CN108304470A - A kind of city underground paths planning method based on ArcGIS - Google Patents
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Abstract
A kind of city underground paths planning method based on ArcGIS, includes the following steps:A1, map vector is obtained;A2, Slope-extraction and processing generation slope map are carried out to altitude data;A3, analyzed River Data and handled generation river distribution map;A4, processing generation lisarithmic map is carried out to the density of population;A5, reclassification is carried out to river reach figure;Reclassification is carried out to slope map;Reclassification is carried out to lisarithmic map;A6, domain analysis is carried out to elevation map, reclassification then is carried out to field figure;A7, the reclassification slope map to generation, reclassification river reach figure and reclassification lisarithmic map merge, and generate ultimate cost datagram;A8, the minimum connectivity network of manufacturing cost between two or more input areas;A9, water channel principium is generated.Present invention combination GIS is based on actual landform, river and density of population situation, improves the validity of the accuracy and decision of subway route planning.
Description
Technical field
The present invention relates to a kind of geographic information data processing, computer application field, geography, graph theory and network analysis,
Communication and Transportation Engineering and Management Science and Engineering more particularly to a kind of city underground paths planning method based on ArcGIS.
Background technology
The fast development of society and the increasingly quickening of urbanization process.Currently, China city is especially metropolitan population
Scale constantly expands, and a large amount of population collections are in big city.Although country takes the policy of " stringent control Development of large city scale ",
But there are certain population size and perfect public service facility in big city as a given area economy, the center of social development,
It needs to expand the radiant force and influence power of oneself again.Along with the fast development of economic society, China big and medium-sized cities generally existing
The phenomenon of crowded road, congested with cars, traffic order confusion, urban traffic blocking becomes government and the puzzlement of the common people.But
It is that town site is narrow, highly dense population is many metropolitan distinguishing features in China.Such as Shanghai, Chongqing, Shenyang city
Construction land is only 50m per capita in city2Left and right.Industrial land, intercity transportation land and inhabitation are arranged in such narrow space
Land used etc., it is necessary to lead to the reduction of land for roads per capita and urban green space.So more public ways can not be arranged.Separately
Outside, the living standard of the people is continuously improved, and car is increasingly entering family, and motor vehicle constantly increases to be held with urban road
It is more and more prominent to measure limited contradiction.Car enters family, the demand of traffic can explosion type rise, traffic jam issue with
Aggravation.The direct method for solving urban traffic congestion is to improve the whole traffic capacity of road, but for building in big city
Road it is extremely limited.
Urban land has not only been saved in the appearance of city underground, the stream of people is diverted to underground, and substantially increase people
Go out line efficiency.Subway has many good qualities, and first, freight volume is big, irreversibly delivers ability per hour, and bus is 2000~5000
People, light rail are 5000~30,000 people, and subway is up to 30,000~70,000 people.Rail traffic ability is 2.4~14 times of bus.Its
Secondary, speed is fast, 10~20 kilometers per hour of bus, 20~30 kilometers of light rail, 35~50 kilometers of subway, and up to 70~80
Kilometer, light rail and subway are 2~4 times of bus.Followed by pollution is few, because electric drive is a kind of clean transporter
Formula.It is finally that energy consumption is fewer, energy consumption is the 15%~40% of road traffic.Take up an area it is fewer, per hour convey 50,000 people needed for
Road width, car is 180 meters, and bus is 9 meters, track traffic synthetic take up an area be road traffic 1/3, subway and
Overhead system light rail land occupation is less, so, the phenomenon that only subway can alleviate city traffic congestion.
For building for city underground, subway route planning is key link.Good subway route planning can improve
The efficiency of service and running quality of subway.However China's most area plans subway route, workload pole using manual type
Greatly.Because subway route planning is related to the factors such as mountainous region, the gradient, river, the density of population, the path planning of manual type is difficult to take into account
Subway cost and service quality cause the problems such as subway utilization rate is relatively low, traffic route is long or input cost is excessively high.
Therefore, existing city underground paths planning method Shortcomings, need to improve.
