Assessment of aquatic plants in the reservoirs of AES-Tiete and development of an integrated control model for the most important species

The general objective of this work was to develop a monitoring and management model for aquatic plants that could be used in reservoir cascades in Brazil, using the reservoirs of AES-Tiete as a study case. The investigations were carried out at the reservoirs of Barra-Bonita, Bariri, Ibitinga, Promissao, and Nova-Avanhandava, located in the Tiete River Basin; Agua Vermelha, located in the Grande River Basin; Caconde, Limoeiro, and Euclides da Cunha, which are part of the Pardo River Basin; and the Mogi-Guacu reservoir, which belongs to the Mogi-Guacu River basin. The main products of this work were: development of techniques using satellite-generated images for monitoring and planning aquatic plant control; planning and construction of a boat to move floating plant masses and an airboat equipped with a DGPS navigation and application flow control system. Results allowed to conclude that the occurrence of all types of aquatic plants is directly associated with sedimentation process and, consequently, with nutrient and light availability. Reservoirs placed at the beginning of cascades are more subject to sedimentation and occurrence of marginal, floating and emerged plants, and are the priority when it comes to controlling these plants, since they provide a supply of weeds for the other reservoirs. Reservoirs placed downstream show smaller amounts of water-suspended solids, with greater transmission of light and occurrence of submerged plants.

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.

Road segment delineation using active testing principle and an edge-based post-processing strategy

This paper presents a semi-automated method for extracting road segments from medium-resolution images based on active testing and edge analysis. The method is based on two sequential and independent stages. Firstly, an active testing method is used to extract an approximated road centreline which is based on a sequential and local exploitation of the image. Secondly, an iterative strategy based on edge analysis and the approximated centreline is used to measure precisely the road centreline. Based on the results obtained using medium-resolution test images, the method seems to be very promising. In general, the method proved to be very accurate whenever the roads are characterized by two well-defined anti-parallel edges and robust even in the presence of larger obstacles such as trees and shadows.

Dinâmica da ocupação do solo bacia do Rio Itiquira, Mato Grosso, Brasil

The study area corresponds to the basin of the Itiquira river high course, totalling 5,361km2. In this area a study of the environmental dynamics was made, applying SIG techniques and satellite images of the years 1966, 1985 and 1996. In 1966 the areas of natural vegetation (forests and groves) occupied 90.64% of the total of the area, which was diminished to 60.57% in 1985 and to only 36.66% in 1996. In this process, 289,382ha of a total of 485,928ha of natural vegetal covering had been lost. At the same time, the agrarian surfaces (agriculture and pasture) that occupied only 0.52% of the total area in 1966, increased to 34.89% in 1985 and to 59.04% in 1996. In 30 years there was an increase of 313,725ha of cultivated lands, corresponding to about 113 times the land occupation of the year of 1966 (2,798ha). The areas classified as urban show a gradual increase since 1966, from 39ha in 1996 to 58ha in 1985, and to 178ha in 1996. The other classes of soil use and occupation (reforestement areas, uncovered and affected by fire and humid areas) added were smaller than 4,27% in 1996.

Detecção de pistas de aeroporto em imagens orbitais utilizando morfologia matemática

The Brazilian Cartography presents great deficiency in cartographic products updating. This form, Remote Sensins techniques together Digital Processing Images - DPI, are contributing to improve this problem. The Mathematical Morphology theory was used in this work. The principal function was the pruning operator. With its were extracted the interest features that can be used in cartographic process updating. The obtained results are positives and showed the use potential of mathematical morphology theory in cartography, mainly in updating.

Mapeamento do uso da terra, vegetação e impactos ambientais por meio de sensoriamento remoto e geoprocessamento

The mapping of the land use, vegetation and environmental impacts using remote sensing ana geoprocessmg allow detection, spatial representation and quantification of the alterations caused by the human action on the nature, contributing to the monitoring and planning of those activities that may cause damages to the environment. This study apply methodologies based on digital processing of orbital images for the mapping of the land use, vegetation and anthropic activities that cause impacts in the environment. It was considered a test area in the district of Assistência and surroundings, in Rio Claro (SP) region. The methodology proposed was checked through the crossing of maps in the software GIS - Idrisi. These maps either obtained with conventional interpretation of aerial photos of 1995, digitized in the software CAD Overlay and geo-referenced in the AutoCAD Map, or with the application of digital classification systems on SPOT-XS and PAN orbital images of 1995, followed by field observations. The crossing of conventional and digital maps of a same area with the CIS allows to verify the overall results obtained through the computational handling of orbital images. With the use of digital processing techniques, specially multiespectral classification, it is possible to detect automatically and visually the impacts related to the mineral extraction, as well as to survey the land use, vegetation and environmental impacts.

