<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings"^^ . "Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers\r\nare faced with choosing the appropriate remote sensing data. The objective of this research is to analyze\r\nthe spatial resolution effects of different remote sensing images on soil prediction models in two\r\nsmallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State),\r\nand provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian\r\nkriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (Kex) in the\r\ntopsoil (0e15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m),\r\nRapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as\r\nband reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple\r\nimages showed relatively strong correlations with soil Kex in two study areas. The research also\r\nsuggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based\r\nsoil prediction models would not necessarily have higher prediction performance than coarse spatial\r\nresolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings\r\nneed select the appropriate spectral indices and consider different factors such as the spatial resolution,\r\nband width, spectral resolution, temporal frequency, cost, and processing time of different remote\r\nsensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to\r\nsmallholder farm settings all over the world and help smallholder farmers implement sustainable and\r\nfield-specific soil nutrient management scheme."^^ . "2017-09-15" . . "200" . . "Elsevier"^^ . . . "Journal of Environmental Management"^^ . . . "03014797" . . . . . . . . . . . . . . . . . . . "S P"^^ . "Wani"^^ . "S P Wani"^^ . . "A"^^ . "Abd-Elrahman"^^ . "A Abd-Elrahman"^^ . . "S"^^ . "Grunwald"^^ . "S Grunwald"^^ . . "S E"^^ . "Smith"^^ . "S E Smith"^^ . . "Y"^^ . "Xu"^^ . "Y Xu"^^ . . . . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings (PDF)"^^ . . . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings (Other)"^^ . . . . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings (Other)"^^ . . . . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings (Other)"^^ . . . . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings (Other)"^^ . . . . . . "Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings (Other)"^^ . . . . . "HTML Summary of #10119 \n\nEvaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings\n\n" . "text/html" . . . "Remote Sensing"@en . . . "Soil"@en . . . "Smallholder Agriculture"@en . . . "Digital Agriculture"@en . .