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		<isbn>978-85-17-00088-1</isbn>
		<label>59761</label>
		<citationkey>TrentinTrenKram:2017:AnDiEs</citationkey>
		<title>Análise da dinâmica espacial do uso da terra a partir de imagens da série Landsat nos municípios da Microrregião Campanha Central/RS</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>1487 KiB</size>
		<author>Trentin, Aline Biasoli,</author>
		<author>Trentin, Carline Biasoli,</author>
		<author>Kramer, Gisieli,</author>
		<electronicmailaddress>alinetrentin@unipampa.edu.br</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>daniela.seki@inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>28-31 maio 2017</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>3004-3011</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The continuous monitoring of land use in the Pampa biome, through Geoprocessing tools, has great importance in respect of use and management of natural vegetation. This article aims to analyse the dynamics of land use and cover in the municipalities of Campanha Central Microregion/RS, in the years 2010 and 2015, using remote sensing image Landsat series. The methodology consisted in the acquisition of Landsat 5 TM satellite images for 2010 and Landsat 8 OLI for 2015. The georeferencing of the Landsat 5 TM scenes using as a basis the Landsat image 8 OLI, then the mosaic of scenes for the two dates. For the classification of the images was considered the maximum likelihood algorithm, based on samples of training according to the main land uses of in the Microregion (field/pasture, forested area, temporary crops, soil exposed and water). The results showed excellent performance of the classifier, greater than 99%, for the two dates. The class field/pasture stood out in the study area, in two years. However, overall there was a decrease in these areas, as a result of the increase of temporary crops and forest areas, possibly linked to intensification of agricultural and forestry activities. These results allowed concluding that the use of remote sensing images in a spatio temporal perspective, can contribute with continuous information and analysis on the characteristics of the region under study.</abstract>
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		<language>pt</language>
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