Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach
ABSTRACTThe fusion of optical imagery with radar data can provide more accurate land cover change analysis of deforestation and tree-based agriculture. Radar data is limited temporally with most geographic areas not covered prior to 2007. This paper presents a new methodology to classify land cover...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-01-01
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| Series: | Journal of Land Use Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/1747423X.2021.2020918 |
| _version_ | 1797245090337390592 |
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| author | Melissa Wagner Elizabeth A. Wentz Michelle Stuhlmacher |
| author_facet | Melissa Wagner Elizabeth A. Wentz Michelle Stuhlmacher |
| author_sort | Melissa Wagner |
| collection | DOAJ |
| description | ABSTRACTThe fusion of optical imagery with radar data can provide more accurate land cover change analysis of deforestation and tree-based agriculture. Radar data is limited temporally with most geographic areas not covered prior to 2007. This paper presents a new methodology to classify land cover change related to oil palm expansion that takes historic data limitations into account. Our approach utilizes Hansen’s Global Forest Cover data, optical imagery, and texture information, to extract land cover information in Sumatra and Western Malaysia, where historical data is absent. Our method demonstrates how to accurately classify oil palm without radar data with overall accuracies for optical only experiments within 4.4% of optical plus radar classifications. Our results show agricultural land use was the primary driver of land cover change with the largest increase due to oil palm expansion (6.1%). Better estimations of oil palm expansion could be used in sustainable land management policies. |
| first_indexed | 2024-04-24T19:21:22Z |
| format | Article |
| id | doaj.art-f20adcc1bc3148c49f73bb82af18b765 |
| institution | Directory Open Access Journal |
| issn | 1747-423X 1747-4248 |
| language | English |
| last_indexed | 2024-04-24T19:21:22Z |
| publishDate | 2022-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Land Use Science |
| spelling | doaj.art-f20adcc1bc3148c49f73bb82af18b7652024-03-25T18:27:59ZengTaylor & Francis GroupJournal of Land Use Science1747-423X1747-42482022-01-01171264610.1080/1747423X.2021.2020918Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approachMelissa Wagner0Elizabeth A. Wentz1Michelle Stuhlmacher2School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USASchool of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USASchool of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USAABSTRACTThe fusion of optical imagery with radar data can provide more accurate land cover change analysis of deforestation and tree-based agriculture. Radar data is limited temporally with most geographic areas not covered prior to 2007. This paper presents a new methodology to classify land cover change related to oil palm expansion that takes historic data limitations into account. Our approach utilizes Hansen’s Global Forest Cover data, optical imagery, and texture information, to extract land cover information in Sumatra and Western Malaysia, where historical data is absent. Our method demonstrates how to accurately classify oil palm without radar data with overall accuracies for optical only experiments within 4.4% of optical plus radar classifications. Our results show agricultural land use was the primary driver of land cover change with the largest increase due to oil palm expansion (6.1%). Better estimations of oil palm expansion could be used in sustainable land management policies.https://www.tandfonline.com/doi/10.1080/1747423X.2021.2020918Data fusionoil palmaccuracy assessmentclassificationdeforestationland cover change |
| spellingShingle | Melissa Wagner Elizabeth A. Wentz Michelle Stuhlmacher Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach Journal of Land Use Science Data fusion oil palm accuracy assessment classification deforestation land cover change |
| title | Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach |
| title_full | Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach |
| title_fullStr | Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach |
| title_full_unstemmed | Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach |
| title_short | Quantifying oil palm expansion in Southeast Asia from 2000 to 2015: A data fusion approach |
| title_sort | quantifying oil palm expansion in southeast asia from 2000 to 2015 a data fusion approach |
| topic | Data fusion oil palm accuracy assessment classification deforestation land cover change |
| url | https://www.tandfonline.com/doi/10.1080/1747423X.2021.2020918 |
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