Identifying hotspots and classifying the spatial distribution pattern of karst collapse pillars with Moran’s index in coal mine

Identifying hotspots and classifying the spatial distribution pattern of karst collapse pillars with Moran’s index in coal mine

Identifying hazardous karst collapse pillars (KCPs) is critical for ensuring safe coal mining operations. While previous studies have focused primarily on physical detection, the spatial clustering characteristics of KCPs have often been overlooked. This study proposes a spatial hotspot identificati...

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Bibliographic Details
Main Authors: Junsheng Yan, Zaibin Liu, Hui Yang, Lin An, Wei Li, Tiantian Wang, Qian Xie, Chenguang Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Earth Science
Subjects:
morphological characteristics
geographic information system
coordinate calibration
spatial distribution index
development patterns
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2025.1593432/full
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Summary:Identifying hazardous karst collapse pillars (KCPs) is critical for ensuring safe coal mining operations. While previous studies have focused primarily on physical detection, the spatial clustering characteristics of KCPs have often been overlooked. This study proposes a spatial hotspot identification method based on Moran’s index and applies it to the Wangpo Coal Mine in Shanxi, China. The method integrates morphological feature analysis of KCPs with a combined weighting scheme using the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM). A spatial distribution index (SDI) was constructed through geographic information system (GIS) overlay analysis and spatial coordinate calibration. Global Moran’s I (0.1110, p < 0.05) indicates a statistically significant positive spatial autocorrelation of KCP distribution. Local Moran’s I further reveals 11 spatially significant KCPs, including 5 high-high clusters. Geological interpretation shows that these high-risk KCPs are predominantly located near the intersections of faults and folds, highlighting the structural control on KCP formation. The proposed method provides a quantitative and spatially interpretable approach for KCP risk identification and has potential for application to other geohazards exhibiting spatial aggregation patterns.
ISSN:2296-6463

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