face of the Environmental CrisisA Press for the Planet: Journalism in the face of the Environmental Crisis
A Press for the Planet: Journalism in the face of the Environmental Crisis
 
best call girls in Pune - 450+ Call Girl Cash Payment 8005736733 Neha Thakur
best call girls in Pune - 450+ Call Girl Cash Payment 8005736733 Neha Thakurbest call girls in Pune - 450+ Call Girl Cash Payment 8005736733 Neha Thakur
best call girls in Pune - 450+ Call Girl Cash Payment 8005736733 Neha Thakur
 
Financing strategies for adaptation. Presentation for CANCC
Financing strategies for adaptation. Presentation for CANCCFinancing strategies for adaptation. Presentation for CANCC
Financing strategies for adaptation. Presentation for CANCC
 
Just Call Vip call girls Wardha Escorts ☎️8617370543 Starting From 5K to 25K ...
Just Call Vip call girls Wardha Escorts ☎️8617370543 Starting From 5K to 25K ...Just Call Vip call girls Wardha Escorts ☎️8617370543 Starting From 5K to 25K ...
Just Call Vip call girls Wardha Escorts ☎️8617370543 Starting From 5K to 25K ...
 
The Economic and Organised Crime Office (EOCO) has been advised by the Office...
The Economic and Organised Crime Office (EOCO) has been advised by the Office...The Economic and Organised Crime Office (EOCO) has been advised by the Office...
The Economic and Organised Crime Office (EOCO) has been advised by the Office...
 
VIP Model Call Girls Lohegaon ( Pune ) Call ON 8005736733 Starting From 5K to...
VIP Model Call Girls Lohegaon ( Pune ) Call ON 8005736733 Starting From 5K to...VIP Model Call Girls Lohegaon ( Pune ) Call ON 8005736733 Starting From 5K to...
VIP Model Call Girls Lohegaon ( Pune ) Call ON 8005736733 Starting From 5K to...
 
Call Girls Nanded City Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Nanded City Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Nanded City Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Nanded City Call Me 7737669865 Budget Friendly No Advance Booking
 
SMART BANGLADESH I PPTX I SLIDE IShovan Prita Paul.pptx
SMART BANGLADESH  I    PPTX   I    SLIDE   IShovan Prita Paul.pptxSMART BANGLADESH  I    PPTX   I    SLIDE   IShovan Prita Paul.pptx
SMART BANGLADESH I PPTX I SLIDE IShovan Prita Paul.pptx
 
Call On 6297143586 Yerwada Call Girls In All Pune 24/7 Provide Call With Bes...
Call On 6297143586  Yerwada Call Girls In All Pune 24/7 Provide Call With Bes...Call On 6297143586  Yerwada Call Girls In All Pune 24/7 Provide Call With Bes...
Call On 6297143586 Yerwada Call Girls In All Pune 24/7 Provide Call With Bes...
 
celebrity 💋 Patna Escorts Just Dail 8250092165 service available anytime 24 hour
celebrity 💋 Patna Escorts Just Dail 8250092165 service available anytime 24 hourcelebrity 💋 Patna Escorts Just Dail 8250092165 service available anytime 24 hour
celebrity 💋 Patna Escorts Just Dail 8250092165 service available anytime 24 hour
 
Junnar ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For S...
Junnar ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For S...Junnar ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For S...
Junnar ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For S...
 
The NAP process & South-South peer learning
The NAP process & South-South peer learningThe NAP process & South-South peer learning
The NAP process & South-South peer learning
 
Election 2024 Presiding Duty Keypoints_01.pdf
Election 2024 Presiding Duty Keypoints_01.pdfElection 2024 Presiding Duty Keypoints_01.pdf
Election 2024 Presiding Duty Keypoints_01.pdf
 
Call Girls Sangamwadi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Sangamwadi Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Sangamwadi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Sangamwadi Call Me 7737669865 Budget Friendly No Advance Booking
 
Antisemitism Awareness Act: pénaliser la critique de l'Etat d'Israël
Antisemitism Awareness Act: pénaliser la critique de l'Etat d'IsraëlAntisemitism Awareness Act: pénaliser la critique de l'Etat d'Israël
Antisemitism Awareness Act: pénaliser la critique de l'Etat d'Israël
 
Pimple Gurav ) Call Girls Service Pune | 8005736733 Independent Escorts & Dat...
Pimple Gurav ) Call Girls Service Pune | 8005736733 Independent Escorts & Dat...Pimple Gurav ) Call Girls Service Pune | 8005736733 Independent Escorts & Dat...
Pimple Gurav ) Call Girls Service Pune | 8005736733 Independent Escorts & Dat...
 

