Georeferenced road extraction and formulation of hypotheses for new road segments

The acquisition and update of Geographic Information System (GIS) data are typically carried out using aerial or satellite imagery. Since new roads are usually linked to georeferenced pre-existing road network, the extraction of pre-existing road segments may provide good hypotheses for the updating process. This paper addresses the problem of extracting georeferenced roads from images and formulating hypotheses for the presence of new road segments. Our approach proceeds in three steps. First, salient points are identified and measured along roads from a map or GIS database by an operator or an automatic tool. These salient points are then projected onto the image-space and errors inherent in this process are calculated. In the second step, the georeferenced roads are extracted from the image using a dynamic programming (DP) algorithm. The projected salient points and corresponding error estimates are used as input for this extraction process. Finally, the road center axes extracted in the previous step are analyzed to identify potential new segments attached to the extracted, pre-existing one. This analysis is performed using a combination of edge-based and correlation-based algorithms. In this paper we present our approach and early implementation results.

Priority areas for riparian forest restoration in southeastern Brazil

Riparian forest restoration projects in the Tropics are complex, demanding longterm research, continuous human efforts and correct use of financial resources. This paper presents an approach to rank priority areas for riparian forest restoration on the upper section of the Pardo River watershed, in São Paulo, Brazil, using remote sensing and GIS techniques. Pardo River watershed is specially important, since it is the major source of drinking water supply for the region and water for domestic and industrial use within Botucatu and surrounding. Results indicated that riparian restoration should involve 81,27% of the protected area and could be made in three phases, allocating resources according to a priority scale.

Semi-automatic modeling of buildings from digital surface models

Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.

Geração de modelos digitais de superfície por meio de plataformas computacionais com estrutura vetorial e raster

Geographic Information Systems (GIS) integrate the technologies related to Geoprocessing, with the ability to manipulate georeferenced information through data storage, management and analysis. One of the GIS applications is the generation of Digital Elevation Models (DEM) as a result of rebuilding the elevation of a region using computation tools and artificial representation. This paper presents the DEM created from a point base in two computational frameworks with different structures (vector and raster), comparing the contour lines generated from these models with the original contour lines from analog cartographic base. It was observed that one of the generated models presented some discrepancies related to real space for both GIS structures. However, using constrained Delaunay's triangulation in raster GIS a digital elevation model was generated with contour lines quite close to the original ones, with satisfactory results. A 3-D terrain representation was also created offering a very useful tool for analysis.

Carta de Aptidão para a implantação de rodovias e avaliação de alternativas de traçado com uso de geotecnologias

This study discuss the use of the geotechnologies to aid the planners on the terrain aptness definition for highways implantation and on the different trace evaluation to the extention of the Governador Carvalho Pinto highway, between Taubaté-SP and Aparecida do Norte-SP. Fratures on the area were mapping using Landsat ETM+, band Pan. In order to elaborate the phisical aptness chart for highway implantation was used the Analitical Hierarchy Process (AHP) operation, in on geographical information system (GIS). Using GIS were realized a ponderate middle with the soils, rocks, relief, slope, fractures and land use/cover maps. Using this physical aptness chart and joinning it with urban and restrict areas (that was inserted by the Boolean operation), were obtained a viability chart for highway implantation. Based on it were proposed three aleatory traces for the Carvalho Pinto highway. This traces were evaluated with the cross tabulation operation. The integration of the restrict areas, land use and phisical aptness in digital media can offer for the planners the cartography of the viability for the highway implantation. The evaliation of these three traces, based on the viability chart, can subsidyse the decision by the planners.

Applying GIS tools for analysing urban thermal environment

A methodology for analyzing the solar access and its influence on both air temperature and thermal comfort of the urban environment was here developed by applying the potentiality of GIS tools. Urban canyons in a specific area of a Brazilian medium sized city were studied. First, a computational algorithm was applied in order to allow the determination of sky view factors (SVF) and sun-paths in urban canyons. Then, air temperatures in 40 measurement points were collected within the study area. Solar radiation values of these canyons were determined and subsequently stored in a GIS database. The creation of thermal maps for the whole neighbourhood was possible due to a statistical treatment of the data, by promoting the interpolation of values. All data could then be spatially cross-examined. In addition, thermal comfort maps for summer and winter periods were generated. The methodology allowed the identification of thermal tendencies within the neighbourhood, what can be useful in the conception of guidelines for urban planning purposes.

Uso de indicadores hidrológicos para classificação de trechos de estradas florestais quanto ao escoamento superficial

Forest roads are frequently pointed as source of environmental problems related to erosion and they also influence harvest cost due to maintenance operations. Roads not well designed are sources of hydrological problems on catchments and the current attention to sustainability of forest exploration projects point out to the need of diagnostics tools for guiding the redesign of the road system. At this study, runoff hydrological indicators for forest road segments were assessed in order to identify critical points of erosion and water concentration on soils. A road network of a forest production area was divided into 252 road segments that were used as observations of four variables: mean terrain slope, main segment slope, LS factor and topographic index. The data analysis was based on descriptive statistics for outliers' identification, principal component analysis and for variability study between variables and between observations, and cluster analysis for similar segments groups' identification. The results allowed classifying roads segments into five mains road types: road on the ridge, on the valley, on the slopes, on the slopes but in a contour line and on the steepest slope. The indicators were able to highlight the most critical segments that differ of others and are potential sources of erosion and water accumulation problems on forest roads. The principal component analysis showed two main variability sources related to terrain topographic characteristics and also road design, showing that indicators represent well those elements. The methodology seems to be appropriated for identification of critical road segments that need to be redesigned and also for road network planning at new forest exploration projects.

