Suspected illegal irrigation area identification method based on multi-source data combination

Abstract

This invention relates to the field of agricultural water resources monitoring and remote sensing information processing technology, and provides a method for identifying suspected illegal irrigation areas based on multi-source data fusion. The method includes generating buffer surface elements based on water intake point vector data, constructing a compliant irrigation area mask by combining irrigation district boundary vector data; extracting suspected illegal irrigation pixel grids from actual irrigated area raster data using a reverse mask; creating a spatial analysis grid to aggregate and statistically analyze the pixel grids, and filtering hotspot grid units; vectorizing the hotspot grid units and fusing adjacent elements to generate candidate illegal patches; spatially associating the candidate illegal patches with actual irrigated area raster data, and identifying patches with an effective irrigated area not less than a second threshold as suspected illegal irrigation area patches. Through reverse identification and spatial aggregation filtering, this method achieves rapid location and accurate screening of illegal irrigation areas even without measurement data, thereby improving the efficiency of water resources supervision.

Description

Technical Field

[0001] This invention relates to the field of agricultural water resources monitoring and remote sensing information processing technology, and in particular to a method for identifying suspected illegal irrigation areas based on multi-source data fusion. Background Technology

[0002] Agricultural irrigation is a crucial link in the agricultural production system, and agricultural irrigation water accounts for the largest proportion of total water consumption. However, under the existing management system, due to factors such as the dispersed nature of water users, insufficient metering and monitoring capabilities, and relatively lagging regulatory measures, some areas have illegal irrigation behaviors such as unlicensed water extraction and water extraction exceeding the permitted amount, which pose a potential threat to regional water resource allocation and ecological environment security.

[0003] To meet the needs of refined water resource management, large and medium-sized irrigation areas with complete metering infrastructure currently rely on real-time data collection through the installation of smart water meters at water intakes. The actual water withdrawal data is then automatically compared and analyzed with water withdrawal permit information in the database. Once the actual water withdrawal exceeds the permitted range, a violation warning is triggered. In areas lacking metering facilities, the main method for verifying and recording irrigation activities is manual on-site investigation and fixed-point monitoring.

[0004] However, the applicability of the metering data comparison scheme is strictly dependent on the existence of reliable metering data. For widely distributed, decentralized irrigation areas, especially groundwater irrigation scenarios dominated by well extraction, the highly concealed nature of water extraction activities, their scattered spatial distribution, and the lagging construction of metering facilities result in large-scale regulatory blind spots. On the other hand, the scheme relying on manual investigation is limited by manpower and timeliness, resulting in extremely limited coverage. It is impossible to conduct a comprehensive verification of decentralized irrigation activities on a large spatial scale, accurately distinguish the spatial distribution of compliant irrigation areas from suspected non-compliant irrigation areas, and quantify the scale of violations in each area, thus restricting the accuracy and effectiveness of water resource supervision. Summary of the Invention

[0005] This invention provides a method for identifying suspected illegal irrigation areas based on multi-source data, which solves the technical problem that it is currently impossible to automatically and comprehensively identify and quantify illegal irrigation behavior in scattered irrigation areas on a large scale under the condition of lack of measurement data.

[0006] This invention provides a method for identifying suspected illegal irrigation areas based on multi-source data fusion, comprising the following steps: Buffer surface features are generated based on the vector data of water intake points within the study area, and a compliant irrigation area mask is generated based on the buffer surface features and the vector data of irrigation area boundaries within the study area. Based on the compliant irrigation area mask, reverse mask extraction is performed on the actual irrigation area raster data in the study area to obtain suspected illegal irrigation cell raster. Create a spatial analysis grid covering the suspected illegal irrigation cell raster, use each grid cell of the spatial analysis grid as a partition, perform spatial aggregation statistics on the suspected illegal irrigation cell raster, and designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells; The hotspot grid cells are converted into vector surface features, and the spatially adjacent vector surface features are subjected to boundary fusion processing to generate candidate violation patches. The candidate illegal patches are spatially correlated with the actual irrigation area raster data to determine the effective irrigation area within each candidate illegal patch, and the candidate illegal patches with an effective irrigation area greater than or equal to a second threshold are designated as suspected illegal irrigation area patches.

[0007] According to the method for identifying suspected illegal irrigation areas based on multi-source data fusion provided by the present invention, the step of spatially associating each candidate illegal patch with the actual irrigation area raster data to determine the effective irrigation area within each candidate illegal patch includes: Unify the candidate violation patches and the actual irrigation area raster data into the target coordinate system; Traverse each of the candidate violation patches, and use the spatial geometric range of each candidate violation patch as a clipping mask to perform spatial clipping processing on the actual irrigation area raster data to obtain the target raster cell set contained in each candidate violation patch. Based on the total number of pixels in the target raster pixel set and the preset pixel unit area, the effective irrigation area within each candidate violation patch is determined.

[0008] According to the method for identifying suspected illegal irrigation areas based on multi-source data fusion provided by the present invention, the step of spatially aggregating and statistically analyzing the suspected illegal irrigation cell raster by using each grid cell of the spatial analysis grid as a partition includes: The suspected illegal irrigation pixel raster is mapped into the spatial analysis grid to identify the suspected illegal irrigation pixels contained in each of the grid cells; The pixel values ​​of suspected illegal irrigation pixels contained in each grid cell are partitioned and summed to obtain the statistical value of the pixel corresponding to each grid cell.

[0009] According to the method for identifying suspected illegal irrigation areas based on multi-source data fusion provided by the present invention, the step of generating buffer surface features based on water intake point vector data within the study area, and generating a compliant irrigation area mask based on the buffer surface features and irrigation district boundary vector data within the study area, includes: Obtain the preset maximum irrigation distance corresponding to each water intake point in the water intake point vector data; Spatial buffer analysis is performed with each water intake point as the center and the corresponding preset maximum irrigation distance as the buffer radius to generate buffer surface elements that characterize the influence range of legal water intake; Spatial topological merging is performed on all the buffer surface features and the irrigation district boundary vector data to generate a compliant irrigation area mask.

