There are few animal germplasm/gene bank collections in Brazil, and basic studies are needed to attend the future internal and external demands from international partners. The aim of this work was ...to validate a “proof of concept” that integrates spatial (georeferenced data) and genetic data regarding the local of origin from 3518 DNA samples from 17 different genetic groups or breeds of sheep in the Brazilian Germplasm bank. Spatialisation shows that not all genetic groups have samples in the bank, and collection is concentrated in the conservation nuclei spread nationwide. Only 21% of states with a specific breed have samples in the gene bank. The mean number of animals sampled per collection was 32, while the mean distance travelled to collect samples was 262 km from the conservation nuclei. For example, the Brazilian Somali were only collected in the conservation nucleus in Ceará State. No samples were collected to date for the Cariri breed, which is recognised by the Brazilian Ministry of Agriculture. Only two farms and one breed in the bank are from the northern region. Of the 27 states, there are samples in the gene bank of sheep from 13, so several states have no samples, requiring collection from herds outside the official system of conservation to make sure that studies using this germplasm realised are not biased. Significant genetic differences are seen above 332 km, which should guide future sampling efforts. Suggestions are given for improving the quantity, quality and diversity of samples in the gene bank.
Spatial patterns of shallow landslide initiation reflect both spatial patterns of heavy rainfall and areas susceptible to mass movements. We determine the areas most susceptible to shallow landslide ...occurrence through the calculation of critical soil cohesion and spatial patterns of rainfall derived from TRMM (Tropical Rainfall Measuring Mission) data for Paraty County, State of Rio de Janeiro, Brazil. Our methodology involved: (a) creating the digital elevation model (DEM) and deriving attributes such as slope and contributing area; (b) incorporating spatial patterns of rainfall derived from TRMM into the shallow slope stability model SHALSTAB; and (c) quantitative assessment of the correspondence of mapped landslide scars to areas predicted to be most prone to shallow landsliding. We found that around 70% of the landslide scars occurred in less than 10% of the study area identified as potentially unstable. The greatest concentration of landslides occurred in areas where the root strength of vegetation is an important contribution to slope stability in regions of orographically-enhanced rainfall on the coastal topographic flank. This approach helps quantify landslide hazards in areas with similar geomorphological characteristics, but different spatial patterns of rainfall.
This research aims to determine the vertical accuracy of the Interferometric Digital Elevation Model (DEM) obtained from the processed Shuttle Radar Topographic Mission (SRTM) data. The research ...compared the SRTM-GL1 (Shuttle Radar Topographic Mission-Global 1) with 30-meter resolution and the following 90-meter resolution models: (a) EMBRAPA; (b) Hydrological data and maps based on Shuttle Elevation Derivatives at multiple Scales (HydroSHEDS) (HydroSHEDS), provided by the United States Geological Survey (USGS); (c) Consultative Group for International Agricultural Research-Consortium for Spatial Information (CGIAR-CSI); and (d) Jonathan de Ferranti. The accuracy analysis considered the diverse Brazilian regions, adopting 1,087 field points from the Global Navigation Satellite System (GNSS) trackers or topography methods. The Jonathan de Ferranti model achieved the best accuracy with RMSE of 9.61m among the 90-meter resolution models. Most SRTM models at 1:100,000 scale reached Grade A of the Cartographic Accuracy Standard. However, the accuracy at the 1: 50,000 scale did not achieve the same performance. SRTM errors are linearly related to slope and the most significant errors always occur in forest areas. The 30-meter resolution SRTM showed an accuracy of around 10% better (RMSE of 8.52m) than the model of Jonathan de Ferranti with 90-meter resolution (RMSE of 9.61m).
Propriedade e títulos de terra no Brasil é um sério problema, onde a ausência de uma situação legal provoca êxodo rural, insegurança jurídica e a impossibilidade de crédito para atividades agrícolas. ...O objetivo dessa pesquisa foi desenvolver uma metodologia de análise de decisão multicritério na seleção de áreas prioritárias para regularização fundiária no Estado da Bahia (Nordeste Brasileiro). As variáveis municipais utilizadas foram: índice de desenvolvimento humano municipal, valor bruto de produção, número de fazendeiros sem os documentos da terra (posseiros), estabelecimentos familiares, declividade e propriedades cadastradas. No processamento dos dados foram utilizados os métodos de análise multicritério (AMC), Analytic Hierarchy Process (AHP) e Fuzzy-AHP. O resultado final foi um mapa de síntese cartográfica proveniente da média aritmética desses modelos, contendo as seguintes classes de prioridade: alta, média, baixa e não prioritária. O método proposto determinou 128 municípios prioritários para ações imediatas de regularização fundiária com índice acima de 0,66. Um recorte acima de 0,80 selecionou 22 municípios considerados como extremamente prioritário. Esses municípios prioritários formam um padrão espacial contínuo ao longo da depressão do rio São Francisco. A grande quantidade de posses e a baixa quantidade de áreas cadastradas no Estado da Bahia indica a importância de ações sistemáticas de georreferenciamento e regularização fundiária.
