Geographic surveying and mapping information acquisition system based on multivariate data fusion processing

Abstract

The invention belongs to the field of geographic surveying and mapping, relates to a multi-source data fusion technology, is used for solving the problem that the accuracy of geographic surveying and mapping information cannot be guaranteed by adopting a single measurement and calculation technology in the prior art, and particularly relates to a geographic surveying and mapping information acquisition system based on multivariate data fusion processing. The server is in communication connection with a data acquisition module, a coincidence analysis module, a verification analysis module, a filling processing module and a perfect analysis module; the data acquisition module is used for acquiring and preprocessing geographic surveying and mapping data to obtain a remote sensing model and a model airplane; according to the method, geographic surveying and mapping data can be collected, remote sensing data and surveying and mapping image data obtained by different means are preprocessed to obtain a remote sensing model and a model airplane, and then regional coincidence coefficient calculation is carried out on a geographic surveying and mapping region in combination with a coincidence analysis process; and feeding back surveying and mapping data differences obtained by different means of the analysis area through the coincidence coefficient.

Description

Technical Field

[0001] The present invention belongs to the field of geographic surveying and mapping, and relates to a multi-source data fusion technology, in particular to a geographic surveying and mapping information acquisition system based on multi-source data fusion processing. Background Art

[0002] Surveying and mapping literally means measuring and drawing. It is based on computer technology, optoelectronic technology, network communication technology, space science, and information science, with global navigation satellite positioning system, remote sensing, and geographic information system as its technical core. It selects existing feature points and boundaries on the ground and uses measurement methods to obtain graphics and positions reflecting the current status of the ground and related information.

[0003] Although there are many core technologies used in geographic surveying and mapping, the geographic surveying and mapping information collection systems in existing technologies can often only use a single measurement technology to collect information. The surveying and mapping technologies suitable for areas with different terrain and landforms are not the same. This leads to the fact that the accuracy of geographic surveying and mapping information obtained by a single measurement technology cannot be guaranteed.

[0004] In response to the above technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide a geographic surveying and mapping information acquisition system based on multivariate data fusion processing, which is used to solve the problem that the existing technology cannot guarantee the accuracy of geographic surveying and mapping information by using a single measurement technology;

[0006] The technical problem to be solved by the present invention is: how to provide a geographic surveying and mapping information acquisition system based on multivariate data fusion processing.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The geographic surveying and mapping information acquisition system based on multivariate data fusion processing includes a server, wherein the server is communicatively connected to a data acquisition module, a coincidence analysis module, a verification analysis module, a filling processing module, and a perfect analysis module;

[0009] The data acquisition module is used to collect and pre-process geographic surveying and mapping data to obtain remote sensing models and aerial models; and send the remote sensing models and aerial models to the coincidence analysis module;

[0010] The overlap analysis module is used to perform overlap analysis on geographic surveying and mapping data: the geographic surveying and mapping area is divided into a plurality of analysis areas, the corresponding areas of the analysis areas in the remote sensing model and the aerial model are marked as remote sensing areas and aerial areas respectively, a set of overlap data groups is formed by the remote sensing areas and the aerial areas corresponding to the same analysis area, the overlap coefficients of the overlap data groups are calculated, and the overlap coefficients of all overlap data groups are sent to the verification analysis module via the server;

[0011] The verification and analysis module is used to verify and analyze the measurement accuracy of the remote sensing model and the aerial model to obtain the basic area and the filling area;

[0012] The filling processing module is used to establish an output model and fill the filling area in the output model with data;

[0013] The improvement analysis module is used to perform data improvement analysis on the basic area of ​​the output model.

[0014] As a preferred embodiment of the present invention, geographic surveying and mapping data include remote sensing data obtained by satellite remote sensing calculation and surveying and mapping image data obtained by aerial photography. The remote sensing data and surveying and mapping image data are cleaned and the same reference is selected in the three-dimensional coordinate system to construct a three-dimensional geographic model to obtain a remote sensing model and an aerial model.

