Land use/land cover classification in a heterogeneous agricultural landscape using PlanetScope data.

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Author(s): BUENO, I. T.; ANTUNES, J. F. G.; TORO, A. P. S. G. D.; WERNER, J. P. S.; COUTINHO, A. C.; FIGUEIREDO, G. K. D. A.; LAMPARELLI, R. A. C.; ESQUERDO, J. C. D. M.; MAGALHÃES, P. S. G.

Summary: This study evaluated the accuracy of LULC classification based on an initial clustering step in a heterogeneous agricultural landscape using PlanetScope imagery while checking for variability among their Normalized Difference Vegetation Index (NDVI) temporal signatures.

Publication year: 2023

Types of publication: Journal article

Unit: Embrapa Digital Agriculture

Keywords: Agricultural crops, Assinatura espectro-temporal, Clustering, Clusterização, Cobertura da terra, Culturas agrícolas, Floresta aleatória, Intra-class variability, Land cover, Land use, OBIA, Object-Based Image Analysis, Random Forest, Spectro-temporal signature, Uso da Terra, Variabilidade intraclasse

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