Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

Tasiyiwa Priscilla Muumbe,Jussi Baade,Christiane Schmullius,Christian Thau,Jenia Singh

doi:10.3390/rs13030507

Tasiyiwa Priscilla Muumbe, Jussi Baade + Show 3 more

Open Access

https://doi.org/10.3390/rs13030507

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Abstract

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.

Highlights

Our meta-analysis takes a detailed look at the geographic distribution of Terrestrial Laser Scanning (TLS) studies, the parameters retrieved from TLS point clouds, known retrieval methods as well as the main opportunities and challenges arising from the studied literature
In the event that a search query returned more than 100 articles, the search was refined by the research areas forestry or remote sensing to narrow down on specific studies employing TLS for vegetation parameter extraction
Of the 113 publications used for the detailed review, 80% of the publications focused on the extraction of vegetation parameters from TLS point clouds, 12% used TLS as auxiliary data (e.g., TLS data used to validate airborne LiDAR) [78,79,80] and 8% applied

Summary

Introduction

Savanna ecosystems span one-fifth of the global land [2,3] which makes up approximately 20% of the terrestrial vegetation and contribute. Savanna ecosystems contribute significantly to the global carbon cycle with a net primary productivity 4.0/). Savannas are vital biomes that play a major role in the provision of ecosystem services. They contribute significantly to the socio-economic needs of most rural households, especially in Africa, where many are dependent on natural resources for their livelihood [6,7]. Savannas support approximately 20% of the world population and account on average 28% of household income in rural areas of developing countries [8,9]

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