Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China
The rapid advancement of remote sensing technology has given rise to numerous global- and regional-scale medium- to high-resolution land cover (LC) datasets, making significant contributions to the exploration of worldwide environmental shifts and the sustainable governance of natural resources. Non...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/6/1111 |
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| author | Xiangyu Ji Xujun Han Xiaobo Zhu Yajun Huang Zengjing Song Jinghan Wang Miaohang Zhou Xuemei Wang |
| author_facet | Xiangyu Ji Xujun Han Xiaobo Zhu Yajun Huang Zengjing Song Jinghan Wang Miaohang Zhou Xuemei Wang |
| author_sort | Xiangyu Ji |
| collection | DOAJ |
| description | The rapid advancement of remote sensing technology has given rise to numerous global- and regional-scale medium- to high-resolution land cover (LC) datasets, making significant contributions to the exploration of worldwide environmental shifts and the sustainable governance of natural resources. Nonetheless, owing to the inherent uncertainties embedded within remote sensing imagery, LC datasets inevitably exhibit inaccuracies. In this study, a local accuracy assessment of LC datasets in Southwest China was conducted. The datasets utilized in our analysis include ESA WorldCover, CLCD, Esri Land Cover, CRLC, FROM-GLC10, GLC_FCS30, GlobeLand30, and SinoLC-1. This study employed a sampling approach that combines proportional allocation and stratified random sampling (SRS) to gather sample points and compute confusion matrices to validate eight LC products. The local accuracy of the eight LC maps differs significantly from the overall accuracy provided by the original authors in Southwest China. ESA WorldCover and CLCD demonstrate higher local accuracy than other products in Southwest China, with their overall accuracy (OA) values being 87.1% and 85.48%, respectively. Simultaneously, we computed the area for each LC map based on categories, quantifying uncertainty through the reporting of confidence intervals for both accuracy and area parameters. This study aims to validate and compare eight LC datasets and assess precision and area of diverse spatial resolution datasets for mapping and monitoring across Southwest China. |
| first_indexed | 2024-04-24T17:51:25Z |
| format | Article |
| id | doaj.art-2bccbe3e61b04908b2ac763158d837cb |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-24T17:51:25Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2bccbe3e61b04908b2ac763158d837cb2024-03-27T14:02:54ZengMDPI AGRemote Sensing2072-42922024-03-01166111110.3390/rs16061111Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest ChinaXiangyu Ji0Xujun Han1Xiaobo Zhu2Yajun Huang3Zengjing Song4Jinghan Wang5Miaohang Zhou6Xuemei Wang7Chongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaChongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaChongqing Engineering Research Center for Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaChongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaChongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaChongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaChongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaSouthwest University Library, Southwest University, Chongqing 400715, ChinaThe rapid advancement of remote sensing technology has given rise to numerous global- and regional-scale medium- to high-resolution land cover (LC) datasets, making significant contributions to the exploration of worldwide environmental shifts and the sustainable governance of natural resources. Nonetheless, owing to the inherent uncertainties embedded within remote sensing imagery, LC datasets inevitably exhibit inaccuracies. In this study, a local accuracy assessment of LC datasets in Southwest China was conducted. The datasets utilized in our analysis include ESA WorldCover, CLCD, Esri Land Cover, CRLC, FROM-GLC10, GLC_FCS30, GlobeLand30, and SinoLC-1. This study employed a sampling approach that combines proportional allocation and stratified random sampling (SRS) to gather sample points and compute confusion matrices to validate eight LC products. The local accuracy of the eight LC maps differs significantly from the overall accuracy provided by the original authors in Southwest China. ESA WorldCover and CLCD demonstrate higher local accuracy than other products in Southwest China, with their overall accuracy (OA) values being 87.1% and 85.48%, respectively. Simultaneously, we computed the area for each LC map based on categories, quantifying uncertainty through the reporting of confidence intervals for both accuracy and area parameters. This study aims to validate and compare eight LC datasets and assess precision and area of diverse spatial resolution datasets for mapping and monitoring across Southwest China.https://www.mdpi.com/2072-4292/16/6/1111land cover datasetsspatial accuracy assessmentarea comparisonremote sensing |
| spellingShingle | Xiangyu Ji Xujun Han Xiaobo Zhu Yajun Huang Zengjing Song Jinghan Wang Miaohang Zhou Xuemei Wang Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China Remote Sensing land cover datasets spatial accuracy assessment area comparison remote sensing |
| title | Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China |
| title_full | Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China |
| title_fullStr | Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China |
| title_full_unstemmed | Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China |
| title_short | Comparison and Validation of Multiple Medium- and High-Resolution Land Cover Products in Southwest China |
| title_sort | comparison and validation of multiple medium and high resolution land cover products in southwest china |
| topic | land cover datasets spatial accuracy assessment area comparison remote sensing |
| url | https://www.mdpi.com/2072-4292/16/6/1111 |
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