[0010] According to the method for identifying suspected illegal irrigation areas based on multi-source data provided by the present invention, the step of performing reverse mask extraction on the actual irrigation area raster data within the study area based on the compliant irrigation area mask to obtain suspected illegal irrigation cell raster includes: Identify the target pixels in the actual irrigated area raster data that indicate the presence of irrigation activity; Using the spatial boundary of the compliant irrigation area mask as a reference, reverse mask extraction is performed on the actual irrigation area raster data to delete the first target cell located within the coverage area of ​​the compliant irrigation area mask, and retain the second target cell located outside the spatial boundary of the compliant irrigation area mask, thus obtaining a raster of suspected illegal irrigation cells.

[0011] The method for identifying suspected illegal irrigation areas based on multi-source data provided by the present invention, after identifying candidate illegal patches with effective irrigated areas greater than or equal to a second threshold as suspected illegal irrigation area patches, further includes: Acquire high-resolution remote sensing images of the target area that cover the study area and whose image acquisition time is the same year as the actual irrigation area raster data; The spatial features of each suspected illegal irrigation area are overlaid and matched with the target high-resolution remote sensing image; Extract the actual ground cover features corresponding to each suspected illegal irrigation area patch in the target high-resolution remote sensing image; If the actual ground cover features do not meet the preset actual irrigation conditions features, the corresponding suspected illegal irrigation area patches are deleted, and the remaining suspected illegal irrigation area patches are used as target illegal irrigation area patches.

[0012] According to the method for identifying suspected illegal irrigation areas based on multi-source data fusion provided by the present invention, after selecting the remaining suspected illegal irrigation area patches as target illegal irrigation area patches, the method further includes: Extract the patch identifier, effective irrigation area, and geographic location coordinates of each target illegal irrigation area. Based on the patch identifier, the target effective irrigation area, and the geographic location coordinates of each target illegal irrigation area patch, an attribute table corresponding to each target illegal irrigation area patch is constructed.

[0013] The present invention also provides a device for identifying suspected illegal irrigation areas based on multi-source data fusion, comprising: The mask construction module is used to generate buffer surface features based on the vector data of water intake points in the study area, and to generate a compliant irrigation area mask based on the buffer surface features and the vector data of irrigation area boundaries in the study area. The illegal irrigation pixel extraction module is used to perform reverse mask extraction on the actual irrigation area raster data in the study area based on the compliant irrigation area mask to obtain suspected illegal irrigation pixel raster. The grid aggregation and statistics module is used to create a spatial analysis grid covering the suspected illegal irrigation cell raster, and to perform spatial aggregation and statistics on the suspected illegal irrigation cell raster using each grid cell of the spatial analysis grid as a partition, and to designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells. The illegal irrigation area vectorization module is used to convert the hotspot grid cells into vector surface features and perform boundary fusion processing on the spatially adjacent vector surface features to generate candidate illegal patches; The illegal irrigation area screening module is used to spatially correlate each of the candidate illegal patches with the actual irrigation area raster data, determine the effective irrigation area within each candidate illegal patch, and identify the candidate illegal patches whose effective irrigation area is greater than or equal to a second threshold as suspected illegal irrigation area patches.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the suspected illegal irrigation area identification method based on multi-source data joint as described above.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for identifying suspected illegal irrigation areas based on multi-source data fusion as described above.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the method for identifying suspected illegal irrigation areas based on multi-source data fusion as described above.

[0017] This invention provides a method for identifying suspected illegal irrigation areas based on multi-source data. It constructs a mask for compliant irrigation areas by integrating vector data from water intake points and irrigation district boundaries, and extracts the mask from the actual irrigation area raster data. This achieves accurate separation of suspected illegal irrigation pixels across the entire area without measurement data. Furthermore, through spatial analysis, grid aggregation statistics, and a first threshold screening, discrete pixels are transformed into hotspot grid units. Finally, through vector fusion and a second threshold verification based on the actual effective irrigation area, a vector pattern representing a large-scale contiguous area of ​​suspected illegal irrigation is output. This avoids the screening bias caused by substituting grid geometric area for actual effective irrigation area. Therefore, this invention achieves rapid location and accurate screening of illegal irrigation areas without measurement data, thereby improving the efficiency of water resource supervision. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the present invention or the conventional ones, the drawings used in the embodiments or conventional descriptions will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the method for identifying suspected illegal irrigation areas based on multi-source data fusion provided in this embodiment of the invention.

[0020] Figure 2 This is an example diagram of merging the water intake buffer zone and the irrigation area boundary provided in an embodiment of the present invention.

[0021] Figure 3 This is an example diagram of extracting illegal irrigation pixels using a reverse mask, provided in an embodiment of the present invention.

[0022] Figure 4 This is an example diagram of grid aggregation statistics provided in an embodiment of the present invention.

[0023] Figure 5 This is an example diagram of hotspot grid vectorization and fusion provided in an embodiment of the present invention.

[0024] Figure 6 This is an example diagram of screening illegal irrigation areas provided in an embodiment of the present invention.

[0025] Figure 7 This is an example diagram of the results of checking illegally irrigated areas provided in an embodiment of the present invention.

[0026] Figure 8 This is a schematic diagram of the structure of the suspected illegal irrigation area identification device based on multi-source data fusion provided in an embodiment of the present invention.

[0027] Figure 9 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0029] It should be noted that in the description of this invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the system or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0030] The terms "first," "second," etc., used in this invention are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0031] Figure 1 This is a flowchart illustrating the method for identifying suspected illegal irrigation areas based on multi-source data fusion provided in this embodiment of the invention. Figure 1 As shown, the method includes the following steps 110, 120, 130, 140 and 150.

[0032] Step 110: Generate buffer surface features based on the vector data of water intake points in the study area, and generate a compliant irrigation area mask based on the buffer surface features and the vector data of irrigation area boundaries in the study area.

[0033] Specifically, the water intake point vector data is a dataset of legally registered water intake points within the study area. The data type is vector point features, and each water intake point includes spatial location information. Here, the source of the water intake point vector data can be the water intake permit ledger of the water resources management department, the groundwater well registration database, or other registered water intake datasets, without any restrictions.

[0034] The irrigation district boundary vector data refers to the vector boundary data of the delineated irrigation district areas within the study area. The data type is vector surface features, including the spatial boundaries of large and medium-sized irrigation districts and other planned irrigation districts that have been included in the regulatory system. Here, the irrigation district boundary vector data needs to undergo topological checks to ensure that the boundaries are seamless and non-overlapping, thereby ensuring the accuracy of subsequent spatial merging operations.

