CN114239250A - System and method for territorial space planning design - Google Patents
System and method for territorial space planning design Download PDFInfo
- Publication number
- CN114239250A CN114239250A CN202111471468.5A CN202111471468A CN114239250A CN 114239250 A CN114239250 A CN 114239250A CN 202111471468 A CN202111471468 A CN 202111471468A CN 114239250 A CN114239250 A CN 114239250A
- Authority
- CN
- China
- Prior art keywords
- land
- sample
- data
- planning
- unit
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000013461 design Methods 0.000 title claims abstract description 14
- 230000008859 change Effects 0.000 claims abstract description 33
- 239000000463 material Substances 0.000 claims abstract description 22
- 239000000523 sample Substances 0.000 claims description 112
- 238000005259 measurement Methods 0.000 claims description 24
- 239000011159 matrix material Substances 0.000 claims description 21
- 230000004927 fusion Effects 0.000 claims description 17
- 239000002689 soil Substances 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 238000013075 data extraction Methods 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 7
- 238000005070 sampling Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 230000007704 transition Effects 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 7
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 230000004083 survival effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Geometry (AREA)
- Tourism & Hospitality (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Computer Hardware Design (AREA)
- Artificial Intelligence (AREA)
- Remote Sensing (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Graphics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Processing Or Creating Images (AREA)
Abstract
The invention relates to the field of homeland planning, and particularly provides a system and a method for design of a homeland space planning. The land model initial data and the land sample initial data in the space to be planned are processed and fused, the land material type and the land map shape data in the land to be planned are combined, various types of land can be predicted separately, the model established by combining the landform has different types and change trends of the land with various materials, and the model after the land planning can be simulated more accurately.
Description
Technical Field
The invention relates to the field of homeland planning, in particular to a system and a method for homeland space planning and design.
Background
The territorial space refers to the territorial space under the jurisdiction of the national ownership and the ownership right, is the place and environment for the survival of the national people, and comprises land, onshore water areas, inland water, territorial sea, territorial space and the like, wherein, when the land space is developed, the land utilization is changed to fundamentally change the structure and the function of the ecological system, has profound influence on resources, environment and society, along with the population growth and the economic development, the development and the utilization of natural resources of human beings are increasing day by day, the change of land utilization is promoted to be more active, the problems caused by the method, such as climate change, biodiversity maintenance, food supply capacity, environmental pollution and the like, become hot problems which are commonly concerned by the society and the scientific community, so the method is very important for simulating the spatial distribution pattern of land utilization change, the dynamic simulation and prediction of the ecological effect are the premise and the basis for making ecological environment planning and researching the land utilization sustainability;
in the prior art, in the process of planning the territorial space, remote sensing data observation is generally adopted to establish a model and predict changes, so that the space is planned, but effective change prediction is difficult to perform according to real-time terrain.
Disclosure of Invention
The invention mainly aims to provide a system and a method for territorial space planning and design so as to solve the problems in the related art.
In order to achieve the above object, according to one aspect of the present invention, there is provided a system for planning and designing a homeland space, comprising a land figure collection module, a land sample collection module, a land figure analysis module, a land sample analysis module, a sample and figure fusion module and an analysis planning module, wherein the land figure collection module is in signal connection with the land figure analysis module, the land sample collection module is in signal connection with the land sample analysis module, the land figure analysis module and the land sample analysis module are both in signal connection with the sample and figure fusion module, the sample and figure fusion module is in signal connection with the analysis planning module, the land figure collection module is used for obtaining initial data of a land figure in a space to be planned, the land sample collection module is used for obtaining initial data of a land sample in a space to be planned, the land figure analysis module is used for analyzing and processing initial data of land figures, the land sample analysis module is used for analyzing and processing the initial data of the land samples, the sample and figure fusion module is used for fusing the processed initial data of the land figures and the land sample data and constructing an original land three-dimensional model, and the analysis planning module is used for analyzing and constructing the original land three-dimensional model and constructing a planning model.
Furthermore, the land figure acquisition module comprises a cloud picture shooting unit and a boundary extraction unit, the cloud picture shooting unit is used for shooting cloud pictures of all regions through the unmanned aerial vehicle and storing shot pictures, and the boundary extraction unit is used for extracting boundary figures of all regions from the shot pictures.
