Modeling of Cotton Yields in the Amu Darya River Floodplains of Uzbekistan Integrating Multitemporal Remote Sensing and Minimum Field Data

Abstract

Increased knowledge about the spatial distribution of cotton (Gossypium hirsutum L.) yield in the Khorezm region in Uzbekistan supports the optimal allocation of resources. This research estimated the spatial distribution of cotton yields in Khorezm by integrating remote sensing, field data, and modeling. The agro‐meteorological model used was based on Monteith's biomass production model with multitemporal MODIS (Moderate Resolution Imaging Spectroradiometer)‐derived parameters from 2002 as primary inputs. The photosynthetically active radiation (PAR) and environmental stress scalars on crop development were estimated with meteorological information. Using high‐spatial‐resolution Landsat 7 ETM+ images, the cotton area was extracted and the cotton fraction determined within the coarse spatial resolution MODIS pixels. The spatial resolution of the MODIS FPAR data was improved by using an empirical relationship to the higher‐resolution MODIS NDVI (Normalized Difference Vegetation Index) data. The estimated raw cotton yield ranged from 1.09 to 3.76 Mg ha⁻¹. The modeling revealed a spatial trend of higher yields in upstream areas and in locations closer to the irrigation channels and lower yields in downstream areas and at sites more distant to the channels. The validated yield estimations showed a 10% deviation from official governmental statistics. The established agro‐meteorological model based on freely available MODIS data and a minimum of field data input is a promising technique for economic and operational late‐season estimation of spatially distributed cotton yield over large regions on which management adjustments could be made.