CN116580532A - Geological disaster early warning system based on radar remote sensing technology - Google Patents
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Abstract
The application discloses a geological disaster early warning system based on a radar remote sensing technology, and belongs to the technical field of geological disaster monitoring. The system comprises a data acquisition module, a data processing module, a data analysis module, a disaster evaluation module and an early warning monitoring module. The data acquisition module is used for acquiring various data required by geological disaster monitoring; the data processing module is used for carrying out operations such as preprocessing, time sequence InSAR processing, intelligent interpretation and the like on the multi-temporal remote sensing image data; the data analysis module is used for integrating the day-air-ground multisource monitoring data to analyze and reflect the distribution characteristics and the disaster degree of geological disasters; the disaster evaluation module is used for performing risk evaluation on hidden danger points of the key areas; the early warning monitoring module is used for carrying out real-time dynamic monitoring early warning on the key areas; the application integrates the space-air-ground integrated monitoring means, realizes more flexibility and timeliness of the monitoring means, has more accurate and reliable monitoring results, and provides scientific basis for relevant departments to develop disaster prevention, disaster reduction and disaster relief work.
Description
Technical Field
The application belongs to the technical field of geological disaster monitoring, and particularly relates to a geological disaster early warning system based on a radar remote sensing technology.
Background
The hilly area of the Chinese mountain land accounts for 65 percent of the area of the national land, the geological conditions are complex, the construction activities are frequent, the sudden geological disaster points such as collapse, landslide, mud-rock flow and the like are wide in multiple surfaces, and the prevention difficulty is high.
More than 70% of these geological disasters that lead to catastrophic consequences are not within the known geological disaster risk, mainly because: the upper middle part of the mountain at the disaster source area is rarely reached, most areas are covered by vegetation, the high-level and hidden characteristics are realized, the traditional manual investigation and group detection group prevention cannot be realized before the disaster, and the hidden danger of the disaster is difficult to discover in advance by the traditional means. Therefore, how to discover and effectively identify the potential hidden trouble of the serious geological disaster in advance and actively prevent and control the serious hidden trouble has become a focus and difficulty of concentrated attention in the field of recent geological disaster prevention and control. The remote sensing technology has the characteristics of quick information acquisition, short period, large information quantity, less condition limitation and the like, and particularly the synthetic aperture radar remote sensing technology can detect millimeter-level earth surface deformation and has incomparable advantages in the geological disaster early warning and monitoring work. The remote sensing technology is utilized to rapidly acquire remote sensing image data of a target area, and information such as disaster conditions, disaster development change trend, disaster loss profile and the like can be comprehensively mastered through analysis and processing, so that data support is provided for administrative command decision and disaster loss evaluation, and the remote sensing image data processing method is an important technical means for completing disaster reduction and relief work.
The reasons for inducing the geological disasters are not only natural factors but also human factors, the occurrence of the geological disasters is regular and circulated, the situation of the geological disaster points is monitored, the occurrence probability of the geological disasters is predicted scientifically, and the alarm is fast given after the occurrence of the geological disasters, so that the loss of people can be saved to the greatest extent. Under the background, modern technological strength is fully utilized, theoretical knowledge of multiple disciplines is integrated, a geological disaster monitoring and early warning system is designed and developed by combining multiple departments, and all-weather monitoring is carried out on a heavy geological disaster area. Once the hidden danger of the geological disaster is found, an alarm is immediately given, so that an emergency rescue and relief scheme is established as early as possible, the loss of the geological disaster is reduced, and the life and property safety of people is protected to the greatest extent.
At present, the early warning of the geological disasters is usually carried out in a field investigation mode, so that the method is time-consuming, labor-consuming and high in cost, and is difficult to meet the requirement of large-area dynamic investigation of the geological disasters, especially the geological disaster information of the geological environment complex areas such as high mountain canyons, high altitudes, high coldness and the like which are behind traffic is difficult to obtain; in addition, geological disaster early warning is simply based on a synthetic aperture radar technology or a high-resolution remote sensing technology, accurate disaster information is difficult to obtain based on a single technology, and monitoring results are unilateral and unreliable; based on the method, the method carries out early identification of major geological disaster hidden dangers by constructing a three-check system integrating space, air and ground, and carries out real-time early warning and forecasting of the geological disaster on the basis of grasping dynamic development rules and characteristics of the geological disaster by professional monitoring, so as to solve the difficult problem and the urgent national demand in the geological disaster prevention and treatment field, namely ' where the hidden dangers are and ' when the hidden dangers are likely to occur '.
