Geological disaster state evaluation method based on multi-source data fusion analysis

Abstract

The invention discloses a geological disaster state assessment method based on multi-source data fusion analysis, and relates to the technical field of geological disaster assessment, and the method comprises the steps: monitoring a target region, and obtaining geological monitoring data; the geological monitoring data are judged, and if it is judged that the land desertification phenomenon exists in the target area, the target area is divided to obtain a desertification area, an intersection area and a green plant area; the environmental state of the intersection area is judged, and the desertification risk of the target area is determined; if it is judged that the land desertification phenomenon does not exist, grid division is conducted on the target area, and grade data are obtained according to the geological monitoring data of the grid areas and the position information of all the grid areas; judging other levels of regions by taking the first level of region as a standard to obtain relational data, and determining that the target region has a desertification risk according to the relational data; and outputting an early warning signal after determining that the desertification risk exists. The method has the effect of improving the land state evaluation accuracy.

Description

Technical Field

[0001] This application relates to the field of geological hazard assessment technology, and in particular to a geological hazard status assessment method based on multi-source data fusion analysis. Background Technology

[0002] Geological hazards include sudden geological hazards and slow-changing geological hazards. Sudden geological hazards (such as landslides and debris flows) often occur instantly after being triggered by heavy rainfall, earthquakes, or human engineering activities, and have a wide range of impacts. Slow-changing geological hazards (such as ground subsidence, soil erosion, desertification, and other land degradation) have evolution cycles ranging from several months to decades and are often related to long-term hydrological, climatic, or human activities.

[0003] Current technologies for detecting and warning of land desertification mainly involve constructing an integrated "space-air-ground" monitoring network. This network utilizes satellite remote sensing and aerial monitoring to observe the vegetation coverage of target areas from a macroscopic perspective, and collects and analyzes environmental information to determine whether the environment is deteriorating. This clarifies the land condition of the target area, enabling timely detection and early warning intervention when land desertification occurs, thereby reducing further desertification.

[0004] Regarding the aforementioned technologies, since land desertification is a long-term disaster, when satellite remote sensing observes changes in vegetation cover in a target area, land desertification has already occurred and affected the vegetation status. Furthermore, due to the cyclical nature of vegetation growth, the vegetation cover area in the target area will decrease during a specific period. This interferes with satellite remote sensing observations, reduces the accuracy of land desertification early warning, and lowers the accuracy of land status assessment, thus requiring improvement. Summary of the Invention

[0005] To improve the accuracy of land status assessment, this application provides a geological hazard status assessment method based on multi-source data fusion analysis.

[0006] This application provides a geological hazard status assessment method based on multi-source data fusion analysis, employing the following technical solution:

[0007] A geological hazard status assessment method based on multi-source data fusion analysis includes:

[0008] The target area is monitored to obtain geological monitoring data; the geological monitoring data is then analyzed to determine whether desertification has already occurred in the target area.

[0009] If it is determined that desertification already exists in the target area, the target area is divided into desertified areas, areas where desertification and vegetation meet, and areas with vegetation.

[0010] Ecological conflict terms are identified based on desertified and green areas. The intersection areas are then assessed based on these ecological conflict terms to determine the data change trends of the intersection areas in terms of ecological conflict terms, thus obtaining the first change trend.

[0011] The first trend of change is judged. If the first trend of change is close to the desert area, the ecological conflict items of the green area are judged to determine whether the ecological conflict items of the green area are trending towards desertification.

[0012] If the ecological conflict factors in the green area remain unchanged or are far from desertification, then the target area is determined to be at risk of land desertification.

[0013] If the ecological conflict factors in the green area tend to become desertified, the green area will be continuously monitored, and the desertification risk of the target area will be determined based on the results of the continuous monitoring.

[0014] Once a target area is determined to have a risk of desertification, an early warning signal is issued to remind relevant personnel to take action.

[0015] Preferably, data stability values ​​are read for desertified areas to obtain desert standard values; data stability values ​​are read for lush vegetation areas to obtain lush vegetation standard values.

[0016] The target area is first divided based on the desert standard value and the green vegetation standard value, resulting in the first area to be judged outside the desert standard value and the green vegetation standard value.

[0017] Based on the desert standard value and the green plant standard value, a finite element analysis is performed on the first area to be judged to determine the distribution of each data value within the range of variation from the desert standard value to the green plant standard value in the first area to be judged, and thus obtain the data value distribution data.

[0018] Analyze the distribution of data values ​​to determine the patterns in the data value distribution.

[0019] If there are sudden changes in the data value distribution pattern or high distribution density, the first region to be judged is further divided using the regions where the data values ​​change suddenly or the distribution density is high, to obtain the intersection region.

[0020] Preferably, after the intersection area is precisely divided, the boundary line of the intersection area is read to obtain the boundary data;

[0021] Acquire the location information of the boundary data and monitor the location information of the boundary data. If the location information of the boundary data in the target area deviates, determine the land desertification risk of the target area based on the deviated location.

[0022] If the location information of the boundary data in the target area is close to the desertification area, then the target area is determined not to have the risk of land desertification.

[0023] If the location information of the boundary data in the target area moves closer to the green vegetation area, the target area is determined to have a risk of desertification.

