Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series
Owing to the rapid urbanization combined with global climate change, dramatic land-use change in coastal watersheds is occurred, which, in turn, cause the evolution of landscape patterns and threaten the valuable but fragile ecosystem. The coastal zone is characterized by severe cloud cover, frequen...
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| Format: | Article |
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IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10704979/ |
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| author | Chao Chen Jintao Liang Taohua Ren Yi Wang Zhisong Liu |
| author_facet | Chao Chen Jintao Liang Taohua Ren Yi Wang Zhisong Liu |
| author_sort | Chao Chen |
| collection | DOAJ |
| description | Owing to the rapid urbanization combined with global climate change, dramatic land-use change in coastal watersheds is occurred, which, in turn, cause the evolution of landscape patterns and threaten the valuable but fragile ecosystem. The coastal zone is characterized by severe cloud cover, frequent changes in land type, and fragmented landscape, so it is challenging to carry out the accurate landscape patterns analysis. To address this problem, this study employed the Google Earth engine cloud platform, Landsat time series, and landscape metrics in the Fragstats model to develop a comprehensive framework that integrates landscape pattern metrics and spatial analysis methods, considering both type level and landscape level. The Hangzhou Bay region was selected for conducting land-use classification and landscape patterns analysis. The results indicate that, during nearly four decades, with the continuous expansion of the urban, the urbanization process has accelerated, and the construction land has expanded by 6.93 times. By analyzing the evolution of landscape patterns, Hangzhou Bay heightened landscape fragmentation and patch shapes became more irregular caused by a trend toward intensified urbanization. The Shannon's diversity index continuously increased from 1.14 to 1.51, while the contagion index consistently decreased from 59.83% to 42.21%, suggesting an increase in land-use diversity, reduced aggregation, and extension tendencies between land patches, along with a decrease in the proportion of highly connected patches within the landscape. This study is anticipated to provide robust evidence for the rational planning of future development directions and the deployment of landscape ecological spatial services. |
| format | Article |
| id | doaj-art-005176c9c9904bbb8d5fe66411d88191 |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-005176c9c9904bbb8d5fe66411d881912025-01-15T00:00:18ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352024-01-0117183791839810.1109/JSTARS.2024.347393710704979Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time SeriesChao Chen0https://orcid.org/0000-0002-3284-0667Jintao Liang1https://orcid.org/0009-0002-2113-9864Taohua Ren2Yi Wang3https://orcid.org/0000-0002-1347-7030Zhisong Liu4School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou, ChinaSchool of Geophysics and Geomatics, China University of Geosciences, Wuhan, ChinaSchool of Information Engineering, Zhejiang Ocean University, Zhoushan, ChinaSchool of Geophysics and Geomatics, China University of Geosciences, Wuhan, ChinaSchool of Information Engineering, Zhejiang Ocean University, Zhoushan, ChinaOwing to the rapid urbanization combined with global climate change, dramatic land-use change in coastal watersheds is occurred, which, in turn, cause the evolution of landscape patterns and threaten the valuable but fragile ecosystem. The coastal zone is characterized by severe cloud cover, frequent changes in land type, and fragmented landscape, so it is challenging to carry out the accurate landscape patterns analysis. To address this problem, this study employed the Google Earth engine cloud platform, Landsat time series, and landscape metrics in the Fragstats model to develop a comprehensive framework that integrates landscape pattern metrics and spatial analysis methods, considering both type level and landscape level. The Hangzhou Bay region was selected for conducting land-use classification and landscape patterns analysis. The results indicate that, during nearly four decades, with the continuous expansion of the urban, the urbanization process has accelerated, and the construction land has expanded by 6.93 times. By analyzing the evolution of landscape patterns, Hangzhou Bay heightened landscape fragmentation and patch shapes became more irregular caused by a trend toward intensified urbanization. The Shannon's diversity index continuously increased from 1.14 to 1.51, while the contagion index consistently decreased from 59.83% to 42.21%, suggesting an increase in land-use diversity, reduced aggregation, and extension tendencies between land patches, along with a decrease in the proportion of highly connected patches within the landscape. This study is anticipated to provide robust evidence for the rational planning of future development directions and the deployment of landscape ecological spatial services.https://ieeexplore.ieee.org/document/10704979/Coastal landscape patternsevolution analysisGoogle Earth engine (GEE)land use and cover change (LUCC)Landsat time-series |
| spellingShingle | Chao Chen Jintao Liang Taohua Ren Yi Wang Zhisong Liu Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Coastal landscape patterns evolution analysis Google Earth engine (GEE) land use and cover change (LUCC) Landsat time-series |
| title | Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series |
| title_full | Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series |
| title_fullStr | Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series |
| title_full_unstemmed | Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series |
| title_short | Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series |
| title_sort | temporal and spatial analysis of coastal landscape patterns using the gee cloud platform and landsat time series |
| topic | Coastal landscape patterns evolution analysis Google Earth engine (GEE) land use and cover change (LUCC) Landsat time-series |
| url | https://ieeexplore.ieee.org/document/10704979/ |
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