Natural resource data fusion method and system

Abstract

The invention relates to a natural resource data fusion method and system. The natural resource data fusion method comprises the following steps: aligning and overlapping two pattern spots from different sources, and splitting a pattern into a plurality of areas by taking the boundary of the pattern spots as a cutting line; according to the area and shape of each region, dividing the region into a trunk region and a fine region; determining a merging strategy of the fine crushing area according to the data attribute of the fine crushing area, wherein the merging strategy reflects which pattern spot the fine crushing area is to be merged with; and merging the fine regions into the corresponding pattern spots based on a merging strategy to form a fusion result. Natural resource data of different sources are fused, fine parts generated in the fusion process are eliminated, and fused pattern spots are complete.

Description

Technical Field

[0001] The present invention relates to the field of natural resource systems, and in particular to a natural resource data fusion method and system. Background Art

[0002] At present, the inventory of natural resource assets owned by the whole people faces the problems of tight time and heavy tasks, and requires scientific and intelligent information support. In the inventory of natural resource assets, various special survey results and field supplementary survey data are collected, and the data are processed and integrated. In order to provide the basic data required for the inventory of natural resource assets, it is necessary to integrate the existing land survey results (such as the third land survey results) with the results of various special surveys. Natural resource data from different sources differ in terms of collection time, processing specifications, etc., resulting in many fragmented areas when data is integrated, which is difficult to process. Summary of the invention

[0003] The purpose of this application is to propose a natural resource data fusion method and system to solve the problem that fragmented areas are difficult to handle in the process of fusing natural resource data from different sources.

[0004] The natural resource data fusion method of this application includes:

[0005] Align and overlap the spots from two different sources, and split the image into several areas using the spot boundaries as cutting lines;

[0006] According to the area and shape of each of the regions, the regions are divided into a main region and fine regions;

[0007] Determining a merging strategy for the fragmented regions according to data attributes of the fragmented regions, wherein the merging strategy reflects which image patch the fragmented regions will be merged with;

[0008] Based on the merging strategy, each of the fragmented areas is merged into a corresponding image patch to form a fusion result.

[0009] Optionally, determining a merging strategy of the fragmented regions according to data attributes of the fragmented regions includes:

[0010] Obtaining the retention priority of the fragmented area according to the data attribute of the image patch to which the fragmented area originally belongs;

[0011] Merging the fragmented areas whose retention priority is higher than a set threshold into the adjacent trunk area;

[0012] The fragmented areas whose retention priority is lower than a set threshold are merged with the remaining patches.

[0013] Optionally, the data attributes include at least two of the following:

[0014] Data acquisition time, data source, and data collection method.

[0015] Optionally, obtaining the retention priority of the fragmented area according to the data attributes of the image patch to which the fragmented area originally belongs includes:

[0016] According to the preset rules, the basic coefficients of different data attributes are determined respectively;

[0017] The retention priority is obtained by multiplying the basic coefficients of different data attributes by their weights.

[0018] Optionally, determining the basic coefficients of different data attributes respectively according to preset rules includes:

[0019] Based on the sequence and time difference of data acquisition time from different sources, a basic coefficient regarding the data acquisition time is determined; wherein, the data acquisition time of the map patch to which the fragmented area originally belongs is later than that of other sources, and the greater the time difference, the greater the basic coefficient regarding the data acquisition time.

[0020] Optionally, according to a preset rule, determining the basic coefficients of different data attributes includes:

[0021] Get the pre-defined base coefficients for each data source or data collection method.

[0022] Optionally, aligning and overlapping the two spots from different sources includes:

[0023] Aligning the image spots from two different sources according to geographic coordinates;

[0024] When the spots of the two different sources have spots of the same natural resource at the same coordinates, alignment correction is performed based on the boundary contours of the spots to overlap the boundaries of the spots of the same natural resource from different sources as much as possible.

[0025] Optionally, after merging the fragmented regions into corresponding image spots based on the merging strategy to form a fusion result, the method further includes:

[0026] Temporarily store the regional division situation before fusion;

[0027] Receive the review results of the auditors, delete the temporarily stored data or modify the merging strategy of the fragmented areas according to the review results and re-form the fusion results.