Furthermore, the land sample collection module comprises a dot matrix determination unit and a sample acquisition unit, wherein the dot matrix determination unit is used for determining dot matrixes according to the areas of all regions and positioning each point in the dot matrixes to the land, and the sample acquisition unit is used for collecting land samples at each positioning point.
Further, the land figure analysis module comprises a boundary analysis unit and a coordinate generation unit, wherein the boundary analysis unit is used for generating land boundary data according to the boundary figures, and the coordinate generation unit is used for calculating three-dimensional coordinate data of land space in each boundary figure according to the shot pictures.
Furthermore, the land sample analysis module comprises a sample comparison unit and a land type generation unit, wherein the sample comparison unit is used for acquiring land material data from the Internet, comparing the collected land sample with the land material data and obtaining the land sample material data, and the land type generation unit classifies the compared land sample material data into corresponding land material types to obtain the sample land types of the positioning points.
Further, the sample and graph fusion module comprises a data extraction unit, a data classification unit and a first three-dimensional graph generation unit, wherein the data extraction unit is used for extracting land boundary data, three-dimensional coordinate data and sample land type data, the data classification unit is used for correspondingly classifying the land boundary data, the three-dimensional coordinate data and the sample land type data of each land area, and the first three-dimensional graph generation unit is used for constructing an original land three-dimensional model according to the classified data.
Furthermore, the analysis planning module comprises a model analysis unit, a change prediction unit and a second three-dimensional graph generation unit, wherein the model analysis unit is used for analyzing the original land three-dimensional model and extracting a possibly changed region in the original land three-dimensional model, the change prediction unit is used for simulating the change trend of the possibly changed region according to the possibly changed region and by combining with influence factors, and the second three-dimensional graph generation unit is used for modifying the original land three-dimensional model according to the change trend to obtain the planning model.
According to another aspect of the present invention, there is provided a method for territorial space planning and design, comprising the steps of:
s1: acquiring initial data of a land graph and initial data of a land sample in a space to be planned;
s2: analyzing and processing initial data of the land graph and initial data of the land sample;
s3: fusing the processed soil map graphic data and the soil sample data and constructing an original soil three-dimensional model;
s4: and analyzing and constructing an original land three-dimensional model and constructing a planning model.
Further, S1 to S4 specifically include: shooting cloud pictures of all regions by an unmanned aerial vehicle, storing the shot pictures, extracting boundary graphs of all regions from the shot pictures, generating land boundary data according to the boundary graphs, and calculating three-dimensional coordinate data of land spaces in all the boundary graphs according to the shot pictures; determining a dot matrix according to the area of each region, positioning each point in the dot matrix to the land, collecting land samples at each positioning point, acquiring land material data from the Internet, comparing the collected land samples with the land material data to obtain the land sample material data, classifying the compared land sample material data into corresponding land material types to obtain the sample land types at each positioning point; extracting land boundary data, three-dimensional coordinate data and sample land type data, correspondingly classifying the land boundary data, the three-dimensional coordinate data and the sample land type data of each land area, and constructing an original land three-dimensional model according to the classified data; analyzing the original land three-dimensional model, extracting a possibly-changed region in the original land three-dimensional model, simulating the change trend of the possibly-changed region according to the possibly-changed region and by combining influence factors, and modifying the original land three-dimensional model according to the change trend to obtain a planning model.
Further, the simulating the change trend of the possibly changed region adopts an incidence matrix method to perform data training, and specifically includes:
after the current candidate measurement is obtained, the database is searched for data needed for subsequent processing in the first step, that is, the measurement z representing the position, speed or identity estimation of the target measurement in the previous sampling period is foundj(tj) And the vector x of the current metrology state estimatej(tj) Correcting the alternative measurement to the observation time tiWhen the measurement is dynamic, the state estimation vector of the alternative measurement needs to be corrected to the observation time tiBy x (t)i)＝Φ(ti，tj)x(tj) + v calculated at tiThe predicted value of the state x of the alternative measurement at the moment, wherein: phi (t)i，tj) Representing a state transition matrix, v is unknown noise; predicting the position of each candidate target measurement as x (t)i+1)＝Φ(ti+1，tj)x(tj)+v。
Compared with the prior art, the invention has the following beneficial effects: the land model initial data and the land sample initial data in the space to be planned are processed and fused, the land material type and the land map shape data in the land to be planned are combined, various types of land can be predicted separately, the model established by combining the landform has different types and change trends of the land with various materials, and the model after the land planning can be simulated more accurately.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
The structure, proportion, size and the like shown in the drawings are only used for matching with the content disclosed in the specification, so that the person skilled in the art can understand and read the description, and the description is not used for limiting the limit condition of the implementation of the invention, so the method has no technical essence, and any structural modification, proportion relation change or size adjustment still falls within the scope of the technical content disclosed by the invention without affecting the effect and the achievable purpose of the invention.
