APPLICATIONS OF GEDI LIDAR FOR REMOTE SENSING OF FOREST STRUCTURE AND BIODIVERSITY INDICATORS

This dissertation advances the understanding and applications of spaceborne lidar for forest integrity and biodiversity monitoring. The three analyses detailed here contribute to our ability to assess forest health as indicated by forest structure and structural diversity and improve our ability to monitor biodiversity using forest structure as a proxy. First, I introduce the application of GEDI lidar for differentiating between forest types by examining structural differences between native mangroves in Nigeria and an invasive palm species introduced to the delta. My findings indicate that even in short, coastal forests, GEDI is capable of quantitatively distinguishing between forest types with Plant Area Vegetation Density profiles demonstrating notable differences in the structure of native mangroves and invasive palms. Second, I compare GEDI metrics between Protected and Non-Protected areas to facilitate an understanding of conservation strategy impacts. The results of this study demonstrate a novel approach to monitoring Protected Areas (PAs) wherein GEDI detects differences in PA impact on forest structure, and these structural differences are further informed by patterns of background deforestation rates. Finally, I apply GEDI metrics of structural complexity and canopy height to improving bird Species Distribution Models (SDMs) in a single Protected Area in Uganda, thereby demonstrating applicability of structural complexity metrics towards biodiversity monitoring in regions known for their endemic species. I demonstrate that the inclusion of structural metrics in SDMs improves modeling of species presence near unique landscape features like swamps, even in contiguous forest. Additionally, this analysis demonstrates the utility of GEDI and structural metrics for modeling endemic and threatened species. These analyses together improve our understanding of forest structure across forested landscapes and supply a methodology for monitoring structural diversity across large scales to improve biodiversity conservation tactics.

Department dc:contributor.department

Geography

Year dc:date.issued

2026

Author dc:creator

• Barenblitt, Abigail

Advisor dc:contributor.advisor

• Duncanson, Laura

Language dc:language.iso

en

Identifier

https://doi.org/10.13016/jw6q-krgj

OAI identifier oai:identifier

oai:drum.lib.umd.edu:1903/35995