SUMMARY OF THE PATENT FOR INVENTION
In view of the above, the application builds a geological disaster early warning system based on a radar remote sensing technology based on a three-check system of the integration of space, space and ground. The system integrates the technologies of optical remote sensing, synthetic aperture radar, unmanned aerial vehicle, laser radar, ground internet of things sensing and the like, combines the related early warning and monitoring model, establishes a grading comprehensive early warning system, utilizes the geological disaster real-time monitoring and early warning system to gradually realize practical and business operation of geological disaster monitoring and early warning, and has higher scientific significance and practical value.
The technical scheme adopted by the application is as follows:
a geological disaster early warning system based on a radar remote sensing technology comprises a data acquisition module, a data processing module, a data analysis module, a disaster evaluation module and an early warning and monitoring module.
The data acquisition module is used for acquiring space-based data, foundation data and related data required by geological disaster monitoring of a target area, wherein the space-based data comprises synthetic aperture radar remote sensing image data and high-resolution remote sensing image data, the related data comprises ground elevation data, topographic data and meteorological data, the space-based data comprises unmanned aerial vehicle data and laser radar data, and the foundation data comprises ground internet of things sensor monitoring data.
The data processing module is used for performing data processing on the space-based data, the air-based data and the foundation data acquired by the data acquisition module to acquire remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results and ground internet of things sensor monitoring results of the target area.
The data analysis module is used for combining remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results, ground internet of things sensor monitoring results, ground elevation data, topographic data and meteorological data, performing space superposition analysis, buffer area analysis and three-dimensional model analysis to obtain geological disaster characteristics, and extracting geological disaster hidden danger points of key areas.
The disaster evaluation module adopts a qualitative risk evaluation method to perform risk evaluation on geological disaster hidden danger points of the key areas before geological disasters occur, so as to obtain evaluation results of geological disaster risk grades of the key areas; and after the geological disaster occurs, analyzing pre-disaster high-resolution remote sensing image data and post-disaster unmanned aerial vehicle images through comparison, combining with the geographical national condition census data, and carrying out rapid evaluation on the disaster-affected area by fusing the post-disaster evaluation model.
The early warning and monitoring module combines the evaluation result of the geological disaster risk level of the key area to dynamically monitor the geological disaster hidden danger point of the key area in real time, reflects the state of disaster condition by combining meteorological data and ground internet of things sensor monitoring data with a ground disaster early warning model, receives disaster early warning information and generates the geological disaster influence level according to the early warning information.
In the technical scheme, in the disaster evaluation module, the requirement on the timeliness of the disaster area evaluation after the occurrence of the geological disaster is high, the space-based remote sensing image data cannot be timely acquired, and the timeliness of the unmanned aerial vehicle data is high in operability, so that the disaster area can be accurately and quickly evaluated by adopting the pre-disaster high-resolution remote sensing image data and the post-disaster unmanned aerial vehicle data for comparison and analysis.
Further, the processing procedure of the data processing module for acquiring data includes:
the remote sensing image monitoring result acquisition module comprises: performing atmospheric correction, radiation correction, geometric correction, image mosaic cutting and image fusion pretreatment on the synthetic aperture radar remote sensing image data and the high-resolution remote sensing image data; performing time sequence InSAR processing on the preprocessed synthetic aperture radar remote sensing image to obtain a target area earth surface deformation result, and performing intelligent interpretation operation on the high-resolution remote sensing image to obtain a geological disaster interpretation result;
unmanned aerial vehicle and laser radar monitoring result acquisition module: performing data processing on unmanned aerial vehicle data and laser radar data and generating a target area three-dimensional model;
the ground internet of things sensor monitoring result acquisition module: and (3) processing and obtaining results of soil humidity, soil pressure, surface vegetation coverage, thickness of loose deposit, distribution and the like of the target area according to geological parameter data monitored by the ground internet of things sensor.