[0028] Optionally, temporarily storing the situation before fusion includes:

[0029] Only temporarily storing the data in the fragmented area;

[0030] The review results of the receiving auditor include:

[0031] Overlaying and displaying the temporarily stored fragmented areas on the fused graph for the auditor to view;

[0032] Receive the review results entered by the auditor by clicking on the detailed area.

[0033] On the other hand, the present application also provides a natural resource data fusion system, comprising:

[0034] The region segmentation module is used to align and overlap the spots from two different sources, and to split the image into several regions using the spot boundaries as cutting lines;

[0035] A region division module, used for dividing the regions into main regions and sub-regions according to the area and shape of each region;

[0036] A strategy determination module, used to determine a merging strategy for the fragmented regions according to data attributes of the fragmented regions, wherein the merging strategy reflects which image patch the fragmented regions will be merged with;

[0037] The data fusion module is used to merge each of the fragmented areas into a corresponding image patch based on the merging strategy to form a fusion result.

[0038] The natural resource data fusion method provided by the present application is to align and overlap the spots from two different sources, and use the spot boundaries as cutting lines to split the graphics into several areas; divide the areas into main areas and fragmented areas according to the area and shape of each area; determine the merging strategy of the fragmented areas according to the data attributes of the fragmented areas, and the merging strategy reflects which spot the fragmented area will be merged with; merge each fragmented area into the corresponding spot based on the merging strategy to form a fusion result. After each fragmented area is merged into the corresponding spot, the fragmented parts generated in the fusion process are eliminated, and the fused spots are complete. Since the fusion process uses the merging of adjacent graphics, it is usually not necessary to redraw the graphics, and the real spot boundaries can be retained as much as possible. The processing operation process is also relatively simple and effective. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A basic flow chart of the natural resource data fusion method according to the first embodiment of the present application;

[0040] Figure 2 The detailed process diagram of the natural resource data fusion method of the first embodiment of the present application is as follows: Figure 1 ;

[0041] Figure 3 The detailed process diagram of the natural resource data fusion method of the first embodiment of the present application is as follows: Figure 2 ;

[0042] Figure 4 The detailed process diagram of the natural resource data fusion method of the first embodiment of the present application is as follows: Figure 3 ;

[0043] Figure 5 The detailed process diagram of the natural resource data fusion method of the first embodiment of the present application is as follows: Figure 4 ;

[0044] Figure 6 The detailed process diagram of the natural resource data fusion method of the first embodiment of the present application is as follows: Figure 5 ;

[0045] Figure 7 A schematic diagram of the image spots to be fused provided in Example 2 of the present application;

[0046] Figure 8 for Figure 7 A schematic diagram of the pattern alignment overlap is provided;

[0047] Fig. 9 for Figure 8 Schematic diagram of the spot alignment correction;

[0048] Fig.10 for Fig. 9 A schematic diagram of splitting a map into several areas;

[0049] Fig.11 A schematic diagram of an exemplary fusion result provided in Example 2 of the present application;

[0050] Fig.12 A schematic diagram of another exemplary fusion result provided in Embodiment 2 of the present application;

[0051] Fig.13 A schematic diagram of reviewing a pattern provided in the second embodiment of the present application;

[0052] Fig.14 A schematic diagram of adjusting the fusion result according to the review result provided in the second embodiment of the present application;

[0053] Fig.15 This is a structural diagram of the natural resource data fusion system provided in Example 3 of the present application. DETAILED DESCRIPTION

[0054] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0055] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0056] Embodiment 1:

[0057] This embodiment provides a natural resource data fusion method. Figure 1 As shown, including:

[0058] S101, aligning and overlapping two image spots from different sources, and dividing the image into several regions using the image spot boundaries as cutting lines;

[0059] The two spots from different sources are the spots to be fused in this embodiment. The sources of the spots include but are not limited to land survey data, various special survey data, and field supplementary data during these surveys. Before the spots are fused, they are aligned, that is, to ensure that the scale and spatial position of each data are on the same basis. Generally speaking, the land survey data is used as the base map, and the remaining spots such as the special survey data are overlapped on the base map of the land survey data for processing. In other embodiments, spots from other sources can also be selected as the base map.

