CN106777302B - Method and device for converting space geographic coordinates - Google Patents
Method and device for converting space geographic coordinates Download PDFInfo
- Publication number
- CN106777302B CN106777302B CN201611259704.6A CN201611259704A CN106777302B CN 106777302 B CN106777302 B CN 106777302B CN 201611259704 A CN201611259704 A CN 201611259704A CN 106777302 B CN106777302 B CN 106777302B
- Authority
- CN
- China
- Prior art keywords
- coordinate
- training
- sample data
- data
- conversion
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000006243 chemical reaction Methods 0.000 claims abstract description 74
- 238000012549 training Methods 0.000 claims abstract description 55
- 230000009466 transformation Effects 0.000 claims abstract description 34
- 238000010801 machine learning Methods 0.000 claims abstract description 21
- 238000005070 sampling Methods 0.000 claims abstract description 20
- 238000012545 processing Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000001131 transforming effect Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000009430 construction management Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Processing Or Creating Images (AREA)
Abstract
The invention provides a method and a device for converting space geographic coordinates, wherein the method comprises the following steps: acquiring sample data, wherein the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system; training a coordinate transformation model according to the sample data by using a machine learning method to obtain a trained coordinate transformation model; and converting the coordinate system of the place to be converted by adopting the coordinate conversion model obtained after training. By collecting sample data under different coordinate systems and training the coordinate transformation model by using a machine learning method, the coordinate transformation model with higher accuracy can be obtained, and further, the coordinate transformation model obtained after training can be used for realizing the mutual transformation between different coordinate systems, so that a user can conveniently read maps by adopting more coordinate systems, and technical support is provided for manufacturing superposed maps under various coordinate systems.
Description
Technical Field
The invention relates to the technical field of electronic maps, in particular to a method and a device for converting space geographic coordinates.
Background
At present, the GPS positioning technology has been widely used, and the GPS coordinate system has become a public general coordinate system, such as a Baidu map, a Gade map, and the like, which all use GPS coordinates.
However, most maps adopt city coordinate systems, which are high-precision city coordinate systems constructed for meeting the requirements of city planning and construction management, the needs of investigation design, construction and management of various projects, topographic map surveying and mapping, town cadastral survey and the like of various cities because the precision of a national control network can only meet the requirements of medium and small scale surveying and mapping. For example, currently, most government intranets adopt local maps of city coordinate systems.
At present, because the scales and the accuracies adopted by each local map are different, the adopted city coordinate system is different from the GPS coordinate system, and the GPS coordinate system and the city coordinate system have no clear and direct conversion relationship, the local map is difficult to be combined with the GPS coordinate for reading, and the general GPS map is difficult to be combined with the city coordinate for reading; with the development of the information society, the requirement of combining the city coordinate system and the GPS coordinate system is more and more strong, for example, a superimposed graph with the two coordinate systems is made so that a user can conveniently read and mark according to different requirements, and therefore, a method capable of converting the city coordinate system and the GPS coordinate system is urgently needed.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method and a device for converting space geographic coordinates, which are used for realizing the mutual conversion among different coordinate systems, so that a user can conveniently read a map by adopting more coordinate systems, and technical support is provided for manufacturing a superposed map under various coordinate systems.
In a first aspect, the present invention provides a method for converting spatial geographic coordinates, including:
acquiring sample data, wherein the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system;
training a coordinate transformation model according to the sample data by using a machine learning method to obtain a trained coordinate transformation model;
and converting the coordinate system of the place to be converted by adopting the coordinate conversion model obtained after training.
Optionally, the training a coordinate transformation model according to the sample data by using a machine learning method includes:
and training a coordinate conversion model established based on a four-parameter method according to the sample data by using a machine learning method.
Optionally, the obtaining sample data includes:
marking coordinate data of a plurality of sampling places from a map as sample data by adopting a map punctuation tool; or,
and acquiring sample data uploaded by a user.
Optionally, the coordinate transformation model is implemented based on JAVA language programming, and an external service interface is provided, so that a user can perform coordinate system transformation on the coordinate transformation model obtained after the external service interface calls training.
Optionally, the performing coordinate system conversion on the coordinate of the to-be-converted location by using the coordinate conversion model obtained after training includes:
and performing coordinate system conversion on the coordinates of the to-be-converted location by using the coordinate conversion model obtained after training by using a distributed flow calculation engine.
