Assessment of tropical forest degradation by selective logging and fire using Landsat imagery

Many studies have assessed the process of forest degradation in the Brazilian Amazon using remote sensing approaches to estimate the extent and impact by selective logging and forest fires on tropical rain forest. However, only a few have estimated the combined impacts of those anthropogenic activities. We conducted a detailed analysis of selective logging and forest fire impacts on natural forests in the southern Brazilian Amazon state of Mato Grosso, one of the key logging centers in the country. To achieve this goal a 13-year series of annual Landsat images (1992-2004) was used to test different remote sensing techniques for measuring the extent of selective logging and forest fires, and to estimate their impact and interaction with other land use types occurring in the study region. Forest canopy regeneration following these disturbances was also assessed. Field measurements and visual observations were conducted to validate remote sensing techniques. Our results indicated that the Modified Soil Adjusted Vegetation Index aerosol free (MSAVI(af)) is a reliable estimator of fractional coverage under both clear sky and under smoky conditions in this study region. During the period of analysis, selective logging was responsible for disturbing the largest proportion (31%) of natural forest in the study area, immediately followed by deforestation (29%). Altogether, forest disturbances by selective logging and forest fires affected approximately 40% of the study site area. Once disturbed by selective logging activities, forests became more susceptible to fire in the study site. However, our results showed that fires may also occur in undisturbed forests. This indicates that there are further factors that may increase forest fire susceptibility in the study area. Those factors need to be better understood. Although selective logging affected the largest amount of natural forest in the study period, 35% and 28% of the observed losses of forest canopy cover were due to forest fire and selective logging combined and to forest fire only, respectively. Moreover, forest areas degraded by selective logging and forest fire is an addition to outright deforestation estimates and has yet to be accounted for by land use and land cover change assessments in tropical regions. Assuming that this observed trend of land use and land cover conversion continues, we predict that there will be no undisturbed forests remaining by 2011 in this study site. Finally, we estimated that 70% of the total forest area disturbed by logging and fire had sufficiently recovered to become undetectable using satellite data in 2004. (C) 2010 Elsevier B.V. All rights reserved.

Carbon Stocks and Isotopic Composition of the Organic Matter in Soils Covered by Native Vegetation and Pasture in Sorocaba, SP, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Assessment of Cerdocyon thous distribution in an agricultural mosaic, southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Análise da incerteza na representação de classes de cobertura do solo urbano resultantes da aplicação de uma rede neural artificial

The great diversity of materials that characterizes the urban environment determines a structure of mixed classes in a classification of multiespectral images. In that sense, it is important to define an appropriate classification system using a non parametric classifier, that allows incorporating non spectral (such as texture) data to the process. They also allow analyzing the uncertainty associated to each class from the output alues of the network calculated in relation to each class. Considering these properties, an experiment was carried out. This experiment consisted in the application of an Artificial Neural Network aiming at the classification of the urban land cover of Presidente Prudente and the analysis of the uncertainty in the representation of the mapped thematic classes. The results showed that it is possible to discriminate the variations in the urban land cover through the application of an Artificial Neural Network. It was also possible to visualize the spatial variation of the uncertainty in the attribution of classes of urban land cover from the generated representations. The class characterized by a defined pattern as intermediary related to the impermeability of the urban soil presented larger ambiguity degree and, therefore, larger mixture.

Modelagem em escala regional da erosão relacionada com a evolução da cobertura do solo: Um estudo de caso no sudeste do Brasil

Accelerated soil erosion is, at present, one of the most widespread environmental problems in the world. Geographic Information Systems (GIS) have become an essential tool in soil erosion studies and consequently in the development of appropriate soil conservation strategies. The objective of this paper was to assess the degree of soil erosion associated with land cover dynamics through GIS analysis and to validate the modeling with indicators of soil erosion. Universal Soil Loss Equation (USLE) model, GIS technology and ground-truth dataset (erosion indicators) were employed to elaborate the soil loss maps for four dates at Sorocaba Municipality (SP, Brazil). It was verified that, although the predicted soil loss rate is normally small along the study area, such rate is significantly greater than the soil formation rate. This shows a non-sustainable situation of soil and land cover management. Unplanned urban expansion seems be the main driving force that acts in increasing the erosion risk/occurrence along the study area.

