Water finding favorable area identification method and device, storage medium and electronic equipment

Abstract

The application provides a water-finding favorable area identification method and device, a storage medium and electronic equipment in the technical field of geological exploration. In the process of determining the water-finding favorable area, the application introduces professional hydrogeological elements, integrates a surface humidity map obtained by inverting SAR data and a surface temperature map obtained by inverting thermal infrared data, determines the weight values of various evidences according to the importance of the close relationship of the water-finding favorable area, and finally calculates the probability value of water finding at any spatial position by using a linear evidence weighting method to identify different levels of predicted target areas. In addition, the application also considers that the single soil moisture inversion result may be affected by ground interference factors, so that the long-term stable trend of the ground humidity cannot be reflected. The time sequence stability index is used to effectively exclude this possibility, so that the soil moisture result of the screened area can better reflect the required information of the water-finding favorable area.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a water-favorable area identification method and device, a storage medium and an electronic device. BACKGROUND

[0002] The method for finding underground water mainly uses single remote sensing information and single technical means. No measured soil moisture and other surface indicators are used, and there is a lack of ground measurement data constraints, which may have greater uncertainty. And the information contained in the hydrogeological professional data is not fully considered. The effect of finding underground water is not ideal. SUMMARY

[0003] (I) Technical problems solved

[0004] In view of the deficiencies in the prior art, the present application provides a water-favorable area identification method and device, a storage medium and an electronic device, which solves the problem of unsatisfactory effect of the prior method in finding underground water.

[0005] (II) Technical solutions

[0006] To achieve the above purpose, the present application is realized by the following technical solutions:

[0007] In a first aspect, a water-favorable area identification method is provided, the method comprising:

[0008] obtaining the soil moisture distribution of the target area based on SAR data;

[0009] obtaining the surface temperature distribution of the target area based on thermal infrared data;

[0010] obtaining the alternative water-favorable area in the hydrogeological map;

[0011] Based on the soil moisture distribution of the target area, the surface temperature distribution of the target area and the alternative water-favorable area, the probability value of finding water in the target area is obtained by using the evidence weight method analysis model, and different levels of water-favorable area are obtained based on the preset threshold value.

[0012] Further, the soil moisture distribution of the target area based on SAR data comprises:

[0013] preprocessing the SAR data to obtain the backscattering coefficient after preprocessing;

[0014] Based on the urban, artificial building and water area in the land use map of the target area, a mask file is formed, the value of the region corresponding to the mask file in the backscattering coefficient after preprocessing is filled with 0, and the backscattering coefficient after masking is obtained.

[0015] Constructing a lookup table based on an AIEM-Dobson model integrated with a Dobson model;

[0016] Based on the pre-processed backscattering coefficient, the bare soil backscattering coefficient of the vegetation coverage area is obtained;

[0017] The bare soil backscattering coefficient is matched with the lookup table value, the soil moisture value is estimated by using the cost function, and the estimated soil moisture value is low-pass filtered and corrected;

[0018] Based on the corrected soil moisture value, the soil moisture distribution corresponding to the area with high stability of soil moisture time series characteristics is screened out as the soil moisture distribution of the target area.

[0019] Further, based on the corrected soil moisture value, the soil moisture distribution corresponding to the area with high stability of soil moisture time series characteristics is screened out as the soil moisture distribution of the target area, comprising:

[0020] The normalized processing is performed on the corrected soil moisture inversion result containing multiple time phases;

[0021] The time series stability index of the soil moisture normalized results of the same position and different time phases is calculated, and the time series stability index is the ratio of the standard deviation to the mean value of the soil moisture normalized results of the same position and different time phases;

[0022] The area smaller than the preset threshold value is taken as the soil moisture distribution of the target area.

[0023] Further, the alternative water-favorable area includes the division of water-bearing rock and the classification of water-rich areas with a capacity of >100 tons / day-night and the area with a buried depth of the roof of underlying water-bearing rock <100m, and the distribution positions of large-bore wells, machine wells, descending springs and ascending springs are marked.

