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CN-121982362-A - Geological disaster detection method and related equipment

CN121982362ACN 121982362 ACN121982362 ACN 121982362ACN-121982362-A

Abstract

The application discloses a geological disaster detection method and related equipment. The method comprises the steps of obtaining a target image acquired for a target area and a reference image of the target area, wherein the reference image can represent the state of the target area under the condition that no geological disaster occurs, comparing the reference image with the target image to obtain an image comparison result, and detecting by utilizing the topographic model data of the target area and the target image in response to the image comparison result meeting the area abnormal condition to obtain a geological disaster detection result of the target area. According to the scheme, accuracy of geological disaster detection can be improved.

Inventors

  • HUANG XINYU

Assignees

  • 浙江大华技术股份有限公司

Dates

Publication Date
20260505
Application Date
20251215

Claims (15)

  1. 1. A method for detecting a geological disaster, comprising: Acquiring a target image acquired from a target area and a reference image of the target area, wherein the reference image can represent the form of the target area under the condition that no geological disaster occurs; comparing the reference image with the target image to obtain an image comparison result; and responding to the image comparison result to meet the regional abnormal condition, and detecting by utilizing the terrain model data of the target region and the target image to obtain a geological disaster detection result of the target region.
  2. 2. The method according to claim 1, wherein the detecting using the terrain model data of the target area and the target image to obtain the geological disaster detection result of the target area comprises: determining a terrain factor by using the terrain model data; extracting features of the target image to obtain first image features; fusing the first image feature and the topographic factors to obtain a fused feature; And detecting by utilizing the fusion characteristics to obtain a geological disaster detection result of the target area.
  3. 3. The method of claim 2, wherein fusing the first image feature and the terrain factor to obtain a fused feature comprises: Generating modulation parameters by using the terrain factors; and modulating the first image feature by using the modulation parameter to obtain a fusion feature.
  4. 4. A method according to claim 3, wherein said generating modulation parameters using said terrain factors comprises: Carrying out convolution processing on the terrain factors to obtain a first convolution characteristic; Activating the first convolution feature or the normalization result of the first convolution feature to obtain an activation feature; Convolving the activation characteristic to obtain a modulation parameter, wherein the modulation parameter comprises a scaling factor and/or an offset factor; Modulating the first image feature by using the modulation parameter to obtain a fusion feature, including: and weighting the first image features by using a scaling factor and/or adding the first image features by using an offset factor to obtain fusion features.
  5. 5. The method according to claim 2, wherein the detecting using the fusion feature to obtain a geological disaster detection result of the target area includes: Extracting multi-scale features from the fusion features, and fusing the multi-scale features to obtain first processing features; Performing attention processing on the first processing feature to obtain a second processing feature; And detecting by using the second processing characteristics to obtain a geological disaster detection result of the target area.
  6. 6. The method of claim 5, wherein the detecting using the second processing feature to obtain a geological disaster detection result of the target area comprises: performing stitching processing on the second processing feature and the second image feature to obtain stitching features, wherein the second image feature is obtained based on the target image; performing depth separable convolution processing on the spliced features to obtain predicted features; And detecting by using the prediction characteristics to obtain a geological disaster detection result of the target area.
  7. 7. The method of claim 5, wherein the extracting multi-scale features from the fused features comprises: carrying out multi-scale cavity convolution processing on the fusion characteristics to obtain multi-scale characteristics; and/or, the fusing the multi-scale features to obtain a first processed feature, including: Determining a weighting parameter using the multi-scale feature; weighting the multi-scale features by using the weighting parameters to obtain first processing features; And/or, performing attention processing on the first processing feature to obtain a second processing feature, including: performing first attention processing on the first processing feature to obtain an attention feature; And performing second attention processing on the attention characteristics to obtain second processing characteristics, wherein one of the first attention processing and the second attention processing is channel attention processing, and the other is space attention processing.
  8. 8. The method of claim 2, wherein the step of determining the position of the substrate comprises, The terrain factors include at least one of slope, slope direction and terrain relief; And/or, the determining the terrain factor by using the terrain model data comprises at least one of the following steps: Gradient information of the terrain model data is obtained; Performing first processing on the gradient information to obtain a gradient; performing second processing on the gradient information to obtain a slope direction; and determining a maximum value and a minimum value from each neighborhood range of the terrain model data, and obtaining the terrain fluctuation degree by utilizing the difference value of the maximum value and the minimum value.
  9. 9. The method of claim 1, wherein said comparing said reference image to said target image results in an image comparison result comprising: and comparing the preset environmental elements in the target image and the reference image to obtain difference information of the preset environmental elements, and taking the difference information as the image comparison result.
  10. 10. The method of claim 9, wherein the predetermined environmental elements comprise vegetation indexes, and the comparing the predetermined environmental elements in the target image and the reference image to obtain difference information of the predetermined environmental elements comprises: respectively acquiring vegetation indexes of the target image and the reference image to obtain a first vegetation index and a second vegetation index; obtaining a difference value between the first vegetation index and the second vegetation index to obtain an index difference value; wherein the regional abnormality condition includes a reduction condition that the index difference satisfies the target image with respect to a preset environmental element in the reference image.
  11. 11. The method as recited in claim 1, further comprising: determining that the geological disaster detection result of the target area is that the geological disaster does not occur according to the image comparison result which does not meet the regional abnormal condition; And/or, the comparing the reference image with the target image, before obtaining an image comparison result, includes: respectively acquiring feature descriptors of feature points of the target image and the reference image; matching each characteristic point of the target image and the reference image by using the characteristic descriptors, and screening out initial matching point pairs; removing initial matching point pairs which do not meet the matching conditions by using a preset sampling inspection algorithm to obtain target matching point pairs; And registering the target image and the reference image by utilizing the target matching point pairs to obtain registered target image and reference image.
  12. 12. The method of claim 11, wherein registering the target image and the reference image using the target matching point pair, after obtaining the registered target image and reference image, comprises: resampling the registered target image or reference image to obtain a resampled target image or reference image, and/or And responding to the matching error index being smaller than a preset index threshold value, determining that the target matching point pair meets the registration condition.
  13. 13. A computer device comprising a memory and a processor coupled to each other, the memory having stored therein program data, the processor being configured to execute the program data to implement the method of detecting a geological disaster according to any one of claims 1 to 12.
  14. 14. A computer-readable storage medium, characterized in that program data executable by a processor for implementing the geological disaster detection method according to any one of claims 1 to 12 are stored.
  15. 15. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the method of detecting a geological disaster according to any one of claims 1 to 12.