[0035] In some embodiments, before generating buffer surface features based on water intake point vector data within the study area, and generating a compliant irrigation area mask based on the buffer surface features and irrigation district boundary vector data within the study area, all input data can be uniformly projected to the same coordinate system to ensure the accuracy of subsequent spatial analysis.

[0036] In this embodiment, when generating buffer surface features, spatial buffer analysis is performed on each water intake point in the water intake point vector data as the center to generate buffer surface features that characterize the influence range of legal water intake.

[0037] The buffer zone surface element is used to characterize the spatial influence area of ​​a legal water intake within a certain radius of its perimeter, which can be compliantly irrigated. Its geometric shape is a circular surface element with each water intake point as the center and a preset buffer radius as the radius. In practical applications, the buffer radius of the buffer zone surface element can be set according to the actual situation of the study area and the maximum compliant irrigation range of the water intake. For example, the buffer radius can be set to 300 meters.

[0038] When generating the compliant irrigation area mask, all buffer surface features are spatially topologically merged with the irrigation area boundary vector data to generate the compliant irrigation area mask; during the spatial topological merging, all buffer surface feature layers are spatially overlaid and merged with the irrigation area boundary vector layer to form a seamless, non-overlapping single continuous vector mask, such as... Figure 2 As shown, the merged compliant irrigation area has a smooth and continuous mask boundary, which includes both the large contiguous compliant area within the irrigation district and the buffer zone around each legal water intake.

[0039] Step 120: Based on the compliant irrigation area mask, perform reverse mask extraction on the actual irrigation area raster data in the study area to obtain suspected illegal irrigation cell raster.

[0040] The actual irrigated area raster data is the annual spatial distribution raster data of the actual irrigated area generated based on multi-source remote sensing images. In practical applications, the raster cell values ​​of the actual irrigated area raster data are expressed in a binarized manner. A cell value of 1 indicates that there is irrigation activity at that location in the current year, and a cell value of 0 indicates that there is no irrigation activity at that location.

[0041] It should be noted that, in this embodiment, reverse mask extraction refers to performing a spatial exclusion operation on the actual irrigation area raster data based on the spatial boundary of the compliant irrigation area mask. That is, the irrigation cells located within the coverage area of ​​the compliant irrigation area mask are deleted, and only the irrigation cells located outside the spatial boundary of the compliant irrigation area mask are retained, thereby obtaining the raster of suspected illegal irrigation cells.

[0042] The suspected non-compliant irrigation cell raster only includes and displays irrigation cells that are spatially separated from all compliant areas; that is, cells located outside the known compliant irrigation area but still exhibiting actual irrigation activity. Figure 3 As shown, the raster of suspected illegal irrigation cells extracted by reverse masking retains only illegal cells with a cell value of 1, showing the potential spatial distribution of illegality outside the compliant area, and providing a clean and accurate input dataset for subsequent grid aggregation statistics.

[0043] In some embodiments, the pixel values ​​of each pixel in the suspected illegal irrigation pixel raster are kept in a binarized state consistent with the original actual irrigation area raster data, that is, pixels with a value of 1 are retained.

[0044] Step 130: Create a spatial analysis grid covering the suspected illegal irrigation cell raster, use each grid cell of the spatial analysis grid as a partition, perform spatial aggregation statistics on the suspected illegal irrigation cell raster, and designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells.

[0045] The spatial analysis grid is a standardized polygonal grid covering the entire study area. Its grid cells are regular polygonal elements, such as squares. The size of the grid cells can be dynamically set according to the spatial resolution of the study area area and the actual irrigation area raster data. In some embodiments, the grid cell size can be set to 1km×1km. In other embodiments, it can also be appropriately adjusted according to the scale requirements and analysis accuracy requirements of the specific study area. This application does not limit the specific value of the grid cell size.

[0046] When performing spatial aggregation statistics, the spatial range of each grid cell is used as an independent statistical partition. The suspected illegal irrigation pixels contained in each grid cell are subjected to partition statistical operation to obtain the statistical value corresponding to each grid cell.

[0047] Here, the statistical values ​​reflect the spatial concentration intensity of illegal irrigation activities within the area of ​​each grid cell. A higher statistical value indicates a higher concentration of illegal irrigation activities within that grid cell. Figure 4 As shown, the statistical values ​​of each grid cell are presented in shades of color, with darker colors indicating a stronger concentration of illegal irrigation in that area.

[0048] When determining hotspot grid cells, a first threshold is set for the above spatial aggregation statistics. Grid cells with statistical values ​​greater than the first threshold are selected as hotspot grid cells. Hotspot grid cells represent areas where illegal irrigation behavior is highly concentrated and have a strong spatial agglomeration effect.

[0049] The first threshold can be adjusted according to factors such as the geographical scale of the study area and the spatial resolution of the raster. In some embodiments, the first threshold can be set to 1000, which requires the sum of the statistical values ​​of suspected illegal irrigation pixels in the grid cell to be greater than 1000. In other embodiments, the first threshold can also be set to other reasonable values ​​according to the actual situation of the study area, and there is no restriction on this.

[0050] Step 140: Convert the hotspot grid cells into vector surface features, and perform boundary fusion processing on the spatially adjacent vector surface features to generate candidate violation patches.

[0051] It should be understood that hotspot grid cells are grid cells whose statistical values ​​are greater than the first threshold. Their initial data format is raster format. Since raster format is not conducive to independent geographic feature management, attribute query and accurate spatial measurement, the raster results of hotspot grid cells are converted into vector surface features in this embodiment.

[0052] Specifically, the transformation operation converts the raster cell geometry of each hotspot grid cell into corresponding independent vector polygon features, generating a series of independent square vector grid surface features. The initially transformed vector surface features consist of a large number of independent square grids, with independent internal boundaries between adjacent grids, making it difficult to intuitively represent a complete and continuous illegal irrigation area. Therefore, in this embodiment, boundary fusion processing is performed on spatially adjacent vector surface features to eliminate the internal boundaries between adjacent grids, merging multiple consecutive adjacent hotspot grid cells into a smooth and continuous overall patch.

