CN116469303B - Territorial space planning and drawing method based on GIS - Google Patents
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Abstract
The invention discloses a territorial space planning and drawing method based on GIS, comprising the following steps: s1: collecting and arranging geographic data, including land utilization data, topography data, weather data and remote sensing image data, and performing topology inspection on the geographic data; s2: setting planning indexes and space limiting conditions according to requirements of homeland space planning; s3: carrying out spatial analysis on the geographic data by using a GIS tool to obtain an optimizable area; s4: planning an optimizable area based on a genetic algorithm to obtain an optimal planning scheme for land utilization type combination and distribution; s5: and drawing the generated planning scheme by using a GIS tool, wherein the GIS software provides symbols, labels and colors required by drawing. The method can improve the scientificity, accuracy and visualization degree of the planning and drawing of the homeland space and provide effective planning support for decision makers.
Description
Technical Field
The invention relates to the technical field of homeland space planning and drawing, in particular to a homeland space planning and drawing method based on GIS.
Background
The territorial space planning plays an important role in social and economic development, and scientific planning and effective drawing are needed for reasonably utilizing land resources, promoting economic development and ecological protection. However, the conventional land space planning and drawing method has limitations in optimizing a planning scheme, and an optimal land utilization type combination and distribution scheme cannot be found. Secondly, the traditional territorial space planning and drawing method often depends on experience and subjective judgment of experts, and the planning scheme is easy to be established under the influence of personal preference and subjective factors. Therefore, a method for planning and drawing a homeland space based on GIS is needed to overcome the problems, realize intuitiveness of result display, and acquire an optimal planning scheme by combining an optimization method.
Disclosure of Invention
In view of the above, the invention provides a GIS-based territorial space planning and drawing method, which aims to realize the integration of geographic data, the satisfaction of planning requirements, the accuracy of space analysis, the acquisition of an optimal planning scheme and the intuitiveness of drawing results based on a GIS (Geographic Information System or Geo-Information system geographic information system) technology. By introducing data topology inspection, an optimization algorithm and a GIS tool, the invention aims to improve the efficiency, accuracy and visualization degree of the planning and drawing of the homeland space so as to support a decision maker to make a scientific and reasonable planning scheme.
The invention provides a GIS-based territorial space planning and drawing method, which comprises the following steps:
s1: collecting and arranging geographic data, including land utilization data, topography data, weather data and remote sensing image data, and performing topology inspection on the geographic data;
s2: setting planning indexes and space limiting conditions according to requirements of homeland space planning;
s3: carrying out spatial analysis on the geographic data by using a GIS tool to obtain an optimizable area;
s4: planning an optimizable area based on a genetic algorithm to obtain an optimal planning scheme for land utilization type combination and distribution;
s5: and drawing the generated planning scheme by using a GIS tool, wherein the GIS software provides symbols, labels and colors required by drawing.
As a further improvement of the present invention:
optionally, collecting and organizing geographic data in the step S1, including land utilization data, topography data, weather data, remote sensing image data, and performing topology inspection on the geographic data, including:
collecting and organizing geographic data, wherein the geographic data comprise land utilization data, topography data, weather data and remote sensing image data; the land utilization data comprise land use and corresponding boundaries, and are used for reflecting the use conditions of the ground surface in different time and different space ranges; the topographic and geomorphic data comprises elevation, gradient and slope direction, and reflects the topographic and geomorphic characteristics of different areas; weather data comprise air temperature, rainfall and wind direction, and reflect weather and weather change rules of different areas; the remote sensing image data comprises a high-resolution satellite image and reflects the ground surface real situation.
Performing topology inspection on the collected and arranged geographic data, wherein the topology inspection is as follows:
checking topological relation between points, and checking distances between different points:
；
wherein , and />Is the abscissa of two points;
checking topological relation between lines, and checking intersection conditions of different lines:
；
wherein a and b represent two lines; and />Representing two endpoints of line a; and />Representing two endpoints of line b; the two-way type opposite sign represents that the two lines intersect;
checking the topological relation of the faces, and introducing a node degree to check a topological matrix among different faces:
；
wherein A and B represent two faces; u-shaped sumRespectively representing the intersection and difference operations; /> and />The dimension and Euler number of the operation result are respectively represented; />The sub-table represents that the result is a null, 0-dimensional, 1-dimensional, 2-dimensional, 0-dimensional, and 1-dimensional combination;connection is the number of connections, hole is the number of holes.
