
1. Introduction: In a geospatial domain, Land Use Land Cover (LULC) classification is an important tool to identify the features of interest such as water bodies, vegetation, built-up area etc. There are many high performance, ready-to-use LULC classification products such as Copernicus Global Land Cover Layers (Buchhorn et al. 2020) and Dynamic World (Brown et al. 2022). However, in some cases such as cloud cover or shadow, these products may not work well and inclusion of additional data may be required. In this Google Earth Engine script, I have supplemented dynamic world data with NDWI spectral index to enhance the classification of wetland which is composed of water and flooded vegetation. A threshold of 0.1 has been adopted for NDWI. Additionally, wetness index for the study region has been computed to further showcase the applicability. The complete script is accompanied by this document in the repository. 2. References:• Buchhorn, M.; Lesiv, M.; Tsendbazar, N. - E.; Herold, M.; Bertels, L.; Smets, B. Copernicus Global Land Cover Layers-Collection 2. Remote Sensing 2020, 12 Volume 108, 1044. doi:10.3390/rs12061044• Brown, C.F., Brumby, S.P., Guzder-Williams, B. et al. Dynamic World, Near real-time global 10 m land use land cover mapping. Sci Data 9, 251 (2022). doi:10.1038/s41597-022-01307-4
Remote Sensing, LULC Classification, Google Earth Engine
Remote Sensing, LULC Classification, Google Earth Engine
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