Speckle noise (salt and pepper) is inherent to synthetic aperture radar (SAR), which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the ...spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA), a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR) images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS) Phased-Array Synthetic-Aperture Radar (PALSAR) sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari), containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF) or noise-adjusted principal components (NAPCs). Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.
O mapa de uso e cobertura da terra é fundamental para o planejamento, manejo e conservação ambiental. Os dados de sensoriamento remoto são a base de informações para o desenvolvimento de tais mapas, ...proporcionando rapidez e custo-efetividade. Na região amazônica, a presença constante de cobertura de nuvens e fumaça torna o uso de imagens de radar mais adequado por operar independentemente dessas barreiras. A presente pesquisa possui como objetivo propor uma metodologia para classificar o uso e cobertura da terra a partir de imagens multitemporais PALSAR-2/ALOS-2 na planície de inundação e arredores na região da ilha do Bananal. A ilha do Bananal é a segunda maior ilha fluvial do mundo com aproximadamente 750 km de extensão e 100 km de largura. A área de estudo está localizada na região de confluência entre os rios Javaés e Araguaia, situada no trecho médio da bacia do rio Araguaia. A metodologia adotada considera as seguintes etapas: aquisição de quatro imagens multitemporais PALSAR-2/ALOS 2 no nível de processamento 1.5 (banda L com resolução de 6,25 metros); (b) Análise de Componentes de Densidade de Probabilidade (ACDP); (c) diminuição do ruído utilizando a transformação Minumum Noise Fraction (MNF); e (d) classificação pelo método Support Vector Machine (SVM) considerando as assinaturas temporais. A combinação da ACDP e MNF permitiu a formulação de diferentes feições que descrevem as diferentes classes presentes na imagem. Comparativamente, as imagens foram processadas utilizando o filtro adaptativo Gamma e o classificador SVM. Os resultados do coeficiente Kappa foi de 0,62 para o método SVM/CDP-MNF e 0,57 para o método SVM/Gamma. O principal fator para a queda do coeficiente Kappa é proveniente da confusão entre as áreas de uso agropecuário (pastagem) e Savana Rupestre, nas áreas adjacentes a ilha do Bananal.
La carte de l'utilisation des sols et de la couverture végétale est fondamentale pour la planification, la gestion et la conservation de l'environnement. Les données de télédétection constituent la base d'informations pour l'élaboration de telles cartes, offrant rapidité et rentabilité. Dans la région amazonienne, la présence constante de nuages et de fumées rend l'utilisation d'images radar plus adaptée pour fonctionner indépendamment de ces obstacles. Cet article vise à classer l'utilisation des terres et la couverture des images SAR multitemporelles du capteur PALSAR 2 dans la région de l'île Bananal. L'île de Bananal est la deuxième plus grande île fluviale du monde avec environ 750 km de long et 100 km de large. Le secteur d'étude est situé dans la région de confluence entre les rivières Javaés et Araguaia, située au milieu du bassin de la rivière Araguaia. La méthodologie adoptée suit les étapes suivantes : (a) acquisition de quatre images multi temporelles Palsar 2/ALOS 2 au niveau de traitement 1.5 (bande L avec une résolution de 6,25 mètres); (b) l'analyse des composantes de densité de probabilité (ACDP); (c) la réduction du bruit à l'aide de la transformation Minimum Noise Fraction (MNF); et (d) classification par la méthode de la Machine à Vecteurs de Support (MVS) en tenant compte des signatures temporelles. La combinaison de ACDP et MNF a permis la formulation de différentes caractéristiques qui décrivent les différentes classes présentes dans l'image. Comparativement, les images ont été traitées en utilisant le filtre adaptatif Gamma et le classificateur MVS. Les résultats du coefficient Kappa sont de 0,62 sur le résultat MVS/ACDP-MNF et de 0,57 sur le score MVS/Gamma. Le principal facteur de diminution du coefficient de Kappa est la confusion entre les secteurs de Savane Rupestre et l'utilisation anthropique (pâturages) dans les secteurs adjacents à l'île de Bananal.