FIG. 1 is a connection diagram of an integral module according to the present invention;
FIG. 2 is a block diagram of a land figure collection module according to the present invention;
FIG. 3 is a block diagram of a land sample collection module according to the present invention;
FIG. 4 is a block diagram of a land pattern analysis module according to the present invention;
FIG. 5 is a block diagram of an analysis module for soil samples according to the present invention;
FIG. 6 is a block diagram of a sample and graph fusion module according to the present invention;
FIG. 7 is a block diagram of an analysis planning module according to the present invention.
Illustration of the drawings: 1. a land figure acquisition module; 100. a cloud picture shooting unit; 101. a boundary extraction unit; 2. a land sample collection module; 200. a dot matrix determination unit; 201. a sample acquisition unit; 3. a land pattern analysis module; 300. a boundary analysis unit; 301. a coordinate generating unit; 4. a land sample analysis module; 400. a sample comparison unit; 401. a land type generation unit; 5. a sample and graph fusion module; 500. a data extraction unit; 501. a data classification unit; 502. a first three-dimensional graphic generation unit; 6. an analysis planning module; 600. a model analysis unit; 601. a change prediction unit; 602. a second three-dimensional graphics generation unit.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. It should be noted that when one component is referred to as being "connected" to another component, it can be directly connected to the other component or intervening components may also be present.
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
A system for planning and designing a national soil space comprises a land figure acquisition module 1, a land sample acquisition module 2, a land figure analysis module 3, a land sample analysis module 4, a sample and figure fusion module 5 and an analysis planning module 6, wherein the land figure acquisition module 1 is in signal connection with the land figure analysis module 3, the land sample acquisition module 2 is in signal connection with the land sample analysis module 4, the land figure analysis module 3 and the land sample analysis module 4 are both in signal connection with the sample and figure fusion module 5, the sample and figure fusion module 5 is in signal connection with the analysis planning module 6, the land figure acquisition module 1 is used for acquiring initial data of a land figure in the space to be planned, the land sample acquisition module 2 is used for acquiring initial data of a land sample in the space to be planned, the land figure analysis module 3 is used for analyzing and processing the initial data of the land figure, the land sample analysis module 4 is used for analyzing and processing initial data of a land sample, the sample and graph fusion module 5 is used for fusing the processed soil map graph data and the land sample data and constructing an original land three-dimensional model, and the analysis planning module 6 is used for analyzing and constructing the original land three-dimensional model and constructing a planning model.
The land figure acquisition module 1 comprises a cloud picture shooting unit 100 and a boundary extraction unit 101, wherein the cloud picture shooting unit 100 is used for shooting cloud pictures of various regions through an unmanned aerial vehicle and storing shot pictures, and the boundary extraction unit 101 is used for extracting boundary figures of the various regions from the shot pictures. The land sample acquisition module 2 comprises a dot matrix determination unit 200 and a sample acquisition unit 201, the dot matrix determination unit 200 is used for determining dot matrixes according to the areas of various regions and positioning each point in the dot matrixes to land, the sample acquisition unit 201 is used for acquiring land samples at each positioning point, the land pattern analysis module 3 comprises a boundary analysis unit 300 and a coordinate generation unit 301, the boundary analysis unit 300 is used for generating land boundary data according to boundary patterns, the coordinate generation unit 301 is used for calculating three-dimensional coordinate data of land spaces in each boundary pattern according to a shot picture, the land sample analysis module 4 comprises a sample comparison unit 400 and a land type generation unit 401, the sample comparison unit 400 is used for acquiring each land material data from the internet and comparing the acquired land samples with the land material data to obtain the land sample material data, the land type generating unit 401 classifies the compared land sample material data into corresponding land material types, and the obtained sample land type, sample and graph fusion module 5 at each positioning point comprises a data extraction unit 500, a data classification unit 501 and a first three-dimensional graph generating unit 502, wherein the data extraction unit 500 is used for extracting land boundary data, three-dimensional coordinate data and sample land type data, the data classification unit 501 is used for correspondingly classifying the land boundary data, the three-dimensional coordinate data and the sample land type data of each land area, and the first three-dimensional graph generating unit 502 is used for constructing an original land three-dimensional model according to the classified data. The analysis planning module 6 includes a model analysis unit 600, a change prediction unit 601 and a second three-dimensional graph generation unit 602, where the model analysis unit 600 is configured to analyze the original land three-dimensional model and extract a region that may change in the original land three-dimensional model, the change prediction unit 601 is configured to simulate a change trend of the region that may change according to the region that may change and by combining with an influence factor, and the second three-dimensional graph generation unit 602 is configured to modify the original land three-dimensional model according to the change trend to obtain a planning model.