[0015] As a preferred embodiment of the present invention, the calculation process of the overlap coefficient of the overlap data group includes: marking the coordinates of the highest point of the remote sensing area in the overlap data group in the spatial coordinate system of the remote sensing model as (YGx, YGy, YGz), marking the coordinates of the highest point of the aviation area in the overlap data group in the spatial coordinate system of the remote sensing model as (HGx, HGy, HGz), substituting (YGx, YGy, YGz) and (HGx, HGy, HGz) into the high point offset calculation formula to obtain the high point offset value PYg of the overlap data group; The coordinates of the lowest point of the remote sensing area in the data group in the spatial coordinate system of the remote sensing model are marked as (YDx, YDy, YDz), and the coordinates of the lowest point of the aviation area in the overlapping data group in the spatial coordinate system of the remote sensing model are marked as (HDx, HDy, HDz). Substitute (YDx, YDy, YDz) and (HDx, HDy, HDz) into the low point offset calculation formula to obtain the low point offset value PYd of the overlapping data group. The high point offset value PYg and the low point offset value PYd are summed and averaged to obtain the overlap coefficient of the overlapping data group.

[0016] As a preferred embodiment of the present invention, the specific process of the verification and analysis module for verifying and analyzing the measurement accuracy of the remote sensing model and the aerial model includes: comparing the overlap coefficient of the overlapping data group with the preset overlap threshold: if the overlap coefficient is less than the overlap threshold, it is determined that the measurement accuracy of the overlapping data group meets the requirements, and the corresponding analysis area is marked as the basic area; if the overlap coefficient is greater than or equal to the overlap threshold, it is determined that the measurement accuracy of the overlapping data group does not meet the requirements, and the corresponding analysis area is marked as the filling area; the filling area is sent to the filling processing module through the server.

[0017] As a preferred embodiment of the present invention, the specific process of the improvement analysis module performing data improvement analysis on the basic area of ​​the output model includes: marking the coordinates of the highest point in the surveying and mapping data of the filling area in the spatial coordinate system of the output model as (CGx, CGy, CGz), substituting (CGx, CGy, CGz) and (YGx, YGy, YGz) into the high point offset calculation formula for numerical calculation, marking the obtained high point offset value PYg as the remote sensing offset high value of the filling area, marking the coordinates of the lowest point in the surveying and mapping data of the filling area in the spatial coordinate system of the output model as (CDx, CDy, CDz), substituting (CDx, CDy, CDz) and (YDx, YDy, YDz) into the low point offset calculation formula for numerical calculation, and marking the obtained low point offset value PYd as the remote sensing offset low value of the filling area; performing numerical calculation on the remote sensing offset high value and the remote sensing offset low value. The remote sensing offset value is obtained by summing and averaging the rows; (CGx, CGy, CGz) and (HGx, HGy, HGz) are substituted into the high point offset calculation formula for numerical calculation, and the obtained high point offset value PYg is marked as the high value of the aerial offset of the filling area; (CDx, CDy, CDz) and (HDx, HDy, HDz) are substituted into the low point offset calculation formula for numerical calculation, and the obtained low point offset value PYd is marked as the low value of the aerial offset of the filling area; the aerial offset high value and the aerial offset low value are summed and averaged to obtain the aerial offset value of the filling area; the remote sensing offset values ​​of all the filling areas are summed and averaged to obtain the remote sensing offset coefficient, and the aerial offset coefficient is summed and averaged to obtain the aerial offset coefficient; the remote sensing offset coefficient is compared with the aerial offset coefficient and the data of the corresponding basic area in the output model is filled based on the comparison result.

[0018] As a preferred embodiment of the present invention, the specific process of comparing the remote sensing offset coefficient with the aerial offset coefficient includes: if the remote sensing offset coefficient is less than or equal to the aerial offset coefficient, the remote sensing data is used to fill the corresponding basic area in the output model; if the remote sensing offset coefficient is greater than the aerial offset coefficient, the surveying and mapping image data is used to fill the corresponding basic area in the output model.