[0060] In other words, the patches from different sources will be divided into overlapping and non-overlapping parts. Generally speaking, for data with similar survey results, most of the areas will overlap, but there may be a small part of the boundary that is different, forming non-overlapping areas.

[0061] S102, dividing the regions into main regions and fragmented regions according to the area and shape of each region;

[0062] It can be understood that the larger area is the main area, and the smaller or narrower areas are the fragmented areas. The main area and the fragmented areas can also be understood as temporary spots formed during the fusion process. The specific division rules can be set by technical personnel, that is, the specific area and narrowness are pre-set, and when the area is below this area or meets the narrowness judgment condition, it is divided into fragmented areas.

[0063] S103, determining a merging strategy for the fragmented regions according to data attributes of the fragmented regions;

[0064] In this embodiment, the merging strategy reflects which image patch the fragmented region will be merged with. Since the fragmented region is formed by dividing the boundaries of the overlapping complete image patches, it will be adjacent to at least one image patch.

[0065] When a fragmented area is adjacent to two or more different patches, multiple merging options will appear. For example, it can be merged into the main area segmented by the original patch, or merged into the main area segmented by another patch of the two patches; in some implementations, it can also be merged into the remaining patches around it.

[0066] This embodiment determines the merging strategy of fragmented regions by using the data attributes of the fragmented regions, and can automatically and flexibly determine the processing form of the fragmented regions based on the actual situation. In some implementation processes, relatively effective and accurate data information can be retained, while reducing manual decision-making intervention and improving efficiency, while avoiding mechanical deletion or merging of fragmented regions.

[0067] S104, merging each fragmented area into a corresponding image patch based on a merging strategy to form a fusion result;

[0068] After each fragmented area is merged into the corresponding image patch, the fragmented parts generated during the fusion process are eliminated, and the fused image patches are complete. Since the fusion process of this embodiment adopts the merging of adjacent graphics, it is usually not necessary to redraw the graphics, and the real image patch boundaries can be retained as much as possible. The processing and calculation process is also relatively simple and effective. Of course, in some processing processes, before or after executing the natural resource data fusion method of this embodiment or during the execution, other additional adjustments can be made to the boundary morphology of the graphics on the premise of meeting the mapping specifications and not conflicting with the scheme of this embodiment. This embodiment does not limit this.

[0069] In some embodiments, Figure 2 As shown in FIG. 1 , the strategy for merging the fragmented regions according to the data attributes of the fragmented regions includes:

[0070] S201, obtaining a retention priority of the fragmented areas according to data attributes of the patches to which the fragmented areas originally belong;

[0071] S202, merging the fragmented areas whose retention priority is higher than the set threshold into the adjacent trunk area;

[0072] It should be noted that after the fragmented areas in the present application are merged into the spots, the fragmented areas are configured according to the properties of the merged spots. For example, if the fragmented areas are merged into a main area of ​​another different natural resource type, it is equivalent to the fragmented areas being modified into another natural resource type, and merged to form a new spot. Of course, if the fragmented areas are merged back into the main area divided by the spot to which they originally belonged, the natural resource type of the fragmented areas does not change. It should be noted that adjacency in this embodiment refers to the existence of at least one adjacent edge; two areas that are only connected at one corner cannot be merged into a more complete area, and do not belong to the adjacency referred to in this embodiment.

[0073] S203, merging the fragmented areas whose retention priority is lower than the set threshold with the remaining image spots;

[0074] Step S203 can also be understood as deleting the fragmented area from the original two image spots to eliminate the fragmented parts.

[0075] If there are multiple adjacent patches to choose from, the patch with the largest area or the largest adjacent range can be selected for merging. This can be flexibly set according to actual conditions.

[0076] The threshold setting of the retention priority is set by the technician based on the actual situation. Data attributes include but are not limited to data acquisition time, data source, and data collection method. In this embodiment, the data attributes may include at least two of them. It can be understood that in actual applications, patches with newer data time and more reliable sources can be retained first. For this, flexible decision-making can be achieved by setting basic coefficients. Therefore, the method of determining the retention priority of patches by the data attributes of the patches can make the fusion results obtained by the natural resource data fusion method of this embodiment relatively reliable and effective.

