HIERARQUIZAÇÃO DAS MORADIAS COM RISCO GEOMORFOLÓGICO ASSOCIADO AO ARROIO CADENA – SANTA MARIA, RS: ESTUDO DE CASO NAS VILAS OLIVEIRA, LÍDIA E URLÂNDIA1

In the city of Santa Maria, the growth of the urban area occurred with the occupation of the margins of Arroio Cadena, which was responsible for the emergence of many risky areas. Oliveira, Lídia and Urlândia villages are in the most problematic areas of the city. In this context, the main objective of this paper is to determine the surface dynamics processes that trigger the risk and to identify and hierarchize the risky dwellings of these villages. To identify the dwellings at margin erosion risk, it was considered the distance between the dwellings and the margins of the Arroio; for the dwellings at overflow risk there was considered the quota of the land where the dwellings are constructed; The dwellings that are both at margin erosion and at flood risk were hierarchized based on the frequency of accidents and on the dwellings’ constructive and structural features; the hierarchization of the dwellings at flood risk was realized based on the frequency of the accidents that occurred. In these villages there are 567 dwellings at risk, from which 107 present margin erosion risk, 260 present flood risk, 64 present both margin erosion risk and flood risk, and 136 present overflow risk. Key words: Geomorphologic risk. Margin erosion. Overflow/flood.Na cidade de Santa Maria o crescimento da área urbana ocorreu com a ocupação das margens do Arroio Cadena que desencadeou o surgimento de várias áreas de risco. As Vilas Oliveira, Lídia e Urlândia encontram-se entre os locais mais problemáticos da cidade. Neste contexto, o objetivo principal deste trabalho consiste em determinar os processos de dinâmica superficial desencadeadores de risco e identificar e hierarquizar as moradias em risco situadas nas vilas citadas. Para identificação das moradias com risco de erosão de margem e inundação o principal fator considerado foi a distância entre as moradias e as margens do Arroio, bem como as características construtivas e estruturais das mesmas. Para as moradias com risco de alagamento foi considerado a cota do terreno em que estão construídas. Nestas vilas foram identificadas 567 moradias em risco, sendo que 107 apresentam risco de erosão de margem, 260 apresentam risco de inundação, 64 possuem risco tanto de erosão de margem como de inundação e 136 apresentam risco de alagamento. Palavras chave: Risco geomorfológico. Erosão de margem. Alagamento/inundação

Boletín del Servicio Meteorológico Nacional: Epoca 2ª Año XIV Número 309 - 1965 Noviembre 05

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Classification and shadowing effects in vineyards, derived from aster images

