Multispectral remote sensing images are the primary source in the land use and land cover
(LULC) monitoring. This is achieved by LULC classification and LULC change detection …

The wetland classification from remotely sensed data is usually difficult due to the extensive
seasonal vegetation dynamics and hydrological fluctuation. This study presents a random …

Spatially and timely accurate information about tropical forest disturbances is crucial for
tracking critical forest changes, supporting forest management, and enabling law …

Urbanization increases the amount of impervious surfaces, making accurate information on
spatial and temporal expansion trends essential; the challenge is to develop a cost-and …

Urbanization creates new development in open spaces and agricultural fields, synonymous
with increasing impervious surfaces. Such surfaces restrain the natural infiltration of water …

Study of gathering some useful insights from our planet Earth-its natural, man-made,
physical, and biological structures is quite engrossing. Earth observation despite being …

Accuracy of land cover classification in remotely sensed images relies on the utilized
classifier and extracted features. Texture features are significant in land cover classification …

No Brasil, as regras de exploração e de conservação da vegetação nativa estão instituídas
no Novo Código Florestal, o registro das informações dos imóveis rurais é realizado através …

Accuracy of land cover classification in remotely sensed images relies on the features
extracted and the classifier used. Texture features are significant in land cover classification …

Abstract Forests constitute 31%(about 4 billion ha) of the land area of the earth, and tropical
forests cover is about 2 billion ha. Tropical forests play a significant role in supporting the …