Abstract
AbstractThe New Madrid Seismic Zone (NMSZ) has historically recorded some of the largest intensity earthquakes in North America, including significant earth movements that resulted in about 2000 felt earthquakes during 1811–1812. The region continues to experience mass wasting due to earth movements. The aim of this study is to understand the influence of geologic variables on mass wasting processes in the greater Cape Girardeau area, which forms the commercial center of Missouri's fertile "Bootheel" region. Earth movement susceptibility was evaluated in Cape Girardeau and Bollinger counties and portions of Stoddard and Scott counties by mapping potential landslide features on topographic maps, field verification of such features, and geospatial analysis of recent LiDAR imagery. In order to evaluate the changes in surface morphology, slope inclination, hillshade aspect, hydrology, lithology, faults, precipitation, seismicity, sinkholes, and geohydrology were considered. Geographically weighted analysis of the geomorphologic variables identified zones of relative risk. In addition, data were evaluated for oil and gas pipelines, bridges, utilities, and open pit mines associated with mass wasting on public and economic infrastructure. The results suggest that anthropogenic changes commonly associated with urban development impact land use, runoff, infiltration, and slope failures, while sustained precipitation and seismic ground shaking tend to trigger landslides. The scale of mass wasting in the study area was robust, varying from as small as one-half hectare to as much as 67 km2. The vulnerability of the population in susceptible areas tends to increase at the lower elevations and on alluvial flood plains. Thus, hazard susceptibility evaluation can be useful in both community planning as well as emergency preparedness.
Publisher
Springer Science and Business Media LLC
Subject
Earth-Surface Processes,Geology,Pollution,Soil Science,Water Science and Technology,Environmental Chemistry,Global and Planetary Change
Reference47 articles.
1. Ashraf I, Zhao Z, Bourque C, Meng F (2012) GIS-evaluation of two slope-calculation methods regarding their suitability in slope analysis using high-precision LiDAR digital elevation models. Hydrol Process 26:1119–1133. https://doi.org/10.1002/hyp.8195
2. Balazy R, Kaminska A, Ciesielski M, Socha J, Pierzchalski M (2019) Modeling the effect of environmental and topographic variables affecting the height increment of Norway Spruce stands in mountainous conditions with the use of LiDAR data. Remote Sens 11(20):2407. https://doi.org/10.3390/rs11202407
3. Bansa KJ (2018) Imaging and mitigating karst features. Doctoral Dissertations 2666. Missouri University of Science Technology http://scholarsmine.mst.edu/doctoral_dissertations/2666. Accessed 16 Feb 2020
4. Cao Z (2016) Improving the accuracy and the efficiency of geo-processing through a combinative geo-computation approach. Doctoral thesis, UCL (University College London)
5. Carrar A, Cardinali M, Guzzetti F (1995) Reichenbach P (1995) GIS technology in mapping landslide hazard. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer Academic Publisher, Dordrecht, pp 135–175
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献