Deforestation is the replacement of forest by other land use while degradation is a reduction of long-term canopy cover and/or forest stock. Forest degradation in the Brazilian Amazon is mainly due to selective logging of intact/un-managed forests and to uncontrolled fires. The deforestation contribution to carbon emission is already known but determining the contribution of forest degradation remains a challenge. Discrimination of logging from fires, both of which produce different levels of forest damage, is important for the UNFCCC (United Nations Framework Convention on Climate Change) REDD+ (Reducing Emissions from Deforestation and Forest Degradation) program. This work presents a semi-automated procedure for monitoring deforestation and forest degradation in the Brazilian Amazon using fraction images derived from Linear Spectral Mixing Model (LSMM). Part of a Landsat Thematic Mapper (TM) scene (path/row 226/068) covering part of Mato Grosso State in the Brazilian Amazon, was selected to develop the proposed method. First, the approach consisted of mapping deforested areas and mapping forest degraded by fires using image segmentation. Next, degraded areas due to selective logging activities were mapped using a pixel-based classifier. The results showed that the vegetation, soil, and shade fraction images allowed deforested areas to be mapped and monitored and to separate degraded forest areas caused by selective logging and by fires. The comparison of Landsat Operational Land Imager (OLI) and RapidEye results for the year 2013 showed an overall accuracy of 94%. We concluded that spatial resolution plays an important role for mapping selective logging features due to their characteristics. Therefore, when compared to Landsat data, the current availability of higher spatial and temporal resolution data, such as provided by Sentinel-2, is expected to improve the assessment of deforestation and forest degradation, especially caused by selective logging. This will facilitate the implementation of actions for forest protection.
Este trabalho avaliou o uso e a cobertura da terra, e comparou os dados obtidos com aqueles das Áreas de Preservação Permanente (APPs), para identificar conflitos do uso da terra no município de Seropédica-RJ. Utilizaram-se duas cenas do satélite CBERS2 e a classificação supervisionada com o método da mínima distância. As APPs foram delimitadas com o auxílio de geotecnologias, baseando-se na legislação ambiental (Lei n.º 12.651/2012) (Brasil, 2012). Utilizou-se no mapeamento das APPs um Modelo Digital de Elevação (1:25.000) e, para a rede de drenagem, cartas planialtimétricas (1:10.000). Identificaram-se 40,02 km 2 de APPs, o que correspondeu a 15,01% do município. A APP do rio Guandu apresentou maior área (7,23%) e lagos urbanos, a menor (0,04%). O município não apresentou APPs de declividade (<40°) e de topo de morro (declividade < 25° com altitude < 100). Em relação aos conflitos do uso da terra, o solo exposto correspondeu a 58,1%, pastagem a 21,7%, areia/mineração a 7,8% e área urbana a 3,9%. Os resultados obtidos indicam eficiência dessas geotecnologias na gestão municipal.
Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.
RESUMO-Os produtos do açaí (Euterpe oleracea Mart.) apresentam grande importância econômica e cultural no Brasil com um crescente mercado consumidor. Com intuito de fornecer bases para ampliação desse cultivo em outros estados, buscou-se elaborar o zoneamento agroclimático para essa cultura no estado do Espírito Santo. Para tanto, utilizou-se de dados meteorológicos de 110 estações de órgãos governamentais e da ferramenta geotecnológica ArcGIS 10.1 para espacializar os dados de temperatura, precipitação e déficit hídrico e depois reclassificá-las para a geração do zoneamento. Os resultados demonstraram que 20,74% da área total do Espírito Santo possui zonas aptas a essa cultura, localizadas nas regiões Nordeste, Serrana e Sul, sendo Linhares o município com maior aptidão. Embora a maior parte do estado tenha algum tipo de restrição que limita o cultivo, seja da variável déficit hídrico, seja da precipitação, algumas técnicas podem minimizar tais restrições. Logo, torna-se viável a implantação da cultura do açaí no estado do Espírito Santo de acordo com as variáveis temperatura, precipitação e déficit hídrico. Palavras-chave: Geotecnologias. Déficit hídrico. Temperatura. Classes de aptidão.
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