Invention content:
In order to overcome the shortcomings of that the path planning of manual type in the prior art, the present invention provide one kind with real space
Manage information according to, by GIS spatial networks analytical technology, consider mountainous region, the gradient, river, the factors such as the density of population city
Iron paths planning method.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of city underground optimum path planning method based on ArcGIS, includes the following steps:
A1, map vector file, including coordinate file, index file and property file are obtained, coordinate file is for recording
Spatial coordinated information, coordinate file are made of header file and entity information two parts;Index file includes the index information of file,
Each record includes corresponding coordinate file, the offset of the file header of recording distance coordinate file in file;Property file packet
The feature of the feature recorded containing one, the data for including in file include altitude data, River Data, density data of population,
Path source point data and path termination data;
A2, altitude data is handled, because of mountainous region, the distribution in the gradient and river influences the path planning of subway
It is larger, so first having to create data set, the gradient, slope aspect category single order terrain factor, the Spatial in ArcGISPro
Analyst Tools drop-down bezel, cluster selection Surface Analysis simultaneously click slope, to altitude data carry out Slope-extraction with
Processing generates slope map;
A3, River Data is handled, the Spatial Analyst Tools drop-down bezel, cluster choosings in ArcGIS Pro
It selects Surface Analysis and clicks hydrologic analysis, River Data is analyzed and is handled, generate river
Distribution map;
A4, demographic data is handled, the influence that the density of population plans subway route is also larger, and therefore, it is necessary to create
The data set for building the density of population, the Spatial Analyst Tools drop-down bezel, clusters in ArcGIS Pro select density,
The density of population is handled, lisarithmic map is generated;
A5, the Reclassify that bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro, to river reach figure
Reclassification is carried out, by 4 grades of equidistantly classification;Reclassification is carried out to slope map, reclassification basic principle is to use equidistantly to be divided into
15 grades, the gradient more high-grade value is bigger;To lisarithmic map carry out reclassification, by 4 grades equidistantly classify, population more multilevel values more
Greatly;
A6, the Neighborhood in bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro
Statistics carries out domain analysis to elevation map, then carries out reclassification to field figure, by 15 grades of equidistantly classification;
A7, Raster Calculator are selected in Spatial Analyst Tools drop-down bezel, clusters, to dividing for generation again
Class slope map, reclassification river reach figure and reclassification lisarithmic map merge, and generate ultimate cost data set, final cost
Datagram is generated by following formula:
Cost data figure=reclassification slope map * a+ reclassifications river reach figure * b+ reclassification lisarithmic map * c+ reclassifications neck
Domain figure * d, wherein a, b, c and d is weighted value, and different weighted values can be chosen according to actual demand;
Cost Weighted in Spatial Analyst Tools drop-down bezel, cluster selection Distance to finally at
Notebook data collection figure carries out the processing of Cost Distance and cost direction,
In the road network analysis of ArcGIS, Shortest Path Analysis and shortest time point are realized using Dijkstra methods
Analysis, the processing procedure of Dijkstra methods are:From any point vs(vs∈Vc∪Vd) set out, gradually to destination node vd(vd∈
Vc∪VdAnd vd≠vs) find shortest path or shortest time and give label to each vertex in the process of implementation:P label tables
Show from vsTo the shortest path of the point or the power of shortest time, also referred to as forever mark, once i.e. certain point vsObtain P labels, value
No longer change in entire solution procedure;T labels are indicated from vsTo the upper bound of the power of the shortest distance or shortest time of the point,
It is referred to as temporary mark or exploratory label, and the T labels of certain point is changed to P labels, at most (k is in figure by k-1 steps
Number of vertex), can solve from vsShortest path to each point or shortest time;
A8, the Cost connectivity in Spatial Analyst Tools drop-down bezel, cluster selections Distance,
Cost connectivity can between two or more input areas the minimum connectivity network of manufacturing cost;
A9, the Cost Path in Spatial Analyst Tools drop-down bezel, cluster selections Distance, generate minimum
Cost path.
Further, in the step A1, the map vector file of the acquisition to wrap expand altitude data, River Data,
Density data of population, path source point data and path termination data.
Further, in the step A7, ultimate cost data set will be by reclassification slope map, reclassification river reach figure and again
Classification lisarithmic map merges generation.
Beneficial effects of the present invention are mainly manifested in:The paths planning method of the present invention combines GIS, based on practically
Shape, river and density of population situation improve the validity of the accuracy and decision of subway route planning.