[0024] In a second aspect, a water-favorable area identification device is provided, which comprises:

[0025] The soil moisture distribution acquisition module acquires the soil moisture distribution of the target area based on SAR data;

[0026] The land surface temperature distribution acquisition module acquires the land surface temperature distribution of the target area based on thermal infrared data;

[0027] The alternative water-favorable area acquisition module acquires the alternative water-favorable area in the hydrogeological map;

[0028] The evidence weight method analysis module obtains a water finding probability value of the target region by using an evidence weight method analysis model based on the soil moisture distribution of the target region, the ground temperature distribution of the target region and the alternative water finding favorable area, and obtains different levels of water finding favorable areas based on a preset threshold.

[0029] Further, the soil moisture distribution of the target region based on the SAR data comprises:

[0030] The SAR data is preprocessed to obtain a preprocessed backscattering coefficient;

[0031] A mask file is formed based on urban areas, artificial buildings and water areas and the like in a land use map of the target region, values of regions corresponding to the mask file in the preprocessed backscattering coefficient are filled with 0 to obtain a backscattering coefficient after masking;

[0032] A lookup table is constructed based on an AIEM-Dobson model integrated with a Dobson model;

[0033] Based on the preprocessed backscattering coefficient, a bare soil backscattering coefficient of a vegetation coverage region is obtained;

[0034] The bare soil backscattering coefficient is matched with the value of the lookup table, a cost function is used to estimate a soil moisture value, and the estimated soil moisture value is low-pass filtered and corrected;

[0035] Based on the corrected soil moisture value, a soil moisture distribution of a region with high temporal stability of soil moisture is screened out as the soil moisture distribution of the target region.

[0036] Further, the soil moisture distribution of the target region based on the corrected soil moisture value, the soil moisture distribution of a region with high temporal stability of soil moisture is screened out as the soil moisture distribution of the target region, comprises:

[0037] The corrected soil moisture inversion results containing multiple time phases are normalized;

[0038] Temporal stability indexes of soil moisture normalization results at the same position and different time phases are calculated, and the temporal stability index is a ratio of a standard deviation to a mean value of soil moisture normalization results at the same position and different time phases;

[0039] Regions less than a preset threshold value are taken as the soil moisture distribution of the target region.

[0040] Further, the alternative water finding favorable area comprises: division of water-bearing rock types, regions with water-richness grading >100 tons / day and night, and regions with overlying water-bearing rock roof depth grading <100m, and distribution positions of large bore wells, machine wells, descending springs and ascending springs are marked.

[0041] In a third aspect, a computer readable storage medium storing a computer program for identifying a water-favorable area is provided, wherein the computer program causes a computer to perform the method for identifying a water-favorable area described above.

[0042] In a fourth aspect, an electronic device is provided, comprising:

[0043] one or more processors;

[0044] a memory; and

[0045] one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the programs include a program for performing the method for identifying a water-favorable area described above.

[0046] (III) Beneficial Effects

[0047] The present application provides a method and device for identifying a water-favorable area, a storage medium and an electronic device. Compared with the prior art, the present application has the following beneficial effects:

[0048] 1. In the process of determining the water-favorable area, the present application introduces professional hydrogeological elements, integrates the surface humidity map obtained by SAR data inversion and the surface temperature map obtained by thermal infrared data inversion, determines the weight value of each evidence according to the importance of the water-favorable area, and finally calculates the probability value of water-finding at any spatial position using the linear evidence weighting method to identify the prediction target area of different levels.

[0049] 2. The present application also considers that the single soil moisture inversion result may be affected by ground interference factors, which cannot reflect the long-term stable trend of ground humidity. The time sequence stability index is used to effectively exclude this possibility, so that the soil moisture result of the screened area can better reflect the information required for the water-favorable area.

[0050] 3. The present application adopts the integrated air-ground combined inversion soil moisture technology. On the basis of using remote sensing information, the soil moisture measured value of the ground sampling point is added to correct the soil moisture obtained by SAR data inversion, improve the accuracy of the inversion soil moisture, and reduce the uncertainty, thereby laying a foundation for the water-favorable area. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0052] Figure 1 This is a flowchart of an embodiment of the present invention;

[0053] Figure 2 This is a flowchart illustrating how timing stability metrics are used to effectively eliminate interference in embodiments of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] This application provides a method, apparatus, storage medium, and electronic device for identifying favorable water-finding areas, which solves the problem that existing methods are not effective in finding groundwater.