[0024] Preferably, continuous monitoring and assessment of green areas are conducted to determine whether ecological conflict factors in green areas consistently tend towards desertification;

[0025] If the ecological conflict factors in the green area consistently tend towards desertification, then the target area is deemed to be at risk of land desertification.

[0026] If the ecological conflict items in the green area do not always tend towards desertification, then the ecological conflict items of the intersection area in the corresponding time period are matched with those of the green area to determine the numerical relationship between the ecological conflict items of the intersection area and those of the green area.

[0027] If the numerical relationship between the intersection area and the green area on the ecological conflict item is positive, then it is determined that there is no risk of land desertification in the target area;

[0028] If the numerical relationship between the intersection area and the green area on the ecological conflict term is not positive, then the target area is determined to have a risk of land desertification.

[0029] Preferably, if it is determined that there is no land desertification in the target area, the target area is divided into grids to obtain grid areas; wherein, the grid areas include the location information of the corresponding area and the geological monitoring data of the corresponding area;

[0030] An environmental status assessment is conducted on the geological monitoring data of the grid area to determine the assessment data. Based on the assessment data and the location information of each grid area, the grid areas are assigned a level number to obtain the level data of the grid area.

[0031] Based on the graded data, the geological monitoring data of other grades are judged using the geological monitoring data of the first grade area as the standard. The relationship between the data changes of the geological monitoring data of other grades and the geological monitoring data of the first grade area is determined, and the relationship data is obtained. If the relationship data is geological monitoring data far away from the first grade area, it is determined that the target area has a risk of desertification.

[0032] Preferably, vegetation survival information is obtained in each grid area, and the vegetation survival information is matched with the geological information in the geological monitoring data of the grid area to determine the satisfaction relationship between the geological state of the grid area and the ecology of the corresponding area, and the satisfaction degree is obtained.

[0033] Obtain the geographic information of the target area, and match the location information of each grid area based on the geographic information to determine the fluctuation value of each grid area;

[0034] The level value of the corresponding grid area is determined based on the satisfaction level and fluctuation value, and the grid area is assigned a level number according to the level value to obtain the level data.

[0035] Preferably, based on the grade data, the data values ​​of the geological monitoring data of the first-level area are used as the evaluation criteria to obtain standard data;

[0036] Based on continuous monitoring, the geological monitoring data in each grid area under continuous monitoring is compared with standard data to obtain the first comparison relationship;

[0037] If the geological monitoring data of the first comparison area is far from the standard data, the corresponding grid area will be marked as the area to be evaluated.

[0038] The assessment area is classified to determine whether a Level 1 area exists within the assessment area.

[0039] If a first-level area is determined to exist, then the level distribution matching is performed. If the area to be evaluated contains some areas of each level, then the target area is determined to have a risk of desertification.

[0040] If the area to be evaluated does not contain any areas of each level or does not have a first-level area, then the level data of the area to be evaluated is judged to determine whether the level of the area to be evaluated is the lowest level.

[0041] If the area to be assessed is determined to be at the lowest level, then the target area is deemed to be at risk of desertification.

[0042] In summary, this application includes at least one of the following beneficial technical effects:

[0043] 1. By initializing the geological monitoring data of the target area, the initial state of the target area during monitoring is determined. If the target area is already in a state of desertification at the time of monitoring, the desertified area, vegetation area, and intersection area are identified through initial identification. The environmental status of the intersection area is continuously assessed based on the desertified and vegetation areas. By using similar data, it is determined whether the intersection area is trending towards a desertified state over a long period of time. This allows for accurate prediction of the current risk of desertification in the target area, ensuring that relevant personnel can promptly detect the land status before desertification fully occurs and intervene to reduce the occurrence of desertification and improve prediction accuracy. If the target area is in a normal land condition during monitoring, the target area is divided to ensure the accuracy of data analysis. Then, the environmental condition of the target area is determined by assessing the geological monitoring data of each grid area. Based on the assessment data and location information of each grid area, the grid areas are graded to identify the grid area with the highest stability. This grid area is then used as the standard to judge other grid areas, thus ensuring the accuracy of the comparison results when the standard target is stable and improving the accuracy of land desertification early warning.

[0044] 2. By continuously monitoring the ecological conflict items in green areas, it is determined whether the ecological conflict items in green areas consistently tend towards desertification, thereby eliminating misjudgments caused by fluctuations in the ecological conflict items of green areas. If it is determined that green areas consistently tend towards desertification, then the target area is identified as having a risk of land desertification. If it is determined that the ecological conflict items in green areas do not consistently tend towards desertification, then by utilizing the influence relationship between the intersection area and the green area, the ecological conflict items of the intersection area are matched with those of the green area. Based on the numerical relationship between the intersection area and the green area, the land desertification risk of the target area is determined, making the assessment of land desertification risk of the target area based on the intersection area more accurate.

[0045] 3. By using geological monitoring data from the first-level region as standard data, the stability and reference value of the standard data are ensured. Simultaneously, by comparing the geological monitoring data of each continuously monitored grid region with the standard data, the regions to be assessed where data deviations have occurred are identified. Then, the regions to be assessed are further judged according to the first-level region to determine the scope of impact of data changes. If a first-level region exists, then grade distribution matching is performed to further verify the scope of impact of data changes in the regions to be assessed, thereby improving the accuracy of desertification risk assessment. If it is determined that the regions to be assessed do not have a first-level region or do not include parts of each grade, then the grade data of the regions to be assessed is judged to determine whether the data changes in the regions to be assessed belong to the lowest grade region with the worst stability. The high sensitivity of the lowest grade region is then used to further judge the regions to be assessed, making the assessment results of land desertification status more accurate. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating the steps of the geological hazard status assessment method based on multi-source data fusion analysis in this embodiment. Detailed Implementation

[0047] The following is in conjunction with the appendix Figure 1 This application will be described in further detail.

