Estudio de bofedales en los Andes ecuatorianos a través de la comparación de imágenes Landsat-8 y Sentinel-2

IF 0.4 Q4 REMOTE SENSING
Carlos Jara, J. Delegido, J. Ayala, P. Lozano, A. Armas, V. Flores
{"title":"Estudio de bofedales en los Andes ecuatorianos a través de la comparación de imágenes Landsat-8 y Sentinel-2","authors":"Carlos Jara, J. Delegido, J. Ayala, P. Lozano, A. Armas, V. Flores","doi":"10.4995/RAET.2019.11715","DOIUrl":null,"url":null,"abstract":"The objective of the present study was to compare the Landsat-8 and Sentinel-2 images to calculate the wetland´s extension, distribution and degree of conservation, in Reserva de Producción de Fauna Chinborazo (RPFCH) protected area located in the Andean region of Ecuador. This process was developed with in situ work in 16 wetlands, distributed in different conservation levels. The Landsat-8 and Sentinel-2 images were processed through a radiometric calibration (restoration of lost lines or píxels and correction of the stripe of the image) and an atmospheric correction (conversion of the digital levels to radiance values), to later calculate the Vegetation spectral indexes: NDVI, SAVI (L = 0.5) where L is a constant of the soil brightness component, EVI2 (improved vegetation index 2), NDWI (standard difference water index), WDRI (wide dynamic range vegetation index) and the Red Edge model that only this one has in Sentinel-2 in this study. Making a classification of the Bofedal ecosystem in satellite images by applying Random Forest, the most important variables with Landsat-8 were EVI2 (37.72%) and SAVI with L = 0.5 (30.97%), while with Sentinel-2 the most important variables correspond to the Red Edge (38.54%) and WDRI (27.06%). With the indices calculated, two categories of analysis were determined: a) wetland integrated by the levels: intervened [1], moderately conserved [2] and conserved [3] and b) other than wetland [4] integrated by areas that do not correspond to this ecosystem. Landsat-8 shows that the percentage of correct classifications of píxels belonging to the wetland category corresponds to: [1] 72.76%, [2] 58.38%, [3] 68.42%, while for the category other [4] were correct 95.15%. With Sentinel-2, the percentage of correct classifications corresponds to [1] 95.00%, [2] 82.60%, [3] 96.25%, while for the category other [4] the correct answers were 98.13%. In this way with Landsat-8 the wetland corresponds to 21.708,54 ha (41.21%), while with Sentinel-2 the wetland represents a total of 20,518 ha (38.95%), of the 52,560 ha that belong to the RPFCH, concluding that Sentinel-2, due to its better spatial resolution, and the incorporation of its new bands in Red Edge, obtains better results in image classification.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":" ","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de Teledeteccion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4995/RAET.2019.11715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 10

Abstract

The objective of the present study was to compare the Landsat-8 and Sentinel-2 images to calculate the wetland´s extension, distribution and degree of conservation, in Reserva de Producción de Fauna Chinborazo (RPFCH) protected area located in the Andean region of Ecuador. This process was developed with in situ work in 16 wetlands, distributed in different conservation levels. The Landsat-8 and Sentinel-2 images were processed through a radiometric calibration (restoration of lost lines or píxels and correction of the stripe of the image) and an atmospheric correction (conversion of the digital levels to radiance values), to later calculate the Vegetation spectral indexes: NDVI, SAVI (L = 0.5) where L is a constant of the soil brightness component, EVI2 (improved vegetation index 2), NDWI (standard difference water index), WDRI (wide dynamic range vegetation index) and the Red Edge model that only this one has in Sentinel-2 in this study. Making a classification of the Bofedal ecosystem in satellite images by applying Random Forest, the most important variables with Landsat-8 were EVI2 (37.72%) and SAVI with L = 0.5 (30.97%), while with Sentinel-2 the most important variables correspond to the Red Edge (38.54%) and WDRI (27.06%). With the indices calculated, two categories of analysis were determined: a) wetland integrated by the levels: intervened [1], moderately conserved [2] and conserved [3] and b) other than wetland [4] integrated by areas that do not correspond to this ecosystem. Landsat-8 shows that the percentage of correct classifications of píxels belonging to the wetland category corresponds to: [1] 72.76%, [2] 58.38%, [3] 68.42%, while for the category other [4] were correct 95.15%. With Sentinel-2, the percentage of correct classifications corresponds to [1] 95.00%, [2] 82.60%, [3] 96.25%, while for the category other [4] the correct answers were 98.13%. In this way with Landsat-8 the wetland corresponds to 21.708,54 ha (41.21%), while with Sentinel-2 the wetland represents a total of 20,518 ha (38.95%), of the 52,560 ha that belong to the RPFCH, concluding that Sentinel-2, due to its better spatial resolution, and the incorporation of its new bands in Red Edge, obtains better results in image classification.
通过Landsat-8和Sentinel-2图像比较研究厄瓜多尔安第斯山脉的沼泽
本研究的目的是比较Landsat-8和Sentinel-2图像,以计算位于厄瓜多尔安第斯地区的Producción de Fauna Chinborazo (RPFCH)保护区湿地的扩展、分布和保护程度。这一过程是在16个湿地的原位工作中开发的,分布在不同的保护水平上。Landsat-8和Sentinel-2图像经过辐射校正(恢复丢失的线或píxels并校正图像的条纹)和大气校正(将数字水平转换为辐射值)处理,然后计算植被光谱指数:NDVI, SAVI (L = 0.5),其中L为土壤亮度分量的常数,EVI2(改良植被指数2),NDWI(标准差水指数),WDRI(宽动态范围植被指数),以及本研究中Sentinel-2中只有该模型的Red Edge模型。利用随机森林对卫星影像上的Bofedal生态系统进行分类,Landsat-8最重要的变量是EVI2(37.72%)和SAVI(30.97%),而Sentinel-2最重要的变量对应于Red Edge(38.54%)和WDRI(27.06%)。根据计算的指数,确定了两类分析:a)受干预的[1]、中度保护的[2]和受保护的[3];b)除湿地[4]外,由与该生态系统不对应的区域进行综合。Landsat-8显示píxels属于湿地类的正确率分别为:[1]72.76%,[2]58.38%,[3]68.42%,其他[4]类的正确率为95.15%。在Sentinel-2中,[1]对应的正确率为95.00%,[2]对应的正确率为82.60%,[3]对应的正确率为96.25%,其他[4]对应的正确率为98.13%。由此可见,Landsat-8对应的湿地面积为21.708,54 ha(41.21%),而Sentinel-2对应的湿地面积为20,518 ha(38.95%),其中52,560 ha属于RPFCH。由此可见,由于Sentinel-2具有更好的空间分辨率,并且在Red Edge中纳入了新的波段,因此在图像分类上取得了更好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Revista de Teledeteccion
Revista de Teledeteccion REMOTE SENSING-
CiteScore
1.80
自引率
14.30%
发文量
11
审稿时长
10 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信