In a second aspect, an apparatus for transforming geographic spatial coordinates includes:
the system comprises a sample acquisition module, a data acquisition module and a data processing module, wherein the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system;
the model training module is used for training a coordinate transformation model according to the sample data by utilizing a machine learning method to obtain a trained coordinate transformation model;
and the coordinate conversion module is used for converting the coordinate system of the place to be converted by adopting the coordinate conversion model obtained after training.
Optionally, the model training module includes:
and the four-parameter model training unit is used for training a coordinate conversion model established based on a four-parameter method according to the sample data by using a machine learning method.
Optionally, the sample acquiring module includes:
the punctuation tool acquisition unit is used for marking the coordinate data of a plurality of sampling sites from the map as sample data by adopting a map punctuation tool;
or,
and the upload data acquisition unit is used for acquiring sample data uploaded by the user.
Optionally, the coordinate conversion model is implemented based on JAVA language programming, and the coordinate conversion module provides an external service interface, so that a user can call the coordinate conversion model obtained after training through the external service interface to perform coordinate system conversion.
Optionally, the coordinate conversion module includes:
and the distributed coordinate conversion unit is used for converting the coordinate system of the place to be converted by using the coordinate conversion model obtained after training by using the distributed flow calculation engine.
According to the technical scheme, the method for converting the space geographic coordinate, provided by the invention, can obtain the coordinate conversion model with higher accuracy by acquiring the sample data under different coordinate systems and training the coordinate conversion model according to the sample data by using a machine learning method, and further can realize mutual conversion between different coordinate systems by using the coordinate conversion model obtained after training, so that a user can conveniently read maps by adopting more coordinate systems, and technical support is provided for manufacturing superposed maps under various coordinate systems.
The device for converting the space geographic coordinate provided by the invention has the same beneficial effects as the method for converting the space geographic coordinate.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below.
Fig. 1 is a flowchart illustrating a method for converting spatial geographic coordinates according to a first embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a device for converting spatial geographic coordinates according to a second embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
The invention provides a conversion method of a space geographic coordinate, a conversion device of the space geographic coordinate and a conversion system of the space geographic coordinate. Embodiments of the present invention will be described below with reference to the drawings.
Fig. 1 shows a flowchart of a method for converting spatial geographic coordinates according to a first embodiment of the present invention. As shown in fig. 1, a method for converting spatial geographic coordinates according to a first embodiment of the present invention includes the following steps:
step S101: the method comprises the steps of obtaining sample data, wherein the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system.
For example, the first coordinate system may be a city coordinate system and the second coordinate system may be GPS coordinates.
The obtaining of the sample data can be that coordinate data of a plurality of sampling places are marked from a map by adopting a map marking tool and are used as sample data; or, the sample data uploaded by the user may be acquired, for example, a data interface is opened for the user, and the sample data fed back by the user is received through the data interface.
The data size of the sample data can be large or small, and generally, the accuracy of the model trained by the sample is higher.
Step S102: and training a coordinate transformation model according to the sample data by using a machine learning method to obtain the trained coordinate transformation model.
After sample data is obtained, a corresponding coordinate conversion model can be trained by using the sample data, machine learning is to acquire new knowledge or skill according to experience data, reorganize the existing knowledge structure and identify the existing knowledge, and a computer algorithm capable of being automatically improved through experience.
In an embodiment provided by the present invention, the coordinate transformation model may be a coordinate transformation model established based on a four-parameter method, and the training of the coordinate transformation model according to the sample data by using a machine learning method includes:
and training a coordinate conversion model established based on a four-parameter method according to the sample data by using a machine learning method.
Among them, the four-parameter method is a method (mathematical equation system) generally used when converting between two different two-dimensional rectangular plane coordinate systems, and constructs a mathematical model in which there are four unknown parameters, that is:
(1) two coordinate translation amounts (Δ X and Δ Y), i.e., a coordinate difference between the coordinate origin points of the two plane coordinate systems;
(2) the rotation angle θ of the plane coordinate axes can make the X and Y axes of the two coordinate systems coincide by rotating by an angle.
(3) And the scale factor m, namely the length ratio of the same straight line in the two coordinate systems, realizes scale conversion.
Usually, at least two public known points are needed, the four unknown parameters can be calculated only by four pairs of XY coordinate values in two different plane rectangular coordinate systems, and the XY coordinate value of a next point in one plane rectangular coordinate system can be converted into the XY coordinate value in the other plane rectangular coordinate system through a four-parameter equation set after the four parameters are calculated.
In the embodiment of the invention, each group of coordinates in the sample data can be converted into a matrix form, then the sample data in the matrix form is adopted for training, and the four parameters are determined by a least square method, so that a more accurate coordinate conversion model can be determined.
