Characterization of different crop types using biophysical indicators derived from Sentinel-2 MSI multi-temporal data in Sudurpashchim Province, Western Nepal

Consistent information on agricultural land use provides a fundamental basis for sustainable land management, achieving zero hunger (SDG2) and maintaining life on land (SDG15) in South Asia and Nepal in particular due to its high vulnerability to natural disasters caused by its diverse geo-climatic system. The present study aims to characterize different crop types (i.e., Maize, Sugarcane, and Wheat) cultivated in Sudurpashchim Province, one of Nepal’s most heavily cultivated areas, and identify their spectral behavior using Sentinel-2 MSI multitemporal data acquired between January and December 2021. In this regard, forty crop profiles were identified based on a 250-m crop-type map provided by the National Soil Science Research Center (NSSRC). Leaf Area Index (LAI), Fractional Vegetation Cover (FVC), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), in combination with Normalized Difference Vegetation Index (NDVI) and Shortwave Infrared bands (SWIR₁ and SWIR₂), were derived for each crop profile, then averaged per crop type to assess the overall trend. The results revealed the efficiency of biophysical indicators in crop type identification during their growing season. While shortwave infrared bands partially failed to characterize different cropping systems, LAI and FVC performed well in terms of separating wheat from other crops in the February-March period, revealed by maximum values reaching 1.2 and 0.4; then a sudden drop to 0.5 and 0.17 for LAI and FVC, respectively, during the harvesting season. For sugarcane, peak values have been observed during the July-September period, with LAI between 0.8 and 1 and FVC of approximately 0.4. Although a less unusual behavior has been registered for maize, local maxima for LAI, FVC, NDVI, and FAPAR around the July-August period have been found. This was followed by a notable decrease in September, which is contemporary with the harvesting season. Despite the fact that the increasing and decreasing trends of biophysical parameters are relatively synchronous with crop calendars, the distinction between different crop profiles can be robustly improved by adding more profiles and using Sentinel-1 SAR to take advantage of weather insusceptibility, which was a limiting factor for Sentinel-2 MSI.