[0056] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0057] Example 1:

[0058] like Figure 1 As shown, this invention provides a method for identifying favorable water-finding areas. This method is executed by a computer and includes:

[0059] Soil moisture distribution in the target area was obtained based on SAR data;

[0060] The surface temperature distribution of the target area is obtained based on thermal infrared data;

[0061] Obtain potential water-finding areas from hydrogeological maps;

[0062] Based on the soil moisture distribution, surface temperature distribution, and candidate water-finding favorable areas in the target area, the probability value of water finding in the target area is obtained by using the evidence weight method analysis model, and different levels of water-finding favorable areas are obtained based on preset thresholds.

[0063] The beneficial effects of the embodiments of the present invention are as follows:

[0064] In the process of identifying favorable areas for water discovery, professional hydrogeological elements are introduced, and surface humidity maps derived from SAR data and surface temperature maps derived from thermal infrared data are integrated. Then, based on the close importance of the favorable areas for water discovery, the weight values ​​of each piece of evidence are determined. Finally, the linear evidence weighting method is used to calculate the probability value of water discovery at any spatial location, so as to identify prediction target areas of different levels.

[0065] The specific implementation process of the present application is described in detail as follows:

[0066] S1, obtaining the soil moisture distribution of the target region based on SAR data;

[0067] In specific implementation, the following steps are specifically included:

[0068] S1.1, pre-processing the SAR data to obtain the pre-processed backscattering coefficient;

[0069] In this embodiment, the SAR data is obtained by a satellite radar (such as a Sentinel satellite) or an airborne radar, and there may be vegetation on the ground, so the backscattering coefficient obtained in this step cannot distinguish between the backscattering coefficient of bare soil and the backscattering coefficient of vegetation-covered area; the influence of vegetation needs to be removed through subsequent steps.

[0070] The pre-processing specifically includes orbit correction, radiation correction, multi-view, filtering, geocoding and radiation normalization processing. Among them, the radiation normalization can eliminate the influence of local incidence angle on soil moisture content inversion by normalizing the backscattering coefficient (which contains the backscattering coefficient of vegetation and bare soil) calculated from the SAR data to the same incidence angle.

[0071] Preferably, the radiation normalization uses the Lambert law in optical remote sensing:

[0072]

[0073] Wherein, θ ref is the reference incidence angle;

[0074] θ is the pixel incidence angle;

[0075] σ 0 is the backscattering coefficient in the SAR data;

[0076] is the backscattering coefficient normalized to the reference incidence angle;

[0077] S1.2, based on the mask file formed by the urban, artificial building and water area in the land use map of the target region, filling the value of the region corresponding to the mask file in the pre-processed backscattering coefficient with 0 to obtain the backscattering coefficient after masking;

[0078] Among the backscattering coefficient normalized to the reference incidence angle, there are strong signal interferences such as artificial buildings, which will affect the discrimination of soil moisture, so the backscattering coefficient of the interference area needs to be removed.

[0079] Land use map is a thematic map that expresses the current situation of land resources, regional differences and classification, which can be obtained from relevant domestic and foreign resource websites; the urban, artificial building and water area in the target area land use map form a mask file; the normalized backscattering coefficient after the reference incident angle is masked, that is, the value of the mask area is filled with zero to reduce the interference to the result.

[0080] S1.3, constructing a lookup table LUT based on the AIEM-Dobson model integrated with the Dobson model;

[0081] The backscattering coefficient is proportional to the soil moisture, and the lookup table can be used to determine the corresponding soil moisture of the backscattering coefficient; but the lookup table needs to be constructed according to the local parameters, and cannot be directly used with the existing public lookup table, so the AIEM-Dobson model integrated with the Dobson model is used to construct.

[0082] The soil moisture in the lookup table is calculated by the AIEM model, so there is a certain error, and therefore it is necessary to correct it with the measured data to make the obtained soil moisture more in line with the actual situation.