[0077] See also Figure 3 In this embodiment, the retention priority of the image spot is obtained according to the data attribute of the image spot, including:

[0078] S301, determining basic coefficients of different data attributes respectively according to preset rules;

[0079] S302, the sum of the results of multiplying the basic coefficients of different data attributes by their weights is obtained to obtain the retention priority;

[0080] Taking two data attributes as an example, assume that the basic coefficient of the data source is A1, and the basic coefficient of the data collection method is A2. In this example, the sum of the weights of different data attributes can be 1. Assume that the weight of the data source is 0.7, and the weight of the data collection method is 0.3. Then the value of its retention priority is 0.7A1+0.3A2. For more data attributes, the calculation method is the same, but when setting the threshold, it can be configured according to the number of data attributes and the weight distribution. Of course, in practical applications, other retention priority calculation rules can also be set.

[0081] In this embodiment, according to the preset rules, the method of determining the basic coefficients of different data attributes respectively specifically includes: determining the basic coefficient of data acquisition time based on the order and time difference of data acquisition time from different sources. Among them, the data acquisition time of the fragmented area is later than that of the other sources, and the greater the time difference, the greater the basic coefficient of data acquisition time. It should be noted that in this embodiment, the basic coefficient of data acquisition time is determined based on the time difference with the other sources. As an example, the earliest time of data acquisition in each source can be set as the benchmark, and the basic coefficient of data acquisition time increases by one level for every month difference. As a more specific example, assuming that the basic coefficient of data acquisition time for the earliest acquisition time is 0.1, the basic coefficient of data acquisition time for the other spots increases by 0.1 for every month later.

[0082] For the basic coefficients of some other data attributes, a relatively simple pre-set method can be used for configuration. In some embodiments, according to preset rules, determining the basic coefficients of different data attributes includes: obtaining the basic coefficients pre-set for each data source or data collection method. For example, different basic coefficients are set for land survey data and special survey data (about data sources), and different basic coefficients are also configured for data obtained by remote sensing mapping and data after field survey (about data collection methods). The basic coefficients corresponding to these data attributes do not need to be calculated, and the pre-configured ones can be directly obtained.

[0083] In some embodiments, see Figure 4 , aligning and overlapping the spots from different sources includes:

[0084] S401, aligning two image spots from different sources according to geographic coordinates;

[0085] S402, when there is a spot of the same natural resource at the same coordinate of two spots from different sources, alignment correction is performed based on the boundary contours of the spots to overlap the boundaries of the spots from different sources of the same natural resource as much as possible;

[0086] Since the acquisition time of the spots from different sources may be different, there may be differences in the acquisition and processing, and there may be errors and other influences. Even for the same natural resources, the spots finally formed are usually not completely consistent. In order to simplify the fusion process of natural resource data, the above steps S401 and S402 of this embodiment perform alignment corrections based on the boundary contours of the spots to try to better overlap the spots of the same natural resource. The alignment correction operations in the above step S402 include but are not limited to adjusting the overall coordinate position of the spots, the overall scaling ratio, or synchronizing areas with only slight differences. The alignment correction process can eliminate the slight differences in spots caused by drawing specifications and errors to a certain extent, thereby reducing the number of areas segmented from subsequent spots and simplifying the data fusion process.

[0087] In some embodiments, see Figure 5 After merging each fragmented area with the adjacent trunk area to form a fusion result based on the merging strategy, it also includes:

[0088] S501, temporarily storing the regional division situation before fusion;

[0089] For example, temporary storage can be formed into a temporary storage file and stored in the system, wherein the regional division situation before fusion can be saved so that the auditor can view it.

[0090] S502, receiving the review results of the auditor, deleting the temporarily stored data or modifying the merging strategy of the fragmented areas according to the review results and re-forming the fusion results;

[0091] For the merged records, the auditor can review the fusion results based on the temporarily stored situation before and after the fusion. For the parts that need to be adjusted, the auditor is allowed to re-integrate, for example, modify the fragmented areas that were originally merged into the main area of ​​the same natural resource type to merge into the main area of ​​another natural resource type next to it. If the auditor believes that the result of the automatic fusion of the system is correct, the corresponding fusion result can be accepted, and the temporarily stored data can be deleted.

