Assessment of land use and cover in the Sucuru Watershed using Google Earth Engine

• Main Author: Sousa, José Hugo Simplicio de
• Publication Date: 2022
• Other Authors: Moreira, Amanda Rezende, Nascimento, Abdalan Andrade do, Ribeiro, George do Nascimento, Oliveira Neto, Jose Nunes de, Prado Júnior, Leonardo Souza do
• Format: Article
• Language: eng
• Source: Revista Verde de Agroecologia e Desenvolvimento Sustentavel
• Download full: https://www.gvaa.com.br/revista/index.php/RVADS/article/view/9621
• topic: Geotechnologies; Remote sensing; Supervised classification; Geotecnologias; Sensoriamento remoto; Classificação supervisionada; Geotecnologias; Sensoriamento remoto; Classificação supervisionada

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.