[0083] Among them, the Dobson model is the most commonly used relationship model for describing the relationship between soil dielectric constant and soil volume water content. It is most commonly used in various soil moisture retrieval algorithms and has high accuracy. The Dobson model is integrated into the AIEM model;

[0084] The input parameters of the Dobson model include: soil moisture range, soil bulk density, soil clay content, soil sand content, and surface temperature, which are ground measured data / experience values. A certain soil moisture range is converted into a dielectric constant range by the Dobson model, which is used as the input of the AIEM model;

[0085] The advanced integral equation model (AIEM) is the most commonly used physical model for describing the backscattering of bare soil surface;

[0086] The input parameters of the AIEM model include: the root mean square height range of soil roughness, the correlation length range (these two data are obtained from soil moisture ground test), the dielectric constant range, and the selected autocorrelation function; the radar wavelength, radar wave incident angle and soil moisture range set by the satellite-borne SAR data;

[0087] Among them, the AIEM model calculates the backscattering coefficient according to the following formula:

[0088]

[0089] wherein p, q represent the polarization characteristics (H or V) of the transmitted and received radar signals;

[0090] represents the backscattering coefficient;

[0091] represents the Kirchhoff term;

[0092] represents the compensation term;

[0093] represents the cross term of the compensation term;

[0094] The three are intermediate calculations in the model, calculated from input parameters and calculation procedures;

[0095] S1.4, based on the pre-processed backscattering coefficient, obtaining the bare soil backscattering coefficient of the vegetation coverage area;

[0096] wherein the backscattering coefficient of the vegetation is obtained by the water cloud model, the water cloud model is calibrated by calculation, and the water cloud model coefficients A and B of the target area are generated by the way of Kriging interpolation, and the backscattering coefficient of the vegetation is calculated according to the backscattering coefficient calculation formula.

[0097]

[0098]

[0099] And the bare soil backscattering coefficient of the vegetation coverage area needs to be obtained by subtracting the backscattering coefficient of the vegetation from the normalized backscattering coefficient corresponding to the vegetation coverage area, that is:

[0100]

[0101] wherein,

[0102] is the normalized backscattering coefficient;

[0103] is the backscattering coefficient of the vegetation;

[0104] is the bare soil backscattering coefficient;

[0105] τ 2 (θ) indicates the double-layer attenuation factor (transmittance) of the vegetation layer;

[0106] θ indicates the incidence angle of the electromagnetic wave;

[0107] A and B are empirical coefficients of the water cloud model, which depend on the vegetation type and the frequency of the incident electromagnetic wave;

[0108] V1 and V2 are two parameters describing vegetation.

[0109] So far, the backscattering coefficient of bare soil of all target areas can be obtained (the backscattering coefficient of bare soil in the non-vegetation coverage area is ).

[0110] S1.5, match the backscattering coefficient of bare soil with the lookup table value, and estimate the soil moisture value by using the cost function.

[0111] The specific cost function calculation strategy is: first, calculate the polarization ratio vh / vv of the dual-polarization data vv and vh, then calculate the dB value of vv and vh polarization, and get the closest row of vv polarization, vh polarization and polarization ratio by subtracting each row from the lookup table, and take the median of the first 10 rows as the final soil moisture inversion value.

[0112] S1.6, low-pass filter the soil moisture value and correct it.

[0113] The soil moisture inversion value obtained in S1.5 has large noise, and low-pass filtering is used to remove extreme values and obtain a smoother soil moisture map.

[0114] The accuracy of the measured and inverted soil moisture values is evaluated and corrected. The correlation coefficient R and the root mean square error RMSE are selected as the accuracy evaluation indexes. The measured soil moisture value is considered as an absolute value, and the inverted soil moisture value is a relative value. The inverted value is adjusted and corrected by referring to the true value, so that the corrected soil moisture inversion value is closer to the true value.

[0115] Considering that a single soil moisture inversion result may be affected by ground interference factors, resulting in that it cannot reflect the long-term stable trend of ground humidity, using the time series stability index can effectively exclude this possibility, so that the soil moisture result of the selected area can better reflect the information required for water-finding favorable areas. Specifically:

[0116] S1.7, select the soil moisture distribution corresponding to the area with high time series characteristic stability as the soil moisture distribution of the target area.