[0053] In boundary fusion processing, spatially adjacent vector surface features refer to vector surface features that share a boundary or share vertices in spatial location. For example, fusion can be performed only on vector surface features that are adjacent on the edges to ensure that the generated candidate illegal patches represent real contiguous illegal irrigation areas; for example, vector surface features that are adjacent at the corners can also be included in the fusion range without restriction.

[0054] like Figure 5 As shown, after boundary fusion processing, the boundaries of the candidate illegal patches are continuous and smooth, without internal broken lines, and each candidate illegal patch represents the whole of the potential illegal irrigation area that is spatially contiguous.

[0055] Step 150: Spatially correlate each candidate violation patch with the actual irrigation area raster data to determine the effective irrigation area within each candidate violation patch, and designate the candidate violation patches with an effective irrigation area greater than or equal to a second threshold as suspected illegal irrigation area patches.

[0056] It should be understood that the geometric boundary area of ​​candidate illegal patches is usually larger than the actual area where irrigation activities actually occur within the patch. If the geometric boundary area of ​​candidate illegal patches is directly used for threshold screening, the area estimate will be too high, which will affect the accuracy of the screening results.

[0057] Based on this, this embodiment spatially correlates each candidate illegal patch with the actual irrigation area raster data to determine the effective irrigation area actually contained within each candidate illegal patch, thereby performing more accurate area verification and threshold screening.

[0058] Among them, the effective irrigation area refers to the total actual ground area occupied by the raster cells with irrigation activities within the spatial geometry of each candidate illegal patch. Since the pixel values ​​of the actual irrigation area raster data are expressed in a binarized manner, the effective irrigation area reflects the actual surface area where irrigation activities occur within the candidate illegal patch, rather than the area enclosed by the grid geometry.

[0059] After determining the effective irrigation area within each candidate illegal patch, a second threshold is set. Candidate illegal patches with an effective irrigation area greater than or equal to the second threshold are retained as suspected illegal irrigation areas; candidate illegal patches with an effective irrigation area less than the second threshold are removed.

[0060] Here, the second threshold is used to filter out candidate illegal patches with small effective irrigation area and low regulatory priority, so that the final identification results focus on large-scale, concentrated areas of suspected illegal irrigation.

[0061] In practical applications, the second threshold can be dynamically set according to factors such as the size of the study area, regulatory requirements, and resource allocation. In some embodiments, the second threshold can be set to 10,000 mu to focus on large-scale contiguous areas suspected of illegal irrigation with high regulatory priority. In other embodiments, the second threshold can also be set to other reasonable values ​​according to the regulatory needs of the specific study area, without any restrictions.

[0062] like Figure 6 As shown, after screening for effective irrigation area, the final output of suspected illegal irrigation area patches only retains contiguous patches with effective irrigation area meeting the scale requirements.

[0063] The proposed method for identifying suspected illegal irrigation areas based on multi-source data integration constructs a mask for compliant irrigation areas by integrating vector data from water intake points and vector data from irrigation district boundaries. It then performs reverse mask extraction on the actual irrigation area raster data, achieving accurate separation of suspected illegal irrigation pixels across the entire area without measurement data. Furthermore, through spatial analysis, grid aggregation statistics, and a first threshold screening, discrete pixels are transformed into hotspot grid units. Finally, through vector fusion and a second threshold verification based on the actual effective irrigation area, a vector pattern representing a large-scale contiguous area of ​​suspected illegal irrigation is output. This avoids the screening bias caused by substituting grid geometric area for actual effective irrigation area. Therefore, this invention achieves rapid location and accurate screening of illegal irrigation areas without measurement data, thereby improving the efficiency of water resource supervision.

[0064] In some embodiments, spatially associating each of the candidate violation patches with the actual irrigation area raster data to determine the effective irrigation area within each of the candidate violation patches includes: Unify the candidate violation patches and the actual irrigation area raster data into the target coordinate system; Traverse each of the candidate violation patches, and use the spatial geometric range of each candidate violation patch as a clipping mask to perform spatial clipping processing on the actual irrigation area raster data to obtain the target raster cell set contained in each candidate violation patch. Based on the total number of pixels in the target raster pixel set and the preset pixel unit area, the effective irrigation area within each candidate violation patch is determined.

[0065] In this embodiment, before performing the spatial clipping operation, the vector data of the candidate illegal patches and the raster data of the actual irrigation area are uniformly projected to the target coordinate system, such as the metric coordinate system, which is a plane rectangular coordinate system obtained by transforming the spherical geographic coordinates based on the map projection using the length as the basic unit.

[0066] Here, the specific type of the target coordinate system can be selected according to the geographical location of the study area. In some embodiments, the CGCS2000 metric coordinate system can be used; in other embodiments, other metric projection coordinate systems that meet the accuracy requirements can also be used, and there is no limitation on this.

[0067] For each candidate illegal patch, its spatial geometric contour boundary is extracted, and the actual irrigation area raster data is cropped patch by patch using the contour boundary as a mask, thereby extracting all raster pixels within the spatial geometric range of the candidate illegal patch and forming a target raster pixel set corresponding to the candidate illegal patch.

[0068] Specifically, the target raster cell set only includes raster cells within the spatial geometry of the candidate illegal patch that have a cell value indicating the presence of irrigation activity, i.e., raster cells with a cell value of 1. Raster cells with a cell value of 0 or NoData are not included in the target raster cell set.

[0069] Finally, the total number of pixels in the target raster pixel set corresponding to each candidate illegal patch is counted, and the total number of pixels is multiplied by the preset pixel unit area to calculate the effective irrigation area within the candidate illegal patch.

[0070] Here, the preset pixel unit area is the actual ground area represented by a single raster pixel in the actual irrigation area raster data. For example, if the spatial resolution of the actual irrigation area raster data is 10 meters, then the preset pixel unit area is 100 square meters. If the spatial resolution of the raster data is different, the preset pixel unit area will be set accordingly based on the actual resolution, which will not be elaborated here.

[0071] The method for identifying suspected illegal irrigation areas based on multi-source data provided in this invention improves the accuracy of the effective irrigation area where irrigation activities actually occur within candidate illegal patches by using a coordinate system, patch-by-patch spatial cropping, and pixel counting.