A method for planning and designing a homeland space is characterized by comprising the following steps:
s1: acquiring initial data of a land graph and initial data of a land sample in a space to be planned;
s2: analyzing and processing initial data of the land graph and initial data of the land sample;
s3: fusing the processed soil map graphic data and the soil sample data and constructing an original soil three-dimensional model;
s4: and analyzing and constructing an original land three-dimensional model and constructing a planning model.
Specifically, S1 to S4 specifically include: shooting cloud pictures of all regions by an unmanned aerial vehicle, storing the shot pictures, extracting boundary graphs of all regions from the shot pictures, generating land boundary data according to the boundary graphs, and calculating three-dimensional coordinate data of land spaces in all the boundary graphs according to the shot pictures; determining a dot matrix according to the area of each region, positioning each point in the dot matrix to the land, collecting land samples at each positioning point, acquiring land material data such as rocks, loose soil and the like from the Internet, comparing the collected land samples with the land material data to obtain the land sample material data, classifying the compared land sample material data into corresponding land material types to obtain the sample land types at each positioning point; extracting land boundary data, three-dimensional coordinate data and sample land type data, correspondingly classifying the land boundary data, the three-dimensional coordinate data and the sample land type data of each land area, and constructing an original land three-dimensional model according to the classified data; analyzing the original land three-dimensional model, extracting a possibly-changed region in the original land three-dimensional model, simulating the change trend of the possibly-changed region according to the possibly-changed region and by combining influence factors, and modifying the original land three-dimensional model according to the change trend to obtain a planning model.
Further, simulating the change trend of the possibly changed region and performing data training by using an incidence matrix method, specifically comprising the following steps:
after the current candidate measurement is obtained, the database is searched for data needed for subsequent processing in the first step, that is, the measurement z representing the position, speed or identity estimation of the target measurement in the previous sampling period is foundj(tj) And the vector x of the current metrology state estimatej(tj) Correcting the alternative measurement to the observation time tiWhen the measurement is dynamic, the state estimation vector of the alternative measurement needs to be corrected to the observation time tiBy x (t)i)＝Φ(ti，tj)x(tj) + v calculated at tiThe predicted value of the state x of the alternative measurement at the moment, wherein: phi (t)i，tj) Representing a state transition matrix, v is unknown noise; predicting the position of each candidate target measurement as x (t)i+1)＝Φ(ti+1，tj)x(tj)+v。
Spatially relative terms, such as "above … …," "above … …," "above … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial relationship to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if a device in the figures is turned over, devices described as "above" or "on" other devices or configurations would then be oriented "below" or "under" the other devices or configurations. Thus, the exemplary term "above … …" can include both an orientation of "above … …" and "below … …". The device may be otherwise variously oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A system for planning and designing a homeland space is characterized by comprising a land figure acquisition module (1), a land sample acquisition module (2), a land figure analysis module (3), a land sample analysis module (4), a sample and figure fusion module (5) and an analysis planning module (6), wherein the land figure acquisition module (1) is in signal connection with the land figure analysis module (3), the land sample acquisition module (2) is in signal connection with the land sample analysis module (4), the land figure analysis module (3) and the land sample analysis module (4) are both in signal connection with the sample and figure fusion module (5), the sample and figure fusion module (5) is in signal connection with the analysis planning module (6), and the land figure acquisition module (1) is used for acquiring initial land figure data in a space to be planned, the land sample acquisition module (2) is used for acquiring initial data of a land sample in a space to be planned, the land graphic analysis module (3) is used for analyzing and processing the initial data of the land graphic, the land sample analysis module (4) is used for analyzing and processing the initial data of the land sample, the sample and graphic fusion module (5) is used for fusing the processed initial data of the land sample and constructing an original land three-dimensional model, and the analysis planning module (6) is used for analyzing and constructing the original land three-dimensional model and constructing a planning model.