Orientation, building height and sky view factor as energy efficiency design parameters

The energy efficiency of buildings should be a goal at the pre-design phase, though the importance of the design variables is often neglected even during the design process. Highlighting the relevance of these design variables, this research studies the relationships of building location variables with the electrical energy consumption of residential units. The following building design parameters are considered: orientation, story height and sky view factor (SVF). The consideration of the SVF as a location variable contributes to the originality of this research. Data of electrical energy consumption and users' profiles were collected and several variables were considered for the development of an Artificial Neural Network model. This model allows the determination of the relative importance of each variable. The results show that the apartments' orientation is the most important design variable for the energy consumption, although the story height and the sky view factor play a fundamental role in that consumption too. We pointed out that building heights above twenty-four meters do not optimize the energy efficiency of the apartments and also that an increasing SVF can influence the energy consumption of an apartment according to their orientation.

Geoprocessamento aplicado na distribuição espacial da capacidade de uso de uma microbacia

The present study aimed to show the spatial distribution of the Rochas watershed (Avaré-SP, Brazil) soil use capacity using the Idrisi geographical information system in order to contribute to a better territorial organization and the planning of the appropriate soil occupation. The obtained results using this methodology showed that most of the Rocha watershed areas are from the following groups: dystrophic yellow-red latosol (36.64%), eutroferric and distroferric red latosol (30.30%) with sandy texture. There was a predominance of areas with slope classes of 0-12%, plain to wavy relief (61.37% of the watershed area) showing that these areas are appropriate for annual culture plantations with wide use of machinery. Most of these areas were classified as class IV (73.79%) as to use capacity. In the studied area the following subclasses of land use capacity were found: IIe, s; IIIe; IVe; IVs; IVe,s; VIe and VIIe. Capacity subclasses IVe; IVe,s; IVs and Vie were the most significant because they are areas that can be used for agriculture but subject to severe soil impoverishment if there are no special care mainly for annual cultures. The Idrisi geographical information system was efficient to determine soil use capacity of the Rocha's watershed showing that the use of geoprocessing tools makes data analysis easier and faster, allowing digital data storage for future analysis uses mainly for territorial planning and environmental studies.

Otimização da distância de extração de madeira com forwarder

The activities and management operations of wood harvesting do not have good computational tools available to help the forest technicians with the task of cost reduction. In many cases, machines of high investment are used in wood harvesting without adequate operation planning; consequently, the cost per hour of these machines, which is high, could be reduced. Using technological resources such as the Geographic Information Systems (GIS) integrated with the Global Positioning System (GPS), which are the basis of precision harvesting. In this research, a technological tool capable of calculating and optimizing the average skidding distance of the forwarder was developed. It was used in stands of different sizes and formats through mathematical techniques and available functionalities in the Geographic Information System GRASS. The developed tool, called optimized model, divides the stand in small parts in relation to shorter skidding distances. The main variable considered was the alignment of plantation. The model was tested in eucalypt stands located in the State of São Paulo. Sixteen stands were randomly selected: eight with a rectangular polygon form, and eight with irregular polygon form. The main variables were collected in these stands. Results showed that the optimized model developed, is efficient and flexible. It was possible to divide the stands in small parts resulting in smaller skidding medium distances. The stands with irregular form had shorter skidding medium distances than the rectangular stands.

Modelagem em escala regional da erosão relacionada com a evolução da cobertura do solo: Um estudo de caso no sudeste do Brasil

Accelerated soil erosion is, at present, one of the most widespread environmental problems in the world. Geographic Information Systems (GIS) have become an essential tool in soil erosion studies and consequently in the development of appropriate soil conservation strategies. The objective of this paper was to assess the degree of soil erosion associated with land cover dynamics through GIS analysis and to validate the modeling with indicators of soil erosion. Universal Soil Loss Equation (USLE) model, GIS technology and ground-truth dataset (erosion indicators) were employed to elaborate the soil loss maps for four dates at Sorocaba Municipality (SP, Brazil). It was verified that, although the predicted soil loss rate is normally small along the study area, such rate is significantly greater than the soil formation rate. This shows a non-sustainable situation of soil and land cover management. Unplanned urban expansion seems be the main driving force that acts in increasing the erosion risk/occurrence along the study area.

Urban heat islands and electrical energy consumption

This study proposes the development of thermal and energy consumption maps to generate useful planning information. A residential neighbourhood in a medium-sized city was selected as the study area. In this area, 40 points were taken as urban reference points where air temperatures at the pedestrian level were collected. At the same time, rural temperatures made available by the city meteorological station were registered. Data of electrical energy consumption of the building units (houses and apartments) were collected through a household survey that was also designed to identify the users' income levels. Then, maps were developed so that the configuration of urban heat islands and electrical energy consumption could be visualised, compared and analysed. The results showed that the income level was the most important variable influencing electrical energy consumption. However, a strong relationship of the consumption with the thermal environment was also observed.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

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.

3D geovisualisation techniques applied in spatial data mining

The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.