COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2
doi: 10.12957/geouerj.2016.19099 Changes in land cover, especially in the tropics, has been occurring at an accelerated rate and with it the largest and most diverse rainforest in the world, the Amazon jungle or the Amazon Biome, also suffers from this process. At present study were compared result...
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Format: | Article |
Language: | Spanish |
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Universidade do Estado do Rio de Janeiro
2016-11-01
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Series: | Geo UERJ |
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Online Access: | https://www.e-publicacoes.uerj.br/index.php/geouerj/article/view/19099 |
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author | Orjana Silva Francisco Dourado |
author_facet | Orjana Silva Francisco Dourado |
author_sort | Orjana Silva |
collection | DOAJ |
description | doi: 10.12957/geouerj.2016.19099
Changes in land cover, especially in the tropics, has been occurring at an accelerated rate and with it the largest and most diverse rainforest in the world, the Amazon jungle or the Amazon Biome, also suffers from this process. At present study were compared results obtained from characterization of land cover by supervised classification by maximum likelihood using LANDSAT 5 TM and ALOS-2 AVNIR images. The study area chosen for this evaluation was the area of the Settlement Project Carlinda in Mato Grosso State, located on the so-called Legal Amazon. From the results it was observed that areas of each classes in the two images have similar values. The small variations should be presented due to the difference between the spatial resolutions of the images and the difference of the spectral bands regions involved in the analysis, especially the Green band. Analyzing the classes according spatial representation, in both images, the water bodies class was the smaller, followed by preserved vegetation class and wetland vegetation class. The class of anthropic vegetation / exposed soil was the most represented class in both classifications. Regarding the study area, it was observed that in the region there is a predominance of areas used in various human activities and gradual reduction of areas with preserved vegetation. This fact is diametrically opposite to what one would expect from an area in the Amazon, where, by the law need 80% of its territory be preserved. |
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institution | Directory Open Access Journal |
issn | 1415-7543 1981-9021 |
language | Spanish |
last_indexed | 2024-12-18T02:16:33Z |
publishDate | 2016-11-01 |
publisher | Universidade do Estado do Rio de Janeiro |
record_format | Article |
series | Geo UERJ |
spelling | doaj.art-d8449d1d1e774372baf7769640567f3d2022-12-21T21:24:22ZspaUniversidade do Estado do Rio de JaneiroGeo UERJ1415-75431981-90212016-11-0102922023310.12957/geouerj.2016.1909913026COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2Orjana Silva0Francisco Dourado1UERJUniversidade do Estado do Rio de Janeiro Faculdade de Geologia Departamento de Geologia Aplicadadoi: 10.12957/geouerj.2016.19099 Changes in land cover, especially in the tropics, has been occurring at an accelerated rate and with it the largest and most diverse rainforest in the world, the Amazon jungle or the Amazon Biome, also suffers from this process. At present study were compared results obtained from characterization of land cover by supervised classification by maximum likelihood using LANDSAT 5 TM and ALOS-2 AVNIR images. The study area chosen for this evaluation was the area of the Settlement Project Carlinda in Mato Grosso State, located on the so-called Legal Amazon. From the results it was observed that areas of each classes in the two images have similar values. The small variations should be presented due to the difference between the spatial resolutions of the images and the difference of the spectral bands regions involved in the analysis, especially the Green band. Analyzing the classes according spatial representation, in both images, the water bodies class was the smaller, followed by preserved vegetation class and wetland vegetation class. The class of anthropic vegetation / exposed soil was the most represented class in both classifications. Regarding the study area, it was observed that in the region there is a predominance of areas used in various human activities and gradual reduction of areas with preserved vegetation. This fact is diametrically opposite to what one would expect from an area in the Amazon, where, by the law need 80% of its territory be preserved.https://www.e-publicacoes.uerj.br/index.php/geouerj/article/view/19099sensoriamento remotolandsatalosclassificaçãouso do soloclassificação supervisionadamáxima verossimilhança. |
spellingShingle | Orjana Silva Francisco Dourado COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2 Geo UERJ sensoriamento remoto landsat alos classificação uso do solo classificação supervisionada máxima verossimilhança. |
title | COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2 |
title_full | COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2 |
title_fullStr | COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2 |
title_full_unstemmed | COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2 |
title_short | COMPARISON OF RESULTS OF THE SUPERVISED CLASSIFICATION OF SOIL COVERAGE BY MAXIMUM LIKELIHOOD OF IMAGES LANDSAT-5 TM AND ALOS AVNIR-2 |
title_sort | comparison of results of the supervised classification of soil coverage by maximum likelihood of images landsat 5 tm and alos avnir 2 |
topic | sensoriamento remoto landsat alos classificação uso do solo classificação supervisionada máxima verossimilhança. |
url | https://www.e-publicacoes.uerj.br/index.php/geouerj/article/view/19099 |
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