Further, the data analysis module is used for combining remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results, ground internet of things sensor monitoring results, ground elevation data, topographic data and meteorological data, performing space superposition analysis, buffer area analysis and three-dimensional model analysis to obtain geological disaster characteristics, and extracting geological disaster hidden danger points of key areas, and mainly comprises the following steps:
step 1: performing large-scale general investigation on geological disaster hidden dangers of a target area according to the earth surface deformation result obtained by processing the synthetic aperture radar remote sensing image and the intelligent interpretation result of the high-resolution remote sensing image, and preliminarily determining geological disaster hidden dangers;
step 2: performing small-range detailed investigation on the initially determined geological disaster hidden danger points by using unmanned plane data and laser radar data, and performing disaster feature recognition and confirmation by combining a target area three-dimensional model to further determine the geological disaster hidden danger points, and analyzing and evaluating the stability, the harmfulness and the development trend of the geological disaster hidden danger points;
step 3: and (3) carrying out ground checking on the geological disaster hidden danger points determined in the step (2) by combining ground internet of things sensor real-time monitoring data, accurately analyzing disaster characteristics, causes, ranges and influence results of the geological disaster hidden danger points through the technologies of space superposition analysis, buffer area analysis, three-dimensional model analysis and the like, analyzing and judging the development degree of the geological disaster hidden danger points, and extracting the geological disaster hidden danger points of key areas.
Further, the early warning and monitoring module mainly comprises: performing disaster early warning and monitoring on the key areas based on the geological disaster hidden danger key areas obtained through processing analysis and evaluation by combining with meteorological data and ground real-time monitoring data, predicting the occurrence level of geological disasters according to a prediction alarm model and comprehensive geological disaster sensitivity index and rainfall induction index and combining with a preset alarm threshold value, analyzing and estimating geological structures, topography and landforms of geological disaster points, main hidden dangers, probability of occurrence of the geological disasters and the like by utilizing the geological disaster prediction alarm model, and sending early warning according to analysis results;
further, the wide-range census mainly includes: the method comprises the steps of selecting, processing and analyzing the data of the synthetic aperture radar remote sensing image by collecting the synthetic aperture radar remote sensing image, the synthetic aperture radar remote sensing image parameters and the synthetic aperture radar remote sensing image orbit information of a target area, obtaining the screening of the surface deformation characteristics of hidden danger points, and primarily screening and confirming hidden danger points with obvious deformation characteristics;
meanwhile, high-resolution remote sensing images of hidden danger sections of nearly 3-5 years are collected, geological disaster intelligent interpretation is carried out on the high-resolution remote sensing images, and hidden danger points with geological disasters are confirmed through preliminary screening by combining InSAR deformation monitoring results.
Further, the concrete construction method of the geological disaster early warning model comprises the following steps:
firstly, subdividing a prediction area map into a plurality of 1km multiplied by 1km cells, and respectively calculating a geological disaster sensitivity index Z and a rainfall induction index R of each cell, thereby determining a prediction alarm index H, and predicting the probability of occurrence of geological disasters. The predictive alarm index H is calculated as follows:
H＝Z×R
and performing superposition analysis by combining the meteorological data and the predictive alarm index, thereby establishing a geological disaster predictive early warning model. The geological disaster occurrence grade set early warning colors are sequentially set to be blue, green, yellow, orange and red according to the light and medium degrees;
in summary, compared with the prior art, the application has the following beneficial effects:
according to the application, the data acquisition module is used for acquiring data of the space foundation, the air foundation, the foundation and the like, the data processing module is used for processing the acquired data, and the data analysis module is used for carrying out integrated analysis on the space-air-ground data, so that geological disaster hidden danger points of a key area are obtained, and pre-disaster early warning and post-disaster assessment can be respectively carried out on the geological disaster hidden danger points of the key area based on the disaster assessment module and the early warning monitoring module, so that scientific support is provided for geological disaster prevention and emergency rescue. The application integrates a space-air-ground integrated monitoring means, carries out early identification of major geological disaster hidden dangers, carries out real-time early warning and forecasting of geological disasters on the basis of grasping dynamic development rules and characteristics of the geological disasters through professional monitoring, and solves the difficult problem and the urgent national demand in the geological disaster prevention and treatment field that hidden dangers are located and the hidden dangers are likely to occur. The space-based remote sensing data has the advantages of wide monitoring range and abundant data quantity, the space-based unmanned aerial vehicle and the laser radar data have the advantages of good timeliness, high precision and the like, and the ground-based ground sensor monitoring data have the advantages of real-time dynamic update and the like, so that the application integrates a space-ground monitoring mode, realizes more flexibility and timeliness of a monitoring means, and has more accuracy and reliability of a monitoring result; and a related early warning monitoring model is combined, a grading comprehensive early warning system is established, practical and business operation of geological disaster monitoring and early warning is realized gradually, and the method has higher scientific significance and practical value.
