A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery
Carbon emissions from forest ecosystems are greatly impacted by the acceleration of fragmentation and edge effects. Understanding these effects requires accurate monitoring of changes in fragmented forest landscapes. However, these changes are often low-intensity and small-scale, making it difficult...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223000481 |
| _version_ | 1797842866762940416 |
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| author | Yaotong Cai Qian Shi Xiaocong Xu Xiaoping Liu |
| author_facet | Yaotong Cai Qian Shi Xiaocong Xu Xiaoping Liu |
| author_sort | Yaotong Cai |
| collection | DOAJ |
| description | Carbon emissions from forest ecosystems are greatly impacted by the acceleration of fragmentation and edge effects. Understanding these effects requires accurate monitoring of changes in fragmented forest landscapes. However, these changes are often low-intensity and small-scale, making it difficult to detect them using medium spatial resolution satellite images (e.g., Landsat). To address this challenge, this study developed the Pure Forest Index (PFI), which uses a combination of the existing vegetation index (VI) and spectral mixture analysis (SMA) to more effectively detect and characterize the contribution of forests to the observed spectral response of a pixel. The PFI was applied to detect forest changes in the Amazon rainforest from 1986 to 2020 using the Continuous Change Detection and Classification (CCDC) algorithm (hereafter referred to as the CCDC-PFI algorithm). The results showed reliable performance in mapping forest changes, with an overall accuracy of 0.94 (±0.03) at the spatial scale and a temporal accuracy of 91.1 % (within a two-year window). Comparison with other indices revealed that the PFI improves the ability to monitor forest dynamics with an increased overall accuracy of 0.02–0.35. The PFI also demonstrated advantages in enhancing sub-pixel forest information and suppressing non-forest backgrounds in various scenes compared to conventional VIs. The proposed approach is expected to benefit further research on forests and ecosystems. |
| first_indexed | 2024-04-09T16:55:06Z |
| format | Article |
| id | doaj.art-b4606560d8604a679d2a9c9a1ca4b3b1 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-09T16:55:06Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-b4606560d8604a679d2a9c9a1ca4b3b12023-04-21T06:41:04ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-04-01118103226A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imageryYaotong Cai0Qian Shi1Xiaocong Xu2Xiaoping Liu3School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, Guangdong province, ChinaCorresponding author.; School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, Guangdong province, ChinaSchool of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, Guangdong province, ChinaSchool of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, Guangdong province, ChinaCarbon emissions from forest ecosystems are greatly impacted by the acceleration of fragmentation and edge effects. Understanding these effects requires accurate monitoring of changes in fragmented forest landscapes. However, these changes are often low-intensity and small-scale, making it difficult to detect them using medium spatial resolution satellite images (e.g., Landsat). To address this challenge, this study developed the Pure Forest Index (PFI), which uses a combination of the existing vegetation index (VI) and spectral mixture analysis (SMA) to more effectively detect and characterize the contribution of forests to the observed spectral response of a pixel. The PFI was applied to detect forest changes in the Amazon rainforest from 1986 to 2020 using the Continuous Change Detection and Classification (CCDC) algorithm (hereafter referred to as the CCDC-PFI algorithm). The results showed reliable performance in mapping forest changes, with an overall accuracy of 0.94 (±0.03) at the spatial scale and a temporal accuracy of 91.1 % (within a two-year window). Comparison with other indices revealed that the PFI improves the ability to monitor forest dynamics with an increased overall accuracy of 0.02–0.35. The PFI also demonstrated advantages in enhancing sub-pixel forest information and suppressing non-forest backgrounds in various scenes compared to conventional VIs. The proposed approach is expected to benefit further research on forests and ecosystems.http://www.sciencedirect.com/science/article/pii/S1569843223000481Change detectionForest disturbanceSpectral mixture analysisPure Forest IndexAmazon rainforest |
| spellingShingle | Yaotong Cai Qian Shi Xiaocong Xu Xiaoping Liu A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery International Journal of Applied Earth Observations and Geoinformation Change detection Forest disturbance Spectral mixture analysis Pure Forest Index Amazon rainforest |
| title | A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery |
| title_full | A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery |
| title_fullStr | A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery |
| title_full_unstemmed | A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery |
| title_short | A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery |
| title_sort | novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series landsat imagery |
| topic | Change detection Forest disturbance Spectral mixture analysis Pure Forest Index Amazon rainforest |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223000481 |
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