2. The system for territorial space planning and design according to claim 1, wherein the land figure acquisition module (1) comprises a cloud picture shooting unit (100) and a boundary extraction unit (101), the cloud picture shooting unit (100) is used for shooting cloud pictures of all regions through an unmanned aerial vehicle and storing shot pictures, and the boundary extraction unit (101) is used for extracting boundary figures of all regions from the shot pictures.
3. The system for territorial space planning and design according to claim 2, wherein the land sample collection module (2) comprises a dot matrix determination unit (200) and a sample acquisition unit (201), the dot matrix determination unit (200) is used for determining a dot matrix according to each regional area and positioning each point in the dot matrix to the land, and the sample acquisition unit (201) is used for collecting a land sample at each positioning point.
4. The system for territorial space planning and design according to claim 3, wherein the land figure analysis module (3) comprises a boundary analysis unit (300) and a coordinate generation unit (301), the boundary analysis unit (300) is used for generating land boundary data according to boundary figures, and the coordinate generation unit (301) is used for calculating three-dimensional coordinate data of land space in each boundary figure according to shot pictures.
5. The system for territorial space planning and design according to claim 4, wherein the land sample analysis module (4) comprises a sample comparison unit (400) and a land type generation unit (401), the sample comparison unit (400) is used for acquiring land material data from the Internet, comparing the acquired land sample with the land material data and obtaining land sample material data, and the land type generation unit (401) classifies the compared land sample material data into corresponding land material types to obtain sample land types at the positioning points.
6. The system for territorial space planning and design according to claim 5, wherein the sample and graph fusion module (5) comprises a data extraction unit (500), a data classification unit (501) and a first three-dimensional graph generation unit (502), the data extraction unit (500) is used for extracting land boundary data, three-dimensional coordinate data and sample land type data, the data classification unit (501) is used for correspondingly classifying the land boundary data, the three-dimensional coordinate data and the sample land type data of each land area, and the first three-dimensional graph generation unit (502) is used for constructing an original land three-dimensional model according to the classified data.
7. The system for territorial space planning and design according to claim 6, wherein the analysis and planning module (6) comprises a model analysis unit (600), a change prediction unit (601) and a second three-dimensional graph generation unit (602), the model analysis unit (600) is used for analyzing the original land three-dimensional model and extracting regions which are possibly changed from the original land three-dimensional model, the change prediction unit (601) is used for simulating the change trend of the regions which are possibly changed according to the regions which are possibly changed and by combining with influence factors, and the second three-dimensional graph generation unit (602) is used for modifying the original land three-dimensional model according to the change trend to obtain the planning model.
8. A method for planning and designing a homeland space is characterized by comprising the following steps:
s1: acquiring initial data of a land graph and initial data of a land sample in a space to be planned;
s2: analyzing and processing initial data of the land graph and initial data of the land sample;
s3: fusing the processed soil map graphic data and the soil sample data and constructing an original soil three-dimensional model;
s4: and analyzing and constructing an original land three-dimensional model and constructing a planning model.
9. The method for territorial space planning and design according to claim 8, wherein the steps S1-S4 specifically include: shooting cloud pictures of all regions by an unmanned aerial vehicle, storing the shot pictures, extracting boundary graphs of all regions from the shot pictures, generating land boundary data according to the boundary graphs, and calculating three-dimensional coordinate data of land spaces in all the boundary graphs according to the shot pictures; determining a dot matrix according to the area of each region, positioning each point in the dot matrix to the land, collecting land samples at each positioning point, acquiring land material data from the Internet, comparing the collected land samples with the land material data to obtain the land sample material data, classifying the compared land sample material data into corresponding land material types to obtain the sample land types at each positioning point; extracting land boundary data, three-dimensional coordinate data and sample land type data, correspondingly classifying the land boundary data, the three-dimensional coordinate data and the sample land type data of each land area, and constructing an original land three-dimensional model according to the classified data; analyzing the original land three-dimensional model, extracting a possibly-changed region in the original land three-dimensional model, simulating the change trend of the possibly-changed region according to the possibly-changed region and by combining influence factors, and modifying the original land three-dimensional model according to the change trend to obtain a planning model.