Optionally, in the step S2, setting a planning index and a space limitation condition according to a requirement of the homeland space planning, including:
based on the data collected and arranged in the step S1, according to the requirements of the homeland space planning, the set planning index set is as follows:
；
wherein, I1 is land utilization type and proportion, which is used for defining land utilization types of different areas and setting corresponding proportion; i2 building height and density, for specifying maximum height and density limits for buildings to control city building size and concentration; i3 is green land coverage, and is used for defining the minimum coverage of urban green land so as to ensure the ecological environment and the life quality of residents;
the set space limitation condition set is:
；
wherein J1 is a water area protection limit for defining a water area protection zone to protect water resources and water ecological environment; j2 is a limitation of the ecological sensitive area and is used for setting the ecological sensitive area so as to protect the biodiversity and the ecological system function; j3 is cultural heritage protection limit for defining construction limit in cultural heritage protection area and protecting integrity and protection value of historical architecture, ancient site and cultural heritage; and J4 is geological relief limit and is used for setting a geological disaster prone area and a landslide area according to geological relief characteristics.
Optionally, in the step S3, performing spatial analysis of geographic data using a GIS tool includes:
based on the planning index and the space limitation condition set in the S2, carrying out space analysis on different geographic data by using a GIS tool:
space inquiry is carried out on the planning index set, land areas are selected according to inquiry conditions, and the land areas are output as inquiry data;
performing buffer area analysis on the space limiting condition set, performing space combination on the obtained multiple buffer areas, and outputting the buffer areas as buffer area data;
and performing space erasure analysis on the query data and the buffer data, and outputting an optimizable area.
Optionally, in the step S4, the planning of the optimizable area based on the genetic algorithm is performed to obtain an optimal planning scheme for combining and distributing the land utilization types, including:
based on the optimizable area obtained in the step S3, the process for obtaining the optimal planning scheme for combining and distributing the land utilization types is as follows:
s41: constructing an optimization objective function:
；
wherein , and />Respectively refers to the economic benefit of land and the ecological benefit of land utilization; />Refers to the i-th land economic benefit coefficient; />Refers to the area occupied by the i-th land; />Refers to the i-th land ecological benefit coefficient; n is the number of land utilization category types;
s42: initializing a population in a genetic algorithm and calculating population fitness, and selecting excellent individuals:
the initialization mode of the population is random initialization, and the calculation mode of the population fitness is as follows:
；
the selection mode of the excellent population is as follows:
；
wherein M is the total number of the population;indicating fitness of the jth population; according to the size of v, selecting the first 20% of population as the excellent population;
s43: in selected excellent populations, the introduction of crossover and mutation operations increases the diversity of the population:
the crossing operation is as follows:
；
wherein , and />Is a randomly selected population among the excellent populations, and +.>；/>A random number between 0 and 1;
the mutation operation is as follows:；
wherein ,the variation step length is randomly generated;
and (3) increasing the population quantity to 40% of the population quantity before the excellent population is selected by using the crossover and mutation operation, repeating the steps S42-S43 until the selected excellent population is less than 3, and selecting the population with the highest fitness value from the final population as the optimal solution, thereby obtaining the optimal planning scheme for the combination and distribution of the land utilization types.
