Vegetation mapping requires accurate information to allow its use in applications such as sustainable forest management against the effects of climate change and the threat of wildfires. Remote sensing provides a powerful resource of fundamental data at different spatial resolutions and spectral regions, making it an essential tool for vegetation mapping and biomass management. Due to the ever-increasing availability of free data and software, satellites have been predominantly used to map, analyze, and monitor natural resources for conservation purposes. This study aimed to map vegetation from Sentinel-2 (S2) data in a complex and mixed vegetation cover of the Lousa district in Portugal. We used 10 multispectral bands with a spatial resolution of 10m, four vegetation indices including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Enhanced Vegetation Index (EVI), and Soil Adjusted Vegetation Index (SAVI). After applying Principal Component Analysis (PCA) on the 10 S2A bands, four texture features including Mean (ME), Homogeneity (HO), Correlation (COR), and Entropy (EN)were derived for the first three Principal Components. After defining the land use classes by object-based, the Random Forest (RF) classifier was applied. The map accuracy will be evaluated by the confusion matrix, using the metrics of Overall Accuracy (OA), Producer Accuracy (PA), User Accuracy (UA), and Kappa Coefficient (K). The described classification methodology is expected to show a high overall accuracy for vegetation mapping.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.