10. The method for territorial space planning design according to claim 9, wherein the simulation of the change trend of the regions with possible changes is performed by data training using an incidence matrix method, which specifically comprises:
after the current candidate measurement is obtained, the database is searched for data needed for subsequent processing in the first step, that is, the measurement z representing the position, speed or identity estimation of the target measurement in the previous sampling period is foundj(tj) And the vector x of the current metrology state estimatej(tj) Correcting the alternative measurement to the observation time tiWhen the measurement is dynamic, the state estimation vector of the alternative measurement needs to be corrected to the observation time tiBy x (t)i)＝Φ(ti，tj)x(tj) + v calculated at tiThe predicted value of the state x of the alternative measurement at the moment, wherein: phi (t)i，tj) Representing a state transition matrix, v is unknown noise; predicting the position of each candidate target measurement as x (t)i+1)＝Φ(ti+1，tj)x(tj)+v。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111471468.5A CN114239250B (en) | 2021-11-24 | 2021-11-24 | System and method for territorial space planning design |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111471468.5A CN114239250B (en) | 2021-11-24 | 2021-11-24 | System and method for territorial space planning design |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114239250A true CN114239250A (en) | 2022-03-25 |
| CN114239250B CN114239250B (en) | 2022-10-21 |
Family
ID=80753133
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111471468.5A Active CN114239250B (en) | 2021-11-24 | 2021-11-24 | System and method for territorial space planning design |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114239250B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116758360A (en) * | 2023-08-21 | 2023-09-15 | 江西省国土空间调查规划研究院 | Land space use management method and system thereof |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102004963A (en) * | 2010-12-02 | 2011-04-06 | 张磊 | Digital city generation method and system |
| CN102117497A (en) * | 2009-12-30 | 2011-07-06 | 新奥特（北京）视频技术有限公司 | Method and system for three-dimensional terrain modeling |
| CN106611246A (en) * | 2015-10-21 | 2017-05-03 | 星际空间（天津）科技发展有限公司 | Integrated management system of land and resources |
| CN108564516A (en) * | 2018-05-08 | 2018-09-21 | 湖南城市学院 | A kind of urban planning decision support system |
| CN110069869A (en) * | 2019-04-26 | 2019-07-30 | 成都晨夏科技有限公司 | A kind of more rule unification regional spatial planning information management platforms |
| CN110580539A (en) * | 2018-06-11 | 2019-12-17 | 深圳市数字城市工程研究中心 | Method and system for feeding back land utilization change based on land space-time model |
| CN111369059A (en) * | 2020-03-05 | 2020-07-03 | 山东大学 | Urban waterlogging prediction method and system based on rapid waterlogging simulation coupling model |
| CN111475563A (en) * | 2020-04-08 | 2020-07-31 | 刘德 | Territorial space planning system based on GIS |
| CN111899338A (en) * | 2020-08-05 | 2020-11-06 | 芯元(浙江)科技有限公司 | Method, device and system for three-dimensional modeling of stratum lithology of coverage area |
| CN112380303A (en) * | 2020-10-26 | 2021-02-19 | 上海市政工程设计研究总院（集团）有限公司 | Information linkage-based territorial space planning and investigation method |
| CN112988788A (en) * | 2021-05-20 | 2021-06-18 | 四川省林业和草原调查规划院 | Method for checking mutation of spatial data in territorial space planning, application system and cloud platform |
-
2021
- 2021-11-24 CN CN202111471468.5A patent/CN114239250B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102117497A (en) * | 2009-12-30 | 2011-07-06 | 新奥特（北京）视频技术有限公司 | Method and system for three-dimensional terrain modeling |
| CN102004963A (en) * | 2010-12-02 | 2011-04-06 | 张磊 | Digital city generation method and system |
| CN106611246A (en) * | 2015-10-21 | 2017-05-03 | 星际空间（天津）科技发展有限公司 | Integrated management system of land and resources |
| CN108564516A (en) * | 2018-05-08 | 2018-09-21 | 湖南城市学院 | A kind of urban planning decision support system |