[0072] In some embodiments, the step of spatially aggregating and statistically analyzing the suspected illegal irrigation raster cells by dividing each grid cell of the spatial analysis grid into partitions includes: The suspected illegal irrigation pixel raster is mapped into the spatial analysis grid to identify the suspected illegal irrigation pixels contained in each of the grid cells; The pixel values ​​of suspected illegal irrigation pixels contained in each grid cell are partitioned and summed to obtain the statistical value of the pixel corresponding to each grid cell.

[0073] In this embodiment, based on the spatial coordinate correspondence, the suspected illegal irrigation pixel grid is spatially superimposed with the spatial analysis grid. All suspected illegal irrigation pixels within the unit range are identified and summarized one by one according to the grid unit. For pixels located at the boundary of the grid unit, the grid unit where the pixel center point is located is taken as the partition to which the pixel belongs.

[0074] Since the pixel values ​​representing irrigation activity in the suspected illegal irrigation pixel grid are all 1, the pixel values ​​of all suspected illegal irrigation pixels contained in each grid cell are summed. The resulting statistical value is the total number of suspected illegal irrigation pixels in that grid cell.

[0075] It should be understood that the statistical value quantifies the spatial concentration intensity of illegal irrigation activities within each grid cell area: the larger the statistical value, the more pixels there are in the grid cell with illegal irrigation activities, and the higher the spatial concentration of illegal irrigation; the smaller the statistical value, the sparser the illegal irrigation activities are in the grid cell.

[0076] In some embodiments, for grid cells that do not contain any suspected illegal irrigation cells, the statistical value of the grid cell is recorded as 0 or NoData, so that it can be automatically excluded in subsequent processing steps.

[0077] The method for identifying suspected illegal irrigation areas based on multi-source data provided in this invention uses a partitioned summation method to statistically analyze suspected illegal irrigation pixels in each grid cell. This effectively quantifies the spatial clustering intensity, distribution density, and hotspot areas of illegal irrigation activities in different geographical locations, thereby identifying irrigation areas where illegal activities are highly concentrated.

[0078] In some embodiments, generating buffer surface features based on water intake point vector data within the study area, and generating a compliant irrigation area mask based on the buffer surface features and irrigation district boundary vector data within the study area, includes: Obtain the preset maximum irrigation distance corresponding to each water intake point in the water intake point vector data; Spatial buffer analysis is performed with each water intake point as the center and the corresponding preset maximum irrigation distance as the buffer radius to generate buffer surface elements that characterize the influence range of legal water intake; Spatial topological merging is performed on all the buffer surface features and the irrigation district boundary vector data to generate a compliant irrigation area mask.

[0079] Among them, the preset maximum irrigation distance is used to characterize the maximum spatial radius of compliant irrigation coverage that a single legal water intake can achieve in its surrounding area, and is a key parameter for defining the compliant influence range of legal water intakes.

[0080] In practical applications, each water intake point can adopt a preset maximum irrigation distance; alternatively, all water intakes in the study area can adopt the same preset maximum irrigation distance without restriction.

[0081] In this embodiment, a circular surface feature is generated with the spatial coordinates of each water intake point as the center point and the preset maximum irrigation distance corresponding to the water intake point as the radius. This circular surface feature represents the spatial influence area of ​​the water intake point within its compliant buffer distance range. Then, spatial buffer analysis is performed on all water intake points in the water intake point vector data one by one. Finally, a set of buffer surface features corresponding to the number of water intake points is obtained. The geometric shape of each buffer surface feature is a regular circle, and the spatial range is determined by the coordinates of the water intake point and its corresponding preset maximum irrigation distance.

[0082] Finally, all buffer zone surface feature layers and irrigation area boundary vector layers are spatially overlaid and merged into a unified vector surface feature. During the spatial topological merging, the merging result is topologically processed to ensure that the generated compliant irrigation area mask meets the requirements of seamless and non-overlapping topological integrity, that is, there are no blank gaps or spatial overlapping areas between the constituent surface features.

[0083] It should be understood that the seamless and non-overlapping topological compliance requirements in this embodiment can ensure that compliant irrigation pixels can be completely and accurately excluded in the subsequent reverse mask extraction operation, without missing any known compliant irrigation areas, thereby reducing the false judgment rate of suspected illegal irrigation pixels.

[0084] like Figure 2 As shown, the compliant irrigation area mask boundary generated after spatial topology merging is smooth and continuous. It includes both the large and medium-sized irrigation area defined by the irrigation area boundary vector data and the surrounding influence area covered by the buffer surface features of each legal water intake. Together, they constitute a complete compliant spatial range.

[0085] The proposed method for identifying suspected illegal irrigation areas based on multi-source data integration provides the following: By performing spatial buffer analysis on each water intake with a preset maximum irrigation distance as the radius, and merging all generated buffer surface features with irrigation area boundary vector data in a spatial topology, the method improves the comprehensive coverage of the compliant irrigation area mask, thereby reducing the false positive rate of suspected illegal irrigation pixel identification.

[0086] In some embodiments, the step of performing reverse mask extraction on the actual irrigated area raster data within the study area based on the compliant irrigation area mask to obtain suspected illegal irrigation cell raster data includes: Identify the target pixels in the actual irrigated area raster data that indicate the presence of irrigation activity; Using the spatial boundary of the compliant irrigation area mask as a reference, reverse mask extraction is performed on the actual irrigation area raster data to delete the first target cell located within the coverage area of ​​the compliant irrigation area mask, and retain the second target cell located outside the spatial boundary of the compliant irrigation area mask, thus obtaining a raster of suspected illegal irrigation cells.

[0087] Specifically, the raster cell values ​​of the actual irrigated area raster data are expressed in a binary manner, that is, a raster cell with a value of 1 indicates that there is irrigation activity in the corresponding year at that spatial location; a raster cell with a value of 0 or NoData indicates that there is no irrigation activity at that spatial location.

[0088] In this embodiment, before performing reverse mask extraction, a pixel value of 1 is used as the criterion to determine all target pixels representing irrigation activities in the actual irrigation area raster data.

[0089] Next, all the identified target pixels are divided into two categories: one category consists of target pixels located within the mask coverage area of ​​the compliant irrigation area, which are called the first target pixels; the other category consists of target pixels located outside the mask space boundary of the compliant irrigation area, which are called the second target pixels.

[0090] Finally, a spatial exclusion operation is performed based on the spatial boundary of the compliant irrigation area mask, removing the first target cell from all target cells and retaining only the second target cell, thereby outputting a raster of suspected non-compliant irrigation cells containing only the second target cell.