Description

Geological disaster detection method and related equipment Technical Field The application relates to the technical field of geological disaster prediction, in particular to a geological disaster detection method and related equipment. Background In nature, geological disasters have the characteristics of strong burst and large destructive power, the occurrence of the geological disasters can seriously affect ecological environment, infrastructure and the like, and the geological disasters need to be detected so as to carry out emergency treatment in advance. At present, the geological disaster detection method is mostly based on single image visual analysis for detection, but is easily interfered by actual environment, so that normal variation of the geological disaster and the natural environment is difficult to distinguish, the misjudgment rate is high, and the detection precision and efficiency are difficult to meet the actual application requirements. Therefore, there is a need for a geologic hazard detection scheme that can improve detection efficiency or accuracy. Disclosure of Invention The application mainly solves the technical problem of providing a geological disaster detection method and related equipment, which can improve the accuracy of geological disaster detection. The first aspect of the application provides a geological disaster detection method, which comprises the steps of obtaining a target image acquired for a target area and a reference image of the target area, wherein the reference image can represent the form of the target area under the condition that the geological disaster does not occur, comparing the reference image with the target image to obtain an image comparison result, and detecting by utilizing the topographic model data of the target area and the target image in response to the image comparison result meeting the area abnormal condition to obtain a geological disaster detection result of the target area. In a second aspect, the present application provides a computer device, which includes a memory and a processor coupled to each other, where the memory stores program data, and the processor is configured to execute the program data to implement the method for detecting a geological disaster. A third aspect of the present application provides a computer-readable storage medium storing program data executable by a processor for implementing the above-described geological disaster detection method. A fourth aspect of the application provides a computer program product comprising a computer program which, when executed by a processor, implements the method of detecting a geological disaster as described above. According to the scheme, the target image acquired for the target area and the reference image of the target area are acquired, the reference image can represent the form of the target area under the condition that no geological disaster occurs, the reference image and the target image are compared to obtain the image comparison result, the fact that the demonstration of the target area is abnormal can be quickly determined, the image comparison result meets the area abnormal condition, the terrain model data of the target area and the target image are combined for further detection to obtain the geological disaster detection result of the target area, the change information of the image and the spatial feature information of the terrain are fully fused, the misjudgment and missed judgment problems possibly caused by the single dependent image or the terrain data are effectively avoided, the accuracy and the reliability of geological disaster detection are remarkably improved, the detection process is firstly screened for the abnormal area, and then the detection efficiency and the detection accuracy are accurately verified. By comparing the reference image of the target area when no geological disaster occurs with the currently acquired target image, a clear direction is provided for the subsequent accurate detection, and the target area is further detected by combining with the topographic model data, It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed. Drawings In order to more clearly illustrate the technical solutions of the present application, the drawings required in the description of the embodiments will be briefly described below, it being obvious that the drawings described below are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein: FIG. 1 is a flow chart of a first embodiment of a method for detecting a geological disaster according to the present application; FIG. 2 is a flow chart of a first embodiment of a method for detecting a geological disaster according to the present ap