The land-use and land-cover map is fundamental for environmental planning, management, and conservation. Remote sensing data is the information basis for the development of such maps, providing speed and cost-effectiveness. In the Amazon region, the constant presence of cloud cover and smoke makes the use of radar images more adequate for operating independently of these barriers. The present research aims to propose a methodology to classify land use and coverage from PALSAR-2/ALOS-2 multitemporal images in the region of Bananal island. The Bananal island is the second largest fluvial island in the world with approximately 750 km long and 100 km wide. The study area is in the confluence between the Javaés and Araguaia rivers, located in the middle Araguaia river basin. The methodology adopted considers the following steps: acquisition of four multitemporal images Palsar 2/ALOS 2 at processing level 1.5 (L band with resolution of 6.25 meters); (b) Probability Density Component Analysis (PDCA); (c) noise reduction using the Minimum Noise Fraction (MNF) transformation; and (d) classification by the Support Vector Machine method considering the temporal signatures. The ACDP and MNF combination allowed the formulation of different features that describe the different classes present in the image. Comparatively, the images were processed using the Gamma adaptive filter and the SVM classifier. The Kappa coefficient results were 0.62 on the SVM/CDP-MNF images and 0.57 on the SVM / Gamma images. The main factor for the decrease of the Kappa coefficient was the confusion between the areas of Savana Rupestre and anthropic use (pasture) in the areas adjacent to the Bananal island
A key problem in the use of physically based models of landslide hazards is how to parameterize the representation of soil properties. We applied a physically based model for the topographic control ...on shallow landsliding (SHALSTAB) to two catchments in Rio de Janeiro to investigate the accuracy of model results in relation to parameterization of soil properties. In so doing, we address the relevance of values derived from laboratory tests to the field problem, as well as the trade-offs inherent in model parameterization. We ran the model for all combinations of reasonable cohesion, bulk density, and friction angle values and compared model predictions to mapped landslides scars. We rank sorted model performance through the proportion of the total area of landslide scars correctly predicted as potentially unstable. Application of the model to an area where soil properties are not well known can be based on either a standard parameterization that emphasizes topographic controls, or on local calibration of soil parameters against a map of known landslide locations. Our analysis suggests that, in general, acquisition of high-quality digital elevation models (DEMs) is more important than generation of spatially detailed soil property values for reconnaissance level assessment of shallow landslide hazards.
Resumo Este artigo discute os aspectos políticos do desdobramento legal e burocrático da Operação Urbana Consorciada “ACLO” em Belo Horizonte. A partir de uma pesquisa documental e entrevistas com ...atores relevantes que permitiram resgatar, através da história oral, elementos do processo de desenvolvimento da política urbana de Belo Horizonte, buscamos compreender as contradições e conflitos que contribuíram para interrupção do projeto urbano. Para isso, foi necessário entender o papel da administração pública e seu quadro técnico, os interesses de agentes econômicos e o marco legal próprio da Operação Urbana. Foi possível observar que sua elaboração envolveu uma luta política e contradições que a gestão não foi capaz de sanar, resultado de premissas e concepções distintas dos atores envolvidos no projeto urbano.
Abstract This article discusses the political aspects of the legal and bureaucratic unfolding of the Consortium Urban Operation “ACLO” in Belo Horizonte. From a documentary research and interviews with relevant actors that allowed us to rescue, through oral history, elements of the urban policy development process in Belo Horizonte, we sought to understand the contradictions and conflicts that contributed to the interruption of the urban project. For this, it was necessary to understand the role of the public administration and its technical framework, the interests of economic agents and the legal framework of Urban Operation. It was possible to observe that its elaboration involved a political struggle and contradictions that the administration was not able to remedy, as a result of different assumptions and conceptions of the actors involved in the urban project.
Deslizamentos ocorrem no Brasil em encostas íngremes após eventos de chuva. No ano de 2008 ocorreram precipitações intensas e concentradas que provocaram inúmeros movimentos de massa no estado de ...Santa Catarina, principalmente na área do entorno do Morro Baú, mudando significativamente a morfologia dos vales e encostas e atingindo a população local. Neste sentido, este trabalho tem como objetivo elaborar o mapeamento de áreas suscetíveis à ocorrência de deslizamentos, a partir do modelo SHALSTAB aferindo-se o desempenho com as cicatrizes mapeadas dos deslizamentos ocorridos em novembro de 2008 na microbacia do Ribeirão Baú. Foi realizado o mapeamento das unidades geotécnicas definindo-se sete unidades, onde foram determinados os parâmetros intercepto coesivo, ângulo de atrito e peso específico. O modelo SHALSTAB foi aplicado utilizando-se os dados topográficos extraídos do modelo digital de terreno (MDT) e os dados geotécnicos. Os resultados demonstraram que a simulação do modelo utilizando a profundidade de 2 metros foi a que apresentou o melhor resultado e obteve a melhor curva de validação, quando comparados com outras simulações utilizando profundidades maiores de solo.
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