Detecção de bordas em imagens digitais através de um processo de difusão anisotrópica não linear

The edges detection model by a non-linear anisotropic diffusion, consists in a mathematical model of smoothing based in Partial Differential Equation (PDE), alternative to the conventional low-pass filters. The smoothing model consists in a selective process, where homogeneous areas of the image are smoothed intensely in agreement with the temporal evolution applied to the model. The level of smoothing is related with the amount of undesired information contained in the image, i.e., the model is directly related with the optimal level of smoothing, eliminating the undesired information and keeping selectively the interest features for Cartography area. The model is primordial for cartographic applications, its function is to realize the image preprocessing without losing edges and other important details on the image, mainly airports tracks and paved roads. Experiments carried out with digital images showed that the methodology allows to obtain the features, e.g. airports tracks, with efficiency.

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.

Análise da evolução da paisagem no entorno da represa dos rios jaguari e jacareí, estado de são paulo, com base em sensoriamento remoto e SIG

The primary objective of this study is to evaluate by means of remote sensing and GIS, the landscape evolution around the Jaguari and Jacareí River Dam, located in the eastern section of the State of São Paulo, Brazil. For this purpose we used LANDSAT 5/YM and CBERS-2/CCD images from 1984/1985 and 2006, respectively, considering the following classes of land use: forest, cultivated forest, agriculture, urban areas and water bodies. The two selected dates reflect important changes in the region such as the installation of the dam and subsequent urbanization of parts of its margins and the enlargement of the Fernão Dias Federal Highway, which contributed to an increase of areas of anthropic activities in the studied region. The results also indicate an increase in areas covered by native and planted forests, thus confirming a similar trend in other areas of the State of São Paulo.

Diagnóstico das áreas de preservação permanente na bacia hidrográfica do rio Tijuco, Ituiutaba - MG, utilizando tecnologia SIG

The present work had the objective to elaborate the map of land use and vegetation covering from Tijuco river watershed, Ituiutaba-MG, based on digital images obtained by satellite from CBERS 2, through automatic delimitation of permanent preservation areas followed by identification of land use conflict based on the Brazilian Forest Code (Law no 4771/1965) and National Council of Environment's Resolution no 303/02. This paper analyzes, through quantitative parameters and the use of Geographic Information System, the maintenance tracks of width recommended by the legislation for permanent preservation areas over water bodies. The results showed a deficit of conserved areas along the riverbanks of 2334 ha that are not in compliance with the legislation. The pasture occupies unduly 0.97% of the area of the basin in the permanent preservation areas at the riverbanks, while agriculture occupies 0.38%.

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.

Paleocanais no megaleque do rio Taquari: mapeamento e signifcado geomorfológico

This paper presents the results of the frst systematic mapping of the paleochannel network on the Taquari megafan (Pantanal, Brazil). We used remote sensing data collected by the ASTER sensor, which captures images with 15 m square pixels. A total of 34 scenes, acquired from 2001-2006, were used in the analysis. These data were processed using a decorrelation stretch technique in order to obtain a better visual identifcation of the paleochannels. The mapping procedure began with the overlay of a 1:50.000 IBGE articulation, in order to systematize the extraction of features and to reduce the subjectivity inherent to visual analysis methods. We mapped a total of 33,205 km of paleochannels. The density of these features is related to the relative ages of distinct geomorphological compartments, known as depositional lobes. The mapped features preserve avulsion events that occurred on the megafan. The results suggest that low-magnitude avulsions occur more frequently than larger events.

Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data

We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.

Land use image classification through optimum-path forest clustering

Land use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.

Mapeamento geoambiental como subsídio na determinação de áreas de instabilidades da faixa de dutos Osvat/Osplan - São Sebastião, SP

Works of linear engineering such as roads, pipelines and transmission lines have specific mapping due to their large scale impact on the environment, thus requiring mapping methods that are both efficient and of low cost. This paper presents a proposal of Geoenvironmental mapping for works linear. The work chosen for the implementation of the method was the Osvat/Osplan pipeline located in the cities of São Sebastião and Caraguatatuba. The geoenvironment mapping was elaborate trough photo-interpretation of images of the ETM+/Landsat-7 sensor and analysis of the drainage network, thus resulting in the partitioning of the geoenvironmental units and the fracture area (structural lineaments and lines of strikes), these maps were subsequently integrated into a product called Map of environmental susceptibility to gravitational and erosive processes, which helped define the areas with potential geotechnical problems that could damage both the pipeline and the environment.