| CN110580539A (en) * | 2018-06-11 | 2019-12-17 | 深圳市数字城市工程研究中心 | Method and system for feeding back land utilization change based on land space-time model |
| CN110069869A (en) * | 2019-04-26 | 2019-07-30 | 成都晨夏科技有限公司 | A kind of more rule unification regional spatial planning information management platforms |
| CN111369059A (en) * | 2020-03-05 | 2020-07-03 | 山东大学 | Urban waterlogging prediction method and system based on rapid waterlogging simulation coupling model |
| CN111475563A (en) * | 2020-04-08 | 2020-07-31 | 刘德 | Territorial space planning system based on GIS |
| CN111899338A (en) * | 2020-08-05 | 2020-11-06 | 芯元(浙江)科技有限公司 | Method, device and system for three-dimensional modeling of stratum lithology of coverage area |
| CN112380303A (en) * | 2020-10-26 | 2021-02-19 | 上海市政工程设计研究总院（集团）有限公司 | Information linkage-based territorial space planning and investigation method |
| CN112988788A (en) * | 2021-05-20 | 2021-06-18 | 四川省林业和草原调查规划院 | Method for checking mutation of spatial data in territorial space planning, application system and cloud platform |
Non-Patent Citations (2)
| Title |
|---|
| 孟宏伟: "基于GIS平台的国土规划多源数据集成应用实例", 《测绘与空间地理信息》 * |
| 牛磊等: "基于Smart3D无人机倾斜摄影三维建模方法研究", 《中国农业信息》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116758360A (en) * | 2023-08-21 | 2023-09-15 | 江西省国土空间调查规划研究院 | Land space use management method and system thereof |
| CN116758360B (en) * | 2023-08-21 | 2023-10-20 | 江西省国土空间调查规划研究院 | Land space use management method and system thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114239250B (en) | 2022-10-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107833280B (en) | Outdoor mobile augmented reality method based on combination of geographic grids and image recognition | |
| Zhou et al. | Individual tree parameters estimation for plantation forests based on UAV oblique photography | |
| CN112257605B (en) | Three-dimensional target detection method, system and device based on self-labeling training sample | |
| CN111033318A (en) | Local weather prediction | |
| CN102959946A (en) | Augmenting image data based on related 3d point cloud data | |
| CN109934847A (en) | The method and apparatus of weak texture three-dimension object Attitude estimation | |
| EP3317852B1 (en) | Method in constructing a model of a scenery and device therefor | |
| Brekke et al. | Multimodal 3d object detection from simulated pretraining | |
| CN107945217A (en) | A kind of image characteristic point suitable for automatic assembling is to rapid screening method and system | |
| CN116843845A (en) | Spatial data integration method and system applied to digital twin city | |
| CN113610070A (en) | Landslide disaster identification method based on multi-source data fusion | |
| CN112084871B (en) | High-resolution remote sensing target boundary extraction method based on weak supervised learning | |
| Vizzari | Peri-urban transformations in agricultural landscapes of Perugia, Italy | |
| CN115565203A (en) | Cross-mode weak supervision three-dimensional human body posture estimation method and system | |
| CN116343103A (en) | Natural resource supervision method based on three-dimensional GIS scene and video fusion | |
| CN114239250B (en) | System and method for territorial space planning design | |
| CN117076928A (en) | Bridge health state monitoring method, device and system and electronic equipment | |
| CN111325184A (en) | Intelligent interpretation and change information detection method for remote sensing image | |
| CN116206068B (en) | Three-dimensional driving scene generation and construction method and device based on real data set | |
| Kuhn et al. | Topology-based analysis for multimodal atmospheric data of volcano eruptions | |
| Ward et al. | A model-based approach to recovering the structure of a plant from images | |
| CN116381650A (en) | Laser radar point cloud position and intensity simulation and test method | |
| CN109118576A (en) | Large scene three-dimensional reconstruction system and method for reconstructing based on BDS location-based service | |
| Lu et al. | M2fNet: Multi-Modal Forest Monitoring Network on Large-Scale Virtual Dataset | |
| CN114818857A (en) | Deep snow fusion method |
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 |