Drawings
The application will now be described by way of example and with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of a geological disaster early warning system according to the present application;
FIG. 2 is a business flow diagram of the geological disaster early warning system of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
Examples
The embodiment of the application discloses a geological disaster early warning system based on a radar remote sensing technology, and the application is described in detail below with reference to fig. 1-2.
A geological disaster early warning system based on a radar remote sensing technology comprises a data acquisition module, a data processing module, a data analysis module, a disaster evaluation module and an early warning and monitoring module;
the data acquisition module is used for acquiring day-based data, space-based data, foundation data and related data required by geological disaster monitoring of a target area, wherein the day-based data comprises synthetic aperture radar remote sensing image data and high-resolution remote sensing image data, the related data comprises ground elevation data, terrain data and meteorological data, the space-based data comprises unmanned plane data and laser radar data, and the foundation data comprises ground internet of things sensor monitoring data;
the data processing module is used for performing data processing on the space-based data, the space-based data and the foundation data acquired by the data acquisition module to acquire remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results and ground internet of things sensor monitoring results of a target area;
the data analysis module is used for combining remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results, ground internet of things sensor monitoring results, ground elevation data, topographic data and meteorological data, performing space superposition analysis, buffer area analysis and three-dimensional model analysis to obtain geological disaster characteristics, and extracting geological disaster hidden danger points of key areas;
the disaster evaluation module adopts a qualitative risk evaluation method to perform risk evaluation on geological disaster hidden danger points of the key areas before geological disasters occur, so as to obtain evaluation results of geological disaster risk grades of the key areas; after the geological disaster occurs, the pre-disaster high-resolution remote sensing image data and post-disaster unmanned aerial vehicle images are compared and analyzed, and the post-disaster evaluation model is fused to rapidly evaluate the disaster-affected area by combining the geographical national condition census data;
the early warning and monitoring module combines the evaluation result of the geological disaster risk level of the key area to dynamically monitor the geological disaster hidden danger point of the key area in real time, reflects the state of disaster condition by combining meteorological data and ground internet of things sensor monitoring data with a ground disaster early warning model, receives disaster early warning information and generates the geological disaster influence level according to the early warning information.
In this embodiment, the data acquisition module mainly includes data acquisition such as space-air-ground; the space-based method comprises the steps of obtaining data of a synthetic aperture radar remote sensing image and a high-resolution optical remote sensing image; the space base comprises unmanned aerial vehicle oblique photogrammetry data and laser radar data acquisition; the foundation comprises real-time monitoring data of a ground internet of things sensor; in addition, the method also comprises the steps of obtaining ground elevation model data, meteorological data, topographic data, basic geographic information and other data; the synthetic aperture radar image is the first-number image data of the sentry of the C wave band, and the spatial resolution of the high-resolution optical remote sensing image data is better than 1m;
in this embodiment, the processing procedure of the data processing module to acquire data includes: performing preprocessing such as atmosphere correction, radiation correction, geometric correction, image mosaic cutting, image fusion and the like on the remote sensing image of the target area; performing time sequence InSAR processing and intelligent interpretation operation on the preprocessed image to obtain a large-scale earth surface deformation result and a ground disaster interpretation result of the target area; generating a three-dimensional model of the key area according to the unmanned aerial vehicle data and the laser radar data, and processing and acquiring results of soil humidity, soil pressure, surface vegetation coverage condition, thickness and distribution of loose deposit and the like of the key area according to geological parameter data monitored by ground internet of things sensing equipment;