[0092] like Figure 6 As shown, in this embodiment, temporarily storing the situation before fusion includes:

[0093] S5011, temporarily storing only the data in the fragmented area;

[0094] The review results of the receiving auditor include:

[0095] S5021. Overlay the temporarily stored fragmented areas on the fused graph for review by the auditors;

[0096] S5022. Receive the review results entered by the auditor in the detailed area;

[0097] The above steps only temporarily store the data of the fragmented areas, which only takes up a small storage space and can ensure that the auditor understands the situation of the image fusion. By overlaying the display on the fused image, the information of the fragmented areas can be presented intuitively, and less system resources are occupied. Auditors can view the merging of the fragmented areas by clicking on the fragmented areas, and make comments on whether the fusion result has passed the review or needs to be modified. In actual applications, when the auditor accepts the fusion result of a certain fragmented area, the graphics of the superimposed fragmented areas can be deleted from the image in real time, and the temporarily saved related data can be deleted at the same time. When working, auditors only need to find the graphics of the fragmented areas displayed on the image to operate, which is convenient for their operation.

[0098] Embodiment 2:

[0099] In order to better understand the natural resource data fusion method of the present application, this embodiment is explained in conjunction with a specific example.

[0100] For ease of understanding, this example only uses two spots as an example. It is understandable that when there are more spots, the spots that need to be fused are processed step by step until all data fusion is completed. In actual applications, for data from multiple different sources, fusion can also be performed step by step, which is not described in detail in this embodiment. Figure 7 As shown, in this example, the source of the first map spot 1 is the land survey data, and the source of the second map spot 2 is the special survey data. Among them, the geographical locations of the first map spot 1 and the second map spot 2 are the same.

[0101] The fusion steps for this example are as follows:

[0102] S601: See Figure 8 As shown, two spots from different sources are aligned and overlapped. The data source of the first spot 1 is the land survey data, and the data source of the second spot 2 is the special survey data. At this time, the first spot 1 and the second spot 2 are superimposed according to the geographic coordinates. In this process, if the scales of the two are different, they are adjusted to the same scale. In this example, different types of spots are distinguished in each figure by solid lines and dotted lines.

[0103] S602: See Fig. 9 As shown, the boundary contours of the first image spot 1 and the second image spot 2 are aligned and corrected. In this example, the shape and position of the left side of the first image spot 1 and the second image spot 2 are basically the same, with only a slight position deviation. The position of the second image spot 2 can be adjusted as a whole to align the two sides to eliminate the deviation and simplify the area that will be formed after segmentation.

[0104] S603: See Fig.10 As shown, the pattern is divided into several regions using the pattern boundary as a cutting line. In this example, the first pattern 1 and the second pattern 2 are mutually divided into five regions, namely, region 11, region 12, region 13, region 14 and region 15.

[0105] S604: According to the area and shape of each area, area 12 and area 15 are divided into main areas, and area 11, area 13 and area 14 are identified as fragmented areas. It should be understood that the steps of this example can be performed only in the form of data calculation in the background, and the graphical presentation of the fusion process is not necessary. The drawings of this example are only for ease of understanding. Of course, in order to facilitate efficient review by auditors, at least part of the data fusion process of this example can also be presented in a graphical manner in practical applications. In this embodiment, the land survey data is used as the base map, wherein the attributes of the main areas where the special survey data and the land survey data overlap inherit the special survey data; for the parts that do not overlap, the attributes are inherited according to the original situation.

[0106] S605: Determine a merging strategy for each fragmented region according to data attributes of the fragmented regions.

[0107] Taking area 11 as an example, area 11 is formed by dividing the non-overlapping part of the second spot 2 and the first spot 1. The data source of the second spot 2 is special survey data, where the basic coefficient for the data source is A21; the basic coefficient for the data collection method of the second spot 2 is A22. The data acquisition time of the second spot 2 is two months later than the data acquisition time of the first spot 1, so the basic coefficient of the first spot 1 for the data acquisition time is A13. In this example, the basic coefficient increases by a for each month of difference, and the basic coefficient of the second spot 2 for the data acquisition time is A23=A13+2a. Therefore, the retention priority value of area 11 is: A21*j+A22*k+A23*l; where j, k, and l are the weights of each data attribute, respectively. In this example, j+k+l=1.

