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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Compara??o de ?ndices de vegeta??o no mapeamento da cobertura da terra no semi?rido: estudo de caso no Munic?pio de Martins/RN

Guedes, J?nio Carlos Fernandes 29 March 2016 (has links)
Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-01-12T14:50:42Z No. of bitstreams: 1 JanioCarlosFernandesGuedes_DISSERT.pdf: 4148387 bytes, checksum: 9d18aacae04088b9f6e20ef25426e179 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-01-18T16:08:26Z (GMT) No. of bitstreams: 1 JanioCarlosFernandesGuedes_DISSERT.pdf: 4148387 bytes, checksum: 9d18aacae04088b9f6e20ef25426e179 (MD5) / Made available in DSpace on 2017-01-18T16:08:26Z (GMT). No. of bitstreams: 1 JanioCarlosFernandesGuedes_DISSERT.pdf: 4148387 bytes, checksum: 9d18aacae04088b9f6e20ef25426e179 (MD5) Previous issue date: 2016-03-29 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / O contexto atual da rela??o homem e natureza vem exigindo novas configura??es no tocante ao uso adequado dos recursos naturais, baseadas nas premissas do Desenvolvimento Sustent?vel. Nesse sentido, se destacam as geotecnologias, caracterizadas como um suporte instrumental eficiente para caracteriza??o de diversos padr?es ambientais. Os levantamentos de cobertura da terra se constituem como um ex?mio exemplo a ser destacado, pois a partir de ?ndices de vegeta??o ? poss?vel distinguir diferentes classes de cobertura da terra. Nesse sentido, esta pesquisa objetivou comparar ?ndices de vegeta??o NDVI e SAVI, quanto a classifica??o e espacializa??o da cobertura da terra no munic?pio de Martins/RN. Para tanto, foram selecionadas imagens do sat?lite Landsat 8 e mapa de uso e cobertura da terra elaborado pelo INPE. Essas imagens passaram por etapas de pr?-processamento, aplicando-se corre??es radiom?tricas e geom?tricas. Posteriormente aplicou-se os ?ndices NDVI e SAVI no software Erdas 9.2, com quantifica??o das classes de cobertura da terra e elabora??o dos layouts no software ArcGis 10.2. A partir destas imagens procedeu-se a pesquisa de campo, onde foram observados e coletados ?s coordenadas de 125 pontos de controle, obtendo-se as seguintes classes de cobertura da terra: Floresta estacional, Savana-Est?pica florestada, Savana-Est?pica arborizada, Agricultura permanente e Tempor?ria, Solo exposto, Zona urbana e Corpo d??gua. As informa??es subsidiar?o a elabora??o da matriz de confus?o, a qual objetivou a avalia??o da acur?cia dos mapas a partir do ?ndice de Exatid?o Global e o ?ndice Kappa para ambos os mapas (NDVI, SAVI, INPE). Diante da matriz de confus?o com um ?ndice Kappa de 66,96%, o ?ndice SAVI apresentou melhores resultados em compara??o com o NDVI para o mapeamento da cobertura da terra do munic?pio de Martins/RN. Na avalia??o da precis?o do mapeamento de cobertura da terra, a partir de uma matriz de confus?o, os ?ndices para avaliar a acur?cia da precis?o dos mapeamentos (?ndice de exatid?o global e Kappa) mostraram-se como ?timas op??es no que diz respeito ? an?lise da vericidade desses dados, obtendo assim melhores resultados para o ?ndice SAVI. Dessa forma, conclui-se que, o uso de imagens de sat?lite provenientes do sensoriamento remoto na aplica??o de ?ndices de vegeta??o, mostrou-se como ferramentas relevantes no estudo da cobertura da terra, juntamente com os ?ndices de Exatid?o Global e o ?ndice Kappa, que por sua vez, mostraram-se como alternativas relevantes no tocante a acur?cia dos mapas de cobertura da terra. / Studies related to sustainable development and proper planning of the use of natural resources is one of the challenges of today's society in the search for instrumental support for the characterization of environmental standards as, for example, the survey of land cover. With the advent of geotechnology, studies about the land cover in the semiarid region from vegetation indices are paramount in the study of natural resources, making it possible to distinguish different types of coverage and land use. Thus it is intended with this work compare the NDVI and SAVI, classification and land cover spatial distribution in Martins / RN. Therefore, satellite images were selected Landsat 8 and a map of land use and land cover developed by INPE. These images have gone through stages of preprocessing, where applied radiometric and geometric corrections, and then applied the NDVI and SAVI index in ERDAS software 9.2, with quantification of the land cover classes and preparation of layout in ArcGIS 10.2 software. In the field, they were observed and collected the coordinates of 125 control points, and then confusion matrix was designed to evaluate the accuracy of the maps from the Global Accuracy index and the Kappa index for both maps (NDVI, SAVI, INPE ). Initially, before the satellite images treatment were observadadas field eight land cover classes in the city of Mantins / RN, as follows: Seasonal Forest, Savannah-Est?pica forested, wooded Savannah-Est?pica, permanent and Agriculture Temporary Soil exposed , urban area and water body. Given the confusion matrix, prepared from 125 control points obtained in the field, with a Kappa index of 66.96%, the SAVI index showed better results compared with NDVI to map Martins municipal land cover / RN. In assessing the accuracy of the land cover mapping from an array of confusion, the indexes to evaluate the accuracy of accuracy of mappings (global and Kappa accuracy Index) showed to be great options with regard to the analysis of vericidade such data, thus obtaining better results for SAVI index. Thus, it is concluded that the use of satellite from remote sensing images in the application of vegetation indices, has proved to be relevant tools in the study of land cover, along with the Global accuracy rates and the Kappa index, which in turn, proved to be relevant alternatives regarding the accuracy of land cover maps.

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