[0048] This application discloses a method for assessing the state of geological hazards based on multi-source data fusion analysis.

[0049] Example: Figure 1 As shown, the present invention provides a geological hazard status assessment method based on multi-source data fusion analysis, comprising:

[0050] S1. Monitor the target area to obtain geological monitoring data; judge the geological monitoring data to determine whether desertification has already occurred in the target area; the geological monitoring data includes soil data, salinity data, environmental data, vegetation data, etc.

[0051] S2, if it is determined that desertification already exists in the target area, the target area is divided into desertified areas, areas where desertification and vegetation meet, and areas with vegetation.

[0052] S3. Based on desertified and green areas, identify ecological conflict items. Based on these ecological conflict items, assess the intersection area and determine the data change trend of the intersection area in terms of ecological conflict items, obtaining the first change trend. Specifically: Construct an ecological model of the desertified area based on geological monitoring data; construct an ecological model of the green area based on geological monitoring data of the green area; compare the green area ecological model with the desertified area ecological model to identify the ecological conflict items between them; monitor the intersection area based on the ecological conflict items to determine the data change trend of the ecological conflict items, and record it as the first change trend; assess the first change trend. If the first change trend approaches the green area, it is determined that desertification in the target area is shrinking; if the first change trend approaches the desertified area, assess the ecological conflict items in the green area to determine whether the ecological conflict items in the green area are also trending towards desertification; if the ecological conflict items in the green area remain unchanged or move away from the desertified area, it is determined that desertification in the target area is expanding; if the ecological conflict items in the green area are trending towards desertification, the target area is marked as dangerous.

[0053] S4. Judge the first trend of change. If the first trend of change is close to the desert area, then judge the ecological conflict items of the green area to determine whether the ecological conflict items of the green area are trending towards desertification.

[0054] S5. If the ecological conflict items in the green area remain unchanged or are far from desertification, then the target area is determined to be at risk of land desertification.

[0055] S6. If the ecological conflict items in the green area tend to become desertified, the green area will be continuously monitored, and the desertification risk of the target area will be determined based on the results of the continuous monitoring.

[0056] S7, when it determines that there is a risk of desertification in the target area, outputs an early warning signal to remind relevant personnel to take action.

[0057] In this embodiment, the initial state of the target area is determined by initializing the geological monitoring data of the target area. If the target area is already in a state of land desertification at the time of monitoring, the desertified area, green area, and intersection area are identified through initial identification of the target area. The environmental state of the intersection area is continuously changed based on the desertified area and green area. Based on similar data, it is determined whether the intersection area is trending towards the environmental state of a desertified area during a long period of change. This accurately predicts the current risk of land desertification in the target area, ensuring that relevant personnel can promptly detect the land state before land desertification fully occurs and intervene to reduce the occurrence of land desertification and improve the accuracy of prediction.

[0058] For example, when monitoring geological hazards (land desertification) in a target area, the state of the target area when the system is introduced is first determined. If land desertification has already occurred in the target area when the system is introduced, the target area needs to be divided to determine which area is a normal green area, which area is a desertified area, and which area is an intersection between desertified and normal areas. After clarifying the situation of desertified and green areas, the environmental state of the intersection area is judged based on this, and the similarity relationship between the intersection area and the desertified and green areas is determined.

[0059] Because desertification is a slow and gradual process rather than a short-term, large-scale change, the state of the confluence area gradually tends to resemble the state of desertification as desertification progresses. Therefore, by utilizing the similarity between the confluence area and the desertified and green areas, the changes in the confluence area can be reflected.

[0060] Assuming the value for the desert region is 0, the value for the green region is 10, and the value for the intersection region is x, if the value for the intersection region is constantly decreasing, it indicates that the desertification trend is becoming more severe; conversely, if the value for the intersection region is constantly increasing, it indicates that the desertification trend is decreasing.

[0061] In this embodiment, by comparing the ecological conditions of desertified areas with those of lush vegetation areas, ecological conflict items that can intuitively reflect the state between desertified and lush vegetation areas are identified, reducing the amount of data to be judged and improving the efficiency of judgment. By monitoring the ecological conflict items, the data changes of the ecological conflict items in the confluence area are determined, and then the data changes are compared with those of lush vegetation areas and desertified areas to determine whether the confluence area tends towards lush vegetation areas or towards desertification areas. When it is determined that the ecological conflict items in the confluence area tend towards lush vegetation areas, the current land state can be directly determined. When it is determined that the ecological conflict items in the confluence area tend towards desertification areas, in order to ensure the accuracy of the judgment, the lush vegetation areas are re-judged, thereby eliminating the possibility that the ecological conflict items in the confluence area tend towards desertification areas due to fluctuations in lush vegetation areas, thus improving the accuracy of land desertification risk assessment.