[0019] The present invention has the following beneficial effects:

[0020] 1. The data acquisition module can be used to collect geographic surveying and mapping data. Remote sensing data and surveying and mapping image data obtained by different means are pre-processed to obtain remote sensing models and aerial models. Then, regional coincidence coefficients are calculated for geographic surveying and mapping areas in combination with the coincidence analysis process. The coincidence coefficients are used to provide feedback on the differences in surveying and mapping data obtained by different means in the analysis area.

[0021] 2. The calibration and analysis module can be used to calibrate and analyze the calculation accuracy of the remote sensing model and the aerial model. The analysis area is marked differently according to the value of the overlap coefficient. Then, combined with the filling processing module, data is filled in the filling area of ​​the output model. Ground measurement is performed on areas where the automatic measurement results differ greatly, thereby ensuring the accuracy of geographic surveying and mapping data.

[0022] 3. The improvement analysis module can be used to perform data improvement analysis on the basic area of ​​the output model. Based on the surveying and mapping data of the filling area, the degree of data deviation in the remote sensing model and the aerial model of the filling area is analyzed. Then, the measurement data with the smallest overall deviation is selected to fill the data in the basic area of ​​the output model. The multi-source data is fused and processed to obtain an accurate output model. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0025] Figure 2 This is a flow chart of the method of embodiment 2 of the present invention. DETAILED DESCRIPTION

[0026] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] Example 1

[0028] like Figure 1 As shown, the geographic surveying and mapping information acquisition system based on multivariate data fusion processing includes a server, and the server is communicatively connected to a data acquisition module, a coincidence analysis module, a verification analysis module, a filling processing module and a perfect analysis module.

[0029] The data acquisition module is used to collect geographic surveying and mapping data: geographic surveying and mapping data includes remote sensing data obtained through satellite remote sensing calculation and surveying and mapping image data obtained through aerial photography. The remote sensing data and surveying and mapping image data are cleaned and the same benchmark is used to construct a three-dimensional geographic model in the three-dimensional coordinate system to obtain a remote sensing model and an aerial model; the remote sensing model and the aerial model are sent to the coincidence analysis module.

[0030] The coincidence analysis module is used to perform coincidence analysis on geographic surveying and mapping data: the geographic surveying and mapping area is divided into several analysis areas, and the corresponding areas of the analysis area in the remote sensing model and the aviation model are marked as remote sensing areas and aviation areas respectively. The remote sensing areas and aviation areas corresponding to the same analysis area constitute a set of coincidence data groups, and the coordinates of the highest point of the remote sensing area in the coincidence data group in the spatial coordinate system of the remote sensing model are marked as (YGx, YGy, YGz), and the coordinates of the highest point of the aviation area in the coincidence data group in the spatial coordinate system of the remote sensing model are marked as (HGx, HGy, HGz). The high point offset calculation formula is used to calculate the high point offset. The high point offset value PYg of the overlapping data set is obtained, where α1, α2 and α3 are all proportional coefficients, and α3>α2>α1>1; the coordinates of the lowest point of the remote sensing area in the overlapping data set in the spatial coordinate system of the remote sensing model are marked as (YDx, YDy, YDz), and the coordinates of the lowest point of the aerial area in the overlapping data set in the spatial coordinate system of the remote sensing model are marked as (HDx, HDy, HDz). The low point offset calculation formula is used. Obtain the low point offset value PYd of the overlapping data group, sum and average the high point offset value PYg and the low point offset value PYd to obtain the overlap coefficient of the overlapping data group, and send the overlap coefficients of all overlap data groups to the verification analysis module through the server; collect geographic surveying and mapping data, pre-process the remote sensing data and surveying and mapping image data obtained by different means to obtain remote sensing models and aerial models, and then combine the overlap analysis process to calculate the regional overlap coefficient of the geographic surveying and mapping area, and use the overlap coefficient to provide feedback on the differences in surveying and mapping data obtained by different means in the analysis area.

