Traditionally radio spectrum was considered a commodity to be allocated in a fixed and centralized manner, but now the technical community and the regulators approach it as a shared resource that can be flexibly and intelligently shared between competing entities. In this thesis we focus on novel strategies to sense and access the radio spectrum within the framework of Opportunistic Spectrum Access via Cognitive Radio Networks (CRNs). In the first part we develop novel transmit opportunity detection methods that effectively exploit the gray space present in packet based networks. Our methods proactively detect the maximum safe transmit power that does not significantly affect the primary network nodes via an implicit feedback mechanism from the Primary network to the Secondary network. A novel use of packet interarrival duration is developed to robustly perform change detection in the primary network's Quality of Service. The methods are validated on real world IEEE 802.11 WLANs. In the second part we study the inferential use of Goodness-of-Fit tests for spectrum sensing applications. We provide the first comprehensive framework for decision fusion of an ensemble of goodness-of-fit tests through use of p-values. Also, we introduce a generalized Phi-divergence statistic to formulate goodness-of-fit tests that are tunable via a single parameter. We show that under uncertainty in the noise statistics or non-Gaussianity in the noise, the performance of such non-parametric tests is significantly superior to that of conventional spectrum sensing methods. Additionally, we describe a collaborative spatially separated version of the test for robust combining of tests in a distributed spectrum sensing setting. In the third part we develop the sequential energy detection problem for spectrum sensing and formulate a novel Sequential Energy Detector. Through extensive simulations we demonstrate that our doubly hierarchical sequential testing architecture delivers a significant throughput improvement of 2 to 6 times over the fixed sample size test while maintaining equivalent operating characteristics as measured by the Probabilities of Detection and False Alarm. We also demonstrate the throughput gains for a case study of sensing ATSC television signals in IEEE 802.22 systems. / text

The decline of coral reef habitats has been witnessed on a global scale, with some of the most dramatic decline occurring in the florida keys. as remote sensing can provide a synoptic view of coral reef ecosystems, 28 landsat images (1984-2002) were utilized to study water clarity and habitat change. first, the data were used to derive the diffuse attenuation coefficient (kd, m-1), a measure of water clarity, for 29 sites throughout the florida keys national marine sanctuary (fknms). landsat-derived kd values from bands 1 (blue) and 2 (green) provided useful information for 26 of 29 sites, whereas band 3 (red) provided no consistent data due to the high absorption of red light by water. it was not possible to assess long-term temporal trends as data were acquired, at most, twice a year. spatial variability was high between sites and between regions (upper, middle and lower keys) for bands 1 (0.019 m-1 - 0.060 m-1) and 2 (0.036 m-1 - 0.076 m-1). the highest kd values were f ound in the upper keys, followed by the middle and lower keys, respectively. this trend was corroborated by in situ monitoring of kd(par). second, the data were used to assess benthic habitat changes in eight coral reef sites located in the fknms. a mahalanobis distance classification was trained for four classes using in situ ground-truth data. overall coral habitat decline was 61% (3.4%/y), from 19% (1984) to 7.7% (2002). in situ monitoring data acquired by the coral reef evaluation and monitoring project (cremp) for the eight reef sites (1996-2002) showed a loss in coral cover of 52%, whereas the landsat-derived coral-habitat cover declined 37% for the same time period. a trend comparison between the full cremp percent coral cover data (1996-2004) and the full landsat-derived coral habitat class (1984-2002) showed no significant difference between the rates of change (ancova f-test, p = 0.303). The derivation of Kd and benthic habitat maps produced from Landsat data could provide c oastal marine managers another tool to help in the decision-making process.

This project analyzes satellite images from 1976, 1985 and 2000 of Dutse, Jigawa state, in north-western Nigeria. The analyzed satellite images were used to determine land-use and vegetation changes that have occurred in the land-use from 1976 to 2000 will help recommend possible planning measures in order to protect the vegetation from further deterioration. Studying land-use change in north-western Nigeria is essential for analyzing various ecological and developmental consequences over time. The north-western region of Nigeria is of great environmental and economic importance having land cover rich in agricultural production and livestock grazing. The increase of population over time has affected the land-use and hence agricultural and livestock production. On completion of this project, the possible land use changes that have taken place in Dutse will be analyzed for future recommendation. The use of supervised classification and change detection of satellite images have produced an economic way to quantify different types of landuse and changes that has occurred over time. The percentage difference in land-use between 1976 and 2000 was 37%, which is considered to be high land-use change within the period of study. The result in this project is being used to propose planning strategies that could help in planning sustainable land-use and diversity in Dutse.

