CLASSIFICAÇÃO NÃO-SUPERVISIONADA DE IMAGENS RAPIDEYE NO MAPEAMENTO DA COBERTURA DAS TERRAS DO DELTA DO PARNAÍBA, PIAUÍ

IF 0.1 Q4 EDUCATION & EDUCATIONAL RESEARCH
João Victor Alves Amorim, G. S. Valladares, M. G. Portela
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引用次数: 0

Abstract

The aim of this paper was the mapping of the land cover classes in an area of the Delta do Parnaíba, Piauí, NE, Brazil using the unsupervised classification method in RapidEye images. Through digital processing of images in a GIS environment, it was possible to map 12 classes of land cover. The results showed that the highest percentage of the study area is covered by fields with the presence of shrub vegetation and a predominance of pasture. Other classes (mobile dunes and sandy shoreline, undergrowth and exposed land) characterize a high level of environmental vulnerability and risk of erosion, illustrating the need for sustainable management techniques. Based on the techniques and evaluation criterias, the mapping indicated very good agreement, emphasizing the quality of the visual interpretation of the image and the classification method employed. AMORIM, J. V. A.; VALLADARES, G. S.; PORTELA, M. G. T. CLASSIFICAÇÃO NÃO SUPERVISIONADA DE IMAGENS RAPIDEYE NO MAPEAMENTO DA COBERTURA DAS TERRAS DO DELTA DO PARNAÍBA, PIAUÍ Geosaberes, Fortaleza, v. 12, p.88-106, 2021. 89
RAPIDEYE图像在parnaiba三角洲土地覆盖制图中的无监督分类,piaui
本文的目的是利用RapidEye图像中的无监督分类方法绘制巴西东北部三角洲地区Parnaíba, Piauí的土地覆盖类别。通过在地理信息系统环境中对图像进行数字处理,可以绘制12类土地覆盖。结果表明:研究区以灌丛植被为主、草地为主的草地覆盖率最高;其他类别(流动沙丘和沙质海岸线、灌木丛和裸露的土地)的特点是环境脆弱性和侵蚀风险很高,说明需要可持续的管理技术。基于技术和评价标准,映射显示出很好的一致性,强调图像的视觉解译质量和所采用的分类方法。阿莫林,j.v.;巴利达雷斯;张晓明,张晓明,张晓明,等。CLASSIFICAÇÃO NÃO快速成像技术研究进展与进展PARNAÍBA, PIAUÍ地球物理学报,vol . 12, p.88-106, 2021。89
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来源期刊
Geosaberes
Geosaberes EDUCATION & EDUCATIONAL RESEARCH-
自引率
0.00%
发文量
11
审稿时长
12 weeks
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