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Software . 2025
License: CC BY
Data sources: Datacite
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
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Supplementation of Dynamic World Data with Additional Indexes to Enhance the Classification Efficiency

Authors: KAPOOR, ADITYA; Jahangeer Jahangeer; Tang, Zhenghong;

Supplementation of Dynamic World Data with Additional Indexes to Enhance the Classification Efficiency

Abstract

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

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Keywords

Remote Sensing, LULC Classification, Google Earth Engine

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average