Optionally, in the step S5, the generated planning scheme is mapped by using a GIS tool, and the GIS software provides symbols, labels and colors required by mapping, including:
and (3) based on the optimal planning scheme of land utilization type combination and distribution obtained in the step (S4), a GIS tool is used for drawing the planning scheme, and drawing elements are as follows:
symbol and legend: using rich symbol libraries provided in a GIS tool, selecting symbols corresponding to land utilization types, and simultaneously adding legends to explain meanings of different symbols and corresponding land utilization types;
labeling and annotation: adding text elements in the graph by using a GIS tool for marking geographic elements, planning indexes and important descriptions, and setting fonts, font sizes, colors and alignment modes at the same time so that marking information is clear and readable;
color: color libraries provided by GIS tools are used, colors are given to different land utilization types from the viewpoint of visual balance, and the visual balance is expressed in the following way:
；
wherein ,define the visual center of the picture,/->Is the q-th land use type; /> and />Respectively the barycentric coordinates of the q-th land utilization type; />The total number of land utilization types; />The calculation mode of (a) is as follows:
；
wherein ,the brightness value of the color of the q-th land use type in the CIELab color space is in the range of [0,100]。
The degree of visual balance is expressed in terms of the distance of the theoretical visual center from the visual center of the drawing:
；
wherein ,is the theoretical visual center.
Generating different color collocations based on weighted random sampling, selecting the collocation with the closest distance between a theoretical visual center and a drawing visual center as the color of different land utilization types, wherein the weighted random sampling process comprises the following steps:
s51: putting the first m colors in the color library into a sampling result set R, calculating the characteristic value of each color in the sampling result set, and finally recording the minimum characteristic value in the color characteristic values in the sampling result set:
；
wherein ,a random number in the range of 0 to 1; />The weight of the kth color in the sampling result set; at the same time, the smallest of the sampling result setsCharacteristic value is marked as threshold +.>；
S52: calculating characteristic values of the residual colors in the color library and determining whether to replace the colors in the sampling result set according to a threshold value:
selecting a color meeting a replacement condition, wherein the replacement condition is as follows:
；
；
wherein r is a random number in the range of 0 to 1; d is a color number satisfying the replacement condition;
replacing the color with the smallest characteristic value in the sampling result set by using the d-th color in the color library, and calculating the corresponding characteristic value:
；
wherein ,is->Random numbers in the range of up to 1; at the same time, the smallest characteristic value in the updated sampling result set is recorded as a threshold value +.>；
S53: repeating S52 until the number of color types in the sampling result set is。
Advantageous effects
According to the invention, the requirements of the homeland space planning are considered, planning is carried out according to the planning index and the space limiting condition, and the planning scheme is ensured to meet the planning target and the requirements. Through flexible parameter setting and rule constraint, a diversified planning scheme can be generated according to different planning requirements.
The invention utilizes the GIS tool to carry out space analysis, and can accurately identify and analyze the optimizable area. Through technical means such as spatial relation judgment, superposition analysis and the like, suitability and potential of different areas can be quantitatively evaluated, and scientific basis is provided for planning decisions.
According to the invention, an optimization algorithm is introduced, so that an optimizable area can be planned, and an optimal land utilization type combination and distribution scheme can be found. And through repeated iteration and evaluation, an optimal scheme meeting the planning target is obtained, and the planning efficiency and the optimization degree are improved.
The invention provides the drawing function by utilizing the GIS software, and can display the result of the planning scheme in an intuitive way. Through the arrangement of drawing elements such as symbols, marks, colors and the like, the spatial layout, type combination and effect of the planning scheme can be clearly displayed, and visual decision references are provided.
In summary, the method of the invention has the beneficial effects of data integration, meeting planning requirements, accurate space analysis, obtaining the optimal planning scheme, intuitive drawing result and the like, can improve the scientificity, accuracy and visualization degree of the homeland space planning drawing, and provides effective planning support for decision makers.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings, without limiting the invention in any way, and any alterations or substitutions based on the teachings of the invention are intended to fall within the scope of the invention.
Example 1: a GIS-based territorial space planning and drawing method, as shown in figure 1, comprises the following steps:
s1: and collecting and arranging geographic data, including land utilization data, topography data, weather data and remote sensing image data, and performing topology inspection on the geographic data.
Collecting and organizing geographic data, wherein the geographic data comprise land utilization data, topography data, weather data and remote sensing image data; the land utilization data comprise land use and corresponding boundaries, and are used for reflecting the use conditions of the ground surface in different time and different space ranges; the topographic and geomorphic data comprises elevation, gradient and slope direction, and reflects the topographic and geomorphic characteristics of different areas; weather data comprise air temperature, rainfall and wind direction, and reflect weather and weather change rules of different areas; the remote sensing image data comprises a high-resolution satellite image and reflects the ground surface real situation.