[0091] It should be understood that the first target pixel represents irrigation pixels located within the known compliant irrigation area, which constitute compliant irrigation behavior and should be excluded; the second target pixel represents pixels located outside all known compliant areas but still having actual irrigation activities, that is, pixels that had irrigation activities in the current year but whose irrigation source cannot be explained by the known compliant scope, which constitute suspected illegal irrigation behavior and should be retained.

[0092] The suspected illegal irrigation area identification method based on multi-source data provided in this invention achieves accurate separation of suspected illegal irrigation pixels across the entire area by performing reverse mask extraction based on a compliant irrigation area mask.

[0093] In some embodiments, after classifying the candidate violation patches with effective irrigated areas greater than or equal to a second threshold as suspected violation irrigation area patches, the method further includes: Acquire high-resolution remote sensing images of the target area that cover the study area and whose image acquisition time is the same year as the actual irrigation area raster data; The spatial features of each suspected illegal irrigation area are overlaid and matched with the target high-resolution remote sensing image; Extract the actual ground cover features corresponding to each suspected illegal irrigation area patch in the target high-resolution remote sensing image; If the actual ground cover features do not meet the preset actual irrigation conditions features, the corresponding suspected illegal irrigation area patches are deleted, and the remaining suspected illegal irrigation area patches are used as target illegal irrigation area patches.

[0094] Specifically, the target high-resolution remote sensing image refers to remote sensing imagery with a spatial resolution superior to that of the actual irrigation area raster data, and which covers the entire study area. The image type of the target high-resolution remote sensing imagery can be optical true-color composite imagery, false-color composite imagery, or other multi-band remote sensing imagery with ground feature identification capabilities.

[0095] It should be noted that the acquisition time of the target high-resolution remote sensing image must be the same as the year corresponding to the actual irrigated area raster data to ensure consistency between the image and the recognition results in the time dimension and avoid comparison deviations caused by interannual land use changes.

[0096] In some embodiments, the spatial resolution of the target high-resolution remote sensing image may be better than 10 meters; in other embodiments, other resolutions that meet the requirements for visualization verification may be used depending on the availability of data, and there are no restrictions on this.

[0097] In this embodiment, the vector outlines of each suspected illegal irrigation area patch are superimposed onto the corresponding spatial location of the target high-resolution remote sensing image, achieving precise alignment and overlay display of the patch and the image in the spatial coordinate system. Through spatial feature overlay matching, the surface cover status corresponding to each suspected illegal irrigation area patch on the high-resolution remote sensing image can be intuitively presented, providing intuitive visual information for the extraction and verification of the true ground cover features.

[0098] Here, the true ground cover features refer to the visual and spectral characteristics of surface features within the spatial range of suspected illegal irrigation areas in the high-resolution remote sensing image of the target, which can be obtained through visual interpretation or automated feature matching.

[0099] When using visual interpretation, the ground cover information is extracted by observing the surface visual features of the corresponding areas of suspected illegal irrigation areas on the target high-resolution remote sensing image. This includes, but is not limited to, crop vegetation cover features, such as farmland green vegetation cover and crop planting textures; irrigation infrastructure features, such as irrigation canal traces and water pipelines; and topographic features, such as terrain slope and aspect.

[0100] If a suspected illegal irrigation area in a map corresponds to a region in a target high-resolution remote sensing image, and its actual ground cover characteristics do not meet the preset characteristics of actual irrigation conditions, such as... Figure 7As shown, if there is no obvious evidence of irrigation within a patch, the surface is covered by permanent water bodies, bare land, or construction land, or the terrain of the patch obviously does not meet irrigation conditions, then the patch is marked as an unreasonable patch and deleted; if the preset characteristics of real irrigation conditions are met, then the patch is retained.

[0101] The target illegal irrigation area patches are suspected illegal irrigation area patches retained after verification by high-resolution remote sensing imagery of the target. Their actual ground cover characteristics are consistent with the actual irrigation conditions, and they have a high degree of identification credibility. After the deletion operation is completed, the attribute table of the remaining patches can be updated synchronously to ensure the integrity and accuracy of the data.

[0102] The method for identifying suspected illegal irrigation areas based on multi-source data provided in this invention verifies the reasonableness of suspected illegal irrigation area patches by combining high-resolution remote sensing images of the target with overlay. This effectively eliminates false positive patches caused by factors such as seasonal water body misjudgment, interannual land use changes, or remote sensing interpretation errors, thereby improving the accuracy and reliability of the target illegal irrigation area patches.

[0103] In some embodiments, after selecting the remaining suspected illegal irrigation area patches as target illegal irrigation area patches, the method further includes: Extract the patch identifier, effective irrigation area, and geographic location coordinates of each target illegal irrigation area. Based on the patch identifier, the target effective irrigation area, and the geographic location coordinates of each target illegal irrigation area patch, an attribute table corresponding to each target illegal irrigation area patch is constructed.

[0104] Here, the patch identifier is a unique number for each target illegal irrigation area patch, used to distinguish and index each patch in the results dataset. The patch identifier can be generated using an automatically incrementing integer numbering method, or it can be a combination of coding methods including the provincial administrative unit code, year, and serial number, so as to facilitate hierarchical management and traceability of the results data.

[0105] The geographic location coordinate attribute is used to characterize the location information of each target illegal irrigation area patch in geospatial space, so as to facilitate users to quickly locate and verify it; in some embodiments, the geographic location coordinate attribute may include the latitude and longitude coordinates of the geometric center point of each target illegal irrigation area patch and the provincial administrative unit where the patch is located.

[0106] In this implementation, the attribute table is a structured data table, with each target illegal irrigation area as the record unit. Each record contains fields such as the corresponding patch identifier, the target effective irrigation area, and the geographic location coordinates.

[0107] In practical applications, the attribute table data format supports export in vector Shapefile format, raster format, and statistical table format, so as to connect with water resources supervision and law enforcement systems, geographic information platforms, and statistical analysis tools.

[0108] The method for identifying suspected illegal irrigation areas based on multi-source data provided in this invention achieves standardized management of the identification results of illegal irrigation areas by constructing a structured attribute table for each target illegal irrigation area patch, which includes patch identifier, target effective irrigation area and geographic location coordinates.

