Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Indigenous peoples and urban settlements: spatial distribution, internal migration and living conditions

Includes bibliography

Submerged macrophytes height estimation by echosounder data sample

Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.

(m,k)-Gur game: Exploiting message discards in order to increase the lifetime and spatial diversity in autonomic wireless sensor networks

The main concern in Wireless Sensor Networks (WSN) algorithms and protocols are the energy consumption. Thus, the WSN lifetime is one of the most important metric used to measure the performance of the WSN approaches. Another important metric is the WSN spatial coverage, where the main goal is to obtain sensed data in a uniform way. This paper has proposed an approach called (m,k)-Gur Game that aims a trade-off between quality of service and the increasement of spatial coverage diversity. Simulation results have shown the effectiveness of this approach. © 2012 IEEE.

Spatial and seasonal patterns in fish assemblage in Córrego Rico, upper Paraná river Basin

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spatial distribution, internal migration and development in Latin America and the Caribbean

Includes bibliography

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Cellular automata-based spatial dynamic modeling for analyzing urban land use change

This paper analyzes land use change in Rio Claro City and its surroundings, located in the southeastern state of Sao Paulo, in the period from 1988 to 1995, using air-borne digital imagery and a cellular automata model. The simulation experiment was carried out in the Dinamica EGO platform and the results revealed a constrained urban sprawl, resulting from both the densification of residential areas implemented in previous years and the economic recession that led to an internal financial crisis in Brazil during the early 1990s. The simulation outputs were validated using a multi-resolution procedure based on a fuzzy similarity index and showed a satisfactory fitness in relation to the historical reference data. © 2013 IEEE.

Simulated annealing for building roof contours identification from lidar data

This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives.

Evolution of the South Atlantic passive continental margin in southern Brazil derived from zircon and apatite (U-Th-Sm)/He and fission-track data

The area between São Paulo and Porto Alegre in southeastern Brazil plays a key area to understand and quantify the evolution of the South Atlantic passive continental margin (SAPCM) in Brazil. In this contribution, we present new thermochronological data attained by fission-track and (U-Th-Sm)/He analysis on apatites and zircons from metamorphic, sedimentary and intrusive rocks. The zircon fission-track ages range between 108.4 (15.0) and 539.9 (68.4). Ma, the zircon (U-Th-Sm)/He ages between 72.9 (5.8) and 525.1(2.4). Ma, whereas the apatite fission-track ages range between 40.0 (5.3) and 134.7 (8.0). Ma, and the apatite (U-Th-Sm)/He ages between 32.1 (1.5) and 93.0 (2.5). Ma. The spatial distribution of these ages shows three distinct blocks with a different evolution cut by old fracture zones. While the central block exhibits an old stable block, the Northern and especially the Southern block underwent complex post-rift exhumation. The sample of the Northern block shows two distinct cooling phases in the Upper Cretaceous and the Paleogene to Neogene. After sedimentation of the Permian sandstones the samples of the Central block were never heated up over 100. °C with a following moderate to fast cooling phase in Cretaceous to Eocene time and a fast cooling between Oligocene to Miocene. The five thermal models obtained in the Southern block indicate a complex evolution with three cooling phases. The exhumation events of the three blocks correspond with the Paraná-Etendekka event, the alkaline intrusions due to the Trinidad hotspot, and the evolution of the continental rift basins in SE Brazil and are, therefore, most likely to be the major force for the post-rift evolution of the passive continental margin in SE Brazil, which therefore corresponds to the three main phases of the Andean orogeny. © 2013 Elsevier B.V.

Comparative neurophysiology of spatial luminance contrast sensitivity

The luminance contrast sensitivity function has been investigated using behavioral and electrophysiological methods in many vertebrate species. Some features are conserved across species as a shape of the function, but other features, such as the contrast sensitivity peak value, spatial frequency contrast sensitivity peak, and visual acuity have changed. Here, we review contrast sensitivity across different classes of vertebrates, with an emphasis on the frequency contrast sensitivity peak and visual acuity. We also correlate the data obtained from the literature to test the power of the association between visual acuity and the spatial frequency of the contrast sensitivity function peak.