Performing topology inspection on the collected and arranged geographic data, wherein the topology inspection is as follows:
checking topological relation between points, and checking distances between different points:
；
wherein , and />Is the abscissa of two points;
checking topological relation between lines, and checking intersection conditions of different lines:
；
wherein a and b represent two lines; and />Representing two endpoints of line a; and />Representing two endpoints of line b; the two-way type opposite sign represents that the two lines intersect;
checking the topological relation of the faces, and introducing a node degree to check a topological matrix among different faces:
；
wherein A and B represent two faces; u-shaped sumRespectively representing the intersection and difference operations; /> and />The dimension and Euler number of the operation result are respectively represented; />The sub-table represents that the result is a null, 0-dimensional, 1-dimensional, 2-dimensional, 0-dimensional, and 1-dimensional combination;connection is the number of connections, hole is the number of holes.
Topology checking can help verify the integrity of the geographic data, ensuring that there are no missing, overlapping, duplicate, or invalid elements in the dataset. Errors and anomalies in the data can be discovered by examining topological relationships between geographic elements, such as adjacency relationships, inclusion relationships, intersection relationships, and the like.
The topology inspection of the surfaces introducing the node degree can detect the topology relation between the surfaces more accurately. By checking the degree of nodes of the faces, it can be ensured that each face is connected to the correct number of adjacent faces to maintain the integrity of the topological relationship. Meanwhile, the surface-to-surface topology inspection introducing the node degree is applicable to various types of surface data, including polygons, polygon meshes, and the like. It is independent of specific geometry and thus can be applied to topology inspection of various geographical data.
S2: and setting planning indexes and space limiting conditions according to the requirements of the homeland space planning.
Based on the data collected and arranged in the step S1, according to the requirements of the homeland space planning, the set planning index set is as follows:
；
wherein, I1 is land utilization type and proportion, which is used for defining land utilization types of different areas and setting corresponding proportion; i2 building height and density, for specifying maximum height and density limits for buildings to control city building size and concentration; i3 is green land coverage, and is used for defining the minimum coverage of urban green land so as to ensure the ecological environment and the life quality of residents;
the set space limitation condition set is:
；
wherein J1 is a water area protection limit for defining a water area protection zone to protect water resources and water ecological environment; j2 is a limitation of the ecological sensitive area and is used for setting the ecological sensitive area so as to protect the biodiversity and the ecological system function; j3 is cultural heritage protection limit for defining construction limit in cultural heritage protection area and protecting integrity and protection value of historical architecture, ancient site and cultural heritage; and J4 is geological relief limit and is used for setting a geological disaster prone area and a landslide area according to geological relief characteristics.
S3: and carrying out spatial analysis on the geographic data by using a GIS tool to obtain an optimizable area.
Based on the planning index and the space limitation condition set in the S2, carrying out space analysis on different geographic data by using a GIS tool:
space inquiry is carried out on the planning index set, land areas are selected according to inquiry conditions, and the land areas are output as inquiry data;
performing buffer area analysis on the space limiting condition set, performing space combination on the obtained multiple buffer areas, and outputting the buffer areas as buffer area data;
and performing space erasure analysis on the query data and the buffer data, and outputting an optimizable area.
S4: and planning the optimizable area based on a genetic algorithm to obtain an optimal planning scheme for land utilization type combination and distribution.
