INVESTIGADORES
PICCOLO Maria Cintia
artículos
Título:
Estimating soil moisture and the relationship with crop yield usingsurface temperature and vegetation index
Autor/es:
HOLZMAN, M.; RIVAS, R.; PICCOLO M.C.
Revista:
ITC JOURNAL
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2014 vol. 28 p. 181 - 192
ISSN:
0303-2434
Resumen:
tSoil moisture availability affects rainfed crop yield. Therefore, the development of methods for pre-harvest yield prediction is essential for the food security. A study was carried out to estimate regionalcrop yield using the Temperature Vegetation Dryness Index (TVDI). Triangular scatters from land surfacetemperature (LST) and enhanced vegetation index (EVI) space from MODIS (Moderate Resolution ImagingSpectroradiometer) were utilized to obtain TVDI and to estimate soil moisture availability. Then soybeanand wheat crops yield was estimated on four agro-climatic zones of Argentine Pampas. TVDI showed astrong correlation with soil moisture measurements, with R2values ranged from 0.61 to 0.83 and alsoit was in agreement with spatial pattern of soil moisture. Moreover, results showed that TVDI data canbe used effectively to predict crop yield on the Argentine Pampas. Depending on the agro-climatic zone,R2values ranged from 0.68 to 0.79 for soybean crop and 0.76 to 0.81 for wheat. The RMSE values were366 and 380 kg ha−1for soybean and they varied between 300 and 550 kg ha−1in the case of wheat crop.When expressed as percentages of actual yield, the RMSE values ranged from 12% to 13% for soybean and14% to 22% for wheat. The bias values indicated that the obtained models underestimated soybean andwheat yield. Accurate crop grain yield forecast using the developed regression models was achieved oneto three months before harvest. In many cases the results were better than others obtained using onlya vegetation index, showing the aptitude of surface temperature and vegetation index combination toreflect the crop water condition. Finally, the analysis of a wide range of soil moisture availability allowedus to develop a generalized model of crop yield and dryness index relationship which could be applicablein other regions and crops at regional scale.