Underground water enrichment assessment method based on remote sensing information

Abstract

The invention relates to an underground water enrichment assessment method based on remote sensing information. The method comprises the following steps of: extracting formation lithology, fracture density, surface temperature, soil humidity, vegetation coverage and water-area density from multispectral data, and extracting topographic slope, geomorphic type and flow accumulation as secondary assessment indexes from DEM (Digital Elevation Model) data, wherein the formation lithology and the fracture density constitute a primary assessment index occurrence space, the surface temperature, the soil humidity and the vegetation coverage constitute a primary assessment index surface indication, and the topographic slope, the geomorphic type, the flow accumulation and the water-area density constitute a primary assessment index supplementing condition; and determining the weight of each assessment index, carrying out normalization treatment on all weights, and then carrying out weighted averaging on the assessment indexes so as to obtain an underground water assessment index for assessing the enrichment of underground water. The method can be applied to a wider area range; and the reliability of underground water enrichment assessment is improved.

Description

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AI Technical Summary

Benefits of technology

This patented technology allows for better understanding about soil properties through remotely monitoring data from underground environments such as rivers or lakes. By analyzing these signals along different stages of excavation, we aimed at providing reliable evaluative indices that reflect both geology and hydraulics factors affecting sediment accumulation rates. Overall, this system enhances environmental safety measures related to land use planning (LCA).

Problems solved by technology

Technological Problem: Existing methods involve evaluating various aspects associated with soil quality such as permafrost depth or hydraulics near slopings. These techniques require specific assumptions about how well different types of materials can exist within their environment. They also lack generalization ability due to limitations like limited applicability and poorly understood geology characteristics.

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