O desenvolvimento de novas tecnologias proporciona meios para novas pesquisas e, no caso dos dados gerados por sensores remotos, seu entendimento e utilização constituem uma ampla fonte para a geração de novos conhecimentos científicos. Imagens de média resolução espacial, a exemplo o sensor ASTER, apresentam fontes de informação de grande valor. O presente trabalho tem o propósito de investigar as potencialidades dessas imagens na discriminação espectral de vinhedos e, adicionalmente, verificar o comportamento espectral de variedades de viníferas frente à influência de efeitos de sombreamento. Para esta análise, a Vinícola Veramonte, no Valle de Casablanca-Chile, foi escolhida por ser adequada em termos de topografia, repartição de parcelas, informações de campo e disponibilidade de imagens. Como imagens ASTER são coletadas com resoluções de 15m e 30m, operações de reamostragem são necessárias para uma maior exploração dos dados. As bandas do subsistema SWIR, com pixels de 30 m, foram reamostradas pelo método do Vizinho mais Próximo para 15 m e processadas junto com as três bandas do subsistema VNIR, possibilitando realizar a investigação espectral utilizando-se 9 bandas. Comparações estatísticas (teste t) foram feitas em imagens originais e reamostradas, constatando-se que ambas não diferem significativamente. A influência da sombra entre fileiras de vinhas na resposta espectral também foi investigada. A proporção de sombra entre as fileiras é variável, em função da orientação das filas, da distância zenital e do azimute do Sol na hora da aquisição da imagem. Foram estudadas as variedades Chardonnay, Merlot e Sauvignon Blanc em três imagens de diferentes datas. Determinados os diferentes grupos, esses foram submetidos a análises de similaridade, usando-se ANOVA, seguidos do teste de Tukey. Comparou-se também a separabilidade de diferentes variedades, que apresentavam a mesma quantidade de sombra. As imagens foram classificadas através do classificador de Mínima Distância para verificar a eficácia desse classificador em detectar a variação de sombra. A validação final foi realizada através da comparação da imagem classificada com as informações contidas no mapa de localização das cepas. Como resultados, foi confirmada a validade da reamostragem de pixels pelo método do vizinho mais próximo, sem alteração do valor digital, e constatou-se a influência do substrato (solo iluminado ou sombreado) na caracterização espectral das variedades viníferas, e a sua influência na classificação das imagens ASTER.Technological developments lead to new sources of research, and in the case of data from remote sensors, their understanding and use allow the generation of new scientific knowledge. For images of medium spatial resolution, the ASTER sensor is an important information source. This study aims to investigate the potential of ASTER images in the discrimination of vineyards, and to verify the spectral behavior of the vinifera varieties in face of the influence of shadow effects. For this analysis, the property of Viña Veramonte, at Valle Casablanca, Chile, was chosen, since it proved to be adequate for its topography, plot partition, field data, and images availability. Since ASTER images are acquired with spatial resolutions of 15m and 30 m, resampling procedures are necessary to the full use of data from the nine spectral bands of VNIR and SWIR; however, such practices are frequently considered as sources of false information, and this issue was investigated first. The six SWIR bands, with 30m pixels, were resampled to 15m using the Nearest Neighbor method, allowing to perform a spectral investigation with nine bands. Statistical comparisons using the t test were applied both to the original and resampled images, being shown that the two images don’t differ significantly; this allowed to proceed the study using resampled images with nine spectral bands. The influence of shadow between rows of vines was then investigated. The percentage of shadow between rows is variable, being a function of row orientation, of Sun’s zenith distance and azimuth, and of the time of image acquisition. Using maps provided by the vineyard managers, informing vine varieties and their places, it was possible to derive the spectral information and to identify the vine parcels in images, which were separated by groups according to their shadow percentages. The grape cultivars Chardonnay, Sauvignon Blanc and Merlot were studied in images of three dates. After defining the three groups, they were analyzed through the ANOVA and Tukey Test methods. A comparison was also made for those varieties which had the same proportion of shadow. All images were classified through the Minimum Distance algorithm, to verify the performance of this classification technique in detecting the shadow change. The final validation was made by comparing the classified image with information from the vineyard map. As results, the validity of the pixel resampling by the Nearest Neighbor method was demonstrated, as the influence of the inter-rows shadow in the classification of ASTER images

Avaliação da fiabilidade de imagens ASTER após processo de reamostragem e geração de imagem sintética

With the advent of new sensors with better spatial resolution, temporal and radiometric, there was a significant increase in the possibilities of using data generated by remote sensors and airborne in the study and monitoring of the cultivated areas. ASTER sensor consists of three subsystems (VNIR, SWIR and TIR) with spatial resolutions of 15, 30 and 90 meters respectively. It is a potential tool for environmental studies. The number of bands subsystem VNIR+SWIR enables the analysis of quantitative spectral behavior of different cultivars, with a cost of imaging very affordable. Using all this spectral information studies which require the application of sorting algorithms, is the requirement that all picture having the same pixel size. Generally, the most straightforward solution to this problem is the resampling of the pixels, by processing the image, generating a synthetic image. The aim of this work was to investigate the reliability of the data generated in the synthetic image and its use for work classification and spectral characterization. For this investigation we used the interpolator known as nearest neighbor and statistical tests. It was possible to confirm the potential of ASTER images in the study of natural phenomena, especially when referring to the analysis and monitoring of crops. The synthetic image not significantly alter the spectral characteristics of the targets, this being possible for processing data manipulation.Pages: 8216-822

Diferenciação espectral e efeitos de sombreamento em vegetações em imagem Hyperion

An Hyperion hyperspectral image was used to investigate the spectral differentiation between several vegetation species. The region investigated was the Pirque zone, near Santiago, Chile, where vineyards can be identified in the image taken in 9 Feb. 2005. Fields with green and dried grass, and vineyards with several row orientations were selected, besides an area covered with sand. The shadow influence between rows in vineyards was investigated. Results show that the Hyperion image can effectively be used to differentiate between vegetation classes, and that shadow effects can influence the spectral response of soil with respect to the response of vegetation, in cases where there are mixture of information from these classes.Pages: 8524-852