[0062] For example, after determining that there is desertification in the target area, the corresponding desertified area and green area are obtained through simple division. By comparing the desertified area and the green area, it is possible to determine which indicators directly determine whether the land is in a desertified state during the process of the land changing from a normal state to desertification, so that the evaluation criteria are more in line with the current environmental state of the target area.

[0063] By comparing desertified and lush areas, the ecological conflicts between the two are identified, and these conflicts are used as criteria to assess the convergence zone. This allows for the determination of changes in the convergence zone's state. When the ecological conflicts in the convergence zone are closer to those in the lush area, it indicates that the ecology of the convergence zone is more stable and suitable. Conversely, when the ecological conflicts in the convergence zone are closer to those in the desertified area, it may indicate that the ecology of the convergence zone is more unsuitable. This unsuitability may be due to changes in the state of the lush area, thus requiring a reassessment of the lush area's state to further determine the ecological state of the convergence zone and make the geological assessment of the target state more accurate.

[0064] For example, the ecological conflict term between desertified and green areas is 'a', meaning that the value of ecological conflict term 'a' in desertified areas is always opposite to that in green areas. For instance, the value of ecological conflict term 'a' in desertified areas is 0, while the value of ecological conflict term 'a' in green areas is 10.

[0065] When the value of the ecological conflict term 'a' in the convergence area increases to near 10, it indicates that the ecology of the convergence area is shifting towards a green area. Conversely, when the value of the ecological conflict term 'a' in the convergence area decreases to near 0, it indicates that the ecology of the convergence area is shifting towards a desertification area.

[0066] The ecological state of the convergence zone is the result of the combined influence of desertification and vegetation zones. The state of the desertification zone is fixed (deteriorating). Therefore, when the ecology of the vegetation zone changes (decreases), the ecological state of the convergence zone tends to become desertified. Thus, when the ecological state of the convergence zone is desertified, it is also necessary to determine whether the state of the vegetation zone has changed. If the state of the vegetation zone has not changed, it indicates that the ecological state of the convergence zone is indeed tending towards desertification. Conversely, if the state of the vegetation zone has changed, it is determined that the change in the ecological state of the convergence zone is due to the disturbance caused by the change in the state of the vegetation zone, thereby improving the accuracy of judging the desertification process of the target area.

[0067] Step S2: If it is determined that desertification already exists in the target area, the target area is divided into desertified areas, areas where desertification and vegetation meet, and vegetation areas, including the following steps:

[0068] S2a: Data stability values ​​are read for desertified areas to obtain desert standard values; data stability values ​​are read for vegetated areas to obtain vegetated standard values.

[0069] S2b, the target area is divided into the first part based on the desert standard value and the green vegetation standard value, and the first area to be judged outside the desert standard value and the green vegetation standard value is obtained;

[0070] S2c, based on the desert standard value and the green plant standard value, performs finite element analysis on the first area to be judged, determines the distribution of each data value within the range of change from the desert standard value to the green plant standard value in the first area to be judged, and obtains the data value distribution data;

[0071] S2d is used to analyze the distribution of data values ​​and determine the distribution pattern of the data values.

[0072] S2e: If there are sudden changes or high distribution density in the data value distribution pattern, the first region to be judged is further subdivided using the regions where the sudden changes or high distribution density occur, resulting in the intersection region. This further refines the regional location information of the intersection region, ensuring that changes in the intersection region accurately reflect the desertification situation in the target area.

[0073] In this embodiment, by reading stable data values ​​from desertified and green areas, the target area is accurately divided into desertified, green, and first-to-be-judged areas. Then, by performing finite element analysis on the first-to-be-judged area, the data value distribution pattern under different data values ​​is obtained. Based on this, the first-to-be-judged area is further subdivided, thereby further refining the regional location information of the intersection area. This ensures that changes in the intersection area accurately reflect the desertification situation of the target area, which helps to assess the state of the target area based on data changes in the intersection area and improves the accuracy of the assessment results.

[0074] For example, since land desertification is a gradual process, the target area can be regarded as a rectangle, with the desertified area on one side of the target area and the green area on the other side. The intersection between the two is a gradually blurred area. Therefore, it is necessary to divide the area into the desertified area with constant values, the green area with constant values, and the intersection area with gradually changing values.

[0075] Since both desertified and green areas are considered as areas with constant values, the geological monitoring data of the target area are divided into desertified areas, green areas, and the first area to be judged.

[0076] Meanwhile, since the impact of desertification on other non-desertified areas is gradual, that is, the closer the location is to the desertification area, the greater the impact of the desertification area, and the farther away the location is from the desertification area, the less the impact of the desertification area is. Therefore, finite element analysis is performed on the first region to be judged to determine the distribution pattern of different data values ​​in the first region to be judged. By filtering the distribution pattern, the corresponding intersection area is determined.

[0077] Since locations closer to desertification areas are more affected by them, while locations farther away are less affected, it is necessary to select specific intersection areas to ensure that the judgment results of the intersection areas accurately reflect the land desertification changes in the target area. This avoids short-term fluctuations in desertification areas and prevents drastic numerical changes in the contact area between the first area to be judged and the desertification area, thereby improving the accuracy of using the analysis results of changes in the intersection areas to reflect the land desertification risk in the target area.

[0078] After determining the intersection area, the following steps are also included:

[0079] S2f: After the intersection area is precisely divided, the boundary line of the intersection area is read to obtain the boundary data;

[0080] S2g acquires the location information of the boundary data and monitors the location information of the boundary data. If the location information of the boundary data in the target area deviates, the land desertification risk of the target area is determined based on the deviated location.