[0031] The verification and analysis module is used to verify and analyze the measurement accuracy of the remote sensing model and the aerial model: the overlap coefficient of the overlapping data group is compared with the preset overlap threshold: if the overlap coefficient is less than the overlap threshold, it is determined that the measurement accuracy of the overlapping data group meets the requirements, and the corresponding analysis area is marked as the basic area; if the overlap coefficient is greater than or equal to the overlap threshold, it is determined that the measurement accuracy of the overlapping data group does not meet the requirements, and the corresponding analysis area is marked as the filling area; the filling area is sent to the filling processing module through the server.

[0032] The filling processing module is used to receive the surveying and mapping data of the filling area obtained by multi-point observation and triangulation of measuring instruments such as total stations and electronic theodolites, establish an output model, and fill the corresponding analysis area in the output model with the surveying and mapping data of the filling area; verify and analyze the measurement accuracy of the remote sensing model and the aerial model, differentiate the analysis area according to the numerical value of the overlap coefficient, and then use the filling processing module to fill the filling area of ​​the output model with data, and perform ground measurement on areas with large differences in automatic measurement results, so as to ensure the accuracy of geographic surveying and mapping data.

[0033] The improvement analysis module is used to perform data improvement analysis on the basic area of ​​the output model: the coordinates of the highest point in the surveying and mapping data of the filling area in the spatial coordinate system of the output model are marked as (CGx, CGy, CGz), (CGx, CGy, CGz) and (YGx, YGy, YGz) are substituted into the high point offset calculation formula for numerical calculation, and the obtained high point offset value PYg is marked as the remote sensing offset high value of the filling area, and the coordinates of the lowest point in the surveying and mapping data of the filling area in the spatial coordinate system of the output model are marked as (CDx, CDy, CD z), substitute (CDx, CDy, CDz) and (YDx, YDy, YDz) into the low point offset calculation formula for numerical calculation, and mark the obtained low point offset value PYd as the low value of remote sensing offset in the filling area; sum and average the high value of remote sensing offset and the low value of remote sensing offset to obtain the remote sensing offset value; substitute (CGx, CGy, CGz) and (HGx, HGy, HGz) into the high point offset calculation formula for numerical calculation, and mark the obtained high point offset value PYg as the high value of aerial offset in the filling area; substitute (CDx, CDy, CD z) and (HDx, HDy, HDz) are substituted into the low point offset calculation formula for numerical calculation, and the obtained low point offset value PYd is marked as the low value of the aerial offset of the filling area; the aerial offset high value and the aerial offset low value are summed and averaged to obtain the aerial offset value of the filling area; the remote sensing offset values ​​of all filling areas are summed and averaged to obtain the remote sensing offset coefficient, and the aerial offset coefficient is summed and averaged to obtain the aerial offset coefficient; the remote sensing offset coefficient is compared with the aerial offset coefficient: if the remote sensing offset coefficient is less than or equal to the aerial offset coefficient, the remote sensing data is used to fill the corresponding basic area in the output model; if the remote sensing offset coefficient is greater than the aerial offset coefficient, the surveying and mapping image data is used to fill the corresponding basic area in the output model; the basic area of ​​the output model is subjected to data improvement analysis, and the surveying and mapping data of the filling area is used as a benchmark to analyze the degree of data deviation of the filling area in the remote sensing model and the aerial model, and then the measured data with the smaller overall deviation is selected to fill the basic area in the output model, and the multi-source data is fused to obtain an accurate output model.

