Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data
Land cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spatial resolution on land cover classification. Sinc...
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MDPI AG
2023-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/13/6136 |
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| author | Runxiang Li Xiaohong Gao Feifei Shi Hao Zhang |
| author_facet | Runxiang Li Xiaohong Gao Feifei Shi Hao Zhang |
| author_sort | Runxiang Li |
| collection | DOAJ |
| description | Land cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spatial resolution on land cover classification. Since it is difficult to obtain multiple spatial resolution remote sensing images of the same area at the same time, the main current method to study the scale effect of land cover classification is to use the same image resampled to different resolutions, however errors in the resampling process lead to uncertainty in the accuracy of land cover classification. To study the land cover classification scale effect of different spatial resolutions of multi-source remote sensing data, we selected 1 m and 4 m of GF-2, 6 m of SPOT-6, 10 m of Sentinel-2, and 30 m of Landsat-8 multi-sensor data, and explored the scale effect of image spatial resolution on land cover classification from two aspects of mixed image element decomposition and spatial heterogeneity. For the study area, we compared the classification obtained from GF-2, SPOT-6, Sentinel-2, and Landsat-8 images at different spatial resolutions based on GBDT and RF. The results show that (1) GF-2 and SPOT-6 had the best classification results, and the optimal scale based on this classification accuracy was 4–6 m; (2) the optimal scale based on linear decomposition depended on the study area; (3) the optimal scale of land cover was related to spatial heterogeneity, i.e., the more fragmented and complex was the space, the smaller the scale needed; and (4) the resampled images were not sensitive to scale and increased the uncertainty of the classification. These findings have implications for land cover classification and optimal scale selection, scale effects, and landscape ecology uncertainty studies. |
| first_indexed | 2024-03-11T01:28:56Z |
| format | Article |
| id | doaj.art-fd14bb9a62f2411d94f54847b0eabb10 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T01:28:56Z |
| publishDate | 2023-07-01 |
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| series | Sensors |
| spelling | doaj.art-fd14bb9a62f2411d94f54847b0eabb102023-11-18T17:31:04ZengMDPI AGSensors1424-82202023-07-012313613610.3390/s23136136Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing DataRunxiang Li0Xiaohong Gao1Feifei Shi2Hao Zhang3School of Geographical Sciences, Qinghai Normal University, Xining 810008, ChinaSchool of Geographical Sciences, Qinghai Normal University, Xining 810008, ChinaSchool of Geographical Sciences, Qinghai Normal University, Xining 810008, ChinaSchool of Geographical Sciences, Qinghai Normal University, Xining 810008, ChinaLand cover data are important basic data for earth system science and other fields. Multi-source remote sensing images have become the main data source for land cover classification. There are still many uncertainties in the scale effect of image spatial resolution on land cover classification. Since it is difficult to obtain multiple spatial resolution remote sensing images of the same area at the same time, the main current method to study the scale effect of land cover classification is to use the same image resampled to different resolutions, however errors in the resampling process lead to uncertainty in the accuracy of land cover classification. To study the land cover classification scale effect of different spatial resolutions of multi-source remote sensing data, we selected 1 m and 4 m of GF-2, 6 m of SPOT-6, 10 m of Sentinel-2, and 30 m of Landsat-8 multi-sensor data, and explored the scale effect of image spatial resolution on land cover classification from two aspects of mixed image element decomposition and spatial heterogeneity. For the study area, we compared the classification obtained from GF-2, SPOT-6, Sentinel-2, and Landsat-8 images at different spatial resolutions based on GBDT and RF. The results show that (1) GF-2 and SPOT-6 had the best classification results, and the optimal scale based on this classification accuracy was 4–6 m; (2) the optimal scale based on linear decomposition depended on the study area; (3) the optimal scale of land cover was related to spatial heterogeneity, i.e., the more fragmented and complex was the space, the smaller the scale needed; and (4) the resampled images were not sensitive to scale and increased the uncertainty of the classification. These findings have implications for land cover classification and optimal scale selection, scale effects, and landscape ecology uncertainty studies.https://www.mdpi.com/1424-8220/23/13/6136land coverscale effectuncertaintyspatial heterogeneity |
| spellingShingle | Runxiang Li Xiaohong Gao Feifei Shi Hao Zhang Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data Sensors land cover scale effect uncertainty spatial heterogeneity |
| title | Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data |
| title_full | Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data |
| title_fullStr | Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data |
| title_full_unstemmed | Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data |
| title_short | Scale Effect of Land Cover Classification from Multi-Resolution Satellite Remote Sensing Data |
| title_sort | scale effect of land cover classification from multi resolution satellite remote sensing data |
| topic | land cover scale effect uncertainty spatial heterogeneity |
| url | https://www.mdpi.com/1424-8220/23/13/6136 |
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