Analyzing of Morphometric Parameters and Designing of Thematic Maps Using Raster Geoprocessing Tool

The quality of landslide susceptibility assessment is effected by landslide inventory and raster resolution.The point landslide inventory and polygon landslide inventory are usually two spatial representations. In order to explore the effect of spatial representation and raster resolution on the assessment result of landslide susceptibility, two spatial representations (point and polygon) in landslide inventory map and four raster resolution (25m, 50m, 75m and 100m) were introduced in the landslide susceptibility model. A total of 489 landslides with accurate boundary information were obtained in Wanzhou District, Chongqing, China. Five geo-environmental predictors and random forest model as a data-driven model were used in the landslide susceptibility assessment. The research results demonstrate that (i) For two spatial representations, the prediction performance of polygon models was higher than that of point models by comparing reliability and accuracy. (ii) For four different raster resolution, the good prediction performance occurred in the 25m model. (iii) Through the analysis of model robustness, the lowest uncertainty was the 25m resolution model, which has more stable prediction performance. The research is useful for selecting the raster resolution and spatial representations in the data-driven landslide susceptibility assessment.

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Predicting copper-polymetallic deposits in Kalatag using the weight of evidence model and novel data sources

Xi,

Ping,

Tao

et al. 2023

Open Geosciences

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The Kalatag Ore Cluster Area, located in the Eastern Tianshan metallogenic belt of Xinjiang, stands out as a notable copper polymetallic mineralization zone, recognized for its diverse ore types and untapped potential. Despite the foundational nature of traditional exploration methods, they have not fully exploited this potential. Addressing this, our study leverages modern geospatial technologies, especially ArcGIS, combined with multi-source geoscience data to refine ore formation predictions in Kalatag. We identified key ore-controlling factors: the ore-bearing strata of Daliugou and Dananhu Groups, buffer zones around faults and intrusions, and geophysical anomalies. From these, a conceptual model was developed using the weight of evidence model. This model pinpointed four ‘A’ class and three ‘B’ class targets for mineral exploration, highlighting the central role of faults in ore control. Significantly, all known ore deposits were encompassed within these targets. Our approach not only paves the way for improved ore prediction in Kalatag but also offers a blueprint for other mineral-rich areas. Merging traditional geology with advanced technology, we elevate mineral exploration’s precision, emphasizing the synergy of an integrated method, especially in geologically complex areas. The effectiveness of our model provides insights for future exploration, particularly in mining areas’ deeper zones.

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Analyzing of Morphometric Parameters and Designing of Thematic Maps Using Raster Geoprocessing Tool

Cited by 8 publications

References 11 publications

Development of Geoprocessing Tool for Wet Gap Crossing in Military Operations

Development of Geoprocessing Tool for Wet Gap Crossing in Military Operations

Effect of landslide spatial representation and raster resolution on the landslide susceptibility assessment

Predicting copper-polymetallic deposits in Kalatag using the weight of evidence model and novel data sources

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