Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas
Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the car...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/3/507 |
| _version_ | 1827605184705986560 |
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| author | Tasiyiwa Priscilla Muumbe Jussi Baade Jenia Singh Christiane Schmullius Christian Thau |
| author_facet | Tasiyiwa Priscilla Muumbe Jussi Baade Jenia Singh Christiane Schmullius Christian Thau |
| author_sort | Tasiyiwa Priscilla Muumbe |
| collection | DOAJ |
| description | Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome. |
| first_indexed | 2024-03-09T06:16:05Z |
| format | Article |
| id | doaj.art-ddb941e2144d49f8962c2bb04c1902cf |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T06:16:05Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ddb941e2144d49f8962c2bb04c1902cf2023-12-03T11:53:07ZengMDPI AGRemote Sensing2072-42922021-01-0113350710.3390/rs13030507Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on SavannasTasiyiwa Priscilla Muumbe0Jussi Baade1Jenia Singh2Christiane Schmullius3Christian Thau4Department for Earth Observation, Friedrich Schiller University Jena, 07743 Jena, GermanyDepartment of Physical Geography, Friedrich Schiller University Jena, 07743 Jena, GermanyDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USADepartment for Earth Observation, Friedrich Schiller University Jena, 07743 Jena, GermanyDepartment for Earth Observation, Friedrich Schiller University Jena, 07743 Jena, GermanySavannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.https://www.mdpi.com/2072-4292/13/3/507terrestrial laser scanning (TLS)savannaAbove Ground Biomass (AGB)3D point cloudvegetation structure |
| spellingShingle | Tasiyiwa Priscilla Muumbe Jussi Baade Jenia Singh Christiane Schmullius Christian Thau Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas Remote Sensing terrestrial laser scanning (TLS) savanna Above Ground Biomass (AGB) 3D point cloud vegetation structure |
| title | Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas |
| title_full | Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas |
| title_fullStr | Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas |
| title_full_unstemmed | Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas |
| title_short | Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas |
| title_sort | terrestrial laser scanning for vegetation analyses with a special focus on savannas |
| topic | terrestrial laser scanning (TLS) savanna Above Ground Biomass (AGB) 3D point cloud vegetation structure |
| url | https://www.mdpi.com/2072-4292/13/3/507 |
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