Resumo em Inglês:
Abstract: This work considers the terrain slope factor as well as census dataset with variables related to socioeconomic and demographic characteristics, sanitation, water supply, garbage collection, and electricity in identifying centralities, or new urban centers in the municipality of Barra do Piraí, located in the State of Rio de Janeiro, Brazil, as a case study. The morphological approach was used with a Principal Components analysis and spatial analysis involving Global Moran Index, Local Indicator of Spatial Association - LISA, and Kernel Density Estimator. Among the variables considered in the study, results indicated that the slope was a preponderant factor in identifying the centralities in the study area and that it limits the urban expansion both in the municipality and in some existing districts.Resumo em Inglês:
Abstract: Multibeam Echosounders (MBES) are hydrographic tools used primarily to survey the seafloor bathymetry and backscatter. Modern MBES systems are not limited to the seafloor, as they can also map water column profiles, which holds important biological, thermal and chemical information of oceans and shores. Unfortunately, this feature is normally disregarded during routine surveys operations, as it generates a very large amount of data, requiring data compression for possible use in future analysis. For the compression, we propose to map the water column data into images and to compress each of them using image compressors. We devised two methods: a lossless coder based on linear predictors, and a lossy coder based on thresholding followed by lossless coding. Both methods seem to better suit the echosounder image data than traditional image coders. We tested our methods in sequences that capture different water column activities in the Bay of Brest, France. Results indicate our method outperforms other standard image compression methods, ranging from 4 to 70% average gains in compression ratio in lossless coding, and equivalent results in lossy coding. Compression-induced distortion was measured as traditional mean squared error and as analysis-parameter estimation errors.