[0081] S2h, if the location information of the boundary data in the target area is close to the desertification area, then the target area is determined not to have the risk of land desertification;

[0082] S2i, if the location information of the boundary data in the target area moves closer to the green area, then the target area is determined to have the risk of land desertification.

[0083] In this embodiment, by monitoring the boundary line of the intersection area, the change in the land desertification risk of the target area can be intuitively judged based on the change in the position of the boundary line, making the judgment result simpler and more direct.

[0084] For example, after accurately delineating the intersection area, assuming the desertification of the target area becomes severe, it's equivalent to the desertified area on one side of the rectangular area shifting to the other. Consequently, the boundary of the intersection area will also shift. By monitoring the boundary of the intersection area, the direction of change can be determined. If the direction of change is towards green areas, it indicates severe desertification; if it's towards desertified areas, it indicates a reduction in desertification. This allows for a preliminary assessment of desertification in the target area. Combined with ecological conflict factors, this makes the geological condition assessment of the target area more accurate, improving the accuracy of the assessment results.

[0085] In step S6, if the ecological conflict factors in the green area tend towards desertification, the green area is continuously monitored, and the desertification risk of the target area is determined based on the continuous monitoring results, including the following steps:

[0086] S61, conduct continuous monitoring and assessment of green areas to determine whether ecological conflict factors in green areas are consistently trending toward desertification;

[0087] S62. If the ecological conflict items in the green area consistently tend towards desertification, then the target area is deemed to be at risk of land desertification.

[0088] S63. If the ecological conflict items of the green area do not always tend to desertification, then the ecological conflict items of the intersection area in the corresponding time period are matched with those of the green area to determine the numerical relationship between the ecological conflict items of the intersection area and those of the green area.

[0089] S64. If the numerical relationship between the intersection area and the green area on the ecological conflict item is positively correlated, then it is determined that there is no risk of land desertification in the target area.

[0090] S65. If the numerical relationship between the intersection area and the green area on the ecological conflict term is not positive, then the target area is determined to have a risk of land desertification.

[0091] In this embodiment, by continuously monitoring the ecological conflict items of the green area, it is determined whether the ecological conflict items of the green area consistently tend towards desertification, thereby eliminating misjudgments caused by fluctuations in the ecological conflict items of the green area. If it is determined that the green area consistently tends towards desertification, then the target area is determined to have a risk of land desertification. If it is determined that the ecological conflict items of the green area do not consistently tend towards desertification, then by utilizing the influence relationship between the intersection area and the green area, the ecological conflict items of the intersection area are matched with those of the green area. Thus, the land desertification risk of the target area is determined based on the numerical relationship between the intersection area and the green area, making the assessment of the land desertification risk of the target area based on the intersection area more accurate.

[0092] For example, if it is determined that the ecological conflict items in a green area tend to be desertified, it means that there is a risk of desertification in the green area. It is necessary to further determine whether the fluctuation in the green area is a data disturbance of environmental change or a real change in geological state.

[0093] By continuously monitoring the green areas, when the data values ​​of the green areas change, there are two possibilities: one is that the green areas are gradually transitioning to desertification, and the other is that the environment of the green areas is fluctuating, which leads to fluctuations in the status monitoring of the green areas, thus showing a temporary tendency towards desertification.

[0094] Therefore, by continuously monitoring green areas, if the data changes only briefly and then return to or exceed the initial value of the green area, it is determined that the green area is not trending towards desertification; otherwise, it is determined that the green area is trending towards desertification. When a green area shows signs of desertification, it indicates that the confluence area is also trending towards desertification.

[0095] When the green area does not tend towards desertification, it is still necessary to assess the confluence area. Since the corresponding desertified area is located behind the confluence area, if the green area becomes desertified, the confluence area will definitely become desertified; however, if the confluence area becomes desertified, the green area may not necessarily become desertified. Therefore, it is necessary to reassess the relationship between the confluence area and the green area.

[0096] Since the condition of the convergence zone is affected by both the green area and the desertified area, when the condition of the green area tends to be better, the condition of the convergence zone should be better. Therefore, the condition of the convergence zone is positively correlated with the condition of the green area.

[0097] Therefore, by comparing the state changes of the green area and the intersection area, it can be determined whether the state of the intersection area also improves when the state of the green area improves, and whether the state of the intersection area also deteriorates when the state of the green area deteriorates. If so, it indicates that the state relationship between the intersection area and the green area is positively correlated; otherwise, it is determined to be non-positively correlated.

[0098] Only when the vegetation area and the confluence area show a positive correlation can it be determined that the confluence area is not desertified if the vegetation area does not exhibit desertification, meaning that the target area does not face the risk of land desertification. This improves the accuracy of land desertification hazard assessment.

[0099] A geological hazard status assessment method based on multi-source data fusion analysis also includes:

[0100] S11 uses desertified areas and green areas as standards to judge the environmental status of the intersection area, determine the trend of change in the intersection area, and determine the desertification risk of the target area based on the trend of change in the intersection area.