Description of the drawings
Fig. 1 is a kind of city underground paths planning method flow chart based on ArcGIS.
Fig. 2 is to carry out the slope map that Slope-extraction is generated with processing to altitude data.
Fig. 3 is the river distribution map for River Data being analyzed and being handled generation.
Fig. 4 is the lisarithmic map that processing generation is carried out to demographic data.
Fig. 5 is the cost data figure to being generated after slope map, river figure, lisarithmic map, elevation field figure reclassification.
Fig. 6 is the city underground path profile of the minimum cost generated.
Specific implementation mode
The present invention is further described below in conjunction with the accompanying drawings.
A kind of referring to Fig.1~Fig. 6, city underground paths planning method based on ArcGIS, includes the following steps:
A1, map vector, including coordinate file, index file and property file are obtained, coordinate file is for recording space
Coordinate information, coordinate file are made of header file and entity information two parts;Index file includes the index information of file, file
In each record include corresponding coordinate file, the offset of the file header of recording distance coordinate file;Property file includes one
The feature of the feature of a record, the data for including in file include altitude data, River Data, density data of population, path
Source point data and path termination data;
A2, altitude data is handled, because of mountainous region, the distribution in the gradient and river influences the path planning of subway
It is larger, so first having to create data set, the gradient, slope aspect category single order terrain factor, the Spatial in ArcGIS Pro
Analyst Tools drop-down bezel, cluster selection Surface Analysis simultaneously click slope, to altitude data carry out Slope-extraction with
Processing generates slope map;
A3, River Data is handled, the SpatialAnalyst Tools drop-down bezel, cluster choosings in ArcGIS Pro
It selects Surface Analysis and clicks hydrologic analysis, River Data is analyzed and is handled, generate river
Distribution map;
A4, demographic data is handled, the influence that the density of population plans subway route is also larger, and therefore, it is necessary to create
The data set for building the density of population, the Spatial Analyst Tools drop-down bezel, clusters in ArcGIS Pro select density,
The density of population is handled, lisarithmic map is generated;
A5, the Reclassify that bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro, to river reach figure
Reclassification is carried out, by 4 grades of equidistantly classification;Reclassification is carried out to slope map, reclassification basic principle is to use equidistantly to be divided into
15 grades, the gradient more high-grade value is bigger;To lisarithmic map carry out reclassification, by 4 grades equidistantly classify, population more multilevel values more
Greatly;
A6, the Neighborhood in bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro
Statistics carries out domain analysis to elevation map, then carries out reclassification to field figure, by 15 grades of equidistantly classification;
A7, Raster Calculator are selected in Spatial Analyst Tools drop-down bezel, clusters, to dividing for generation again
Class slope map, reclassification river reach figure and reclassification lisarithmic map merge, and generate ultimate cost data set, final cost
Datagram is generated by following formula:
Cost data figure=reclassification slope map * a+ reclassifications river reach figure * b+ reclassification lisarithmic map * c+ reclassifications neck
Domain figure * d, wherein a, b, c and d is weighted value, and different weighted values can be chosen according to actual demand,
Cost Weighted in Spatial Analyst Tools drop-down bezel, cluster selection Distance to finally at
Notebook data collection figure carries out the processing of Cost Distance and cost direction,
In the road network analysis of ArcGIS, Shortest Path Analysis and shortest time point are realized using Dijkstra methods
Analysis, the processing procedure of Dijkstra methods are:From any point vs(vs∈Vc∪Vd) set out, gradually to destination node vd(vd∈
Vc∪VdAnd vd≠vs) find shortest path or shortest time and give label to each vertex in the process of implementation:P label tables
Show from vsTo the shortest path of the point or the power of shortest time, also referred to as forever mark, once i.e. certain point vsObtain P labels, value
No longer change in entire solution procedure;T labels are indicated from vsTo the upper bound of the power of the shortest distance or shortest time of the point,
It is referred to as temporary mark or exploratory label, and the T labels of certain point is changed to P labels, at most (k is in figure by k-1 steps
Number of vertex), can solve from vsShortest path to each point or shortest time;
A8, the Cost connectivity in Spatial Analyst Tools drop-down bezel, cluster selections Distance,
Cost connectivity can between two or more input areas the minimum connectivity network of manufacturing cost;
A9, the Cost Path in Spatial Analyst Tools drop-down bezel, cluster selections Distance, generate minimum
Cost path.
