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首页> 外文期刊>Environmental & Engineering Geoscience >Using GIS-Based Spatial Analysis to Determine Factors Influencing the Formation of Sinkholes in Greene County, Missouri
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Using GIS-Based Spatial Analysis to Determine Factors Influencing the Formation of Sinkholes in Greene County, Missouri

机译:基于GIS的空间分析,确定了密苏里州绿色县下沉孔形成的因素

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摘要

Sinkholes are inherent features of the karst terrain of Greene County, Missouri, that present hazards and engineering challenges to construction/infrastructure development. Analysis of relationships between the spatial distribution of sinkholes and possible influencing factors can help in understanding the controls involved in the formation of sinkholes. The spatial analysis outlined herein can aid in the assessment of potential sinkhole hazards. In this research, Geographic Information System-based ordinary least squares regression (OLS) and geographically weighted regression (GWR) methods were used to determine and evaluate principal factors appearing to influence the formation and distribution of karst sinkholes. From the OLS result, seven out of 12 possible influencing factors were found to exert significant control on sinkhole formation processes in the study area. These factors are overburden thickness, depth to groundwater, slope of the ground surface, distance to the nearest surface drainage line, distance to the nearest geological structure (such as faults or folds), distance to the nearest road, and distance to the nearest spring. These factors were then used as independent variables in the GWR model. The GWR model examined the spatial non-stationarity among the various factors and demonstrated better performance over OLS. GWR model coefficient estimates for each variable were mapped. These maps provide spatial insights into the influence of the variables on sinkhole densities throughout the study area. GWR spatial analysis appears to be an effective approach to understand sinkhole-influencing factors. The results could be useful to provide an objective means of parameter
机译:下沉是密苏里州格林县喀斯特地形的内在特点,对建筑/基础设施开发提供危险和工程挑战。下沉孔的空间分布与可能影响因素之间的关系分析有助于了解涉及污水孔的形成的控制。本文所述的空间分析可以有助于评估潜在的污水孔危害。在该研究中,基于地理信息系统的普通最小二乘回归(OLS)和地理加权回归(GWR)方法来确定和评估出现的主要因素影响喀斯特下沉孔的形成和分布。从OLS结果中,发现了12种可能的影响因素的7种可能对研究区域中的污水孔形成过程发挥了重要控制。这些因素是覆盖层厚度,深度到地下水位,地面坡度,距离最近的表面排水线,距离到最近的地质结构(如故障或折叠),距离最近的道路,距离到最近的春天。然后将这些因素用作GWR模型中的独立变量。 GWR模型在各种因素中检测了空间非公平性,并表现出更好的OLS性能。每个变量的GWR模型系数估计映射。这些地图为整个研究区域的污水孔密度对变量的影响提供了空间洞察。 GWR空间分析似乎是理解污水池影响因素的有效方法。结果可能有助于提供目标参数

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