[0034] Example 2

[0035] like Figure 2 As shown, the geographic surveying and mapping information collection method based on multivariate data fusion processing includes the following steps:

[0036] Step 1: Clean the remote sensing data and surveying image data and construct a 3D geographic model using the same reference in the 3D coordinate system to obtain the remote sensing model and the aerial model;

[0037] Step 2: Divide the geographical survey area into several analysis areas, mark the corresponding areas of the analysis areas in the remote sensing model and the aerial model as remote sensing areas and aerial areas respectively, and form a set of overlapping data groups from the remote sensing areas and aerial areas corresponding to the same analysis area, and obtain the overlap coefficient of the overlapping data group;

[0038] Step 3: Compare the overlap coefficient of the overlap data set with the preset overlap threshold and mark the corresponding analysis area as the basic area or the filling area based on the comparison result;

[0039] Step 4: Create an output model and fill the corresponding analysis area in the output model with the surveying and mapping data of the fill area;

[0040] Step 5: Calculate the remote sensing offset coefficient and the aviation offset coefficient, compare the remote sensing offset coefficient with the aviation offset coefficient, and fill the output model with data based on the comparison results.

[0041] The geographic surveying and mapping information acquisition system based on multivariate data fusion processing performs data cleaning on remote sensing data and surveying and mapping image data, and selects the same benchmark to construct a three-dimensional geographic model in a three-dimensional coordinate system to obtain a remote sensing model and an aerial model; divides the geographic surveying and mapping area into several analysis areas, and marks the corresponding areas of the analysis areas in the remote sensing model and the aerial model as remote sensing areas and aerial areas respectively, and forms a set of overlapping data groups by the remote sensing areas and aerial areas corresponding to the same analysis area, and obtains the overlapping coefficient of the overlapping data group; compares the overlapping coefficient of the overlapping data group with a preset overlapping threshold value, and marks the corresponding analysis area as a basic area or a filling area based on the comparison result; fills the corresponding analysis area in the output model with the surveying and mapping data of the filling area; calculates the remote sensing offset coefficient and the aerial offset coefficient, compares the remote sensing offset coefficient with the aerial offset coefficient, and fills the output model with data based on the comparison result.

[0042] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

[0043] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0044] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. The geographical surveying and mapping information acquisition system based on multivariate data fusion processing is characterized by: The system comprises a server, wherein the server is communicatively connected to a data acquisition module, a coincidence analysis module, a verification analysis module, a filling processing module and a perfection analysis module; The data acquisition module is used to collect and pre-process geographic surveying and mapping data to obtain remote sensing models and aerial models; and send the remote sensing models and aerial models to the coincidence analysis module; The overlap analysis module is used to perform overlap analysis on geographic surveying and mapping data: the geographic surveying and mapping area is divided into a plurality of analysis areas, the corresponding areas of the analysis areas in the remote sensing model and the aerial model are marked as remote sensing areas and aerial areas respectively, a set of overlap data groups is formed by the remote sensing areas and the aerial areas corresponding to the same analysis area, the overlap coefficients of the overlap data groups are calculated, and the overlap coefficients of all overlap data groups are sent to the verification analysis module via the server; The verification and analysis module is used to verify and analyze the measurement accuracy of the remote sensing model and the aerial model to obtain the basic area and the filling area; The filling processing module is used to establish an output model and fill the filling area in the output model with data; The improvement analysis module is used to perform data improvement analysis on the basic area of ​​the output model.

2. The geographic surveying and mapping information acquisition system based on multivariate data fusion processing according to claim 1 is characterized in that: Geographic surveying and mapping data include remote sensing data obtained through satellite remote sensing calculations and surveying and mapping image data collected through aerial photography. The remote sensing data and surveying and mapping image data are cleaned and the same benchmark is used to construct a three-dimensional geographic model in a three-dimensional coordinate system to obtain a remote sensing model and an aerial model.