Classificação de áreas de favelas a partir de imagens IKONOS: Viabilidade de uso de uma abordagem orientada a objeto

The growth of large cities is usually accelerated and disorganized, which causes social, economical and infrastructural conflicts and frequently, occupation in illegal areas. For a better administration of these areas, the public manager needs information about their location. This information can be obtained through land utilization and land cover maps, where orbital images of remote sensing are used as one of the most traditional sources of data. In this context, the present work tested the applicability of the object-based classification to categorize two slum areas, taking into account the structure of the streets, size of the huts, distance between the houses, among other parameters. These area combinations of physical aspects were analyzed using the image IKONOS II and the software eCognition. Slum areas tend to be, to the contrary of the planned areas, disarranged, with narrow streets, small houses built with a variety of materials and without definition of blocks. The results of land cover classification for slum areas are encouraging because they are accurate and little ambiguous in the classification process. Thus, it would allow its utilization by urban managers.

Simulação de perdas de solo em função de cenários de adequação ambiental em microbacias agrícolas

In São Paulo state, deforestation and agriculture activities are increasing soil losses processes, especially in areas of susceptible soils where soil conservation practices are not adopted. Environmental adequacy at property level regarding Permanent Protection Areas and Legal Reserves is considered a potential factor for reducing soil losses and it was based on this fact that we assessed soil losses of different scenarios of environmental adequacy. Simulations of erosive processes were carried out in 15 catchments of the Corumbataí river basin, with different forest restoration scenarios, as well as the current situation of land use/ land cover. The scenarios include reforestation of Permanent Preservation Areas (PPA); the reforestation hydrological sensitive areas; and two scenarios, the Legal Reserve installation in 20% of each catchment, being one of them for most critical areas in terms of erosion and the other at random. It was observed that the establishment of PPA and the reforestation of hydrological sensitive areas (HSA), offered a small contribution to the control of the erosive process, resulting in a reduction of 10% and 7.4%, respectively, while the legal reserve in critical areas has the significant reduction of 69.8%. The random scenario, in turn, resulted in a reduction of 21.4% of erosion. Results show that reforestation can reduce soil losses, but previous studies of land prioritization and planning could significantly increase its efficiency.

Mammal defaunation as surrogate of trophic cascades in a biodiversity hotspot

Preserving large tracts of natural habitats is essential to maintain biodiversity. Nevertheless, even large areas may still suffer from less visible impacts such as loss of ecological processes. Because mapping ecological processes over large scales is not practical, an alternative is to map surrogate species that are key for those processes. In this study, we chose four species of Neotropical large mammals (the largest apex predator: jaguar - Panthera onca; the largest herbivore: tapir - Tapirus terrestris; the largest seed predator: white-lipped peccary - Tayassu pecari; and the largest arboreal seed disperser: muriqui - Brachyteles spp.) in an ecosystem with an old history of human impact (the Atlantic Forest) to test whether areas with native forest still harbor ecological processes that may guarantee long-term ecosystem maintenance. We gathered 94 locations with recent presence of the four species to map current ranges and model suitable areas. Our results reveal that 96% of the remaining Atlantic Forest is depleted of at least one of the four surrogate species and 88% is completely depleted of all four surrogate species. We also found that only 16% is still environmentally suitable for all four, and 55% is completely unsuitable to all four of them. Our study highlights the importance of looking beyond land cover to fully depict intactness of natural areas, and suggests that ecosystems with a long history of human impact (such as the Atlantic Forest) may be suffering from ecological impacts not seen at a first glance. © 2013 Elsevier Ltd.

Evolução espaço-temporal do uso e cobertura do solo nas estâncias turísticas de Avaré e Paranapanema, no reservatório de Jurumirim (SP)

Pós-graduação em Geografia - IGCE

Análise da incerteza na representação de classes temáticas resultantes da aplicação de uma rede neural artificial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Imagens multitemporais ALOS/PALSAR baseada em orientação a objeto na discriminação da cobertura da terra

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sistema hierárquico de classificação para mapeamento da cobertura da terra nas escalas regional e urbana

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Potencialidades de uso de imagens IKONOS/GEO para aplicações em áreas urbanas

Pós-graduação em Ciências Cartográficas - FCT

Geoestística e sensoriamento remoto na classificação de imagens em áreas cultivadas com citros

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geotecnologias aplicadas à estimativa de perdas de solo por erosão hídrica na sub-bacia do Ribeirão das Perobas, Município de Santa Cruz do Rio Pardo-SP

Pós-graduação em Agronomia (Energia na Agricultura) - FCA