Análise da transformação do uso da terra, vegetação e impactos ambientais por meio de sensoriamento remoto e geoprocessamento

The mapping of the land use, vegetation and environmental impacts using remote sensing and geoprocessing allows detection, spatial representation and quantifying all alterations due to the human action in the nature, contributing to the monitoring and planning of those activities that cause damages to the environment. The aim of this research is analyze the transformation ocurred with the land use and vegetation in order to detect environmental impacts during the period from 1962 to 1995, considering a test area in the district of Assistência and surroundings, in the Rio Claro (SP) region. In order to archieve such aim the authors used boolean operations available in the Geographical Information System (GIS) - Idrisi. The maps were obtained through the ordinary (conventional) interpretation of aerial photos, later digitized in the software CAD Overlay and georeferenced in AutoCAD Map. It's observed that operations such as crossing digitized maps of one specific area in two differents dates, using GIS, produce overall results that might point out expansion or retraction's trends of the mapped classes, as well as quantify the intensity of the phenomena.

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.

Geoprocessamento e sensoriamento remoto aplicado na determinação da aptidão agrícola de uma microbacia

Soil use for the development of activities as agriculture and livestock has been causing great alterations in the environment, mainly when these are practiced intensively, disrespecting the fragility and aptitude of the natural resources. Therefore, it is essential that the planning of the agricultural activities is done, taking into consideration the several environmental criteria involved in the decision-making process. Thus, this study aimed to analyze the agricultural aptitude classes of lands from a watershed through geographical information system (GIS). The Arroio Ajuricaba watershed is located in the Municipality of Marechal Cândido Rondon - PR among the coordinates UTM 787309m E and 793892m E; 7275026m N and 7281310m N, in the Spindle 21, presenting an area of 1681ha. Soil maps, in semi detail scale, was the digital cartographic base used. The results allowed to conclude that 42.41% of the basin presented a good aptitude for farming in handling level of high technology (handling level C), regular aptitude for B, and restricted aptitude for A [class 1(a)bC] and that 12% of the area had regular aptitude for farming in the three handling levels (class 1abc). The watershed lands (14.24%) presented regular aptitude for farming in handling level C, restricted aptitude for B, and inapt for A [class of aptitude 2(b)c]; 15.85% presented good aptitude for planted pasture (class 4P) and 12.21% were considered without aptitude for agricultural use (class 6). We can say that 71.94% of the lands has aptitude for farming, although they present different degrees of limitations that request different treatments for its conservation.

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.

Análise do risco de ocorrência da monilíase em cacaueiro no Brasil face às mudanças climáticas globais

The aim of this study was to evaluate the potential risk of moniliasis occurrence and the impacts of climate change on this disease in the coming decades, should this pathogen be introduced in Brazil. To this end, climate favorability maps were devised for the occurrence of moniliasis, both for the present and future time. The future scenarios (A2 and B2) focused on the decades of 2020, 2050 and 2080. These scenarios were obtained from six global climate models (GCMs) made available by the third assessment report of Intergovernmental Panel on Climate Change (IPCC). Currently, there are large areas with favorable climate conditions for moniliasis in Brazil, especially in regions at high risk of introduction of that pathogen. Considering the global warming scenarios provided by the IPCC, the potential risk of moniliasis occurrence in Brazil will be reduced. This decrease is predicted for both future scenarios, but will occur more sharply in scenario A2. However, there will still be areas with favorable climate conditions for the development of the disease, particularly in Brazil's main producing regions. Moreover, pathogen and host alike may undergo alterations due to climate change, which will affect the extent of their impacts on this pathosystem.

Impact of climate change on the phoma leaf spot of coffee in Brazil

The potential impact of global climate change on the spatial-temporal distribution of phoma leaf spot of coffee in Brazil was evaluated. Maps were prepared with the favorability of the climate to the occurrence of the disease in the current period and future. The future scenarios used were centered for the decades of 2010-2030, 2040-2060, and 2070-2090 (scenarios A2 and B2). These scenarios were obtained from six global climate models (GCM's) provided by the Intergovernmental Panel on Climate Change (IPCC). Assuming the future scenarios outlined by the IPCC, a reduction will occur in the occurrence of climatic favorability of phoma leaf spot in Brazil in both future scenarios (A2 and B2). As with the temporal distribution, the period of greatest risk of phoma leaf spot will tend to diminish in future decades. These planned changes will be larger in the A2 scenario compared to the predicted scenario B2. Despite the decrease in the favorability of phoma leaf spot in the country, some regions still present a potential risk of this disease. Furthermore, the increased frequency of extreme weather was not taken in to account. These will certainly influence the magnitude of potential impacts of climate change on the phoma leaf spot in Brazil.

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.

Criminalidade urbana e condições de vida na região administrativa de Campinas (SP) no ano de 2000: uma análise espacial

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Regressão logística aplicada na análise espacial de dados arqueológicos

Pós-graduação em Ciências Cartográficas - FCT

Ergonomia de quadras urbanas: condição térmica do pedestre

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Delimitação de unidades ambientais na bacia do Rio Capivara, Botucatu (SP)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Monitoramento das perdas de solo da sub-bacia Ribeirão das Bicas - Botucatu/SP, utilizando fotogrametria digital

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variabilidade espacial e correlações entre atributos de solo e produtividade na agricultura de precisão

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Estudo de ilhas de calor no município de Piratininga/SP, por meio de dados orbitais do landsat 5 sensor tm

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Geoprocessamento aplicado no uso e ocupação do solo no município de Lençóis Paulista/SP: Milena Montanholi Mileski. -

Pós-graduação em Agronomia (Energia na Agricultura) - FCA