Physical Sciences and Mathematics Commons^™

Mapping Soil Organic Carbon (Soc) In A Semi-Arid Mountainous Watershed Using Variables From Hyperspectral, Lidar And Traditional Datasets, Ryan Matthew Will

Boise State University Theses and Dissertations

Quantifying soil organic carbon (SOC) in complex terrain is challenging due to its high spatial variability. Generally, limited discrete observations of SOC data are used to develop spatially distributed maps of SOC by developing quantitative relationships between SOC and available spatially distributed variables. In many ecosystems, remotely sensed information on aboveground vegetation can be used to predict belowground carbon stocks. In this research, we developed maps of SOC across a semi-arid watershed based on discrete field observations and modeling using a suite of variables inclusive of hyperspectral and lidar datasets; these observations provide insights into the controls on soil carbon …