By taking Los Angeles,U.S somewhere as an example, steps are as follows for a kind of city underground paths planning method based on ArcGIS:
A1, the map vector for obtaining Los Angeles,U.S somewhere, it is ESRI (companies of U.S. environment system research institute
Environmental Systems Research Institute, Inc) provide a kind of vector data form, without topology
The map vector of information, acquisition includes coordinate file, index file and property file, and coordinate file is for recording space coordinate
Information, coordinate file are made of header file and entity information two parts, and index file includes the index information of file, every in file
The offset of a file header of the record comprising corresponding coordinate file recording distance coordinate file, property file include a record
Feature feature;The data for including in file include River Data, demographic data, path source point data, path termination number
According to;
A2, altitude data is handled, because of mountainous region, the distribution in the gradient and river influences the path planning of subway
It is larger, so first having to create data set, the gradient, slope aspect category single order terrain factor, the Spatial in ArcGIS Pro
Analyst Tools drop-down bezel, cluster selection Surface Analysis simultaneously click slope, to altitude data carry out Slope-extraction with
Processing, generates slope map, and Fig. 1 is to carry out processing generation to obtaining the altitude data in the map vector in Los Angeles,U.S somewhere
Slope map, the gradient is higher, and corresponding texture color is deeper;
A3, River Data is handled, the Spatial Analyst Tools drop-down bezel, cluster choosings in ArcGIS Pro
It selects Surface Analysis and clicks hydrologic analysis, River Data is analyzed and is handled, generate river
Distribution map, Fig. 2 are the river figures that processing generation is carried out to obtaining the River Data in the map vector in Los Angeles,U.S somewhere,
Darker regions in river figure are river distributed areas;
A4, demographic data is handled, the influence that the density of population plans subway route is also larger, and therefore, it is necessary to create
The data set for building the density of population, the Spatial Analyst Tools drop-down bezel, clusters in ArcGIS Pro select density,
The density of population is handled, lisarithmic map is generated, Fig. 3 is to obtaining the people in the map vector in Los Angeles,U.S somewhere
Mouth data carry out the lisarithmic map of processing generation, and the red area in lisarithmic map is population concentration region;
A5, using in ArcGIS Pro Spatial Analyst Tools pull down bezel, cluster the river reaches Reclassify figure into
Row classification, by 4 grades of equidistantly classification;Reclassification is carried out to slope map, reclassification basic principle is to use equidistantly to be divided into 15 grades,
The gradient more high-grade value is bigger;Reclassification is carried out to lisarithmic map, equidistantly classification, population more multilevel values are bigger by 4 grades;
A6, the Neighborhood in bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro
Statistics carries out domain analysis to elevation map, then carries out reclassification to field figure, by 15 grades of equidistantly classification;
A7, reclassifications of the Raster Calculator to generation is selected in Spatial Analyst Tools drop-down bezel, clusters
Slope map, reclassification river reach figure and reclassification lisarithmic map merge, and generate ultimate cost data set.Final cost number
It is generated by following formula according to figure:
Cost data figure=(reclassification slope map * 0.25+ reclassifications river reach figure 0.25+ reclassification lisarithmic maps * 0.25
+ reclassification field figure * 0.25), it is the cost data figure generated that wherein a, b, c and d, which are set as 0.25, Fig. 4,;
Cost Weighted in Spatial Analyst Tools drop-down bezel, cluster selection Distance to finally at
Notebook data figure carries out the processing of Cost Distance and cost direction,
In the road network analysis of ArcGIS, Shortest Path Analysis and shortest time point are realized using Dijkstra methods
Analysis, the basic ideas of Dijkstra methods are:From any point vs(vs∈Vc∪Vd) set out, gradually to destination node vd(vd∈
Vc∪VdAnd vd≠vs) find shortest path or shortest time and give label to each vertex in the process of implementation:P label tables
Show from vsTo the shortest path of the point or the power of shortest time, also referred to as forever mark, once i.e. certain point vsObtain P labels, value
No longer change in entire solution procedure;T labels are indicated from vsTo the upper bound of the power of the shortest distance or shortest time of the point,
It is referred to as temporary mark or exploratory label, and the T labels of certain point is changed to P labels, at most (k is in figure by k-1 steps
Number of vertex), can solve from vsShortest path to each point or shortest time;
A8, the Cost connectivity in Spatial Analyst Tools drop-down bezel, cluster selections Distance,
Cost connectivity can between two or more input areas the minimum connectivity network of manufacturing cost;
A9, the Cost Path in Spatial Analyst Tools drop-down bezel, cluster selections Distance, generate minimum
Cost path, Fig. 5 are the water channel principium figure generated, and red and yellow line therein is the ground railway cooked up
Line.
