Doctor of Philosophy (PhD)
Geography and Anthropology
With the ability to attenuate wave and limit erosion, coastal wetlands are important to protect shoreline for coastal communities. Micro-topography in coastal wetlands has a significant influence on hydrology, habitat variability and ecosystem functions. However, when mapping micro-topography by terrestrial LiDAR in coastal environments, the coverage of dense vegetation leads to a relatively low chance of laser penetration through the canopy to the ground. This dissertation proposes a rapid and flexible terrain mapping solution for the densely vegetated coastal environment by integrating crown structure from terrestrial LiDAR with terrain samples from GPS. The validated results in the study site demonstrate that the proposed method successfully corrected the terrain in low and tall vegetation.
Based on the accurate micro-topography mapping, this dissertation used an object-oriented tool, Coastal Morphology Analyst (CMA), to examine sediment change patterns for the study site. The CMA analysis identified depositional and erosional objects successfully, which are the useful data source for coastal wetland restoration and essential data input for vegetation pattern analysis.
The micro-topographic derived variables slope and Topographic Wetness Index (TWI) were generated to analyze the influence of micro-topography on sediment change and vegetation patterns. The single variable slope cannot separate erosion and deposition efficiently, but the single variable TWI is capable of separating at least 75% of the erosional and depositional objects. The erosion is more likely to occur at the place with small TWI. When integrating the class change type, TWI is a better variable to predict the erosional area for bank nourishment to improve wetland engineering.
The class change between 2015 and 2016 was calculated by subtracting the classification of 2015 from 2016. For low vegetation, 69% of the areas converted to tall vegetation and 30% of the areas remained low vegetation. For tall vegetation, 98% of the areas remained tall vegetation and only 2% of the areas converted to low vegetation. Therefore, more low vegetation converted to tall vegetation from 2015 to 2016. For bare ground, 77% and 13% of the areas converted to tall and low vegetation respectively, while only 10% of the areas remained bare ground. For the wetland restoration in the area with the similar environmental condition, Spartina alterniflora is a preferred choice for planting.
Zhang, Xukai, "Monitoring Sediment Dynamics and Vegetation Competition Based on Micro-Topography and Terrestrial LiDAR for Wetland Restoration" (2019). LSU Doctoral Dissertations. 4801.