The present thesis employed event-related potentials, the minute responses of the brain, to examine the differences in processing of increases and decreases in auditory intensity. The manner in which intensity was manipulated (i.e., whether it represented physical or psychological change) varied across the studies of the thesis. Study 1 investigated the processing of physical intensity change during wakefulness and natural sleep. An oddball paradigm (80 dB standard, 90 dB increment, 60 dB decrement) was presented to subjects during the waking state and during sleep. The increment elicited a larger deviant-related negativity and P3a than the decrement in the waking state. During sleep, only the increment deviant continued to elicit ERPs related to the detection of change. The waking and sleeping findings support the notion that increases in intensity are more salient to an observer. Studies 2 and 3 of this thesis determined the degree to which this differential salience could be attributed to the fact that intensity increments result in increased activation of the change and transient detection systems while intensity decrements result in greater activation of only the change detection system. In order to address this question, an alternating intensity pattern was employed (HLHLHLHL) with deviants created by the repetition of a tone in the sequence (HLHLHHHL) that violated the expectancy for a higher (psychological decrements) or lower intensity tone (psychological increments). Because deviant stimuli were physically identical to preceding standards, this manipulation should not have led to increased output of the transient detection system (N1 enhancement), permitting isolation of the output of the change detection system (Mismatch Negativity, MMN). The findings of these studies indicated that psychological increments resulted in shorter latency and larger amplitude MMNs than psychological decrements and that these differences could not be explained by the physical differences between deviant stimuli or temporal integration. This thesis provides convincing evidence that stimuli representing increments in intensity result in faster and more robust change detection. Further, the increased salience of increment stimuli cannot be solely explained by the contribution of transient detector activation, as it persists even when deviance-related processing is isolated to the change detection system.

Rapid urban growth and unprecedented rural to urban transition, along with a huge population growth are new phenomena for both high and low income countries, which started in the mid-20th century. However, urban growth rates and patterns are different in developed countries and developing ones. In less developed countries, urbanization and rural to urban transition usually takes place in an unmanaged way and they are associated with a series of socioeconomical and environmental issues and problems. Identification of the city growth trends in past decades can help urban planners and managers to minimize these negative impacts. In this research, urban growth in the city of Isfahan, Iran, is the subject of study. Isfahan the third largest city in Iran has experienced a huge urban growth and population boom during the last three decades. This transition led to the destruction of natural and agricultural lands and environmental pollutions. Historical and recent remotely sensed data, along with different remote sensing techniques and methods have been used by researchers for urban land use and land cover change detection. In this study three Landsat TM and ETM+ images of the study site, acquired in 1985, 2000 and 2009 are used. Before starting processing, radiometric normalization is done to minimize the atmospheric effects. Then, processing methods including principal component analysis (PCA), vegetation indices and supervised classification are implemented on the images. Accuracy assessment of the PCA method showed that the first PC was responsible for more than 81% of the total variance, and therefore used for analysis of PCA differencing. ΔPC1t1-t2 shows the amount of changes in land use and land cover during the period of study. In this study ten vegetation indices were selected to be applied to the 1985 image. Accuracy assessments showed that Transformed Differencing Vegetation Index (TDVI) is the most sensitive and accurate index for mapping vegetation in arid and semi-arid urban areas. Hence, TDVI was applied to the 2000 and 2009 images. ΔTDVIt1-t2 showed the changes in land use and land cover especially the land use transformation from vegetation cover into the urban class. Supervised classification is the last method applied to the images. Training sites were assigned for the selected classes and accuracy was monitored during the process of training site selection. The results of classification show the expansion of urban class and diminishment in natural and agricultural lands.