[0117] In specific implementation, as shown in Figure 2 , first, normalize the soil moisture inversion results of multiple time phases.

[0118] Then, calculate the time series stability index of the normalized soil moisture results at the same position and different time phases. The index is the ratio of the standard deviation to the mean of the normalized soil moisture results at the same position and different time phases. The smaller the ratio, the more stable the time series soil moisture characteristics.

[0119] Finally, a threshold value of the temporal stability index is set to screen out the areas with soil moisture distribution less than the threshold value as the target area, and the soil moisture distribution is used as the input condition of the subsequent evidence weight method analysis model.

[0120] S2, obtaining the surface temperature distribution of the target area based on the thermal infrared data;

[0121] In the specific implementation, the thermal infrared data can be obtained by the SDGSAT-1 satellite, and the S2 step can be implemented by any mainstream surface temperature algorithm, which is not limited herein.

[0122] S3, obtaining the alternative water-finding favorable area in the hydrogeological map;

[0123] Through human-computer interaction, the areas meeting the conditions on the hydrogeological map are framed to divide the water-bearing rock and classify the areas with water-richness greater than 100 tons / day-night, and the areas with the overlying water-bearing rock roof buried depth less than 100 m, and the distribution positions of large-diameter wells, machine wells, descending springs and ascending springs are marked in the framed areas, that is, the alternative water-finding favorable area identified by the water geology map.

[0124] Thus, the soil moisture distribution of the target area, the surface temperature distribution of the target area and the alternative water-finding favorable area have been obtained.

[0125] S4, based on the soil moisture distribution of the target area, the surface temperature distribution of the target area and the alternative water-finding favorable area, the evidence weight method analysis model is used to obtain the probability value of water-finding in the target area, and different levels of water-finding favorable areas are obtained based on the preset threshold value.

[0126] The evidence weight method analysis model is based on the Bayesian conditional probability, and the soil moisture distribution obtained by SAR data inversion, the surface temperature distribution obtained by thermal infrared data inversion and the hydrogeological elements (the division of water-bearing rock and the classification of water-richness, the classification of the overlying water-bearing rock roof buried depth and the positions of large-diameter wells, machine wells and hot springs) provide the necessary data basis for the application of the evidence weight method.

[0127] On this basis, the water well position is taken as the verified water-finding favorable area, the correlation degree of each evidence layer and the water-finding favorable area and the prediction evaluation evidence weight value are calculated, and the water-finding favorable area probability of each unit in the prediction area is calculated.

[0128] The prediction and evaluation result of the evidence weight method is a posterior probability map of the underground water-finding favorable area, and the value is between 0 and 1. The size of the posterior probability value corresponds to the size of the water-finding favorable area probability. After determining the critical value in the entire prediction and evaluation range, the areas with posterior probability greater than the critical value in the map are the predicted water-finding favorable areas. The evidence weight method comprehensive analysis can be realized in mature commercial software, which is not described herein.

[0129] Example 2:

[0130] A water-favorable area identification device, comprising:

[0131] a soil moisture distribution acquisition module configured to acquire a soil moisture distribution of a target area based on SAR data;

[0132] a land surface temperature distribution acquisition module configured to acquire a land surface temperature distribution of the target area based on thermal infrared data;

[0133] an alternative water-favorable area acquisition module configured to acquire an alternative water-favorable area in a hydrogeological map;

[0134] an evidence weight method analysis module configured to acquire a water-finding probability value of the target area by using an evidence weight method analysis model based on the soil moisture distribution of the target area, the land surface temperature distribution of the target area, and the alternative water-favorable area, and to divide the water-favorable area into different levels based on a preset threshold.

[0135] Embodiment 3:

[0136] A computer readable storage medium storing a computer program for water-favorable area identification, wherein the computer program causes a computer to perform the following steps:

[0137] acquire a soil moisture distribution of a target area based on SAR data;

[0138] acquire a land surface temperature distribution of the target area based on thermal infrared data;

[0139] acquire an alternative water-favorable area in a hydrogeological map;

[0140] acquire a water-finding probability value of the target area by using an evidence weight method analysis model based on the soil moisture distribution of the target area, the land surface temperature distribution of the target area, and the alternative water-favorable area, and divide the water-favorable area into different levels based on a preset threshold.