[0101] S12, if it is determined that there is no desertification in the target area, the target area is divided into grids to obtain grid areas; wherein, the grid area includes the location information of the corresponding area and the geological monitoring data of the corresponding area; wherein, for example, the target area is a rectangular area, the grid division is to divide the entire rectangular area into nine grids, wherein the area corresponding to each grid is a grid area.

[0102] S13. Environmental status assessment is performed on the geological monitoring data of the grid area to determine the assessment data. Based on the assessment data and the location information of each grid area, the grid area is assigned a grade number to obtain the grade data of the grid area. Among them, environmental status assessment refers to determining the degree of matching between the geological information at the corresponding location and the vegetation survival conditions in the corresponding area. The more suitable it is for vegetation survival, the higher the assessment data.

[0103] S14. Based on the grade data, the geological monitoring data of other grades are judged using the geological monitoring data of the first grade area as the standard. The relationship between the data changes of the geological monitoring data of other grades and the geological monitoring data of the first grade area is determined, and the relationship data is obtained. If the relationship data is geological monitoring data far away from the first grade area, it is determined that the target area has a risk of desertification.

[0104] S15: When a target area is determined to have a risk of desertification, an early warning signal is output to remind relevant personnel to take action.

[0105] In this embodiment, if the target area is in a normal land condition during monitoring, the target area is divided to ensure the accuracy of data analysis. Then, the land condition of the target area is determined by assessing the environmental condition of the geological monitoring data of each grid area. Based on the assessment data and location information of each grid area, the grid areas are assigned a level number to identify the grid area with the highest stability. This grid area is then used as a standard to judge other grid areas, thus ensuring the accuracy of the comparison results when the standard target is stable, and improving the accuracy of land desertification early warning.

[0106] For example, if the target area does not exhibit desertification when the system is introduced, the target area is divided into grids, breaking down a large area into smaller, interconnected regions. This results in more accurate analysis of each grid region. Environmental status is assessed using geological monitoring data from each grid region to determine its environmental condition. After determining the environmental condition, each grid region is assigned a level number based on its location. Assuming the target area is considered a rectangular region with uniform environmental conditions across all locations, when desertification occurs within this rectangular region, areas closer to the center experience less external interference and have a lower risk of desertification. Therefore, each grid region within the rectangular region needs to be assigned a level number based on its location; higher levels correspond to more difficult-to-change environmental conditions. The first level is higher than the second level.

[0107] Once the region with the highest stability (Level 1) is identified, the data values ​​of other regions are compared against these Level 1 values ​​to determine their changes. If the data values ​​converge towards Level 1, the environment is improving; conversely, if they deviate from Level 1, the environment is deteriorating. This effectively identifies the risk of desertification in the region, allowing for early detection of desertification and maximizing the accuracy of early warnings.

[0108] In step S13, an environmental status assessment is performed on the geological monitoring data of the grid area to determine the assessment data. Based on the assessment data and the location information of each grid area, the grid areas are assigned a level number to obtain the level data of the grid areas. This includes the following steps:

[0109] S131, Obtain vegetation survival information in each grid area, and match the vegetation survival information with the geological information in the geological monitoring data of the grid area to determine the satisfaction relationship between the geological state of the grid area and the ecology of the corresponding area, and obtain the satisfaction degree;

[0110] S132, Obtain the geographic information of the target area, and match the location information of each grid area according to the geographic information to determine the fluctuation value of each grid area.

[0111] S133. Determine the grade value of the corresponding grid area based on the satisfaction level and fluctuation value, and assign grade numbers to the grid areas according to the grade values ​​to obtain grade data.

[0112] In this embodiment, the geological monitoring data of the grid area is compared with the vegetation survival information of the corresponding area to determine the fault tolerance rate of the environmental state relative to the vegetation information in the corresponding area. Then, the location information of each grid area is matched with the geographical information of the target area to further determine the interference intensity of the grid area. By comprehensively judging the grid area based on the fault tolerance rate and the interference intensity, the grade value of each grid area is determined. This allows the stability of the corresponding grid area to be directly evaluated by using the grade data, providing accurate data for subsequent judgments and ensuring the accuracy of the judgment results.

[0113] For example, when it is determined that there are no desertified areas within the target area, it indicates that the ecological condition of the target area is in a vegetated state. In this case, the status assessment of the target area is no longer based on desertification, but on the current state. The current actual state is compared with the survival needs of the vegetation in the corresponding area to determine the current state of the target area. If the current state does not meet the needs of the vegetation, it indicates that the target area is in a state of gradual degradation, with poor environmental stability and susceptibility to damage. Conversely, when the current environment of the target area meets the needs of the vegetation and has a surplus, it is determined that the current state of the target area is normal, with high environmental stability and strong resistance to interference. Therefore, by matching the geological information of each grid area with the corresponding vegetation survival information, the relationship between the geological information and the vegetation survival information is determined. If the geological information is greater than the vegetation survival information, it indicates that the stability of the area is high, and the greater the excess, the more stable the area. Thus, the corresponding satisfaction level is determined.

[0114] However, due to the different geographical information of the target area, the results are different. For example, if the area outside the target area is desert and only the monitored target area is covered with vegetation, then the land condition at the edge of the target area is most susceptible to external interference and most easily changed, while the land condition at the center of the target area is least susceptible to external interference and least easily changed. Therefore, it is necessary to determine the probability of the grid area at each location being affected based on the geographical information of the target area and obtain the corresponding fluctuation value.

