Alessandra Rodrigues Gomes

TL;DR: In this article, a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008 was created by using Landsat-5/TM images analyzed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series.

TL;DR: The aim of this paper is to present the methodology and results of the DETER based on AWIFS data, called DETER-B, which is effective in detecting deforestation smaller than 25 ha and presents higher detection capability in identifying areas between 25 and 100 ha.

TL;DR: The present work evaluates Deep Learning-based strategies for automatic deforestation detection, namely, Early Fusion (EF), Siamese Network (SN), and Convolutional Support Vector Machine (CSVM) as well as Support vector Machine (SVM), used as the baseline.

TL;DR: In this paper, the authors use a recently developed high-resolution land use/land cover dataset to track secondary forests in the Brazilian Amazon over 14 years, providing the first estimates of secondary forest loss for the region.

TL;DR: In this article, the authors argue that Maranhao state must urgently establish a policy of zero deforestation, protect secondary forests and comply with the national forest restoration policy, thus ensuring long-term economic sustainability.