[0109] The following describes the suspected illegal irrigation area identification device based on multi-source data joint provided by the embodiments of the present invention. The suspected illegal irrigation area identification device based on multi-source data joint described below can be referred to in correspondence with the suspected illegal irrigation area identification method based on multi-source data joint described above.

[0110] The suspected illegal irrigation area identification device based on multi-source data fusion provided in this embodiment of the invention, such as... Figure 8 As shown, it includes the following modules: The mask construction module 810 is used to generate buffer surface features based on the vector data of water intake points in the study area, and to generate a compliant irrigation area mask based on the buffer surface features and the vector data of irrigation area boundaries in the study area. The illegal irrigation pixel extraction module 820 is used to perform reverse mask extraction on the actual irrigation area raster data in the study area based on the compliant irrigation area mask to obtain suspected illegal irrigation pixel raster. The grid aggregation and statistics module 830 is used to create a spatial analysis grid covering the suspected illegal irrigation cell grid, and to perform spatial aggregation and statistics on the suspected illegal irrigation cell grid by taking each grid cell of the spatial analysis grid as a partition, and to take the grid cell with the statistical value greater than a first threshold as the hot grid cell. The illegal irrigation area vectorization module 840 is used to convert the hotspot grid cells into vector surface features and perform boundary fusion processing on the spatially adjacent vector surface features to generate candidate illegal patches. The illegal irrigation area screening module 850 is used to spatially correlate each of the candidate illegal patches with the actual irrigation area raster data, determine the effective irrigation area within each candidate illegal patch, and identify the candidate illegal patches whose effective irrigation area is greater than or equal to a second threshold as suspected illegal irrigation area patches.

[0111] The suspected illegal irrigation area identification device based on multi-source data provided in this invention integrates vector data of water intake points and vector data of irrigation area boundaries to construct a mask of compliant irrigation areas, and performs reverse mask extraction on the actual irrigation area raster data to achieve accurate separation of suspected illegal irrigation pixels across the entire area under the condition of no metering data. Then, through spatial analysis grid aggregation statistics and first threshold screening, discrete pixels are transformed into hotspot grid units. Finally, through vector fusion and second threshold verification based on the real effective irrigation area, vector pattern results representing large-scale contiguous suspected illegal irrigation areas are output, avoiding the screening bias caused by substituting grid geometric area for real effective irrigation area. Thus, this invention achieves rapid location and accurate screening of illegal irrigation areas under the condition of no metering data, thereby improving the efficiency of water resource supervision.

[0112] Figure 9 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 9 As shown, the electronic device may include: a processor 910, a communications interface 920, a memory 930, and a communications bus 940, wherein the processor 910, the communications interface 920, and the memory 930 communicate with each other via the communications bus 940. The processor 910 can call logical instructions in the memory 930 to execute a method for identifying suspected illegal irrigation areas based on multi-source data fusion. This method includes: Buffer surface features are generated based on the vector data of water intake points within the study area, and a compliant irrigation area mask is generated based on the buffer surface features and the vector data of irrigation area boundaries within the study area. Based on the compliant irrigation area mask, reverse mask extraction is performed on the actual irrigation area raster data in the study area to obtain suspected illegal irrigation cell raster. Create a spatial analysis grid covering the suspected illegal irrigation cell raster, use each grid cell of the spatial analysis grid as a partition, perform spatial aggregation statistics on the suspected illegal irrigation cell raster, and designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells; The hotspot grid cells are converted into vector surface features, and the spatially adjacent vector surface features are subjected to boundary fusion processing to generate candidate violation patches. The candidate illegal patches are spatially correlated with the actual irrigation area raster data to determine the effective irrigation area within each candidate illegal patch, and the candidate illegal patches with an effective irrigation area greater than or equal to a second threshold are designated as suspected illegal irrigation area patches.

[0113] Furthermore, the logical instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the conventional, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., each of which can store program code.

[0114] On the other hand, embodiments of the present invention also provide a computer program product, the computer program product including a computer program, the computer program being able to be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer is able to execute the suspected illegal irrigation area identification method based on multi-source data joint provided in each of the above embodiments, the method including: Buffer surface features are generated based on the vector data of water intake points within the study area, and a compliant irrigation area mask is generated based on the buffer surface features and the vector data of irrigation area boundaries within the study area. Based on the compliant irrigation area mask, reverse mask extraction is performed on the actual irrigation area raster data in the study area to obtain suspected illegal irrigation cell raster. Create a spatial analysis grid covering the suspected illegal irrigation cell raster, use each grid cell of the spatial analysis grid as a partition, perform spatial aggregation statistics on the suspected illegal irrigation cell raster, and designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells; The hotspot grid cells are converted into vector surface features, and the spatially adjacent vector surface features are subjected to boundary fusion processing to generate candidate violation patches. The candidate illegal patches are spatially correlated with the actual irrigation area raster data to determine the effective irrigation area within each candidate illegal patch, and the candidate illegal patches with an effective irrigation area greater than or equal to a second threshold are designated as suspected illegal irrigation area patches.

[0115] In another aspect, embodiments of the present invention also provide a non-transitory computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program is implemented to perform the suspected illegal irrigation area identification method based on multi-source data joint analysis provided in each of the above embodiments. The method includes: Buffer surface features are generated based on the vector data of water intake points within the study area, and a compliant irrigation area mask is generated based on the buffer surface features and the vector data of irrigation area boundaries within the study area. Based on the compliant irrigation area mask, reverse mask extraction is performed on the actual irrigation area raster data in the study area to obtain suspected illegal irrigation cell raster. Create a spatial analysis grid covering the suspected illegal irrigation cell raster, use each grid cell of the spatial analysis grid as a partition, perform spatial aggregation statistics on the suspected illegal irrigation cell raster, and designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells; The hotspot grid cells are converted into vector surface features, and the spatially adjacent vector surface features are subjected to boundary fusion processing to generate candidate violation patches. The candidate illegal patches are spatially correlated with the actual irrigation area raster data to determine the effective irrigation area within each candidate illegal patch, and the candidate illegal patches with an effective irrigation area greater than or equal to a second threshold are designated as suspected illegal irrigation area patches.

