Authors: Tarek Kandakji*, Texas Tech University, Jeff Lee, Texas Tech University, Junran Li, University of Tulsa, Tom Gill, University of Texas at El Paso
Topics: Geomorphology, Earth Science, Soils
Keywords: aeolian, GIS, spatiotemporal, dust, remote sensing
Session Type: Paper
Start / End Time: 2:40 PM / 4:20 PM
Room: Oakley, Sheraton, 4th Floor
Presentation File: No File Uploaded
Dust point sources were identified in a previous study using remote sensing data. However, the spatio-temporal analysis of these points have yet to be investigated. In this study, we conducted an extensive spatio-temporal point pattern analysis of identified dust point sources in Southwestern U.S. The study area covers northwestern Texas, eastern New Mexico, western Oklahoma, southwestern Kansas, and southeastern Colorado. In addition to cluster analysis, a complete spatial randomness (CSR) analysis is conducted, and accordingly we estimated the k-function, F-function, G-function and J-function. To determine the frequency of dust events, time series analysis is conducted. Afterwards, the spatio-temporal analysis is coupled with land use and geomorphology maps in order to reach a better understanding of dust point hot spots.