Detecting regions of change while reducing unimportant changes in multiple outdoor images of the same scene containing fence wires (i.e., a chain-link mesh fence) acquired by a mobile camera from slightly different viewing positions, angles and at different times is a very difficult problem. Regions of change include appearing of new objects and/or disappearing of old objects behind fence wires, breaches in the integrity of fence wires and attached objects in front of fence wires. Unimportant changes are mainly caused by camera movement, considerable background clutter, illumination variation, tiny sizes of fence wires and non-uniform illumination that occurs across fence wires. There are several issues that arise from these kinds of multiple outdoor images. The issues are: (1) parallax (the apparent displacement of an object as seen from two different positions that are not on a line with the object) among objects in the scene, (2) changing in size of same objects as a result of camera movement in forward or backward direction, (3) background clutter of outdoor scenes, (4) thinness of fence wires and (5) significant illumination variation that occurs in outdoor scenes and across fence wires. In this dissertation, an automated change detection method is proposed for these kinds of multiple outdoor images. The change detection method is composed of two distinct modules, which are a module for detecting object presence and/or absence behind fence wires and another module for detecting breaches in the integrity of fence wires and/or attached objects in front of fence wires. The first module consist of five main steps: (1) automated image registration, (2) confidence map image production by the Zitnick and Kanade algorithm, (3) occlusion map image generation, (4) significant or unimportant changes decision by the first hybrid decision-making system and (5) false positives reduction by the template subtraction approach. The second module integrates: (1) the Sobel edge detector combined with an adaptive thresholding technique in extracting edges of fence wires, (2) an area-based measuring in separating small and big objects based on their average areas determined once in the calibration process and (3) the second hybrid decision-making system in classifying objects as significant or unimportant changes. Experimental results demonstrate that the change detection method can identify and indicate approximate locations and possible percentages of significant changes whilst reducing unimportant changes in these kinds of multiple outdoor images. The study has utilized occluded regions in a confidence map image produced by the Zitnick and Kanade algorithm as potential significant changes in the image change detection research. Moreover, the study proves that the use of the Sobel edge detector combined with an adaptive thresholding technique is applicable in extracting edges of outdoor fence wires. In the future, the method could be integrated into patrol robots in order to provide assistance to human guards in protecting outdoor perimeter security. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1522689 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2010

The constant analysis of the condition of ciliary vegetation is fundamental in the management and conservation of natural resources as well as in the maintenance of local biodiversity. The main objective of this study is to detect and analyze the changes of vegetation cover of riparian areas in the Rio Vacacaí Mirim basin, in the state of Rio Grande do Sul, using the technique of Radiometric Rotation Controlled by Axis of Non-Change (RCEN). The RCEN technique allows the control of the digital algorithm of the detection of these changes, through the radiometric rotation of the multitemporal image and band of the visible spectrum, generating an image detection of these changes. In this study, images from the remote sensor Thematic Mapper - Landsat 5 were used to visualize and obtain information from research areas and GIS to perform RCEN procedures and image visualization. At work, pairs of images were analyzed, between the years of 2001 and 2011, in periods of 5 to 10 years, allowing the analysis of these changes over time. The resulting detection images, after statistical analysis, were categorized into three classes: degradation, preservation and recovery of vegetation cover. These results are based on the values of the pixels analyzed in each of the studied scenes: in the areas of degradation the pixels present themselves with positive (clearer) values, in the preservation areas the pixels present themselves with values close to zero and in the recovery areas present negative (darker) values. The analysis of the resulting cartographic material allowed a broader and more detailed view of the change of the scene along the Vacacaí Mirim basin, resulting from the impact of the anthropic actions suffered and the new landscape of soybean cultivation, replacing the bovine farming areas. In the study it was verified how much the basin was degraded during 10 years, but in the analysis of