Luiz Augusto Manfré

Environmental fragility evaluation and guidelines for environmental zoning: a study case on Ibiuna (the Southeastern Brazilian region)

Environmental fragility models are important decision tools for policy makers as they help quantify environmental sensitivity and understand the relationship between human activities and environmental quality. The objective of this study was to evaluate three different environmental fragility models within the Brazilian rainforest region and to use the results to develop environmental zone classes. Two rural river basins located in Ibiuna, Sao Paulo state, Brazil, were studied. Input variables, including slope class, relief dissection rate, soil class, lithology, land cover, and climate data, were used to compute environmental fragility classes using three standard models. The model outputs were evaluated on their ability to accurately predict the most sensitive and least sensitive areas. The best models for each region were used to derive environmental zoning maps, including restoration priorities, best regions for agriculture, and areas with high needs for soil management. These maps will help support land use strategies for environmental restoration. This study provides insight into territorial ordering and management of environmental services with a regional perspective.

Regional and local topography subdivision and landform mapping using SRTM-derived data: a case study in southeastern Brazil

Topographic subdivisions and landforms are important relief characteristics that serve as a basis for several types of regional and local planning. This paper presents an assessment of the application of a global landform classification method on a regional scale using Sao Paulo State as the study area and on a local scale using the city of Sao Paulo as the study area. In addition, a new approach that includes elevation derivatives for local analysis is presented. The study hypothesizes that the automated object-based classification of topography from shuttle radar topography mission (SRTM) data method could also be used for local mapping when supported by elevation derivative data. SRTM data were used in the regional approach and post-processed elevation data derived from SRTM were used for the local analysis. The results were compared with the best available geomorphological maps and topographic surface descriptions of the region. The new method resulted in a regional-scale product in which the boundaries and features of the topography matched those in the geomorphological maps and in the literature. The method did not perform well when classifying the local topographic subdivisions of Sao Paulo, even when using the interpolated elevation data. However, the surface edges and shapes identified in the topographic maps were represented in the resulting map. To refine the results, a new approach was proposed using data derived from a digital elevation model, such as drainage densities, horizontal and vertical curvatures, and slope gradients. The use of these products in the image segmentation process and classification criteria was fundamental for obtaining the results. Theoretical thresholds were used to define the relief classes, and landform characteristics were taken into account in developing the landform map. The success of this new approach is attributed to the comprehensive database that supported the topographic subdivision analysis. In summary, this study indicates that a method developed for use on a global scale can be replicated for use on a regional scale but not on a local scale. The new approach produced reasonable results and can be used in other regions. Greater detail can be obtained using various thresholds of horizontal and vertical curvatures, for example, when delineating hazard areas. The products have potential applications in urban planning, ecological-economic zoning, urban drainage, hazard mitigation, environmental issues, erosional dynamics and transportation planning.

Evaluation of Multiple Classifier Systems for Landslide Identification in LANDSAT Thematic Mapper (TM) Images

Landslide scar location is fundamental for the risk management process, e.g., it allows mitigation of these areas, decreasing the associated hazards for the population. Remote sensing data usage is an essential tool for landslide identification, mapping, and monitoring. Despite its potential use for landslide risk management, remote sensing usage does have a few drawbacks. The aforementioned events commonly occur at high steep slope regions, frequently associated with shadow occurrence in satellite images, which impairs the identification process and results in low accuracy classifications. In this sense, this paper aims to evaluate the accuracy of different ensembles of multiple classifier systems (MCSs) for landslide scar identification. A severe landslide event on a steep slope with a high rainfall rate area in the southeast region of Brazil was chosen. Ten supervised classifiers were used to identify this severe event and other possible features for the LANDSAT thematic mapper (TM) from June of 2000. The results were evaluated, and nine MCSs were constructed based on the accuracy of the classifiers. Voting was applied through the ensemble method, coupled with contextual analysis and random selection tie-breaker methods. Accuracy was evaluated for each classification ensemble, and a progressive enhancement in the ensemble accuracy was noted as the least accurate classifiers were removed. The best accuracy for landslide identification emerged from the ensemble of the three most accurate classification results. In summary, MCS application generally improved the classification quality and led to fewer omission errors, coupled with a better classification percentage for the ‘landslide’ class. However, the MCS ensemble algorithm selection must be customized to the purpose of the classification. It is crucial to assess single accuracy indicators of each algorithm to ascertain those with the most consistent performance regarding the final results.

Soil quality attributes related to urbanization in Brazilian watershed

AbstractIn this study we investigated the variation of soil attributes according to urban-related land cover categories. The study was carried out in an urbanized watershed located in the Brazilian subtropical region (Sorocaba Municipality, Sao Paulo). Soil samples were collected considering the land cover category for analysis of physical, chemical and isotopic attributes. The land cover influenced the soils attributes. Soils from wooded and grassed areas presented significant differences, especially for values of C isotopes. Soil bulk density was significantly altered. According to considered land cover mosaic in the study, we estimated 10,241.28 tons of C stored in the thickness 20 cm of the watershed (whole area), and this amount is almost a half of the total potential of C storing in the watershed. We stress that projects of planned land cover should effectively implemented in urbanized regions to effectively contribute in storing more C and improving the soil-related ecosystem services.