[0115] By combining the satisfaction level (stability) and fluctuation value (interference intensity) of the target area itself, the level value of the grid area at each location is determined, which is used to evaluate the security of the grid area.

[0116] In step S14, based on the grade data, the geological monitoring data of other grades are judged using the geological monitoring data of the first-grade area as the standard. The relationship between the data changes of the geological monitoring data of other grades and the geological monitoring data of the first-grade area is determined, and the relationship data is obtained. If the relationship data is geological monitoring data far away from the first-grade area, it is determined that the target area has a risk of desertification. This includes the following steps:

[0117] S141, based on the grade data, the data values ​​of the geological monitoring data of the first-level area are used as the evaluation criteria to obtain standard data;

[0118] S142, Based on continuous monitoring, the geological monitoring data in each grid area of ​​continuous monitoring is compared with standard data to obtain the first comparison relationship;

[0119] S143, If the geological monitoring data of the first comparison relationship is far from the standard data of the grid area, then the corresponding grid area is marked as the area to be evaluated;

[0120] S144, perform a level assessment on the area to be assessed to determine whether a first-level area exists in the area to be assessed;

[0121] S145. If a first-level area is determined to exist, then level distribution matching is performed. If the area to be evaluated contains some areas of each level, then the target area is determined to have a risk of desertification.

[0122] S146 If the area to be evaluated does not contain any areas of each level or does not contain a first-level area, then the level data of the area to be evaluated is judged to determine whether the level of the area to be evaluated is the lowest level.

[0123] S147. If the area to be assessed is determined to be at the lowest level, then the target area is deemed to be at risk of desertification.

[0124] In this embodiment, geological monitoring data from the first-level region is used as standard data to ensure the stability and reference value of the standard data. Simultaneously, by comparing the geological monitoring data of each continuously monitored grid region with the standard data, the regions to be assessed where data deviations have occurred are identified. Then, the regions to be assessed are further judged according to the first-level region to determine the scope of impact of data changes in the regions to be assessed. If a first-level region exists, then grade distribution matching is performed to further verify the scope of impact of data changes in the regions to be assessed, thereby improving the accuracy of desertification risk assessment. If it is determined that the regions to be assessed do not have a first-level region or do not contain parts of each grade, then the grade data of the regions to be assessed is judged to determine whether the data changes in the regions to be assessed belong to the lowest grade region with the worst stability. The high sensitivity of the lowest grade region is then used to further judge the regions to be assessed, making the assessment results of land desertification status more accurate.

[0125] For example, since higher-level raster areas have higher stability and more stable data changes, the data values ​​of higher-level raster areas are used as the standard to evaluate the geological monitoring data of other-level areas.

[0126] First, by comparing the geological monitoring data in each grid area during continuous monitoring with the standard data value of the selected area, the relationship between the state of each grid area and the standard state during continuous monitoring is determined, i.e., whether it is closer to or farther away from the standard state (since the geological monitoring data of the first-level area is selected as the standard data, the data value of the standard data is basically at its maximum, so the relationship is only one of being closer to or farther away).

[0127] When it is determined that the geological monitoring data in some areas are far from the standard data, these areas are marked as areas to be evaluated. The data deviation in these areas may be due to numerical fluctuations or the decrease in values ​​due to desertification in the target area, so further analysis is required.

[0128] By classifying the area to be evaluated, we first determine whether the values ​​of the first-level area itself have changed. If they have changed, it is highly likely that the change is due to desertification. To ensure accuracy, further judgment is required. By classifying the area to be evaluated at each level, if there are changes in the data at each level, it further indicates that the change in the data value is caused by desertification in the target area.

[0129] If the area to be assessed does not include parts of each level or does not have a first-level area, it indicates that the change in the value is not caused by overall desertification. Therefore, it is necessary to determine the lowest level of the area to be assessed. If all are at the lowest level, it indicates that the most unstable area has changed, and it is mostly a collective change. Thus, it can be determined that the change in the value may cause land desertification, and therefore, it is determined that there is a risk of desertification.

[0130] Compared with existing geological hazard status assessment methods based on multi-source data fusion analysis, this invention improves the accuracy of land status assessment.

[0131] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for assessing the state of geological hazards based on multi-source data fusion analysis, characterized in that, include: The target area is monitored to obtain geological monitoring data; The geological monitoring data is analyzed to determine whether desertification has already occurred in the target area; If it is determined that desertification already exists in the target area, the target area is divided into desertified areas, areas where desertification and vegetation meet, and areas with vegetation. Ecological conflict terms are identified based on desertified and green areas. The intersection areas are then assessed based on these ecological conflict terms to determine the data change trends of the intersection areas in terms of ecological conflict terms, thus obtaining the first change trend. The first trend of change is judged. If the first trend of change is close to the desert area, the ecological conflict items of the green area are judged to determine whether the ecological conflict items of the green area are trending towards desertification. If the ecological conflict factors in the green area remain unchanged or are far from desertification, then the target area is determined to be at risk of land desertification. If the ecological conflict factors in the green area tend to become desertified, the green area will be continuously monitored, and the desertification risk of the target area will be determined based on the results of the continuous monitoring. Once a target area is determined to have a risk of desertification, an early warning signal is issued to remind relevant personnel to take action.