the drainage along the same approximately 30% of the same one was in stage of conservation and regeneration. Increasingly, the need for studies, monitoring and inspection of riparian areas, so important in maintaining the aquatic ecosystem, availability and quality of water and preservation of biodiversity, as a consequence, with the mandatory registration of all rural owners in the Environmental Registry Rural, demonstrating the importance of research. / A análise constante da condição das vegetações ciliares é fundamental na gestão e conservação dos recursos naturais assim como na manutenção da biodiversidade local. O objetivo principal desse estudo é detectar e analisar as mudanças de cobertura vegetal de áreas ciliares na bacia do Rio Vacacaí Mirim, no estado do Rio Grande do Sul utilizando a técnica de Rotação Radiométrica Controlada por Eixo de Não Mudança (RCEN). A técnica RCEN permite o controle do algoritmo digital da detecção dessas mudanças, através da rotação radiométrica da imagem multitemporal e banda do espectro visível, gerando uma imagem detecção dessas mudanças. Neste estudo foram utilizadas imagens do sensor remoto Thematic Mapper - Landsat 5, para visualização e obtenção de informações das áreas de pesquisa e SIG para realização dos procedimentos da técnica RCEN e visualização das imagens detecção de mudanças. No trabalho, pares de imagens foram analisados, compreendidos entre os anos de 2001 e 2011, em períodos de 5 a 10 anos, possibilitando a análise dessas mudanças ao longo do tempo. As imagens detecção resultantes, após análises estatísticas, foram categorizadas em três classes: degradação, preservação e recuperação da cobertura vegetal. Estes resultados se baseiam nos valores dos pixels analisados em cada uma das cenas estudadas: nas áreas de degradação os pixels se apresentam com valores positivos (mais claros), nas áreas de preservação os pixels se apresentam com valores próximos a zero e nas áreas de recuperação, apresentam valores negativos (mais escuros). A análise do material cartográfico resultante, possibilitou uma visão mais ampla e detalhada da mudança da cena ao longo da bacia do Vacacaí Mirim, através do resultado do impacto das ações antrópicas sofridas e da nova paisagem de cultivo da soja em substituição a áreas de bovinocultura. No estudo verificou-se o quanto a bacia foi degradada ao longo de 10 anos, porém, na análise da drenagem ao longo da mesma aproximadamente 30% da mesma encontrou-se em estágio de conservação e regeneração. A cada dia aumenta a necessidade de estudos, monitoramento e fiscalização de áreas ciliares, tão importantes na manutenção do ecossistema aquático, da disponibilidade e qualidade da água e preservação da biodiversidade, consequentemente, com a obrigatoriedade da inscrição de todos os proprietários rurais no Cadastro Ambiental Rural, demonstrando a importância da pesquisa.

A evolução do sistema Terrestre sempre foi constante, apresentando períodos com instabilidade de grande, média ou pequena magnitude. A zona costeira é um ambiente que está na interface entre o continente e o oceano, na qual as dunas dessa região apresentam intenso dinamismo, o que torna imprescindível o seu constante monitoramento. A técnica de rotação radiométrica controlada por eixo de não mudança (RCEN) possibilita a análise multitemporal de uma paisagem através da avaliação dos padrões de resposta espectral de toda a imagem, sem a necessidade de correção dos efeitos atmosféricos. Os objetivos desta dissertação são analisar a dinâmica espaço-temporal do Parque Nacional dos Lençóis Maranhenses (PNLM) no período de 1984 a 2014, a partir da análise de imagens de satélite e avaliar a técnica RCEN para a identificação e monitoramento das alterações do parque. A área de estudo está localizada na região nordeste do Brasil, litoral oriental do estado do Maranhão, e tornou-se uma área de proteção ambiental por meio do Decreto Federal nº 86.060, de 02 de junho de 1981. Para as análises foram utilizadas imagens dos satélites Landsat 5 - Sensor TM e Landsat 8 - Sensor OLI para os períodos estudados. A borda limite do parque na parte interior do continente foi vetorizada a partir das imagens dos anos de 1984 e de 2014, para se avaliar o avanço e a retração das dunas. Foram elaborados mapas com o deslocamento dunário em um período de 30 anos sendo identificado um maior avanço em relação à retração em toda a área. A variação do comportamento espectral de pontos de monitoramento também foi avaliada, para identificar o período da ocorrência da mudança. A RCEN foi testada na borda interna limítrofe do parque, na qual foi determinado o ângulo de rotação dos eixos radiométricos, que é o principal parâmetro para a obtenção da imagem de detecção de mudanças. Foi possível a identificação das áreas de não mudança (90,67%) e a variação das dunas (5, 20%), vegetação (3,86%) e água (0,27%) em relação à área total. Identificou-se que a expansão das dunas, do litoral em direção ao interior do continente, ocorre no sentido nordeste - sudoeste, seguindo a circulação dos ventos alísios e que a vegetação ocupou os espaçamentos