Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data
Shorelines are vulnerable to anthropogenic activities including urbanization, land reclamation and sediment loading. Shoreline changes may be a reflection of the degradation of coastal ecosystems because of human activities. Understanding the shoreline dynamics is, therefore, a topic of global conce...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-07-01
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| Series: | Big Earth Data |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/20964471.2020.1740491 |
| _version_ | 1818671696921493504 |
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| author | Lixia Chu Francis Oloo Martin Sudmanns Dirk Tiede Daniel Hölbling Thomas Blaschke Iulian Teleoaca |
| author_facet | Lixia Chu Francis Oloo Martin Sudmanns Dirk Tiede Daniel Hölbling Thomas Blaschke Iulian Teleoaca |
| author_sort | Lixia Chu |
| collection | DOAJ |
| description | Shorelines are vulnerable to anthropogenic activities including urbanization, land reclamation and sediment loading. Shoreline changes may be a reflection of the degradation of coastal ecosystems because of human activities. Understanding the shoreline dynamics is, therefore, a topic of global concern. Earth observation data, such as multi-temporal satellite images, are an important resource for assessing changes in coastal ecosystems. In this research, we used Google Earth Engine (GEE) to monitor and map historical shoreline dynamics in the Hangzhou Bay in China where the Qiantang River flows into the East China Sea. Specifically, we aimed to capture and quantify both the spatial and temporal shoreline changes and to assess the link between anthropogenic activities and shoreline changes on the integrity of this coastal area. We implemented a Tasselled Cap analysis (TCA) on Landsat imagery from 1985 to 2018 in GEE to calculate the wetness coefficient. We then applied Otsu method for automatic image thresholding on the wetness coefficient to detect waterbodies and shoreline changes. Further, we adopted the nighttime light data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) from 1992 to 2013 as a proxy of human activities. The results show that in the hotspot areas, the shoreline has moved by more than 5 km in the last decades, accounting for approximately 900 km2 of land accretion. Within this area, the human activity, indicated by the intensity of nighttime light, increased significantly. The results of this work reveal the influence of human activities on the shoreline dynamics and can support policies that promote the sustainable use and conservation of coastal environments. Our methodology can be transferred and applied to other coastal zones in various regions and scaled up to larger areas. |
| first_indexed | 2024-12-17T07:28:07Z |
| format | Article |
| id | doaj.art-dd8746e7ad014f6cae8020ea65c8fb9c |
| institution | Directory Open Access Journal |
| issn | 2096-4471 2574-5417 |
| language | English |
| last_indexed | 2024-12-17T07:28:07Z |
| publishDate | 2020-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Big Earth Data |
| spelling | doaj.art-dd8746e7ad014f6cae8020ea65c8fb9c2022-12-21T21:58:34ZengTaylor & Francis GroupBig Earth Data2096-44712574-54172020-07-014324226410.1080/20964471.2020.17404911740491Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO dataLixia Chu0Francis Oloo1Martin Sudmanns2Dirk Tiede3Daniel Hölbling4Thomas Blaschke5Iulian Teleoaca6Z_GIS, University of SalzburgZ_GIS, University of SalzburgZ_GIS, University of SalzburgZ_GIS, University of SalzburgZ_GIS, University of SalzburgZ_GIS, University of SalzburgWest University of TimişoaraShorelines are vulnerable to anthropogenic activities including urbanization, land reclamation and sediment loading. Shoreline changes may be a reflection of the degradation of coastal ecosystems because of human activities. Understanding the shoreline dynamics is, therefore, a topic of global concern. Earth observation data, such as multi-temporal satellite images, are an important resource for assessing changes in coastal ecosystems. In this research, we used Google Earth Engine (GEE) to monitor and map historical shoreline dynamics in the Hangzhou Bay in China where the Qiantang River flows into the East China Sea. Specifically, we aimed to capture and quantify both the spatial and temporal shoreline changes and to assess the link between anthropogenic activities and shoreline changes on the integrity of this coastal area. We implemented a Tasselled Cap analysis (TCA) on Landsat imagery from 1985 to 2018 in GEE to calculate the wetness coefficient. We then applied Otsu method for automatic image thresholding on the wetness coefficient to detect waterbodies and shoreline changes. Further, we adopted the nighttime light data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) from 1992 to 2013 as a proxy of human activities. The results show that in the hotspot areas, the shoreline has moved by more than 5 km in the last decades, accounting for approximately 900 km2 of land accretion. Within this area, the human activity, indicated by the intensity of nighttime light, increased significantly. The results of this work reveal the influence of human activities on the shoreline dynamics and can support policies that promote the sustainable use and conservation of coastal environments. Our methodology can be transferred and applied to other coastal zones in various regions and scaled up to larger areas.http://dx.doi.org/10.1080/20964471.2020.1740491shorelines dynamicshuman activitiesgoogle earth engineearth observation |
| spellingShingle | Lixia Chu Francis Oloo Martin Sudmanns Dirk Tiede Daniel Hölbling Thomas Blaschke Iulian Teleoaca Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data Big Earth Data shorelines dynamics human activities google earth engine earth observation |
| title | Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data |
| title_full | Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data |
| title_fullStr | Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data |
| title_full_unstemmed | Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data |
| title_short | Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data |
| title_sort | monitoring long term shoreline dynamics and human activities in the hangzhou bay china combining daytime and nighttime eo data |
| topic | shorelines dynamics human activities google earth engine earth observation |
| url | http://dx.doi.org/10.1080/20964471.2020.1740491 |
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