in the embodiment, a pre-processed synthetic aperture radar image is subjected to time sequence InSAR processing mainly by adopting a differential interferometry short baseline set time sequence analysis technology (Small Baseline Subset InSAR, SBAS-InSAR), a sentinel first image orbit parameter file is utilized to remove a reference ellipsoid phase, a digital elevation model is utilized to remove a terrain phase, and a time-space domain filter is utilized to remove noise and an atmospheric phase, so that a target area earth surface deformation phase is obtained through time sequence calculation;
in this embodiment, the data analysis module mainly includes the following steps:
step 1: firstly, recognizing and determining the area which has been obviously deformed and destroyed and is being deformed in history by means of the earth surface deformation result and the optical remote sensing interpretation result obtained by InSAR processing, and realizing the general investigation of the hidden danger area and the scanning performance of serious geological disasters;
step 2: then, by means of airborne LiDAR and unmanned aerial vehicle aerial photography, the detail investigation of the high risk area of the geological disaster, the concentrated distribution area of hidden danger or the topography and topography of the hidden danger point of the serious geological disaster, the deformation damage signs of the earth surface, the rock mass structure and the like is carried out, the detail investigation of the hidden danger of the serious geological disaster is realized, the disaster feature recognition and confirmation are carried out, and the stability, the harmfulness and the development trend are primarily analyzed and evaluated;
step 3: finally, screening and confirming or eliminating general investigation and detailed investigation results through ground investigation and rechecking and observation of the ground surface and the inside of a slope, realizing the check of hidden danger of serious geological disasters, accurately analyzing disaster characteristics, causes, ranges and influence results of hidden danger points of the ground disasters through techniques such as space superposition analysis, buffer area analysis, three-dimensional model analysis and the like, and analyzing and judging the development degree of the hidden danger points;
in this embodiment, the disaster assessment module mainly includes: considering the liability, vulnerability and failure results of geological disaster hidden danger points of a key area, adopting a qualitative risk evaluation method to evaluate the risk of the hidden danger points of the key area, and giving out more specific risk condition evaluation; meanwhile, after the disaster occurs, combining the pre-disaster high-resolution remote sensing image, unmanned aerial vehicle data and an evaluation model, and rapidly evaluating disaster-affected conditions such as geological disaster scale, disaster-affected population, road and bridge houses and the like;
in this embodiment, the early warning monitoring module may dynamically monitor rainfall information, geological deformation information, soil parameters and other information of the geological disaster point, set a geological disaster warning threshold according to historical data, and if the comprehensive analysis result exceeds the threshold, immediately send early warning information to the relevant departments, and indicate the spatial position of the geological disaster point in a map display form; the specific system business flow is shown in figure 2;
the early warning monitoring module utilizes a geological disaster prediction alarm model to analyze and estimate geological structures, topography, main hidden dangers, probability of occurrence of geological disasters and the like of geological disaster points, and sends early warning according to analysis results. The method comprises the following specific steps:
step 1: and (3) data collection: the geological disaster monitoring and early warning system comprehensively collects key information of geological disaster points, including rainfall information, geological disaster incentive information, geological topography characteristics and the like, then utilizes a principal component analysis method to carry out integrated analysis on the data, determines the influence effectiveness of each factor according to analysis results, and finally uniformly sets the influence weights of each factor and determines main factors inducing the geological disasters;
step 2: risk assessment: the geological disaster monitoring and early warning system comprehensively analyzes rainfall information and other geological disaster incentive information, so that risk assessment of geological disasters is made. The risk assessment process includes dividing basic cells, operating cell geological factors, and obtaining decision support, wherein the concrete steps are as follows:
step 1: the evaluation cells are divided. The administrative division map was subdivided into evaluation cells of 2km×2km using a grid division method. The occurrence probability and the severity of geological disasters are mainly influenced by factors such as rainfall, geological conditions and the like. After a plurality of evaluation grids are drawn, disaster causing factors in each evaluation cell are comprehensively analyzed, the grade of each evaluation cell is determined by combining a geological disaster prediction alarm model, and colors corresponding to the grade are drawn, so that the prediction result of each evaluation cell can be clearly judged.
