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		<isbn>978-65-89159-04-9</isbn>
		<citationkey>SantosJoMoPaSoSi:2023:GoEaEn</citationkey>
		<title>Google Earth Engine no mapemento de áreas de pastagem e culturas anuais em Rondônia</title>
		<format>Internet</format>
		<year>2023</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Santos, Marcelo Henrique de Oliveira,</author>
		<author>Johann, Jerry Adriani,</author>
		<author>Moura, Valdir,</author>
		<author>Paludo, Alex,</author>
		<author>Souza, Ranieli dos Anjos de,</author>
		<author>Silveira, João Felipe Cesar,</author>
		<affiliation>Universidade Estadual do Oeste do Paraná (UNIOESTE)</affiliation>
		<affiliation>Universidade Estadual do Oeste do Paraná (UNIOESTE)</affiliation>
		<affiliation>Instituto Federal de Rondônia (IFRO)</affiliation>
		<affiliation>Universidade Estadual do Oeste do Paraná (UNIOESTE)</affiliation>
		<affiliation>Instituto Federal de Rondônia (IFRO)</affiliation>
		<affiliation>Universidade Estadual do Oeste do Paraná (UNIOESTE)</affiliation>
		<electronicmailaddress>marcelohenriquetricolor@gmail.com</electronicmailaddress>
		<electronicmailaddress>jerry.johann@unioeste.br</electronicmailaddress>
		<electronicmailaddress>valdir.moura@ifro.edu.br</electronicmailaddress>
		<electronicmailaddress>paludo.alex@hotmail.com</electronicmailaddress>
		<electronicmailaddress>ranieli.anjos@ifro.edu.br</electronicmailaddress>
		<electronicmailaddress>joaofelipecs17@gmail.com</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<editor>Sanches, Ieda DelArco,</editor>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 20 (SBSR)</conferencename>
		<conferencelocation>Florianópolis</conferencelocation>
		<date>02-05 abril 2023</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>e155984</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>full paper</tertiarytype>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<keywords>índices de vegetação, agricultura, pecuária, processamento em nuvem, vegetation indices, agriculture, livestock, cloud processing, orbital images.imagens orbitais.</keywords>
		<abstract>Este estudo teve como objetivo realizar o mapeamento de áreas com culturas anuais (verão e inverno) e pastagens no estado de Rondônia, utilizando imagens de satélite e aplicando técnicas de sensoriamento remoto e de aprendizagem de máquina. Para a realização dos mapeamentos se utilizaram as composições RGB (8,11,4) para o Sentinel 2 e RGB (5,6,4) para o Landsat 8 e índices de vegetação (NDVI, EVI e SAVI) de forma conjunta com no algoritmo classificador Naive Bayes. A classificação foi realizada utilizando a platafor ABSTRACT: This study aimed to map areas with annual crops (summer and winter) and pastures in Rondônia state, using satellite images and applying remote sensing and machine learning techniques. To carry out the mappings, the RGB (8,11,4) compositions Sentinel 2 and RGB (5,6,4) Landsat 8 and vegetation indices (NDVI, EVI and SAVI) were user together with the Naive Bayes classifier algorithm. The classification was performed using the Google Earth Engine platform. With the classification, the areas with summer, winter and pasture crops were quantified, by Rondônia microregion, for 2020/2021 harvest. As a result, 384 thousand ha were mapped with summer crops, 219 thousand ha with winter crops and 7.73 million ha with pasture.</abstract>
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		<language>pt</language>
		<targetfile>155984.pdf</targetfile>
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