[0141] Embodiment 4:

[0142] An electronic device, comprising:

[0143] one or more processors;

[0144] a memory; and

[0145] one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the programs comprise instructions for performing the following steps:

[0146] acquire a soil moisture distribution of a target area based on SAR data;

[0147] Obtain the ground surface temperature distribution of the target area based on the thermal infrared data;

[0148] Obtain the alternative water-finding favorable area in the hydrogeological map;

[0149] Based on the soil moisture distribution of the target area, the ground surface temperature distribution of the target area and the alternative water-finding favorable area, the probability value of water-finding of the target area is obtained by using the evidence weight method analysis model, and different levels of water-finding favorable areas are obtained based on the preset threshold.

[0150] It can be understood that the water-finding favorable area identification device, the computer readable storage medium and the electronic equipment provided by the embodiments of the present application correspond to the water-finding favorable area identification method, and the explanation, examples, advantages and other parts of the related content can refer to the corresponding content in the water-finding favorable area identification method, which will not be repeated here.

[0151] In summary, compared with the prior art, the present application has the following advantages:

[0152] 1. The integrated air-ground combined inversion soil moisture technology is adopted. On the basis of using remote sensing information, the measured value of soil moisture of the ground sampling point is added to correct the soil moisture inversion by SAR data, improve the accuracy of the inverted soil moisture, and reduce the uncertainty, thereby laying a foundation for the water-finding favorable area.

[0153] 2. The professional hydrogeological elements are introduced. The hydrogeological data is professional investigation data of groundwater, and is a discipline for studying the laws of quantity and quality of groundwater changing with space and time and reasonably utilizing groundwater or preventing its hazards. The burial, distribution, movement and composition of groundwater are different in different environments. The surface humidity map inverted by SAR data, the surface temperature map inverted by thermal infrared data and the hydrogeological elements (including the division of water-bearing rock and the classification of water-richness, the classification of the roof buried depth of underlying water-bearing rock and the positions of large-bore wells, machine wells and hot springs) are integrated, and then according to the importance of the water-finding favorable area, the weight values of each evidence are determined, and finally the linear evidence weighting method is used to calculate the probability value of water-finding at any spatial position, so as to distinguish different levels of prediction target areas.

[0154] 3. The present application also considers that the single soil moisture inversion result may be affected by the ground interference factors, so that the long-term stable trend of the ground humidity cannot be reflected. The time sequence stability index is used to effectively exclude this possibility, so that the soil moisture result of the screened area can better reflect the information required by the water-finding favorable area.

[0155] It should be noted that, through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software plus necessary universal hardware platforms. Based on such an understanding, the above technical solutions can be embodied in the form of a software product in essence or in the form of a part of the prior art that makes a contribution. The computer software product can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments. In this article, relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the processes, methods, articles or devices that include a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "includes a" does not exclude the presence of other identical elements in the process, method, article or device that includes the element.