Step 2: and calculating the geological factors of the cells. In combination with common causes of geological disasters, the system of the embodiment incorporates 6 main disaster causing factors including rainfall, topography, human engineering activities, stratum lithology, surface soil layer thickness and geological structures, wherein rainfall information is acquired through a meteorological bureau, human engineering activity information is downloaded from a constructional bureau network, and the other four indexes are determined according to corresponding attribute conditions. The rainfall is a main factor for inducing the geological disaster, the probability of occurrence of the geological disaster is determined to a certain extent by the risk level of the rainfall, and for this purpose, the critical effective rainfall and the effective rainfall of each evaluation cell are comprehensively analyzed, and the risk level of the rainfall of each cell can be determined by comparison. And finally, comprehensively analyzing the geological disaster sensitivity index and the rainfall induction index, thereby determining the probability and the grade of geological disasters in different areas.
Step 3: and acquiring decision support. And according to the operation result, a geological disaster early warning prediction model is called to smear the colors corresponding to the early warning grades on each evaluation cell, so that the early warning result can be intuitively presented. And forecasting, analyzing and estimating the occurrence level of the geological disaster by combining a preset alarm threshold, sending out early warning according to the analysis result, and making an adaptive emergency treatment scheme by the functional department according to the early warning level so as to implement effective prevention and treatment measures as soon as possible for the areas with high risk level.
In this embodiment, the specific construction method of the geological disaster early warning model is as follows:
firstly, subdividing a prediction area map into a plurality of 1km multiplied by 1km cells, and respectively calculating a geological disaster sensitivity index Z and a rainfall induction index R of each cell, thereby determining a prediction alarm index H, and predicting the probability of occurrence of geological disasters. The predictive alarm index H is calculated as follows:
H＝Z×R
and performing superposition analysis on the meteorological data and the early warning alarm index by using a geographic information system, thereby establishing a geological disaster prediction early warning model. The geological disaster occurrence grade set early warning colors are sequentially set to be blue, green, yellow, orange and red according to the light and medium degrees;
in the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. The geological disaster early warning system based on the radar remote sensing technology is characterized by comprising a data acquisition module, a data processing module, a data analysis module, an early warning and monitoring module and a disaster evaluation module;
the data acquisition module is used for acquiring day-based data, space-based data, foundation data and related data required by geological disaster monitoring of a target area, wherein the day-based data comprises synthetic aperture radar remote sensing image data and high-resolution remote sensing image data, the related data comprises ground elevation data, terrain data and meteorological data, the space-based data comprises unmanned plane data and laser radar data, and the foundation data comprises ground internet of things sensor monitoring data;
the data processing module is used for performing data processing on the space-based data, the space-based data and the foundation data acquired by the data acquisition module to acquire remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results and ground internet of things sensor monitoring results of a target area;
the data analysis module is used for combining remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results, ground internet of things sensor monitoring results, ground elevation data, topographic data and meteorological data, performing space superposition analysis, buffer area analysis and three-dimensional model analysis on the results to obtain geological disaster characteristics, and extracting geological disaster hidden danger points of key areas;
the disaster evaluation module adopts a qualitative risk evaluation method to perform risk evaluation on geological disaster hidden danger points of the key areas before geological disasters occur, so as to obtain evaluation results of geological disaster risk grades of the key areas; after geological disasters occur, analyzing pre-disaster high-resolution remote sensing image data and post-disaster unmanned aerial vehicle images through comparison, combining geographical national condition census data, and quickly evaluating disaster areas by fusing post-disaster evaluation models;
the early warning and monitoring module combines the evaluation result of the geological disaster risk level of the key area to dynamically monitor the geological disaster hidden danger point of the key area in real time, reflects the state of disaster condition by combining meteorological data and ground internet of things sensor monitoring data with a ground disaster early warning model, receives disaster early warning information and generates the geological disaster influence level according to the early warning information.
