Estimating regional winter wheat yield with WOFOST through the assimilation of green area index retrieved from MODIS observations

A.J.W. de Wit, G. Duveiller, P. Defourny

Research output: Contribution to journalArticleAcademicpeer-review

74 Citations (Scopus)

Abstract

Here, we describe and test a method for optimising winter wheat green area index (GAI) simulated with the WOFOST crop model using MODIS estimates of GAI in the Walloon region of Belgium. Detailed crop type maps during the period of 2000–2009 were used to derive time series of crop-specific GAI by selecting only the 250-m MODIS pixels that have at least 75% purity of the target crop. Two important model parameters were optimised by minimising the difference between the simulated and observed GAI for each individual pixel and year. The resulting year-specific joint parameter distributions were then used to run an ensemble of crop simulations in which the ensemble was initialised by sampling from the joint distribution of the corresponding year. The semi-variograms of the retrieved parameters revealed that the spatial patterns were consistent with agricultural practices and that seasonal characteristics of weather patterns in Wallonia can explain – at least partially – the temporal variability observed in the retrieved parameter distributions. Finally, the results of the average ensemble crop simulation were aggregated to the provincial and regional levels. A validation using yields reported by EUROSTAT over the period 2000–2009 revealed that assimilating MODIS with GAI provides an improved relationship between simulation results and reported yields at the regional level.
Original languageEnglish
Pages (from-to)39-52
JournalAgricultural and Forest Meteorology
Volume164
DOIs
Publication statusPublished - 2012

Fingerprint

moderate resolution imaging spectroradiometer
MODIS
winter wheat
wheat
crop
winter
crops
pixel
simulation
crop models
Belgium
purity
variogram
agricultural practice
time series analysis
weather
index
assimilation
time series
parameter

Keywords

  • remotely-sensed data
  • crop yield
  • ndvi data
  • spatial-resolution
  • model
  • validation
  • simulation
  • vegetation
  • radiation
  • avhrr

Cite this

@article{3b429ab2730b491f94bfd1258d61e516,
title = "Estimating regional winter wheat yield with WOFOST through the assimilation of green area index retrieved from MODIS observations",
abstract = "Here, we describe and test a method for optimising winter wheat green area index (GAI) simulated with the WOFOST crop model using MODIS estimates of GAI in the Walloon region of Belgium. Detailed crop type maps during the period of 2000–2009 were used to derive time series of crop-specific GAI by selecting only the 250-m MODIS pixels that have at least 75{\%} purity of the target crop. Two important model parameters were optimised by minimising the difference between the simulated and observed GAI for each individual pixel and year. The resulting year-specific joint parameter distributions were then used to run an ensemble of crop simulations in which the ensemble was initialised by sampling from the joint distribution of the corresponding year. The semi-variograms of the retrieved parameters revealed that the spatial patterns were consistent with agricultural practices and that seasonal characteristics of weather patterns in Wallonia can explain – at least partially – the temporal variability observed in the retrieved parameter distributions. Finally, the results of the average ensemble crop simulation were aggregated to the provincial and regional levels. A validation using yields reported by EUROSTAT over the period 2000–2009 revealed that assimilating MODIS with GAI provides an improved relationship between simulation results and reported yields at the regional level.",
keywords = "remotely-sensed data, crop yield, ndvi data, spatial-resolution, model, validation, simulation, vegetation, radiation, avhrr",
author = "{de Wit}, A.J.W. and G. Duveiller and P. Defourny",
year = "2012",
doi = "10.1016/j.agrformet.2012.04.011",
language = "English",
volume = "164",
pages = "39--52",
journal = "Agricultural and Forest Meteorology",
issn = "0168-1923",
publisher = "Elsevier",

}

Estimating regional winter wheat yield with WOFOST through the assimilation of green area index retrieved from MODIS observations. / de Wit, A.J.W.; Duveiller, G.; Defourny, P.

In: Agricultural and Forest Meteorology, Vol. 164, 2012, p. 39-52.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Estimating regional winter wheat yield with WOFOST through the assimilation of green area index retrieved from MODIS observations

AU - de Wit, A.J.W.

AU - Duveiller, G.

AU - Defourny, P.

PY - 2012

Y1 - 2012

N2 - Here, we describe and test a method for optimising winter wheat green area index (GAI) simulated with the WOFOST crop model using MODIS estimates of GAI in the Walloon region of Belgium. Detailed crop type maps during the period of 2000–2009 were used to derive time series of crop-specific GAI by selecting only the 250-m MODIS pixels that have at least 75% purity of the target crop. Two important model parameters were optimised by minimising the difference between the simulated and observed GAI for each individual pixel and year. The resulting year-specific joint parameter distributions were then used to run an ensemble of crop simulations in which the ensemble was initialised by sampling from the joint distribution of the corresponding year. The semi-variograms of the retrieved parameters revealed that the spatial patterns were consistent with agricultural practices and that seasonal characteristics of weather patterns in Wallonia can explain – at least partially – the temporal variability observed in the retrieved parameter distributions. Finally, the results of the average ensemble crop simulation were aggregated to the provincial and regional levels. A validation using yields reported by EUROSTAT over the period 2000–2009 revealed that assimilating MODIS with GAI provides an improved relationship between simulation results and reported yields at the regional level.

AB - Here, we describe and test a method for optimising winter wheat green area index (GAI) simulated with the WOFOST crop model using MODIS estimates of GAI in the Walloon region of Belgium. Detailed crop type maps during the period of 2000–2009 were used to derive time series of crop-specific GAI by selecting only the 250-m MODIS pixels that have at least 75% purity of the target crop. Two important model parameters were optimised by minimising the difference between the simulated and observed GAI for each individual pixel and year. The resulting year-specific joint parameter distributions were then used to run an ensemble of crop simulations in which the ensemble was initialised by sampling from the joint distribution of the corresponding year. The semi-variograms of the retrieved parameters revealed that the spatial patterns were consistent with agricultural practices and that seasonal characteristics of weather patterns in Wallonia can explain – at least partially – the temporal variability observed in the retrieved parameter distributions. Finally, the results of the average ensemble crop simulation were aggregated to the provincial and regional levels. A validation using yields reported by EUROSTAT over the period 2000–2009 revealed that assimilating MODIS with GAI provides an improved relationship between simulation results and reported yields at the regional level.

KW - remotely-sensed data

KW - crop yield

KW - ndvi data

KW - spatial-resolution

KW - model

KW - validation

KW - simulation

KW - vegetation

KW - radiation

KW - avhrr

U2 - 10.1016/j.agrformet.2012.04.011

DO - 10.1016/j.agrformet.2012.04.011

M3 - Article

VL - 164

SP - 39

EP - 52

JO - Agricultural and Forest Meteorology

JF - Agricultural and Forest Meteorology

SN - 0168-1923

ER -