[0108] Taking area 13 as an example, area 13 is formed by the segmentation of the first map spot 1, and its data source is the land survey data, among which the basic coefficient regarding the data source is A31 (due to different data sources, A31 is not equal to A21). The basic coefficient of the data collection method of the first map spot 1 is A32 (which can be the same as A22 or different). The basic coefficient of the first map spot 1 regarding the data acquisition time is A13 (which is the earliest time in this fusion, and A13 is the reference value of the basic coefficient regarding the data acquisition time). Therefore, the retention priority value of area 13 is: A11*j+A12*k+A13*l; wherein j, k, and l are the weights of each data attribute respectively. In this example, j+k+l=1.

[0109] The calculation method of the retention priority of area 14 is similar to the above example and will not be described in detail here.

[0110] In this example, it is assumed that the retention priority of regions 11 and 13 is higher than the set threshold; the retention priority of region 14 is lower than the set threshold. In this example, region 11 is merged with region 12, and region 13 is merged back to the adjacent region 12, then the area covered by regions 11, 12, and 13 forms a new third spot 3. Region 14 is not merged back into the original first spot 1 or second spot 2, which is equivalent to incorporating spots outside the first spot 1 and the second spot 2 (not shown in the figure) for merging. Region 15 forms a new fourth spot 4. In this example, the fusion result is as follows: Fig.11 shown.

[0111] For ease of understanding, Fig.12 The fusion result of another case is shown. In this case, assuming that the retention priority of region 11 is lower than the set threshold, and the retention priorities of regions 13 and 14 are higher than the set threshold, then regions 12, 13 and 14 will form a new third image spot 3; and region 15 will form a new fourth image spot 4.

[0112] It can be seen that through the above method of this example, the natural resource patches can be flexibly and automatically fused based on the actual conditions of each fragmented area, and the fused patches are complete without fragmented areas.

[0113] S606: Temporarily store the data of the fragmented areas, and provide an interface in the GIS (Geographic Information System) system for graphically querying the data of the fragmented areas before the fusion data. For example, when the user's mouse points to the fused area, the merged fragmented areas can be displayed with different transparency or colors.

[0114] S607: Receive the review result of the auditor. The auditor can confirm or modify the fusion result by clicking on the fragmented areas displayed in different transparency or colors in the fused area.

[0115] As an example, see Fig.13 As shown in FIG. 1 , assuming that the auditor clicks on the fragmented area originally belonging to area 14 and issues an instruction to adjust the merging strategy of the area (modify strategy), which is equivalent to a failure in the review result. Then the fragmented area originally belonging to area 14 is automatically merged into the remaining surrounding patches, forming the following Fig.14 Of course, the specific modification and merging of the fragmented areas originally belonging to the area 14 into which other patches can be selected by the auditor, or can be automatically modified according to a preset rule.

[0116] If the auditor chooses to accept the review result, it is equivalent to the review result being passed. At this time, the temporary data of the fragmented area originally belonging to area 14 can be deleted, and at the same time, the different transparency or color of the corresponding area on the spot can also be eliminated, retaining the complete spot after fusion.

[0117] Embodiment three:

[0118] This embodiment provides a natural resource data fusion system 100, see Fig.15 As shown, including:

[0119] The region segmentation module 101 is used to align and overlap two image spots from different sources, and to divide the image into a number of regions using the image spot boundaries as cutting lines.

[0120] The region division module 102 is used to divide the region into a main region and sub-regions according to the area and shape of each region.

[0121] The strategy determination module 103 is used to determine a merging strategy for the fragmented regions according to data attributes of the fragmented regions, wherein the merging strategy reflects which image patch the fragmented regions will be merged with.

[0122] The data fusion module 104 is used to merge the fragmented areas into corresponding image spots based on the merging strategy to form a fusion result.