[0156] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for identifying a water-favorable area, characterized in that, The method comprises: obtaining soil moisture distribution of a target area based on SAR data; obtaining surface temperature distribution of the target area based on thermal infrared data; obtaining an alternative water-finding favorable area in a hydrogeological map, wherein the alternative water-finding favorable area comprises a division of water-bearing rock and a region with water-richness grading > 100 tons / day and night and a region with underlying water-bearing rock roof depth grading < 100 m, and is marked with the distribution positions of large-diameter wells, machine wells, descending springs and ascending springs; obtaining a water-finding probability value of the target area by using an evidence weight analysis model based on the soil moisture distribution of the target area, the surface temperature distribution of the target area and the alternative water-finding favorable area, and dividing the water-finding favorable area into different levels based on a preset threshold value; the method for obtaining the soil moisture distribution of the target area based on the SAR data comprises: performing preprocessing on the SAR data to obtain a backscattering coefficient after preprocessing, wherein the preprocessing comprises radiation normalization processing, and the radiation normalization processing is performed by normalizing the backscattering coefficient calculated from the SAR data to the same incident angle, wherein, is the reference incidence angle; θ is the incidence angle of the electromagnetic wave; is the backscattering coefficient in the SAR data; is the backscattering coefficient normalized to the reference incidence angle; forming a mask file based on the urban, artificial building and water area in the land use map of the target area, filling the values of the regions corresponding to the mask file in the backscattering coefficient after preprocessing with 0 to obtain a backscattering coefficient after masking; constructing a lookup table based on an AIEM-Dobson model integrated with a Dobson model; Based on the pre-processed backscattering coefficient, the backscattering coefficient of bare soil in the vegetation-covered area is acquired , wherein, is the backscatter coefficient normalized to a reference incidence angle, is the backscatter coefficient of the vegetation, is the two-layer attenuation factor of the vegetation layer; and θ is the incidence angle of the electromagnetic wave. matching the bare soil backscattering coefficient with the lookup table value, estimating the soil moisture value by using a cost function, and performing low-pass filtering and correction on the estimated soil moisture value; performing normalization processing on the soil moisture inversion results after correction containing multiple time phases; calculating the time sequence stability index of the soil moisture normalization results at the same position and different time phases, and the time sequence stability index is the ratio of the standard deviation to the mean value of the soil moisture normalization results at the same position and different time phases; regarding the regions smaller than a preset threshold value as the soil moisture distribution of the target area.

2. A water-favorable area identification device, characterized by comprising: The device comprises: a soil moisture distribution obtaining module for obtaining the soil moisture distribution of the target area based on the SAR data; a surface temperature distribution obtaining module for obtaining the surface temperature distribution of the target area based on the thermal infrared data; an alternative water-finding favorable area obtaining module for obtaining an alternative water-finding favorable area in a hydrogeological map, wherein the alternative water-finding favorable area comprises a division of water-bearing rock and a region with water-richness grading > 100 tons / day and night and a region with underlying water-bearing rock roof depth grading < 100 m, and is marked with the distribution positions of large-diameter wells, machine wells, descending springs and ascending springs; an evidence weight analysis module for obtaining a water-finding probability value of the target area by using an evidence weight analysis model based on the soil moisture distribution of the target area, the surface temperature distribution of the target area and the alternative water-finding favorable area, and dividing the water-finding favorable area into different levels based on a preset threshold value; the method for obtaining the soil moisture distribution of the target area based on the SAR data comprises: The SAR data is preprocessed to obtain a preprocessed backscattering coefficient, wherein the preprocessing includes radiation normalization processing, and the radiation normalization processing normalizes the backscattering coefficient calculated from the SAR data to the same incident angle, wherein is the reference incidence angle; θ is the incidence angle of the electromagnetic wave; is the backscattering coefficient in the SAR data; is the backscattering coefficient normalized to the reference incidence angle; A mask file is formed based on the town, artificial building and water area in the land use map of the target area, and the value of the region corresponding to the mask file in the preprocessed backscattering coefficient is filled with 0 to obtain a backscattering coefficient after masking; A lookup table is constructed based on an AIEM-Dobson model integrated with a Dobson model; Based on the pre-processed backscattering coefficient, the backscattering coefficient of bare soil in the vegetation-covered area is acquired , wherein, is the backscatter coefficient normalized to a reference incidence angle, is the backscatter coefficient of the vegetation, is the two-layer attenuation factor of the vegetation layer; and θ is the incidence angle of the electromagnetic wave. The bare soil backscattering coefficient is matched with the lookup table value, the soil moisture value is estimated by using a cost function, and the estimated soil moisture value is low-pass filtered and corrected; The normalized soil moisture inversion results of the multiple time phases are normalized; The time sequence stability index of the soil moisture normalization results of the same position and different time phases is calculated, and the time sequence stability index is the ratio of the standard deviation to the mean of the soil moisture normalization results of the same position and different time phases; The region smaller than the preset threshold value is taken as the soil moisture distribution of the target area.

3. A computer-readable storage medium, characterized in that, The computer program for identifying the water-favorable area is stored, and the computer program enables the computer to execute the method for identifying the water-favorable area according to claim 1. 4.An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the programs comprise a program for executing the method for identifying the water-favorable area according to claim 1.

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