The four-parameter method is a method for performing coordinate conversion which is commonly used in the prior art, specific steps are not repeated, and the method combining machine learning and the four-parameter method is adopted in the embodiment of the invention.
Step S103: and converting the coordinate system of the place to be converted by adopting the coordinate conversion model obtained after training.
After the training of the coordinate transformation model is completed, the trained coordinate transformation model can be used for transforming the coordinates, and the transformation can be from the coordinates in the first coordinate system to the second coordinate system, or from the coordinates in the second coordinate system to the first coordinate system, which are all within the protection scope of the present invention.
In an embodiment provided by the present invention, the coordinate conversion model is implemented based on JAVA language programming, and provides an external service interface, so that a user performs coordinate system conversion on the coordinate conversion model obtained after invoking and training through the external service interface, for example, a webservice/http server may be used to provide services to the outside.
It should be noted that the map is composed of a large number of coordinate points, and in the embodiment of the present invention, a coordinate system may be converted for a certain point in the map, or a coordinate system of a part of points may be converted in batch, or all points of the entire map may be converted, so as to facilitate making a map with multiple coordinate systems superimposed, and facilitate a user to read.
Considering that for the case of many coordinate points, due to the large data volume, the conversion process will consume resources of the conversion system greatly, and the conversion efficiency will also be low, therefore, in an embodiment provided by the present invention, the performing coordinate system conversion on the coordinates of the to-be-converted location by using the coordinate conversion model obtained after training includes:
and performing coordinate system conversion on the coordinates of the to-be-converted location by using the coordinate conversion model obtained after training by using a distributed flow calculation engine.
The distributed stream computing engine is mainly used for processing mass data, adopts distributed computing (a plurality of background machines are used for processing simultaneously), can effectively improve the conversion efficiency of mass coordinates, solves the problems of large computation load and low efficiency when a single computer processes, is particularly suitable for the situation of coordinate conversion of all points of a map, and further makes a superposed map under various coordinate systems. The distributed stream computing engine may adopt Storm, Spark, Samza, etc., and the present invention is not limited to the specific implementation manner, and the above is within the protection scope of the present invention.
By the steps S101 to S103, the process of the method for converting space geographic coordinates according to the first embodiment of the present invention is completed. According to the method for converting the space geographic coordinates, provided by the embodiment of the invention, the coordinate conversion model with higher accuracy can be obtained by acquiring the sample data under different coordinate systems and training the coordinate conversion model according to the sample data by using a machine learning method, and then the coordinate conversion model obtained after training can be used for realizing the mutual conversion between different coordinate systems, so that a user can conveniently read maps by adopting more coordinate systems, and technical support is provided for manufacturing superposed maps under various coordinate systems.
In the first embodiment, a method for converting a spatial geographic coordinate is provided, and correspondingly, an apparatus for converting a spatial geographic coordinate is also provided. Please refer to fig. 2, which is a schematic diagram of a device for converting space-geographic coordinates according to a second embodiment of the present invention. Since the apparatus embodiments are substantially similar to the method embodiments, they are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for relevant points. The device embodiments described below are merely illustrative.
A second embodiment of the present invention provides a device for converting spatial geographic coordinates, including:
the system comprises a sample acquisition module 101, a data processing module and a data processing module, wherein the sample acquisition module 101 is used for acquiring sample data, the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system;
the model training module 102 is used for training a coordinate transformation model according to the sample data by using a machine learning method to obtain a trained coordinate transformation model;
and the coordinate conversion module 103 is configured to perform coordinate system conversion on the coordinates of the to-be-converted location by using the coordinate conversion model obtained after training.
In an embodiment provided by the present invention, the model training module 102 includes:
and the four-parameter model training unit is used for training a coordinate conversion model established based on a four-parameter method according to the sample data by using a machine learning method.
In an embodiment provided by the present invention, the sample acquiring module 101 includes:
the punctuation tool acquisition unit is used for marking the coordinate data of a plurality of sampling sites from the map as sample data by adopting a map punctuation tool;
or,
and the upload data acquisition unit is used for acquiring sample data uploaded by the user.
In an embodiment provided by the present invention, the coordinate transformation model is implemented based on JAVA language programming, and the coordinate transformation module 103 provides an external service interface, so that a user can perform coordinate system transformation on the coordinate transformation model obtained after invoking and training through the external service interface.
In an embodiment provided by the present invention, the coordinate transformation module 103 includes:
and the distributed coordinate conversion unit is used for converting the coordinate system of the place to be converted by using the coordinate conversion model obtained after training by using the distributed flow calculation engine.
