Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model
Land cover change (LCC) is increasingly affecting global climate change, energy cycle, carbon cycle, and water cycle, with far-reaching consequences to human well-being. Web service-based online change detection applications have bloomed over the past decade for monitoring land cover change. Current...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/3/736 |
| _version_ | 1827759598199635968 |
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| author | Huaqiao Xing Haihang Wang Jinhua Zhang Dongyang Hou |
| author_facet | Huaqiao Xing Haihang Wang Jinhua Zhang Dongyang Hou |
| author_sort | Huaqiao Xing |
| collection | DOAJ |
| description | Land cover change (LCC) is increasingly affecting global climate change, energy cycle, carbon cycle, and water cycle, with far-reaching consequences to human well-being. Web service-based online change detection applications have bloomed over the past decade for monitoring land cover change. Currently, massive processing services and data services have been published and used over the internet. However, few studies consider both service integration and resource sharing in land cover domain, making end-users rarely able to acquire the LCC information timely. The behavior interaction between services is also growing more complex due to the increasing use of web service composition technology, making it challenging for static web services to provide collaboration and matching between diverse web services. To address the above challenges, a Dynamic Service Computing Model (DSCM) was proposed for monitoring LCC. Three dynamic computation strategies were proposed according to different users’ requirements of change detection. WMS-LCC was first developed by extending the existing WMS for ready-use LCC data access. Spatial relation-based LCC data integration was then proposed for extracting LCC information based on multi-temporal land cover data. Processing service encapsulation and service composition methods were also developed for chaining various land cover services to a complex service chain. Finally, a prototype system was implemented to evaluate the validity and feasibility of the proposed DSCM. Two walk-through examples were performed with GlobeLand30 datasets and muti-temporal Landsat imagery, respectively. The experimental results indicate that the proposed DSCM approach was more effective and applicable to a wider range of issues in land cover change detection. |
| first_indexed | 2024-03-11T09:27:56Z |
| format | Article |
| id | doaj.art-fc8b13582f8143e3a3fe99e138dc37e6 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:27:56Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-fc8b13582f8143e3a3fe99e138dc37e62023-11-16T17:53:29ZengMDPI AGRemote Sensing2072-42922023-01-0115373610.3390/rs15030736Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing ModelHuaqiao Xing0Haihang Wang1Jinhua Zhang2Dongyang Hou3School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaLand cover change (LCC) is increasingly affecting global climate change, energy cycle, carbon cycle, and water cycle, with far-reaching consequences to human well-being. Web service-based online change detection applications have bloomed over the past decade for monitoring land cover change. Currently, massive processing services and data services have been published and used over the internet. However, few studies consider both service integration and resource sharing in land cover domain, making end-users rarely able to acquire the LCC information timely. The behavior interaction between services is also growing more complex due to the increasing use of web service composition technology, making it challenging for static web services to provide collaboration and matching between diverse web services. To address the above challenges, a Dynamic Service Computing Model (DSCM) was proposed for monitoring LCC. Three dynamic computation strategies were proposed according to different users’ requirements of change detection. WMS-LCC was first developed by extending the existing WMS for ready-use LCC data access. Spatial relation-based LCC data integration was then proposed for extracting LCC information based on multi-temporal land cover data. Processing service encapsulation and service composition methods were also developed for chaining various land cover services to a complex service chain. Finally, a prototype system was implemented to evaluate the validity and feasibility of the proposed DSCM. Two walk-through examples were performed with GlobeLand30 datasets and muti-temporal Landsat imagery, respectively. The experimental results indicate that the proposed DSCM approach was more effective and applicable to a wider range of issues in land cover change detection.https://www.mdpi.com/2072-4292/15/3/736land cover changedynamic service computingweb-based geoprocessingweb service encapsulationweb service composition |
| spellingShingle | Huaqiao Xing Haihang Wang Jinhua Zhang Dongyang Hou Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model Remote Sensing land cover change dynamic service computing web-based geoprocessing web service encapsulation web service composition |
| title | Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model |
| title_full | Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model |
| title_fullStr | Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model |
| title_full_unstemmed | Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model |
| title_short | Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model |
| title_sort | monitoring land cover change by leveraging a dynamic service oriented computing model |
| topic | land cover change dynamic service computing web-based geoprocessing web service encapsulation web service composition |
| url | https://www.mdpi.com/2072-4292/15/3/736 |
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