deixados pelas dunas ou pela água das lagoas. A RCEN foi eficaz ao traduzir as alterações na área analisada. Considerando o tipo de mudanças identificadas, entende-se que monitorar o deslocamento dunário no PNLM é relevante para o planejamento do parque, pois este representa um importante ecossistema da região, bem como é um considerável polo turístico para o Brasil. / The Earth system evolution has always been constant, presenting large, medium or small magnitude instability. The coastal zone is an environment that occurs at the interface between the continent and the ocean, where the dunes have an intense dynamic, requiring their constant monitoring. The radiometric rotation controlled by no change axis (RCEN) technique allow multi-temporal analysis of a landscape by evaluating the spectral response patterns of the entire image, without the need for correction of atmospheric effects. The aim of this study was to analyze the spatio-temporal dynamics of the Parque Nacional dos Lençóis Maranhenses (PNLM) during 1984 to 2014, from satellite imagery analysis and evaluate the RCEN technique for the identification and monitoring of these changes. The study area is located in northeastern Brazil, eastern coast of the state of Maranhão, and has become an environmental protection area through the Federal Decree No. 86060 of June 2, 1981. For these analyses were used satellite images from the Landsat 5-TM and Landsat 8-OLI sensors. The park edge boundary in the inner part of the continent was vectored from the images of the years 1984 and 2014, to assess the advancement and retraction of the dunes. Were made maps with the dunes changes over a period of 30 years and were identified a bigger advancement in relation of the shrinkage among throughout the area. The spectral pattern variation in some monitoring points was also evaluated to identify the timing of the change occurrence. The RCEN was tested in the adjacent inner border of the park in where the angle of rotation of radiometric axis was determined, considering that this angle is the main parameter for obtaining the change detection image. Were identified areas without changes (90.67%) and the variation of the dunes (5, 20%), vegetation (3.86%) and water (0.27%) in relation to the total area. It was identified that the expansion of the dunes, occurs from the coast line towards the interior of the continent, with the northeast – southwest direction, following the circulation of trade winds, while the vegetation occupied the gaps left by the dunes or water ponds. The RCEN was effective in identify the changes in the study area. Considering those changes detected, monitoring the dunes movement in PNLM is relevant to the park planning, once it represents an important ecosystem of the region and is a great tourist hub for Brazil.

A evolução do sistema Terrestre sempre foi constante, apresentando períodos com instabilidade de grande, média ou pequena magnitude. A zona costeira é um ambiente que está na interface entre o continente e o oceano, na qual as dunas dessa região apresentam intenso dinamismo, o que torna imprescindível o seu constante monitoramento. A técnica de rotação radiométrica controlada por eixo de não mudança (RCEN) possibilita a análise multitemporal de uma paisagem através da avaliação dos padrões de resposta espectral de toda a imagem, sem a necessidade de correção dos efeitos atmosféricos. Os objetivos desta dissertação são analisar a dinâmica espaço-temporal do Parque Nacional dos Lençóis Maranhenses (PNLM) no período de 1984 a 2014, a partir da análise de imagens de satélite e avaliar a técnica RCEN para a identificação e monitoramento das alterações do parque. A área de estudo está localizada na região nordeste do Brasil, litoral oriental do estado do Maranhão, e tornou-se uma área de proteção ambiental por meio do Decreto Federal nº 86.060, de 02 de junho de 1981. Para as análises foram utilizadas imagens dos satélites Landsat 5 - Sensor TM e Landsat 8 - Sensor OLI para os períodos estudados. A borda limite do parque na parte interior do continente foi vetorizada a partir das imagens dos anos de 1984 e de 2014, para se avaliar o avanço e a retração das dunas. Foram elaborados mapas com o deslocamento dunário em um período de 30 anos sendo identificado um maior avanço em relação à retração em toda a área. A variação do comportamento espectral de pontos de monitoramento também foi avaliada, para identificar o período da ocorrência da mudança. A RCEN foi testada na borda interna limítrofe do parque, na qual foi determinado o ângulo de rotação dos eixos radiométricos, que é o principal parâmetro para a obtenção da imagem de detecção de mudanças. Foi possível a identificação das áreas de não mudança (90,67%) e a variação das dunas (5, 20%), vegetação (3,86%) e água (0,27%) em relação à área total. Identificou-se que a expansão das dunas, do litoral em direção ao interior do continente, ocorre no sentido nordeste - sudoeste, seguindo a circulação dos ventos alísios e que a vegetação ocupou os espaçamentos deixados pelas dunas ou pela água das lagoas. A RCEN foi eficaz ao