The process of obtaining the planning scheme for the optimal land use type combination and distribution based on the optimizable area obtained in S3 is that the types of land use types in the present embodiment are cultivated land, garden land, woodland, grassland, commercial land, industrial and mining storage land, residential land, public management and public service land, special land, transportation land, water area and water conservancy facility land, and other land:
s41: constructing an optimization objective function:
；
wherein , and />Respectively refers to the economic benefit of land and the ecological benefit of land utilization; />Refers to the i-th land economic benefit coefficient; />Refers to the area occupied by the i-th land; />Refers to the i-th land ecological benefit coefficient; n is the number of land utilization category types;
s42: initializing a population in a genetic algorithm and calculating population fitness, and selecting excellent individuals:
the initialization mode of the population is random initialization, and the calculation mode of the population fitness is as follows:
；
the selection mode of the excellent population is as follows:
；
wherein M is the total number of the population;indicating fitness of the jth population; according to the size of v, selecting the first 20% of population as the excellent population;
s43: in selected excellent populations, the introduction of crossover and mutation operations increases the diversity of the population:
the crossing operation is as follows:
；
wherein , and />Is a randomly selected population among the excellent populations, and +.>；/>A random number between 0 and 1;
the mutation operation is as follows:；
wherein ,the variation step length is randomly generated;
using crossover and mutation operations to increase the population quantity to 40% of the previous population quantity before the excellent population is selected, repeating the steps S42-S43 until the selected excellent population is less than 3, and selecting the population with the highest fitness value from the final population as the optimal solution, thereby obtaining the optimal planning scheme of land use type combination and distribution;
the multi-objective optimization problem in the homeland space planning often involves a large number of decision variables and constraint conditions, and has higher complexity. The genetic algorithm is taken as a powerful optimization method, can effectively process the complexity, and searches the optimal solution or near optimal solution through evolution and search of candidate solutions.
There are a number of non-linear factors and interactions in land utilization planning problems, such as land suitability, resource utilization benefits, etc. Genetic algorithms can model nonlinear relationships and search for solutions with better fitness through genetic coding and individual fitness evaluation.
Genetic algorithms search in the form of populations, maintaining diversity of the populations by crossover, mutation, etc. In homeland space planning, it is very important to maintain diversity, as different planning schemes may have different advantages and disadvantages. Genetic algorithms are able to explore multiple possible solutions in solution space through genetic manipulation and find the optimal planning scheme for land use type combinations and distributions.
S5: and drawing the generated planning scheme by using a GIS tool, wherein the GIS software provides symbols, labels and colors required by drawing.
And (3) based on the optimal planning scheme of land utilization type combination and distribution obtained in the step (S4), a GIS tool is used for drawing the planning scheme, and drawing elements are as follows:
symbol and legend: using rich symbol libraries provided in a GIS tool, selecting symbols corresponding to land utilization types, and simultaneously adding legends to explain meanings of different symbols and corresponding land utilization types;
labeling and annotation: adding text elements in the graph by using a GIS tool for marking geographic elements, planning indexes and important descriptions, and setting fonts, font sizes, colors and alignment modes at the same time so that marking information is clear and readable;
color: color libraries provided by GIS tools are used, colors are given to different land utilization types from the viewpoint of visual balance, and the visual balance is expressed in the following way:
；
wherein ,define the visual center of the picture,/->Is the q-th land use type; /> and />Respectively the barycentric coordinates of the q-th land utilization type; />The total number of land utilization types; />The calculation mode of (a) is as follows:
；
wherein ,the brightness value of the color of the q-th land use type in the CIELab color space is in the range of [0,100]。
The degree of visual balance is expressed in terms of the distance of the theoretical visual center from the visual center of the drawing:
；
wherein ,in this embodiment, the theoretical visual center is the center of the output picture.