Remote Sensing Based Yield Model and Application to Major Exporting Countries

  • 1. Remote sensing based yield model and application to major exporting countries B. Franch1,2, E. Vermote3, Sergii Skakun2,3, Jean-Claude Roger2,3, I. Becker-Reshef2, C. Justice2,3 1 Global Change Unit, Image Processing Laboratory, Universitat de Valencia, Paterna, 46980 Valencia, Spain 2 Department of Geographical Sciences, University of Maryland, College Park MD 20742, United States 3 NASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, United States befranch@umd.edu
  • 2. Land Climate Data Record Multi instrument/Multi sensor Science Quality Data Records used to quantify trends and changes Why do we use coarse resolution? Emphasis on data consistency
  • 3. Coarse (250m) Moderate (30m) Fine (5m) Problems when working with coarse spatial resolution data
  • 4. Basis: Strong correlation between NDVI Peak and yield Tucker 1980, Hatfield 1983, Benedetti 1993, Doraiswamy 1995, Rasmussen 1997, Mika 2002 Becker-Reshef I, Vermote E, Lindeman M, Justice C. 2010. In Remote Sensing of Environment, 114, 1312–1323. Previous remote sensing methods (Becker-Reshef et al., 2010) USA (MODIS) USA (AVHRR) Franch, B., Vermote, E., Roger, J.C., Murphy, E., Becker-Reshef, I., Justice, C., Claverie, M., Nagol, J., Csiszar, I., Meyer, D., Baret, F., Masuoka, E., Wolfe, R. and Devadiga, S., (2017) A 30+ year AVHRR Land Surface Reflectance Climate Data Record and its application to wheat yield monitoring, Remote Sensing, 9, 296
  • 5. Improvement of the method The NDVI peak occurs around 1 month prior to the harvest (earliest forecast using this method) Inclusion of an additional parameter (the Growing Degree Days, GDD) to improve the timeliness of the prediction YIELD MONITORING Franch, B., E. F. Vermote, I. Becker-Reshef, M. Claverie, J. Huang, J. Zhang, C. Justice and J. A. Sobrino, 2015. Remote Sensing of Environment Tbase = 0 °C
  • 6. Improvement of the method The NDVI peak occurs around 1 month prior to the harvest (earliest forecast using this method) Inclusion of an additional parameter (the Growing Degree Days, GDD) to improve the timeliness of the prediction YIELD MONITORING Franch, B., E. F. Vermote, I. Becker-Reshef, M. Claverie, J. Huang, J. Zhang, C. Justice and J. A. Sobrino, 2015. Remote Sensing of Environment Tbase = 0 °CReliable estimation (10% error) between 1- 1.5 month prior to the peak NDVI (meaning 2-2.5 months prior to harvest) USA
  • 7. For each AU and a given date, the total DVI signal from each pixel can be written as: 𝐷𝐷𝐷𝐷𝐷𝐷𝑖𝑖 = 𝐷𝐷𝐷𝐷𝐷𝐷𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 − 𝐷𝐷𝐷𝐷𝐷𝐷𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 � 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑖𝑖 + 𝐷𝐷𝐷𝐷𝐷𝐷𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 DVIwheat : DVI signal from the wheat DVIothers: DVI from other surfaces within the pixel Wpct: percentage of wheat within the pixel or wheat purity MODIS 1km RGB (2/21/2017) Harper county (Kansas) 2017 wheat mask (from CDL) Harper county (Kansas) Franch, B., Vermote, E. F., Skakun, S., Roger, J. C., Becker-Reshef, I., Murphy, E., & Justice, C. (2019). Remote sensing based yield monitoring: Application to winter wheat in United States and Ukraine. International Journal of Applied Earth Observation and Geoinformation, 76, 112-127. 100% 0% New method
  • 8. Calibration equations For each AU, a separate linear regression was built with different combinations of regressors Seasonal Peak Peak length Input parameters Evaporative Fraction (after the peak)
  • 10. US winter wheat validation County level validation National level validation Black dots: each county and year from 2001-2016 Red dots: each county in 2017
  • 11. Application to other countries 60% of the global wheat exports in 2018
  • 12. Yield forecasting Working on adapting Franch et al. (2015) to the new method
  • 13. County level validation National level validation US corn validation
  • 14. County level validation National level validation US soybean validation
  • 15. Conclusions • A generic crop yield simple regression model has been developed based on a the “wheat” DVI at the peak of the growing process, the length of the peak and EF information. • Can estimate yield for the main wheat exporting countries with an accuracy – 7% at national level – 15% at sub-national level • The new method shows high correlation with official statistics and captures well extreme yield conditions (maximum and minimum). Freezing and flooding is still a problem • First results on yield forecasting show promising results • The model is also applicable to other cereals (corn and soybean)