traduzir as alterações na área analisada. Considerando o tipo de mudanças identificadas, entende-se que monitorar o deslocamento dunário no PNLM é relevante para o planejamento do parque, pois este representa um importante ecossistema da região, bem como é um considerável polo turístico para o Brasil. / The Earth system evolution has always been constant, presenting large, medium or small magnitude instability. The coastal zone is an environment that occurs at the interface between the continent and the ocean, where the dunes have an intense dynamic, requiring their constant monitoring. The radiometric rotation controlled by no change axis (RCEN) technique allow multi-temporal analysis of a landscape by evaluating the spectral response patterns of the entire image, without the need for correction of atmospheric effects. The aim of this study was to analyze the spatio-temporal dynamics of the Parque Nacional dos Lençóis Maranhenses (PNLM) during 1984 to 2014, from satellite imagery analysis and evaluate the RCEN technique for the identification and monitoring of these changes. The study area is located in northeastern Brazil, eastern coast of the state of Maranhão, and has become an environmental protection area through the Federal Decree No. 86060 of June 2, 1981. For these analyses were used satellite images from the Landsat 5-TM and Landsat 8-OLI sensors. The park edge boundary in the inner part of the continent was vectored from the images of the years 1984 and 2014, to assess the advancement and retraction of the dunes. Were made maps with the dunes changes over a period of 30 years and were identified a bigger advancement in relation of the shrinkage among throughout the area. The spectral pattern variation in some monitoring points was also evaluated to identify the timing of the change occurrence. The RCEN was tested in the adjacent inner border of the park in where the angle of rotation of radiometric axis was determined, considering that this angle is the main parameter for obtaining the change detection image. Were identified areas without changes (90.67%) and the variation of the dunes (5, 20%), vegetation (3.86%) and water (0.27%) in relation to the total area. It was identified that the expansion of the dunes, occurs from the coast line towards the interior of the continent, with the northeast – southwest direction, following the circulation of trade winds, while the vegetation occupied the gaps left by the dunes or water ponds. The RCEN was effective in identify the changes in the study area. Considering those changes detected, monitoring the dunes movement in PNLM is relevant to the park planning, once it represents an important ecosystem of the region and is a great tourist hub for Brazil.

Esta tese investiga uma abordagem supervisionada para o problema da detecção de mudanças em imagens multitemporais de sensoriamento remoto empregando Support Vector Machines (SVM) com o uso dos kernels polinomial e gaussiano (RBF). A proposta metodológica está baseada na diferença das imagens-fração produzidas para cada data. Em imagens de cenas naturais a diferença nas frações de solo e vegetação tendem a apresentar uma distribuição simétrica em torno da origem. Esse fato pode ser usado para modelar duas distribuições normais multivariadas: mudança e não-mudança. O algoritmo Expectation-Maximization (EM) é implementado para estimar os parâmetros (vetor de médias, matriz de covariância e probabilidade a priori) associados a essas duas distribuições. Amostras aleatórias são extraídas dessas distribuições e usadas para treinar o classificador SVM nesta abordagem supervisionada. A metodologia proposta realiza testes com o uso de conjuntos de dados multitemporais de imagens multiespectrais TM-Landsat, que cobrem a mesma cena em duas datas diferentes. Os resultados são comparados com outros procedimentos, incluindo trabalhos anteriores, um conjunto de dados sintéticos e o classificador SVM One-Class. / In this thesis, we investigate a supervised approach to change detection in remote sensing multi-temporal image data by applying Support Vector Machines (SVM) technique using polynomial kernel and Gaussian kernel (RBF). The methodology is based on the difference-fraction images produced for two dates. In natural scenes, the difference in the fractions such as vegetation and bare soil occurring in two different dates tend to present a distribution symmetric around the origin of the coordinate system. This fact can be used to model two normal multivariate distributions: class change and no-change. The Expectation-Maximization algorithm (EM) is implemented to estimate the parameters (mean vector, covariance matrix and a priori probability) associated with these two distributions. Random samples are drawn from these distributions and used to train the SVM classifier in this supervised approach.The proposed methodology performs tests using multi-temporal TMLandsat multispectral image data covering the same scene in two different dates. The results are compared to other procedures including previous work, a synthetic data set and SVM One-Class.