Análise da vulnerabilidade natural à erosão na Bacia Hidrográfica do Rio Tijucas através de técnicas de geoprocessamento: um subsídio à governança territorial

This study analyzed the natural erosion vulnerability of a watershed, using geoprocessing techniques aiming to subsidize planning and the territorial governance. The study area was the Tijucas River Basin (SC), region that suffered damages with the intense rainfall and erosive processes, such as landslides, in the end of 2008. The methodology applied to generate the natural erosion vulnerability chart was developed by the Crepani et al. (2001) and serves as a subsidy to the Ecological and Economical Zoning, which is an instrument of the National Environment Policy (6.938/97 Law) and the criteria for its elaboration in Brazil are disposed on the 4.297/02 Decree. It was used the Thematic Charts of RADAMBRASIL Project as cartographic bases and the hydrological data of the rainfall stations of ANA (National Water Agency). The results obtained in this research are the natural erosion vulnerability maps for the subjects of Geology, Geomorphology, Vegetation, Pedology and Climate and the Natural Erosion Vulnerability Map for the studied area. The Tijucas River Watershed presented moderately stable areas (11%), middling stable/vunerable areas (79%) and moderately vunerable areas (10%). A municipal analysis of the results was performed, which indicated Canelinha, Itapema and Rancho Queimado as the cities with the largest moderately vulnerable areas. The results were presented in a meeting to representatives of the Tijucas River Watershed comittee representatives, and can subsidize future plans, programs and public political programs aimed to the minimize environmental impacts of erosive processes.Pages: 1113-112

Monitoring flood extent in the lower Amazon River floodplain using ALOS/PALSAR ScanSAR images

The Amazon River floodplain is subject to large seasonal variations in water level and flood extent, due to the large size and low relief of the basin, and the large amount of precipitation in the region. Synthetic Aperture Radar (SAR) data can be used to map flooded area in these wetlands, given its ability to provide continuous information without being heavily affected by cloud cover. As part of JAXA's Kyoto & Carbon Initiative, extensive wide-swath, multi-temporal SAR coverage of the Amazon basin has been obtained using the ScanSAR mode of ALOS PALSAR. This study presents a method for monitoring flood extent variation using ALOS ScanSAR images, tested at the Curuai Lake floodplain, in the lower Amazon River, Brazil. Twelve ScanSAR scenes were acquired between 2006 and 2010, including seven during the 2007 hydrological year. Water level records, field photographs, optical images (Landsat-5/TM and MODIS/Terra and Aqua) and topographic data were used as auxiliary information. A data mining algorithm allowed the implementation of a hierarchical, object-based classification algorithm, able to map land cover types and flooding status in the study area for all available dates. Land cover based on the entire time series (classification levels 1 and 2) had overall accuracies of 90% and 83%, respectively. Level 3 classifications (one map per image date) were validated only for the lowest and highest water stages, with overall accuracies of 76% and 78%, respectively. Total flood extent (Level 4) was mapped with 84% and 94% accuracies, for the low and high water stages, respectively. Regression models were fitted between mapped flooded area and water levels at the Curuai gauge to predict flood extent. A polynomial model had R2 = 0.95 (p < 0.05) and an overall root mean square error (RMSE) of 241 km2, while a logistic model had R2 = 0.98 (p < 0.05) and RMSE = 127 km2

Simulação de uma imagem WFI/CBERS-3 para a classificação de massas d’água no Reservatório de Ibitinga – SP

Even though currently there are a lot of sensors with adequate spectral and radiometric resolutions and field of view to the water properties characterization, the low spatial resolution limits the application of their images on the inland water study. The WFI sensor that will be launched at the CBERS-3 satellite may fill this gap by having spectral, radiometric and spatial characteristics that attend the application needs for inland water studies. To assess a sensor performance before its launch there are available image simulation methods. This article aimed to assess the potential of a WFI/CBERS-3 image to distinguish optically distinct water masses in the Ibitinga ReservoirSP. Therefore, it was accomplished the image simulation of this sensor from a QuickBird scene, which has similar spectral and radiometric properties to the WFI sensor. Unsupervised classifications were performed with different numbers of spectral classes for the simulated image and for a TM/Landsat-5 image (resampled to the same pixel size). It was realized that the application of high radiometric resolution images allows the obtaining of better results for the optically distinct water masses classification. However, the use of high spatial resolution images on the simulation process may complicate the water masses distinction due to the direct surface reflection of the Sun light. The surface water ripples caused by the wind action intensify the brightness in these images, damaging the classification. Nevertheless, the WFI/CBERS-3 image simulation indicated a high potential of this sensor to water quality studies in inland aquatic systems.Pages: 2530-253