Physical Sciences and Mathematics Commons^™

Deriving Landscape-Scale Vegetation Cover And Aboveground Biomass In A Semi-Arid Ecosystem Using Imaging Spectroscopy, Andrew Poley

Boise State University Theses and Dissertations

Environmental disturbances in semi-arid ecosystems have highlighted the need to monitor current and future vegetation conditions across the landscape. Imaging spectroscopy provide the necessary information to derive vegetation characteristics at high-spatial resolutions across large geographic areas. The work of this thesis is divided into two sections focused on using imaging spectroscopy to estimate and classify vegetation cover, and approximate aboveground biomass in a semi-arid ecosystem.

The first half of this thesis assesses the ability of imaging spectroscopy to derive vegetation classes and their respective cover across large environmental gradients and ecotones often associated with semi-arid ecosystems. Optimal endmember selection and …

Predicting Northern Bobwhite Habitat In Semiarid Rangeland Using Landsat Imagery, Jeffrey G. Whitt, Kelly S. Reyna

National Quail Symposium Proceedings

Multiple studies have attempted to model northern bobwhite (Colinus virginianus) distribution using classified remotely sensed imagery in combination with pattern recognition software. These models tend to be more accurate in humid subtropical regions. To identify bobwhite habitat in subhumid and semiarid rangeland, we performed our own classification on 4 LANDSAT scenes of Clay County, Texas, from July and December 2015. Stands of mature little bluestem (Schizachyrium scoparium) provide excellent bobwhite nesting cover and could be identified using LANDSAT imagery. Habitat was scored from 0 to 1.0 based on estimated range health, presence of little bluestem, and …

Evaluation Of Modis Land Surface Temperature Data To Estimate Near-Surface Air Temperature In Northeast China, Yuan Z. Yang, Wen H. Cai, Jian Yang

Forestry and Natural Resources Faculty Publications

Air temperature (T_air) near the ground surface is a fundamental descriptor of terrestrial environment conditions and one of the most widely used climatic variables in global change studies. The main objective of this study was to explore the possibility of retrieving high-resolution T_air from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products, covering complex terrain in Northeast China. The All Subsets Regression (ASR) method was adopted to select the predictors and build optimal multiple linear regression models for estimating maximum (T_max), minimum (T_min), and mean (T_mean) air temperatures. …