3. The geographic surveying and mapping information acquisition system based on multivariate data fusion processing according to claim 2 is characterized in that: The calculation process of the coincidence coefficient of the coincidence data set includes: marking the coordinates of the highest point of the remote sensing area in the coincidence data set in the spatial coordinate system of the remote sensing model as (YGx, YGy, YGz), marking the coordinates of the highest point of the aviation area in the coincidence data set in the spatial coordinate system of the remote sensing model as (HGx, HGy, HGz), substituting (YGx, YGy, YGz) and (HGx, HGy, HGz) into the high point offset calculation formula to obtain the high point offset value PYg of the coincidence data set; substituting the remote sensing area in the coincidence data set into the high point offset calculation formula PYg ... The coordinates of the lowest point of the domain in the spatial coordinate system of the remote sensing model are marked as (YDx, YDy, YDz), and the coordinates of the lowest point of the aerial area in the coincident data set in the spatial coordinate system of the remote sensing model are marked as (HDx, HDy, HDz). Substitute (YDx, YDy, YDz) and (HDx, HDy, HDz) into the low point offset calculation formula to obtain the low point offset value PYd of the coincident data set. The high point offset value PYg and the low point offset value PYd are summed and averaged to obtain the coincidence coefficient of the coincident data set.

4. The geographic surveying and mapping information acquisition system based on multivariate data fusion processing according to claim 3 is characterized in that: The specific process of the verification and analysis module for verifying and analyzing the measurement accuracy of the remote sensing model and the aerial model includes: comparing the overlap coefficient of the overlapping data group with the preset overlap threshold: if the overlap coefficient is less than the overlap threshold, it is determined that the measurement accuracy of the overlapping data group meets the requirements, and the corresponding analysis area is marked as the basic area; if the overlap coefficient is greater than or equal to the overlap threshold, it is determined that the measurement accuracy of the overlapping data group does not meet the requirements, and the corresponding analysis area is marked as the filling area; the filling area is sent to the filling processing module through the server.

5. The geographic surveying and mapping information acquisition system based on multivariate data fusion processing according to claim 4 is characterized in that: The specific process of the data improvement analysis of the basic area of ​​the output model by the improvement analysis module includes: marking the coordinates of the highest point in the surveying and mapping data of the filling area in the spatial coordinate system of the output model as (CGx, CGy, CGz), substituting (CGx, CGy, CGz) and (YGx, YGy, YGz) into the high point offset calculation formula for numerical calculation, marking the obtained high point offset value PYg as the remote sensing offset high value of the filling area, marking the coordinates of the lowest point in the surveying and mapping data of the filling area in the spatial coordinate system of the output model as (CDx, CDy, CDz), substituting (CDx, CDy, CDz) and (YDx, YDy, YDz) into the low point offset calculation formula for numerical calculation, marking the obtained low point offset value PYd as the remote sensing offset low value of the filling area; summing the remote sensing offset high value and the remote sensing offset low value and taking the average value to obtain to the remote sensing offset value; substitute (CGx, CGy, CGz) and (HGx, HGy, HGz) into the high point offset calculation formula for numerical calculation, and mark the obtained high point offset value PYg as the aerial offset high value of the filling area; substitute (CDx, CDy, CDz) and (HDx, HDy, HDz) into the low point offset calculation formula for numerical calculation, and mark the obtained low point offset value PYd as the aerial offset low value of the filling area; sum and average the aerial offset high value and the aerial offset low value to obtain the aerial offset value of the filling area; sum and average the remote sensing offset values ​​of all the filling areas to obtain the remote sensing offset coefficient, and sum and average the aerial offset values ​​of all the filling areas to obtain the aerial offset coefficient; compare the remote sensing offset coefficient with the aerial offset coefficient and fill the corresponding basic area in the output model with data based on the comparison results.

6. The geographic surveying and mapping information acquisition system based on multivariate data fusion processing according to claim 5 is characterized in that: The specific process of comparing the remote sensing offset coefficient with the aerial offset coefficient includes: if the remote sensing offset coefficient is less than or equal to the aerial offset coefficient, the remote sensing data is used to fill the corresponding basic area in the output model; if the remote sensing offset coefficient is greater than the aerial offset coefficient, the surveying and mapping image data is used to fill the corresponding basic area in the output model.

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