[0116] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0117] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the conventional, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in each of the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for identifying suspected illegal irrigation areas based on multi-source data fusion, characterized in that, include: Buffer surface features are generated based on the vector data of water intake points within the study area, and a compliant irrigation area mask is generated based on the buffer surface features and the vector data of irrigation area boundaries within the study area. Based on the compliant irrigation area mask, reverse mask extraction is performed on the actual irrigation area raster data in the study area to obtain suspected illegal irrigation cell raster. Create a spatial analysis grid covering the suspected illegal irrigation cell grid, use each grid cell of the spatial analysis grid as a partition, perform spatial aggregation statistics on the suspected illegal irrigation cell grid, and designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells; The hotspot grid cells are converted into vector surface features, and the spatially adjacent vector surface features are subjected to boundary fusion processing to generate candidate violation patches. The candidate illegal patches are spatially correlated with the actual irrigation area raster data to determine the effective irrigation area within each candidate illegal patch, and the candidate illegal patches with an effective irrigation area greater than or equal to a second threshold are designated as suspected illegal irrigation area patches.

2. The method for identifying suspected illegal irrigation areas based on multi-source data fusion according to claim 1, characterized in that, The step of spatially associating each of the candidate violation patches with the actual irrigation area raster data to determine the effective irrigation area within each of the candidate violation patches includes: Unify the candidate violation patches and the actual irrigation area raster data into the target coordinate system; Traverse each of the candidate violation patches, and use the spatial geometric range of each candidate violation patch as a clipping mask to perform spatial clipping processing on the actual irrigation area raster data to obtain the target raster cell set contained in each candidate violation patch. Based on the total number of pixels in the target raster pixel set and the preset pixel unit area, the effective irrigation area within each candidate violation patch is determined.

3. The method for identifying suspected illegal irrigation areas based on multi-source data fusion according to claim 1, characterized in that, The step of spatially aggregating and statistically analyzing the suspected illegal irrigation raster cells, using each grid cell of the spatial analysis grid as a partition, includes: The suspected illegal irrigation pixel raster is mapped into the spatial analysis grid to identify the suspected illegal irrigation pixels contained in each of the grid cells; The pixel values ​​of suspected illegal irrigation pixels contained in each grid cell are partitioned and summed to obtain the statistical value of the pixel corresponding to each grid cell.

4. The method for identifying suspected illegal irrigation areas based on multi-source data fusion according to claim 1, characterized in that, The process of generating buffer surface features based on water intake point vector data within the study area, and generating a compliant irrigation area mask based on the buffer surface features and irrigation district boundary vector data within the study area, includes: Obtain the preset maximum irrigation distance corresponding to each water intake point in the water intake point vector data; Spatial buffer analysis is performed with each water intake point as the center and the corresponding preset maximum irrigation distance as the buffer radius to generate buffer surface elements that characterize the influence range of legal water intake; Spatial topological merging is performed on all the buffer surface features and the irrigation district boundary vector data to generate a compliant irrigation area mask.

5. The method for identifying suspected illegal irrigation areas based on multi-source data fusion according to claim 1, characterized in that, The step of performing reverse mask extraction on the actual irrigated area raster data within the study area based on the compliant irrigation area mask to obtain raster cells suspected of violating irrigation regulations includes: Identify the target pixels in the actual irrigated area raster data that indicate the presence of irrigation activity; Using the spatial boundary of the compliant irrigation area mask as a reference, reverse mask extraction is performed on the actual irrigation area raster data to delete the first target cell located within the coverage area of ​​the compliant irrigation area mask, and retain the second target cell located outside the spatial boundary of the compliant irrigation area mask, thus obtaining a raster of suspected illegal irrigation cells.

6. The method for identifying suspected illegal irrigation areas based on multi-source data fusion according to claim 1, characterized in that, After classifying the candidate illegal patches with an effective irrigation area greater than or equal to the second threshold as suspected illegal irrigation areas, the method further includes: Acquire high-resolution remote sensing images of the target area that cover the study area and whose image acquisition time is the same year as the actual irrigation area raster data; The spatial features of each suspected illegal irrigation area are overlaid and matched with the target high-resolution remote sensing image; Extract the actual ground cover features corresponding to each suspected illegal irrigation area patch in the target high-resolution remote sensing image; If the actual ground cover features do not meet the preset actual irrigation conditions features, the corresponding suspected illegal irrigation area patches are deleted, and the remaining suspected illegal irrigation area patches are used as target illegal irrigation area patches.

7. The method for identifying suspected illegal irrigation areas based on multi-source data fusion according to claim 1, characterized in that, After selecting the remaining suspected illegal irrigation area patches as target illegal irrigation area patches, the method further includes: Extract the patch identifier, effective irrigation area, and geographic location coordinates of each target illegal irrigation area. Based on the patch identifier, the target effective irrigation area, and the geographic location coordinates of each target illegal irrigation area patch, an attribute table corresponding to each target illegal irrigation area patch is constructed.

8. A device for identifying suspected illegal irrigation areas based on multi-source data fusion, characterized in that, include: The mask construction module is used to generate buffer surface features based on the vector data of water intake points in the study area, and to generate a compliant irrigation area mask based on the buffer surface features and the vector data of irrigation area boundaries in the study area. The illegal irrigation pixel extraction module is used to perform reverse mask extraction on the actual irrigation area raster data in the study area based on the compliant irrigation area mask to obtain suspected illegal irrigation pixel raster. The grid aggregation and statistics module is used to create a spatial analysis grid covering the suspected illegal irrigation cell raster, and to perform spatial aggregation and statistics on the suspected illegal irrigation cell raster using each grid cell of the spatial analysis grid as a partition, and to designate grid cells with statistical values ​​greater than a first threshold as hotspot grid cells. The illegal irrigation area vectorization module is used to convert the hotspot grid cells into vector surface features and perform boundary fusion processing on the spatially adjacent vector surface features to generate candidate illegal patches; The illegal irrigation area screening module is used to spatially correlate each of the candidate illegal patches with the actual irrigation area raster data, determine the effective irrigation area within each candidate illegal patch, and identify the candidate illegal patches whose effective irrigation area is greater than or equal to a second threshold as suspected illegal irrigation area patches.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the method for identifying suspected illegal irrigation areas based on multi-source data combination as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for identifying suspected illegal irrigation areas based on multi-source data as described in any one of claims 1 to 7.

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