2. The geological hazard status assessment method based on multi-source data fusion analysis according to claim 1, characterized in that: If desertification is determined to exist in the target area, the target area is divided into desertified areas, areas where desertification and vegetation meet, and vegetation areas, including: Data stability values ​​were read from desertified areas to obtain desert standard values; data stability values ​​were read from lush areas to obtain lush standard values. The target area is first divided based on the desert standard value and the green vegetation standard value, resulting in the first area to be judged outside the desert standard value and the green vegetation standard value. Based on the desert standard value and the green plant standard value, a finite element analysis is performed on the first area to be judged to determine the distribution of each data value within the range of variation from the desert standard value to the green plant standard value in the first area to be judged, and thus obtain the data value distribution data. Analyze the distribution of data values ​​to determine the patterns in the data value distribution. If there are sudden changes in the data value distribution pattern or high distribution density, the first region to be judged is further divided using the regions where the data values ​​change suddenly or the distribution density is high, to obtain the intersection region.

3. The geological hazard status assessment method based on multi-source data fusion analysis according to claim 2, characterized in that, After determining the intersection area, the following is also included: After the intersection area is precisely divided, the boundary line of the intersection area is read to obtain the boundary data; Acquire the location information of the boundary data and monitor the location information of the boundary data. If the location information of the boundary data in the target area deviates, determine the land desertification risk of the target area based on the deviated location. If the location information of the boundary data in the target area is close to the desertification area, then the target area is determined not to have the risk of land desertification. If the location information of the boundary data in the target area moves closer to the green vegetation area, the target area is determined to have a risk of desertification.

4. The geological hazard status assessment method based on multi-source data fusion analysis according to claim 1, characterized in that: If the ecological conflict factors in the green area tend towards desertification, then the green area will be continuously monitored, and the desertification risk of the target area will be determined based on the continuous monitoring results, including: Continuous monitoring and assessment of green areas are conducted to determine whether ecological conflicts in these areas consistently tend towards desertification. If the ecological conflict factors in the green area consistently tend towards desertification, then the target area is deemed to be at risk of land desertification. If the ecological conflict items in the green area do not always tend towards desertification, then the ecological conflict items of the intersection area in the corresponding time period are matched with those of the green area to determine the numerical relationship between the ecological conflict items of the intersection area and those of the green area. If the numerical relationship between the intersection area and the green area on the ecological conflict item is positive, then it is determined that there is no risk of land desertification in the target area; If the numerical relationship between the intersection area and the green area on the ecological conflict term is not positive, then the target area is determined to have a risk of land desertification.

5. The geological hazard status assessment method based on multi-source data fusion analysis according to claim 1, characterized in that, Also includes: If it is determined that there is no desertification in the target area, the target area is divided into grids to obtain grid regions; the grid regions include the location information of the corresponding areas and the geological monitoring data of the corresponding areas. An environmental status assessment is conducted on the geological monitoring data of the grid area to determine the assessment data. Based on the assessment data and the location information of each grid area, the grid areas are assigned a level number to obtain the level data of the grid area. Based on the graded data, the geological monitoring data of other grades are judged using the geological monitoring data of the first grade area as the standard. The relationship between the data changes of the geological monitoring data of other grades and the geological monitoring data of the first grade area is determined, and the relationship data is obtained. If the relationship data is geological monitoring data far away from the first grade area, it is determined that the target area has a risk of desertification.

6. The geological hazard status assessment method based on multi-source data fusion analysis according to claim 5, characterized in that: The process involves conducting an environmental status assessment on the geological monitoring data of the grid area, determining the assessment data, and, based on the assessment data and the location information of each grid area, assigning a level number to the grid area to obtain the level data of the grid area, including: The vegetation survival information of each grid area is obtained, and the vegetation survival information is matched with the geological information in the geological monitoring data of the grid area to determine the satisfaction relationship between the geological status of the grid area and the ecology of the corresponding area, and the satisfaction degree is obtained. Obtain the geographic information of the target area, and match the location information of each grid area based on the geographic information to determine the fluctuation value of each grid area; The level value of the corresponding grid area is determined based on the satisfaction level and fluctuation value, and the grid area is assigned a level number according to the level value to obtain the level data.

7. The geological hazard status assessment method based on multi-source data fusion analysis according to claim 5, characterized in that: The process involves using geological monitoring data from the first-level region as a standard to evaluate geological monitoring data from other levels, determining the relationship between changes in geological monitoring data from other levels and those from the first-level region, and obtaining relational data. If the relational data is geological monitoring data far from the first-level region, the target area is determined to have a risk of desertification, including: Based on the grade data, the data values ​​of the geological monitoring data of the first-level area are used as the evaluation criteria to obtain standard data; Based on continuous monitoring, the geological monitoring data in each grid area under continuous monitoring is compared with standard data to obtain the first comparison relationship; If the geological monitoring data of the first comparison area is far from the standard data, the corresponding grid area will be marked as the area to be evaluated. The assessment area is classified to determine whether a Level 1 area exists within the assessment area. If a first-level area is determined to exist, then the level distribution matching is performed. If the area to be evaluated contains some areas of each level, then the target area is determined to have a risk of desertification. If the area to be evaluated does not contain any areas of each level or does not have a first-level area, then the level data of the area to be evaluated is judged to determine whether the level of the area to be evaluated is the lowest level. If the area to be assessed is determined to be at the lowest level, then the target area is deemed to be at risk of desertification.

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