Described above is the excellent results that one embodiment that the present invention provides shows, it is clear that the present invention not only fits
Above-described embodiment is closed, it can under the premise of without departing from essence spirit of the present invention and without departing from content involved by substantive content of the present invention
Many variations are done to it to be implemented.
Claims (3)
1. a kind of city underground paths planning method based on ArcGIS, it is characterised in that:The city underground path planning side
Method includes the following steps:
A1, map vector, including coordinate file, index file and property file are obtained, coordinate file is for recording space coordinate
Information, coordinate file are made of header file and entity information two parts;Index file includes the index information of file, every in file
A record includes corresponding coordinate file, the offset of the file header of recording distance coordinate file;Property file includes a note
The feature of the feature of record, the data for including in file include altitude data, River Data, density data of population, path source point
Data and path termination data;
A2, altitude data is handled, because of mountainous region, the distribution in the gradient and river on the path planning of subway influence compared with
Greatly, so first having to create data set, the gradient, slope aspect category single order terrain factor, the Spatial in ArcGIS Pro
Analyst Tools drop-down bezel, cluster selection Surface Analysis simultaneously click slope, to altitude data carry out Slope-extraction with
Processing generates slope map;
A3, River Data is handled, the Spatial Analyst Tools drop-down bezel, cluster selections in ArcGIS Pro
Surface Analysis simultaneously click hydrologic analysis, are analyzed River Data and are handled, and river point is generated
Butut;
A4, demographic data is handled, the influence that the density of population plans subway route is also larger, and therefore, it is necessary to founders
The data set of mouth density, the Spatial Analyst Tools drop-down bezel, clusters in ArcGIS Pro select density, to people
Mouth density is handled, and lisarithmic map is generated;
A5, the Reclassify that bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro, carry out river reach figure
Reclassification, by 4 grades of equidistantly classification;Reclassification is carried out to slope map, reclassification basic principle is to use equidistantly to be divided into 15 grades,
The gradient more high-grade value is bigger;Reclassification is carried out to lisarithmic map, equidistantly classification, population more multilevel values are bigger by 4 grades;
A6, the Neighborhood in bezel, cluster is pulled down using Spatial Analyst Tools in ArcGIS Pro
Statistics carries out domain analysis to elevation map, then carries out reclassification to field figure, by 15 grades of equidistantly classification;
A7, Raster Calculator are selected in Spatial Analyst Tools drop-down bezel, clusters, to the reclassification slope of generation
Degree figure, reclassification river reach figure and reclassification lisarithmic map merge, and generate ultimate cost data set, final cost data
Figure is generated by following formula:
Cost data figure=reclassification slope map * a+ reclassifications river reach figure * b+ reclassification lisarithmic map * c+ reclassifications field
Scheme * d,
Wherein a, b, c and d are weighted values, and different weighted values can be chosen according to actual demand,
Cost Weighted in Spatial Analyst Tools drop-down bezel, cluster selections Distance are to ultimate cost number
The processing of progress Cost Distance and cost direction is schemed according to collection,
In the road network analysis of ArcGIS, realize that Shortest Path Analysis and shortest time are analyzed using Dijkstra methods,
The processing procedure of Dijkstra methods is:From any point vs(vs∈Vc∪Vd) set out, gradually to destination node vd(vd∈Vc∪
VdAnd vd≠vs) find shortest path or shortest time and give label to each vertex in the process of implementation:P labels indicate from
vsTo the shortest path of the point or the power of shortest time, also referred to as forever mark, once i.e. certain point vsP labels are obtained, value is whole
No longer change in a solution procedure;T labels are indicated from vsTo the upper bound of the power of the shortest distance or shortest time of the point, also claimed
For temporary mark or exploratory label, and the T labels of certain point are changed to P labels, at most (k is the top in figure by k-1 steps
Points), it can solve from vsShortest path to each point or shortest time;
A8, Cost connectivity, Cost in Spatial Analyst Tools drop-down bezel, cluster selections Distance
Connectivity can between two or more input areas the minimum connectivity network of manufacturing cost;
A9, the Cost Path in Spatial Analyst Tools drop-down bezel, cluster selections Distance, generate minimum cost
Path.
