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Registros de precipitação pluvial em áreas pouco acessíveis, normalmente não apresentam uma boa distribuição espacial dos postos de coleta, principalmente pela questão físiográfica (relevo e rede de drenagem, por exemplo). Entretanto, aspectos estruturais, como baixo investimento em redes de monitoramento, também são comuns. A área do presente estudo (Bacia Hidrográfica do Rio Jordão – BHRJ), localizada na região centro-sul do estado do Paraná – Brasil, possui problemas correlatos. Nesse sentido, o objetivo dessa pesquisa foi validar um método de ajuste e correção entre fontes de dados distintas, focando a correção das informações provenientes do Tropical Rainfall Measuring Mission (TRMM), associadas aos de postos pluviométricos em superfície, buscando melhorar a representação espacial. Esse procedimento foi realizado com base na criação de equações lógicas e aplicação de testes estatísticos. Os dados do sensor TRMM foram analisados, ajustados e comparados com dados de pluviômetros localizados no entorno e dentro da BHRJ para o período de 2009 a 2018. Os resultados obtidos por meio de técnicas estatísticas, como a correlação linear (r), Coeficiente de Determinação (r²), Erro Médio Absoluto (EMA), foi considerado satisfatório, com valores de r² próximo de 90%. Dessa forma, identificou-se que a região de estudo tem elevada variabilidade temporal e espacial da precipitação pluvial, mas as técnicas de ajustes utilizadas propiciaram melhor representação espacial, possibilitando a utilização dos dados oriundos de sensores remotos em complemento aos de postos de superfície, com bom nível de confiança.

The present work sought to demonstrate the importance using geoprocessing techniques and methodologies in the identification and analysis of the temporal and spatial distribution of air temperature. Therefore, an environment with difficulties for systematic monitoring of climatic elements was selected in the Serra da Esperancaarea, southern region of the State of Parana. Two methodologies established in geoprocessing were used: the first deals with the interpretation of orbital images and the second makes reference to the interpolation of surface data. These methodologies, used in an integrated way, made it possible to know the relationship between the spatial and temporal distribution of air temperature with vegetation and the terrain altimetry. The air temperature data were monitored at 4 (four) points, following the contours of the federal highway that passes through the study area. Satellite images were obtained of July 26th, 2015 and January 18th, 2016, representing winter and summer southern conditions. The results indicated that this relationship exists and that in the absence of absolute data monitored at conventional collection points, geostatistics techniques allow good estimation. Moreover, this methodology can be used to control land use change in permanent preservation areas.

The present study aimed to compare the maps of slope obtained in 1997 in the Geographic Information System (GIS, SGI/INPE), with the declivity maps generated in 2014 in the Georeferenced Information Processing System (SPRING). The input data from the testing areas, topographic maps and Shuttle Radar Topography Mission (SRTM) images were stored in SPRING databases. The test areas were built with well-defined isolines concerning the horizontal spacing between the contour lines. The Interpolation methods analyzed were: Weighted Mean/Elevation/Quadrant, Weighted Mean/Quadrant, Weighted Mean, Simple Mean, Nearest Neighbor, Linear and Quintic Surface with breaklines. All these methods were used to draw rectangular grids with 1mx1m spatial resolution. In order to obtain the Triangulated Irregular Network (TIN) grid, the interpolations used were Delaunay, lower angle and isolines. Out of these methods, we selected the TIN grid with Delaunay interpolator which allowed the generation slope image with spatial resolution of1m. This image was sliced according to slope classes generating digital declivity maps. Next, we established statistical procedures, indexes of Percentage of Accuracy (PA) and indexes of Percentage of Total Accuracy (PAT)) for the evaluation of the classes of slope and declivity areas obtained in the two periods. We concluded that the results were on average10% higher for areas classified as plan relief and over 100% higher for areas of corrugated and mountainous relief. The input data from topographic maps

With the changes that are occurring in land ownership structure of our country, the National Institute of Agrarian Reform (INCRA), through Law 10.267/2001, which refers to the georeferencing of rural properties, attempted to establish a new methodology to surveying rural properties and also integrate their databases with other agencies at the federal sphere in order to completely understand the reality of rural properties in Brazil. With it the process of georeferencing, go through several transformations, which 1 Geografo; Mestrando no Programa de Pos-graduacao em Geografia (PPGG) na Universidade Estadual do Centro-Oeste, UNICENTRO; Endereco: Rua Simeao Camargo Varela de Sa, 03, CEDETEG, CEP: 85040080, Guarapuava, Parana, Brasil; E-mail: brunhct@hotmail.com (*) Autor para correspondencia. 2 Dr.; Professor do Departamento de Geografia, Programa de Pos-graduacao em Geografia, Pesquisador do Nucleo de Pesquisas Ambientais (NPA) da Universidade Estadual do Centro-Oeste, UNICENTRO; Endereco: Rua Simeao Camargo Varela de Sa, 03, CEDETEG, CEP: 85040-080, Guarapuava, Parana, Brasil; E-mail: bertotti99@gmail.com Ambiencia Guarapuava (PR) v.10 n.3 p. 839 847 Set/Dez. 2014 ISSN 1808 0251 Recebido para publicacao em 20/02/2014 e aceito em 13/10/2014 DOI:10.5935/ambiencia.2014.03.14nt Ambiencia Revista do Setor de Ciencias Agrarias e Ambientais V.10 N.3 Set./Dez. 2014 840 through new information technologies becoming increasingly automatic, from a process with many bureaucratic procedures, to a fully online form. So has the need to develop a Landed Property Management System (SIGEF), which will be portrayed on this paper.