The above is a description of an embodiment of a device for converting spatial geographic coordinates according to a second embodiment of the present invention.
The device for converting the space geographic coordinate and the method for converting the space geographic coordinate provided by the invention have the same inventive concept and the same beneficial effects, and are not repeated herein.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It should be noted that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The device for converting a space geographic coordinate provided in the embodiment of the present invention may be a computer program product, and includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to execute the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment, and will not be described herein again.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (6)
1. A method for converting space geographic coordinates is characterized by comprising the following steps:
acquiring sample data, wherein the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system;
training a coordinate transformation model according to the sample data by using a machine learning method to obtain a trained coordinate transformation model;
carrying out coordinate system conversion on the coordinates of the to-be-converted place by adopting the coordinate conversion model obtained after training;
the method for converting the coordinate of the place to be converted by adopting the coordinate conversion model obtained after training comprises the following steps:
performing coordinate system conversion on the coordinates of the to-be-converted location by using the coordinate conversion model obtained after training by using a distributed flow calculation engine;
the acquiring sample data includes:
marking coordinate data of a plurality of sampling places from a map as sample data by adopting a map punctuation tool; or,
and acquiring sample data uploaded by a user.
2. The method for transforming space geographic coordinates according to claim 1, wherein said training a coordinate transformation model according to the sample data by using a machine learning method comprises:
and training a coordinate conversion model established based on a four-parameter method according to the sample data by using a machine learning method.
3. The method for converting spatial geographic coordinates of claim 1, wherein the coordinate conversion model is implemented based on JAVA language programming and provides an external service interface, so that a user can perform coordinate system conversion on the coordinate conversion model obtained after the user invokes training through the external service interface.
4. A device for converting spatial geographic coordinates, comprising:
the system comprises a sample acquisition module, a data acquisition module and a data processing module, wherein the sample data comprises coordinate data of a plurality of sampling positions in a map, and the coordinate data of each sampling point comprises a first coordinate in a first coordinate system and a second coordinate in a second coordinate system;
the model training module is used for training a coordinate transformation model according to the sample data by utilizing a machine learning method to obtain a trained coordinate transformation model;
the coordinate conversion module is used for converting the coordinate system of the place to be converted by adopting the coordinate conversion model obtained after training;
the coordinate conversion module includes:
the distributed coordinate conversion unit is used for performing coordinate system conversion on the coordinates of the to-be-converted location by using the coordinate conversion model obtained after training by using the distributed flow calculation engine;
the sample acquisition module comprises:
the punctuation tool acquisition unit is used for marking the coordinate data of a plurality of sampling sites from the map as sample data by adopting a map punctuation tool;
or,
and the upload data acquisition unit is used for acquiring sample data uploaded by the user.
5. The device for converting spatial geographic coordinates of claim 4, wherein the model training module comprises:
and the four-parameter model training unit is used for training a coordinate conversion model established based on a four-parameter method according to the sample data by using a machine learning method.
6. The device for converting spatial geographic coordinates of claim 4, wherein the coordinate conversion model is implemented based on JAVA language programming, and the coordinate conversion module provides an external service interface so that a user can perform coordinate system conversion on the coordinate conversion model obtained after the user invokes training through the external service interface.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611259704.6A CN106777302B (en) | 2016-12-30 | 2016-12-30 | Method and device for converting space geographic coordinates |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611259704.6A CN106777302B (en) | 2016-12-30 | 2016-12-30 | Method and device for converting space geographic coordinates |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106777302A CN106777302A (en) | 2017-05-31 |
| CN106777302B true CN106777302B (en) | 2020-10-09 |
Family
ID=58954054
