One-Class Classification of Natural Vegetation Using Remote Sensing: A Review
Advances in remote sensing (RS) technology in recent years have increased the interest in including RS data into one-class classifiers (OCCs). However, this integration is complex given the interdisciplinary issues involved. In this context, this review highlights the advances and current challenges...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/10/1892 |
| _version_ | 1797534369290649600 |
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| author | Sébastien Rapinel Laurence Hubert-Moy |
| author_facet | Sébastien Rapinel Laurence Hubert-Moy |
| author_sort | Sébastien Rapinel |
| collection | DOAJ |
| description | Advances in remote sensing (RS) technology in recent years have increased the interest in including RS data into one-class classifiers (OCCs). However, this integration is complex given the interdisciplinary issues involved. In this context, this review highlights the advances and current challenges in integrating RS data into OCCs to map vegetation classes. A systematic review was performed for the period 2013–2020. A total of 136 articles were analyzed based on 11 topics and 30 attributes that address the ecological issues, properties of RS data, and the tools and parameters used to classify natural vegetation. The results highlight several advances in the use of RS data in OCCs: (i) mapping of potential and actual vegetation areas, (ii) long-term monitoring of vegetation classes, (iii) generation of multiple ecological variables, (iv) availability of open-source data, (v) reduction in plotting effort, and (vi) quantification of over-detection. Recommendations related to interdisciplinary issues were also suggested: (i) increasing the visibility and use of available RS variables, (ii) following good classification practices, (iii) bridging the gap between spatial resolution and site extent, and (iv) classifying plant communities. |
| first_indexed | 2024-03-10T11:29:37Z |
| format | Article |
| id | doaj.art-57acd7541f604001a2328ff62aa14054 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T11:29:37Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-57acd7541f604001a2328ff62aa140542023-11-21T19:21:45ZengMDPI AGRemote Sensing2072-42922021-05-011310189210.3390/rs13101892One-Class Classification of Natural Vegetation Using Remote Sensing: A ReviewSébastien Rapinel0Laurence Hubert-Moy1Place du Recteur Henri Le Moal, LETG UMR 6554 CNRS, University of Rennes, 35000 Rennes, FrancePlace du Recteur Henri Le Moal, LETG UMR 6554 CNRS, University of Rennes, 35000 Rennes, FranceAdvances in remote sensing (RS) technology in recent years have increased the interest in including RS data into one-class classifiers (OCCs). However, this integration is complex given the interdisciplinary issues involved. In this context, this review highlights the advances and current challenges in integrating RS data into OCCs to map vegetation classes. A systematic review was performed for the period 2013–2020. A total of 136 articles were analyzed based on 11 topics and 30 attributes that address the ecological issues, properties of RS data, and the tools and parameters used to classify natural vegetation. The results highlight several advances in the use of RS data in OCCs: (i) mapping of potential and actual vegetation areas, (ii) long-term monitoring of vegetation classes, (iii) generation of multiple ecological variables, (iv) availability of open-source data, (v) reduction in plotting effort, and (vi) quantification of over-detection. Recommendations related to interdisciplinary issues were also suggested: (i) increasing the visibility and use of available RS variables, (ii) following good classification practices, (iii) bridging the gap between spatial resolution and site extent, and (iv) classifying plant communities.https://www.mdpi.com/2072-4292/13/10/1892MaxEntearth observationplant communitiesconservationSDMbiogeography |
| spellingShingle | Sébastien Rapinel Laurence Hubert-Moy One-Class Classification of Natural Vegetation Using Remote Sensing: A Review Remote Sensing MaxEnt earth observation plant communities conservation SDM biogeography |
| title | One-Class Classification of Natural Vegetation Using Remote Sensing: A Review |
| title_full | One-Class Classification of Natural Vegetation Using Remote Sensing: A Review |
| title_fullStr | One-Class Classification of Natural Vegetation Using Remote Sensing: A Review |
| title_full_unstemmed | One-Class Classification of Natural Vegetation Using Remote Sensing: A Review |
| title_short | One-Class Classification of Natural Vegetation Using Remote Sensing: A Review |
| title_sort | one class classification of natural vegetation using remote sensing a review |
| topic | MaxEnt earth observation plant communities conservation SDM biogeography |
| url | https://www.mdpi.com/2072-4292/13/10/1892 |
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