2. The geological disaster early warning system based on the radar remote sensing technology according to claim 1, wherein the data processing module specifically comprises:
the remote sensing image monitoring result acquisition module comprises: performing atmospheric correction, radiation correction, geometric correction, image mosaic cutting and image fusion pretreatment on the synthetic aperture radar remote sensing image data and the high-resolution remote sensing image data; performing time sequence InSAR processing on the preprocessed synthetic aperture radar remote sensing image to obtain a target area earth surface deformation result, and performing intelligent interpretation operation on the high-resolution remote sensing image to obtain a geological disaster interpretation result;
unmanned aerial vehicle and laser radar monitoring result acquisition module: performing data processing on unmanned aerial vehicle data and laser radar data and generating a target area three-dimensional model;
the ground internet of things sensor monitoring result acquisition module: and (3) processing and obtaining results of soil humidity, soil pressure, surface vegetation coverage, thickness of loose deposit, distribution and the like of the target area according to geological parameter data monitored by the ground internet of things sensor.
3. The geological disaster early warning system based on the radar remote sensing technology according to claim 2, wherein the data analysis module is used for combining remote sensing image monitoring results, unmanned aerial vehicle and laser radar monitoring results, ground internet of things sensor monitoring results, ground elevation data, topographic data and meteorological data, performing spatial superposition analysis, buffer area analysis and three-dimensional model analysis to obtain geological disaster characteristics, and extracting geological disaster hidden danger points of key areas, and mainly comprises the following steps:
step 1: performing large-scale general investigation on geological disaster hidden dangers of a target area according to the earth surface deformation result obtained by processing the synthetic aperture radar remote sensing image and the intelligent interpretation result of the high-resolution remote sensing image, and preliminarily determining geological disaster hidden dangers;
step 2: performing small-range detailed investigation on the initially determined geological disaster hidden danger points by using unmanned plane data and laser radar data, and performing disaster feature recognition and confirmation by combining a target area three-dimensional model to further determine the geological disaster hidden danger points, and analyzing and evaluating the stability, the harmfulness and the development trend of the geological disaster hidden danger points;
step 3: and (3) carrying out ground checking on the geological disaster hidden danger points determined in the step (2) by combining ground internet of things sensor real-time monitoring data, accurately analyzing disaster characteristics, causes, ranges and influence results of the geological disaster hidden danger points through the technologies of space superposition analysis, buffer area analysis, three-dimensional model analysis and the like, analyzing and judging the development degree of the geological disaster hidden danger points, and extracting the geological disaster hidden danger points of key areas.
4. The geological disaster early warning system based on the radar remote sensing technology according to claim 3, wherein the method for reflecting the disaster condition by combining meteorological data and ground internet of things sensor monitoring data with a ground disaster early warning model specifically comprises the following steps: and analyzing and estimating the geological structure, the topography, the main hidden danger, the disaster grade, the probability of occurrence of the geological disaster and the like of the geological disaster point according to the meteorological data and the ground internet of things sensor monitoring data combined with the ground disaster early warning model, and sending early warning according to the analysis result.
5. The geological disaster warning system based on radar remote sensing technology as set forth in claim 4, wherein said extensive census mainly comprises:
the method comprises the steps of selecting, processing and analyzing the data of the synthetic aperture radar remote sensing image by collecting the synthetic aperture radar remote sensing image, the synthetic aperture radar remote sensing image parameters and the synthetic aperture radar remote sensing image orbit information of a target area, obtaining the screening of the surface deformation characteristics of hidden danger points, and primarily screening and confirming hidden danger points with obvious deformation characteristics;
and collecting high-resolution remote sensing images of the target area, performing intelligent interpretation of geological disasters on the high-resolution remote sensing images, and primarily screening and confirming hidden danger points with obvious geological disasters by combining deformation monitoring results.
6. The geological disaster early warning system based on the radar remote sensing technology according to claim 5, wherein the geological disaster early warning model is specifically constructed by the following steps:
step 1: firstly, subdividing a target area into a plurality of 1km multiplied by 1km cells, and respectively calculating a geological disaster sensitivity index Z and a rainfall induction index R of each cell, thereby determining a prediction alarm index H, and predicting the probability of occurrence of geological disasters, wherein the calculation formula of the prediction alarm index H is as follows:
H＝Z×R
step 2: establishing a geological disaster prediction early warning model by combining meteorological data and prediction alarm indexes; the geological disaster occurrence level early warning colors are sequentially set to be blue, green, yellow, orange and red according to the light and medium degrees.
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