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611259704.6A Active CN106777302B (en) | 2016-12-30 | 2016-12-30 | Method and device for converting space geographic coordinates |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106777302B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107845060A (en) * | 2017-10-31 | 2018-03-27 | 广东中星电子有限公司 | Geographical position and corresponding image position coordinates conversion method and system |
| US11127193B2 (en) * | 2018-05-11 | 2021-09-21 | Resight Ltd. | System and method for determining an approximate transformation between coordinate systems |
| CN109492064A (en) * | 2018-10-23 | 2019-03-19 | 上海同岩土木工程科技股份有限公司 | The quick coordinate transformation method of underground engineering spatial information and geographical space unification |
| CN112146645B (en) * | 2019-06-28 | 2022-07-22 | 浙江商汤科技开发有限公司 | Method and device for aligning coordinate system, electronic equipment and storage medium |
| CN110602449A (en) * | 2019-09-01 | 2019-12-20 | 天津大学 | Intelligent construction safety monitoring system method in large scene based on vision |
| CN111708046A (en) * | 2020-04-28 | 2020-09-25 | 上海高仙自动化科技发展有限公司 | Method and device for processing plane data of obstacle, electronic equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105279243A (en) * | 2015-09-28 | 2016-01-27 | 张新长 | Spatial data conversion method and system |
| CN105760451A (en) * | 2016-02-04 | 2016-07-13 | 东南大学 | Big data real-time display and output end based on coordinate transformation and used for urban planning |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7107286B2 (en) * | 1999-07-26 | 2006-09-12 | Geoqwest International Inc. | Integrated information processing system for geospatial media |
| KR101609178B1 (en) * | 2013-09-16 | 2016-04-07 | 엔에이치엔엔터테인먼트 주식회사 | Service method and system for providing reward using moving path of users |
| CN103646109B (en) * | 2013-12-25 | 2017-01-25 | 武汉大学 | Spatial data matching method based on machine learning |
| CN103810286B (en) * | 2014-02-25 | 2017-05-24 | 合肥亿图网络科技有限公司 | Coordinate point positioning method for matching two-dimensional map with three-dimensional map |
-
2016
- 2016-12-30 CN CN201611259704.6A patent/CN106777302B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105279243A (en) * | 2015-09-28 | 2016-01-27 | 张新长 | Spatial data conversion method and system |
| CN105760451A (en) * | 2016-02-04 | 2016-07-13 | 东南大学 | Big data real-time display and output end based on coordinate transformation and used for urban planning |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106777302A (en) | 2017-05-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106777302B (en) | Method and device for converting space geographic coordinates | |
| Hesselbarth et al. | landscapemetrics: an open‐source R tool to calculate landscape metrics | |
| CN107239531B (en) | Implementation method for expanding WMS service of GeoServer releasing custom tiles | |
| Lwin et al. | Web-based GIS system for real-time field data collection using a personal mobile phone | |
| US20140278228A1 (en) | Mapping uncertain geometries to graticules | |
| CN113272798B (en) | Map acquisition method, map acquisition device, computer equipment and storage medium | |
| CN109041218B (en) | Method for predicting user position and intelligent hardware | |
| CN104123695A (en) | Method for realizing coordinate conversion | |
| CN105718498B (en) | The method and apparatus of network map mix-loaded | |
| CN110209748B (en) | Method and apparatus for indexing geofences | |
| Yao et al. | A field survey system for land consolidation based on 3S and speech recognition technology | |
| CN111447292A (en) | IPv6 geographical position positioning method, device, equipment and storage medium | |
| CN102568357A (en) | Electronic device and method for conducting automatic exhibition guide in exhibition hall by utilizing same | |
| CN111881230A (en) | Rendering method and device for map area and electronic equipment | |
| CN114064829A (en) | Method and device for carrying out aggregation display on positioning points and electronic equipment | |
| CN104202817A (en) | Multi-hotspot fingerprint map storage and matching method in large-scale indoor space | |
| CN105354326A (en) | Spatial position indexing method and system | |
| CN103280152A (en) | Building coding method based on longitude and latitude coordinate conversion code | |
| CN111382165A (en) | Mobile homeland management system | |
| KR20150021168A (en) | Field investigation system using smart device | |
| CN114170455A (en) | Object gathering method and device, electronic equipment and storage medium | |
| CN108132992B (en) | Personnel information basic address coding method and system and electronic equipment | |
| CN118520065B (en) | GIS map-based data processing method and device, electronic equipment and storage medium | |
| CN116128835B (en) | Point cloud analysis-based power transmission wire sag measurement method, device and equipment | |
| Kamínek et al. | Mobile usage of digital geographical data in the Apple iPhone device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP02 | Change in the address of a patent holder |
Address after: 518000 2203/2204, Building 1, Huide Building, Beizhan Community, Minzhi Street, Longhua District, Shenzhen, Guangdong Patentee after: SHENZHEN AUDAQUE DATA TECHNOLOGY Ltd. Address before: 518000 units J and K, 12 / F, block B, building 7, Baoneng Science Park, Qinghu Industrial Zone, Qingxiang Road, Longhua New District, Shenzhen City, Guangdong Province Patentee before: SHENZHEN AUDAQUE DATA TECHNOLOGY Ltd. |
|
| CP02 | Change in the address of a patent holder |