This was a mixed-method user-centered study regarding the University of North Texas's student-owned learner record and credentialing system. Through methods of quantitative and qualitative inquiry, student perceptions were unearthed and recommendations to improve the system were provided.

This study implemented a GIS-based analysis of local climate zones (LCZ) in Denton, TX with data sets from 2009, 2011, 2015, and 2016. The LCZ scheme enables evaluation of distinct regions' thermal characteristics with greater granularity than conventional urban-rural dichotomies. Further, the GIS-based approach to LCZ mapping allows use of high-resolution lidar data, the availability of which for the study area enabled estimation of geometric and surface cover parameters: height of roughness elements, sky-view factor, and building surface fraction. Pervious surface fraction was estimated from National Landcover Database impervious imagery. A regular grid was used to estimate per-cell mean values for each parameter, and with a decision-making algorithm (if/then statements) two maps were produced (2011 and 2015) and six LCZ identified in each: LCZ 6 (open low-rise), LCZ 8 (large low-rise), LCZ 9 (sparsely built), LCZ A (dense trees), LCZ B (scattered trees), and LCZ C (bush/scrub). Post-processing was carried out to ensure identified zones met the spatial minimum for qualification as LCZ. Landsat Collection 2 Level 2 surface temperature products from various seasons of 2011 and 2015 were acquired to examine LCZ thermal differentiability, and preliminary surface urban heat island intensity values were estimated. Particular attention was afforded to …

Due to inadequate long-term and large-scale observation approach for observation of soil moisture across the globe, this study intends to unveil the importance of using simulated soil moisture fields from land surface models, forced with observed precipitation and near-surface meteorology in monitoring drought and formulating effective water management practices for continued production irrigation applications. This study shows that socio-economic and ecosystem effects can be determined by evaluating spatial-temporal changes in irrigation applications. Thus, it facilitates understanding of the importance of water management and how water, energy, and carbon flows protect our climate and environment. By using Soil Moisture Active Passive (SMAP) in monitoring soil moisture, the information obtained is critical in providing early drought warnings, particularly in those parts of the United States that experience flash agricultural droughts. Further, this study highlights that frequent and reliable soil moisture measurements from SMAP helped improve the predictive capability of weather and climate models.