2. a kind of city underground paths planning method based on ArcGIS according to claim 1 or 2, it is characterised in that:
In the step A1, the map vector file of the acquisition, which will wrap, expands altitude data, River Data, density data of population, road
Diameter source point data and path termination data.
3. a kind of city underground paths planning method based on ArcGIS according to claim 1 or 2, it is characterised in that:
In the step A7, ultimate cost data set will by reclassification slope map, reclassification river reach figure and reclassification lisarithmic map into
Row, which merges, to be generated.
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CN201711445717.7A CN108304470B (en) | 2017-12-27 | 2017-12-27 | ArcGIS-based urban subway path planning method |
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CN201711445717.7A CN108304470B (en) | 2017-12-27 | 2017-12-27 | ArcGIS-based urban subway path planning method |
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CN108304470A true CN108304470A (en) | 2018-07-20 |
CN108304470B CN108304470B (en) | 2021-10-29 |
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110851548A (en) * | 2019-10-14 | 2020-02-28 | 上海市政工程设计研究总院(集团)有限公司 | Municipal facility site selection layout method based on ArcGIS analysis |
CN116433105A (en) * | 2023-05-22 | 2023-07-14 | 深圳大学 | Method for quantitatively evaluating distribution coupling degree of rail transit and urban space elements |
CN117128977A (en) * | 2023-10-26 | 2023-11-28 | 中国测绘科学研究院 | High-quality green road path planning method, device and equipment based on double-image fusion |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104200263A (en) * | 2014-07-23 | 2014-12-10 | 浙江工业大学 | Power distribution network route planning method based on tabu differential evolution and GIS (Geographic Information System) |
CN106840178A (en) * | 2017-01-24 | 2017-06-13 | 中南大学 | A kind of map building based on ArcGIS and intelligent vehicle autonomous navigation method and system |
CN107292989A (en) * | 2016-04-10 | 2017-10-24 | 青岛理工大学 | High voltage power transmission cruising inspection system based on 3DGIS technologies |
CN107480808A (en) * | 2017-07-13 | 2017-12-15 | 河海大学 | A kind of High aititude mountain area diversion works layout of roads method |
-
2017
- 2017-12-27 CN CN201711445717.7A patent/CN108304470B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104200263A (en) * | 2014-07-23 | 2014-12-10 | 浙江工业大学 | Power distribution network route planning method based on tabu differential evolution and GIS (Geographic Information System) |
CN107292989A (en) * | 2016-04-10 | 2017-10-24 | 青岛理工大学 | High voltage power transmission cruising inspection system based on 3DGIS technologies |
CN106840178A (en) * | 2017-01-24 | 2017-06-13 | 中南大学 | A kind of map building based on ArcGIS and intelligent vehicle autonomous navigation method and system |
CN107480808A (en) * | 2017-07-13 | 2017-12-15 | 河海大学 | A kind of High aititude mountain area diversion works layout of roads method |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110851548A (en) * | 2019-10-14 | 2020-02-28 | 上海市政工程设计研究总院(集团)有限公司 | Municipal facility site selection layout method based on ArcGIS analysis |
CN116433105A (en) * | 2023-05-22 | 2023-07-14 | 深圳大学 | Method for quantitatively evaluating distribution coupling degree of rail transit and urban space elements |
CN116433105B (en) * | 2023-05-22 | 2023-09-19 | 深圳大学 | Method for quantitatively evaluating distribution coupling degree of rail transit and urban space elements |
CN117128977A (en) * | 2023-10-26 | 2023-11-28 | 中国测绘科学研究院 | High-quality green road path planning method, device and equipment based on double-image fusion |
CN117128977B (en) * | 2023-10-26 | 2024-01-19 | 中国测绘科学研究院 | High-quality green road path planning method, device and equipment based on double-image fusion |
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