Comparative geospatial study demonstrates superior classification accuracy for decision tree algorithms in watershed mapping, highlighting cloud computing utility for environmental management.
Human activities modify the natural characteristics of numerous watersheds worldwide. Google Earth Engine provides tools for the analysis of land use and natural resources. In this work, we classify current land use and cover in the Sucuru watershed, Paraíba, Brazil. We compared the accuracy of five supervised classification algorithms of Google Earth Engine. Classifiers based on Decision Trees, such as the Classification and Regression Trees (CART) and Random Forest (RF), showed the best accuracy and visual inspection values. The Google Earth Engine is a powerful tool for analysis of large-scale environmental data, monitoring land use changes, and providing information for sustainable management.
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Sousa et al. (2022) studied this question.
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