Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data
Mangrove forests are among the most productive ecosystems on Earth and mainly grow at tropical and subtropical latitudes. They provide many important ecological and societal functions. However, rapid spatiotemporal variations in mangroves have been observed worldwide, especially in the coastal zones...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/8/921 |
| _version_ | 1819004404953513984 |
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| author | Chunlei Ma Bin Ai Jun Zhao Xiaoping Xu Wei Huang |
| author_facet | Chunlei Ma Bin Ai Jun Zhao Xiaoping Xu Wei Huang |
| author_sort | Chunlei Ma |
| collection | DOAJ |
| description | Mangrove forests are among the most productive ecosystems on Earth and mainly grow at tropical and subtropical latitudes. They provide many important ecological and societal functions. However, rapid spatiotemporal variations in mangroves have been observed worldwide, especially in the coastal zones of developing areas, and the integrity of mangroves has been significantly affected by anthropogenic activities in recent decades. The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution over the past 30 years in Guangdong Province. This goal was achieved by classifying multi-temporal Landsat images using a decision tree method based on Classification and Regression Tree (CART) algorithm. The driving forces resulting in these spatiotemporal variations of mangroves were then discussed. Our analysis revealed that the classification method used in this study yielded good accuracy, with an overall accuracy and kappa coefficient of higher than 90% and 0.8, respectively. In Guangdong province, the mangrove forests covered areas of 9305, 9556, 6793, and 9700 ha in 1985, 1995, 2005, and 2015, respectively, with remarkable inter-annual changes. Mangrove forests are mainly located in Western Guangdong, and few are located in Eastern Guangdong. The distribution of mangrove patches became more fragmented from 1985 to 2005 and less fragmented from 2005 to 2015, and the distribution pattern in 2015 showed stronger connectivity than that in 1985. Natural factors, such as temperature, sea level rise, extreme weather events, and the length of the coastline, have macroscopic effects on the distribution of mangrove forests. Anthropogenic activities, such as deforestation, urbanization, and aquaculture development, have negative effects on the distribution of mangroves. On the other hand, the establishment of nature reserves has positive effects on the distribution of mangroves. The findings of this study provide a reference for the management and protection of mangroves, which is of great practical significance. |
| first_indexed | 2024-12-20T23:36:22Z |
| format | Article |
| id | doaj.art-12eb30eea4a74f42aa3bd2395300d45b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T23:36:22Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-12eb30eea4a74f42aa3bd2395300d45b2022-12-21T19:23:11ZengMDPI AGRemote Sensing2072-42922019-04-0111892110.3390/rs11080921rs11080921Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing DataChunlei Ma0Bin Ai1Jun Zhao2Xiaoping Xu3Wei Huang4School of Marine Sciences, Sun Yat-sen University, Tangjiawan Town, Xiangzhou District, Zhuhai 519082, ChinaSchool of Marine Sciences, Sun Yat-sen University, Tangjiawan Town, Xiangzhou District, Zhuhai 519082, ChinaSchool of Marine Sciences, Sun Yat-sen University, Tangjiawan Town, Xiangzhou District, Zhuhai 519082, ChinaSchool of Marine Sciences, Sun Yat-sen University, Tangjiawan Town, Xiangzhou District, Zhuhai 519082, ChinaSchool of Marine Sciences, Sun Yat-sen University, Tangjiawan Town, Xiangzhou District, Zhuhai 519082, ChinaMangrove forests are among the most productive ecosystems on Earth and mainly grow at tropical and subtropical latitudes. They provide many important ecological and societal functions. However, rapid spatiotemporal variations in mangroves have been observed worldwide, especially in the coastal zones of developing areas, and the integrity of mangroves has been significantly affected by anthropogenic activities in recent decades. The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution over the past 30 years in Guangdong Province. This goal was achieved by classifying multi-temporal Landsat images using a decision tree method based on Classification and Regression Tree (CART) algorithm. The driving forces resulting in these spatiotemporal variations of mangroves were then discussed. Our analysis revealed that the classification method used in this study yielded good accuracy, with an overall accuracy and kappa coefficient of higher than 90% and 0.8, respectively. In Guangdong province, the mangrove forests covered areas of 9305, 9556, 6793, and 9700 ha in 1985, 1995, 2005, and 2015, respectively, with remarkable inter-annual changes. Mangrove forests are mainly located in Western Guangdong, and few are located in Eastern Guangdong. The distribution of mangrove patches became more fragmented from 1985 to 2005 and less fragmented from 2005 to 2015, and the distribution pattern in 2015 showed stronger connectivity than that in 1985. Natural factors, such as temperature, sea level rise, extreme weather events, and the length of the coastline, have macroscopic effects on the distribution of mangrove forests. Anthropogenic activities, such as deforestation, urbanization, and aquaculture development, have negative effects on the distribution of mangroves. On the other hand, the establishment of nature reserves has positive effects on the distribution of mangroves. The findings of this study provide a reference for the management and protection of mangroves, which is of great practical significance.https://www.mdpi.com/2072-4292/11/8/921mangrovechange detectioncoastal zone in Guangdong ProvinceLandsatCART |
| spellingShingle | Chunlei Ma Bin Ai Jun Zhao Xiaoping Xu Wei Huang Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data Remote Sensing mangrove change detection coastal zone in Guangdong Province Landsat CART |
| title | Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data |
| title_full | Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data |
| title_fullStr | Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data |
| title_full_unstemmed | Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data |
| title_short | Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data |
| title_sort | change detection of mangrove forests in coastal guangdong during the past three decades based on remote sensing data |
| topic | mangrove change detection coastal zone in Guangdong Province Landsat CART |
| url | https://www.mdpi.com/2072-4292/11/8/921 |
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