Spatial distribution of the amazon river prawn Macrobrachium Amazonicum (Heller, 1862) (Decapoda, Caridea, Palaemonidae) in two perennial creeks of an estuary on the northern coast of Brazil (Guajará Bay, Belém, Pará)

Macrobrachium amazonicum é o crustáceo dulcícola mais frequentemente consumido pelas populações ribeirinhas da Amazônia. Entretanto, apesar de sua relativa abundância e vasto conhecimento da espécie a partir de dados de cultivo, pouco se conhece sobre sua biologia no ambiente natural, especialmente quanto à forma de utilização de canais fortemente influenciados pelas marés. Amostras desse camarão foram coletadas em setembro/06 (período seco) e março/07 (período chuvoso), em dois canais perenes da Baía do Guajará, Pará, utilizando armadilhas (matapis) como as utilizadas pelos pescadores locais para identificar a distribuição espacial dos organismos. Os canais de maré são utilizados por camarões de todos os tamanhos nas duas estações do ano, inclusive para a reprodução. A maior abundância de indivíduos da espécie foi encontrada no período seco, nas áreas a montante dos canais. Postula-se que a abundante matéria orgânica alóctone e a busca de locais protegidos podem ser os fatores que explicam a concentração da abundância e da atividade reprodutiva nas áreas a montante dos canais.

The AIDS epidemic in the Amazon region: a spatial case-control study in Rondonia, Brazil

OBJETIVO Analisar mudanças espaciais no risco de Aids e a relação entre incidência da doença e variáveis socioeconômicas. MÉTODOS Estudo caso-controle espacial, de base populacional, realizado em Rondônia, Brasil, com 1.780 casos notificados pelo Sistema de Vigilância Epidemiológica e os controles a partir de dados demográficos de 1987 a 2006. Os casos foram agrupados em cinco períodos de cinco anos consecutivos. Um modelo aditivo generalizado foi ajustado aos dados. O status dos indivíduos (caso ou controle) foi considerado como a variável dependente e independente: um alisamento ( spline ) bidimensional das coordenadas geográficas e variáveis socioeconômicas municipais. Os valores observados para o teste Moran I foram comparados com a distribuição de referência dos valores obtidos em condições de aleatoriedade espacial. RESULTADOS O risco de Aids apresentou padrão espacial e temporal marcado. A incidência associou-se a indicadores socioeconômicos municipais, como urbanização e capital humano. As maiores taxas de incidência de Aids ocorreram em municípios ao longo da rodovia BR-364; os resultados do teste Moran I mostram correlação espacial positiva associada à contiguidade dos municípios com a rodovia, no terceiro e quarto períodos (p = 0,05). CONCLUSÕES A incidência da doença foi maior em municípios de maior riqueza econômica e urbanização e naqueles cortados pelas estradas principais de Rondônia. O rápido desenvolvimento associado à ocupação de regiões remotas pode ser acompanhado por aumento de riscos à saúde.

Interaction between GIS and hydrologic model: a preliminary approach using ArcHydro Framework Data Model

In different regions of Brazil, population growth and economic development can degrade water quality, compromising watershed health and human supply. Because of its ability to combine spatial and temporal data in the same environment and to create water resources management (WRM) models, the Geographical Information System (GIS) is a powerful tool for managing water resources, preventing floods and estimating water supply. This paper discusses the integration between GIS and hydrological models and presents a case study relating to the upper section of the Paraíba do Sul Basin (Sao Paulo State portion), situated in the Southeast of Brazil. The case study presented in this paper has a database suitable for the basin's dimensions, including digitized topographic maps at a 50,000 scale. From an ArcGIS®/ArcHydro Framework Data Model, a geometric network was created to produce different raster products. This first grid derived from the digital elevation model grid (DEM) is the flow direction map followed by flow accumulation, stream and catchment maps. The next steps in this research are to include the different multipurpose reservoirs situated along the Paraíba do Sul River and to incorporate rainfall time series data in ArcHydro to build a hydrologic data model within a GIS environment in order to produce a comprehensive spatial-temporal model.

Spatial distribution of dengue incidence and socio-environmental conditions in Campinas, São Paulo State, Brazil, 2007

This study aimed to analyze the spatial distribution of dengue risk and its association with socio-environmental conditions. This was an ecological study of the counts of autochthonous dengue cases in the municipality of Campinas, São Paulo State, Brazil, in the year 2007, aggregated according to 47 coverage areas of municipal health centers. Spatial models for mapping diseases were constructed with Bayesian hierarchical models, based on Integrated Nested Laplace Approximation (INLA). The analyses were stratified according to two age groups, 0 to 14 years and above 14 years. The results indicate that the spatial distribution of dengue risk is not associated with socio-environmental conditions in the 0 to 14 year age group. In the age group older than 14 years, the relative risk of dengue increases significantly as the level of socio-environmental deprivation increases. Mapping of socio-environmental deprivation and dengue cases proved to be a useful tool for data analysis in dengue surveillance systems.