[0123] The specific steps that can be executed by the modules in the natural resource data fusion system 100 of this embodiment can also refer to the description of the natural resource data fusion method provided above in this embodiment, which will not be described in detail in this embodiment.

[0124] In addition, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present disclosure that are equivalent, modified, omitted, combined (e.g., various embodiments intersecting), adapted or changed. It is not limited to the examples described in this specification or during the implementation of this application, and its examples will be interpreted as non-exclusive.

[0125] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of them) can be used in combination with each other. For example, those of ordinary skill in the art may use other embodiments when reading the above description.

[0126] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A natural resource data fusion method, characterized in that: include: Align and overlap the spots from two different sources, and split the image into several areas using the spot boundaries as cutting lines; According to the area and shape of each of the regions, the regions are divided into a main region and fine regions; Determining a merging strategy for the fragmented regions according to data attributes of the fragmented regions, wherein the merging strategy reflects which image patch the fragmented regions will be merged with; Based on the merging strategy, each of the fragmented areas is merged into a corresponding image patch to form a fusion result.

2. The natural resource data fusion method according to claim 1, characterized in that: Determining the merging strategy of the fragmented regions according to the data attributes of the fragmented regions includes: Obtaining the retention priority of the fragmented area according to the data attribute of the image patch to which the fragmented area originally belongs; Merging the fragmented areas whose retention priority is higher than a set threshold into the adjacent trunk area; The fragmented areas whose retention priority is lower than a set threshold are merged with the remaining patches.

3. The natural resource data fusion method according to claim 2, characterized in that: The data attributes include at least two of the following: Data acquisition time, data source, and data collection method.

4. The natural resource data fusion method according to claim 3, characterized in that: The obtaining of the retention priority of the fragmented area according to the data attribute of the image patch to which the fragmented area originally belongs comprises: According to the preset rules, the basic coefficients of different data attributes are determined respectively; The retention priority is obtained by multiplying the basic coefficients of different data attributes by their weights.

5. The natural resource data fusion method according to claim 4, characterized in that: Determining the basic coefficients of different data attributes according to the preset rules includes: Based on the sequence and time difference of data acquisition time from different sources, a basic coefficient regarding the data acquisition time is determined; wherein, the data acquisition time of the map patch to which the fragmented area originally belongs is later than that of other sources, and the greater the time difference, the greater the basic coefficient regarding the data acquisition time.

6. The natural resource data fusion method according to claim 4, characterized in that: According to the preset rules, the basic coefficients of different data attributes are determined to include: Get the pre-defined base coefficients for each data source or data collection method.

7. The natural resource data fusion method according to claim 1, characterized in that: The aligning and overlapping of two spots from different sources comprises: Aligning the image spots from two different sources according to geographic coordinates; When the spots of the two different sources have spots of the same natural resource at the same coordinates, alignment correction is performed based on the boundary contours of the spots to overlap the boundaries of the spots of the same natural resource from different sources as much as possible.

8. The natural resource data fusion method according to any one of claims 1 to 7, characterized in that: After merging the fragmented regions into corresponding image spots based on the merging strategy to form a fusion result, the method further includes: Temporarily store the regional division situation before fusion; Receive the review results of the auditors, delete the temporarily stored data or modify the merging strategy of the fragmented areas according to the review results and re-form the fusion results.

9. The natural resource data fusion method according to claim 8, characterized in that: The temporary storage of the situation before fusion includes: Only temporarily storing the data in the fragmented area; The review results of the receiving auditor include: Overlaying and displaying the temporarily stored fragmented areas on the fused graph for the auditor to view; Receive the review results entered by the auditor by clicking on the detailed area.

10. A natural resource data fusion system, characterized in that: include: The region segmentation module is used to align and overlap the spots from two different sources, and to split the image into several regions using the spot boundaries as cutting lines; A region division module, used for dividing the regions into main regions and sub-regions according to the area and shape of each region; A strategy determination module, used to determine a merging strategy for the fragmented regions according to data attributes of the fragmented regions, wherein the merging strategy reflects which image patch the fragmented regions will be merged with; The data fusion module is used to merge each of the fragmented areas into a corresponding image patch based on the merging strategy to form a fusion result.

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