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

摘要: Increased knowledge about the spatial distribution of cotton (Gossypium hirsutum L.) yield in Khorezm region Uzbekistan supports optimal allocation resources. This research estimated the cotton yields 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. photosynthetically active radiation (PAR) environmental stress scalars on crop development were estimated with meteorological information. Using high-spatial-resolution Landsat 7 ETM+ images, cotton area extracted fraction determined within the coarse resolution pixels. the MODISFPARdata improved using an empirical relationship to the higher-resolution NDVI (Normalized Difference Vegetation Index) data. raw ranged 1.09 to 3.76 Mg ha -1 . modeling revealed a trend higher upstream areas locations closer to irrigation channels and lower downstream at sites more distant the channels. validated estimations showed 10% deviation from official governmental statistics. established freely available data minimum field data input is promising technique for economic operational lateseason estimation spatially distributed over large regions on which management adjustments could be made.