NDLI: Early Maize Yield Forecasting From Remotely Sensed Temperature/Vegetation Index Measurements

Content Provider	IEEE Xplore Digital Library
Author	Holzman, M.E. Rivas, R.E.
Copyright Year	2008
Abstract	High and low soil moisture availability is one of the main limiting factors-affecting crops productivity. Thus, determination of the relationship between them is crucial for food security and support importing- exporting strategies. The aim of this work was to analyze the aptitude of temperature vegetation dryness index (TVDI) to forecast maize yield. MODIS/AQUA enhanced vegetation index and land surface temperature (LST) at 1 km were used to calculate TVDI and maize yield over a large agricultural area of Argentine Pampas. The comparison between TVDI and official yield statistics was carried out to derive regression models in two agro-climatic zones, obtaining linear and quadratic adjustments. The models account for between 73% and 83% of yield variability, with the best prediction in the humid zone. The RMSE values ranged from 14% to 19% of average yield. The bias showed a slightly higher difference between predicted and observed yield data in semi-arid zone. The models showed aptitude to estimate yield with reasonable accuracy 8-12 weeks before harvest. In addition, the TVDI-maize yield relationship and the impact of submonthly water stress were evaluated at field scale using yield measurements to ensure the analysis on maize. The highest $\text{R}^{2}$ (0.61) was obtained using monthly values suggesting that the entire critical stage should be taken into account for yield forecasting. Although these results would not be directly extrapolated to other agricultural regions in the world, the proposed model is promising for forecasting spatial yield in other regions with poor data coverage several weeks before harvest.
Starting Page	507
Ending Page	519
Page Count	13
File Size	2984432
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 Soil moisture Vegetation mapping Indexes Land surface temperature Remote sensing temperature vegetation dryness index (TVDI) Optical–thermal soil moisture stress index
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science Computers in Earth Sciences

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