This study investigates the efficacy of NDVI (Normalized Difference Vegetation Index), EOMI (Exogenous Organic Matter Index), and MNDWI (Modified Normalized Difference Water Index) in identifying application of manure in sandy soil farmlands. By leveraging Sentinel-2 multispectral imagery acquired over Turkish farmland in the Adana region, this study aims to assess the joint utilization of these indices to enhance detection methodologies within the specified geographic context.
Detecting Manure Applications in Sandy Soil Peanut Farmlands Using Multitemporal Sentinel-2 Multispectral Data: A Case Study
Cihangiroglu M.;Marzi D.;Dell'acqua F.
2024-01-01
Abstract
This study investigates the efficacy of NDVI (Normalized Difference Vegetation Index), EOMI (Exogenous Organic Matter Index), and MNDWI (Modified Normalized Difference Water Index) in identifying application of manure in sandy soil farmlands. By leveraging Sentinel-2 multispectral imagery acquired over Turkish farmland in the Adana region, this study aims to assess the joint utilization of these indices to enhance detection methodologies within the specified geographic context.File in questo prodotto:
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