NDLI: Crop Monitoring Using Vegetation and Thermal Indices for Yield Estimates: Case Study of a Rainfed Cereal in Semi-Arid West Africa

Content Provider	IEEE Xplore Digital Library
Author	Leroux, L. Baron, C. Zoungrana, B. Traore, S.B. Lo Seen, D. Begue, A.
Copyright Year	2008
Abstract	For the semiarid Sahelian region, climate variability is one of the most important risks of food insecurity. Field experimentations as well as crop modeling are helpful tools for the monitoring and the understanding of yields at local scale. However, extrapolation of these methods at a regional scale remains a demanding task. Remote sensing observations appear as a good alternative or addition to existing crop monitoring systems. In this study, a new approach based on the combination of vegetation and thermal indices for rainfed cereal yield assessment in the Sahelian region was investigated. Empirical statistical models were developed between MODIS NDVI and LST variables and the crop model SARRA-H simulated aboveground biomass and harvest index in order to assess each component of the yield equation. The resulting model was successfully applied at the Niamey Square Degree (NSD) site scale with yield estimations close to the official agricultural statistics of Niger for a period of 11 years (2000-2011) ($r = 0.82,\;\text{p-value} <; 0.05$). The combined NDVI and LST indices-based model was found to clearly outperform the model based on NDVI alone ($r = 0.59,\;\text{p-value} <; 0.10$). In areas where access to ground measurements is difficult, a simple, robust, and timely satellite-based model combining vegetation and thermal indices from MODIS and calibrated using crop model outputs can be pertinent. In particular, such a model can provide an assessment of the year-to-year yield variability shortly after harvest for regions with agronomic and climate characteristics close to those of the NSD study area.
Starting Page	347
Ending Page	362
Page Count	16
File Size	3290897
File Format	PDF
ISSN	19391404
Volume Number	9
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Agriculture MODIS Remote sensing Indexes Vegetation mapping Yield estimation Biomass remote sensing Crop model crop yield harvest index land surface temperature (LST) NDVI Niger rainfed cereal
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Computers in Earth Sciences

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