Generating different color collocations based on weighted random sampling, selecting the collocation with the closest distance between a theoretical visual center and a drawing visual center as the color of different land utilization types, wherein the weighted random sampling process comprises the following steps:
s51: putting the first m colors in the color library into a sampling result set R, calculating the characteristic value of each color in the sampling result set, and finally recording the minimum characteristic value in the color characteristic values in the sampling result set:
；
wherein ,a random number in the range of 0 to 1; />The weight of the kth color in the sampling result set; at the same time, the smallest characteristic value in the sampling result set is marked as a threshold value +.>；
S52: calculating characteristic values of the residual colors in the color library and determining whether to replace the colors in the sampling result set according to a threshold value:
selecting a color meeting a replacement condition, wherein the replacement condition is as follows:
；
；
wherein r is a random number in the range of 0 to 1; d is a color number satisfying the replacement condition;
replacing the color with the smallest characteristic value in the sampling result set by using the d-th color in the color library, and calculating the corresponding characteristic value:
；
wherein ,is->Random numbers in the range of up to 1; at the same time, the smallest characteristic value in the updated sampling result set is recorded as a threshold value +.>；
S53: repeating S52 until the number of color types in the sampling result set is。
The colors of the different land use types should have sufficient differentiation and identification to enable the viewer to clearly identify and distinguish the individual types. The visual balance can ensure proper contrast between colors, avoid confusion and ambiguity between colors, and make the map clearer and more readable. Visual balance can guide the visual attention of an observer through the attributes of brightness, saturation, hue and the like of the color, and highlight important land utilization types or areas. Through reasonable design of colors, specific geographic features, planning emphasis or spatial distribution modes can be highlighted, so that the map has more visual effects and information transmission capability. The visual balance may create an aesthetically pleasing and comfortable map appearance. The selection and combination of colors should take into account the harmony and uniformity of colors, avoiding too abrupt or uncoordinated color combinations. The reasonable color selection can give people a comfortable feeling, and the overall aesthetic feeling and the acceptability of the map are improved.
It should be noted that, the foregoing reference numerals of the embodiments of the present invention are merely for describing the embodiments, and do not represent the advantages and disadvantages of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (3)
1. A GIS-based territorial space planning and drawing method is characterized by comprising the following steps:
s1: collecting and organizing geographic data including land utilization data, topography data, climate and weather data, remote sensing image data, and performing topology inspection on the geographic data, including:
collecting and organizing geographic data, wherein the geographic data comprise land utilization data, topography data, weather data and remote sensing image data; the land utilization data comprise land use and corresponding boundaries, and are used for reflecting the use conditions of the ground surface in different time and different space ranges; the topographic and geomorphic data comprises elevation, gradient and slope direction, and reflects the topographic and geomorphic characteristics of different areas; weather data comprise air temperature, rainfall and wind direction, and reflect weather and weather change rules of different areas; the remote sensing image data comprise high-resolution satellite images and reflect the ground surface real conditions;
performing topology inspection on the collected and arranged geographic data, wherein the topology inspection is as follows:
checking topological relation between points, and checking distances between different points:
；
wherein , and />Is the abscissa of two points;
checking topological relation between lines, and checking intersection conditions of different lines:
；
wherein a and b represent two lines; and />Representing two endpoints of line a; />Andrepresenting two endpoints of line b; the two-way type opposite sign represents that the two lines intersect;
checking the topological relation of the faces, and introducing a node degree to check a topological matrix among different faces:
；
wherein A and B represent two faces; u-shaped sumRespectively representing the intersection and difference operations; /> and />The dimension and Euler number of the operation result are respectively represented; />The sub-table represents that the result is a null, 0-dimensional, 1-dimensional, 2-dimensional, 0-dimensional, and 1-dimensional combination;connection is the number of connections, hole is the number of holes;
s2: setting planning indexes and space limiting conditions according to the requirements of homeland space planning, including:
based on the data collected and arranged in the step S1, according to the requirements of the homeland space planning, the set planning index set is as follows:
；
wherein, I1 is land utilization type and proportion, which is used for defining land utilization types of different areas and setting corresponding proportion; i2 building height and density, for specifying maximum height and density limits for buildings to control city building size and concentration; i3 is green land coverage, and is used for defining the minimum coverage of urban green land so as to ensure the ecological environment and the life quality of residents;
the set space limitation condition set is:
；
wherein J1 is a water area protection limit for defining a water area protection zone to protect water resources and water ecological environment; j2 is a limitation of the ecological sensitive area and is used for setting the ecological sensitive area so as to protect the biodiversity and the ecological system function; j3 is cultural heritage protection limit for defining construction limit in cultural heritage protection area and protecting integrity and protection value of historical architecture, ancient site and cultural heritage; j4 is geological landform limitation and is used for setting a geological disaster prone area and a landslide area according to geological landform characteristics;
s3: performing spatial analysis on the geographic data by using a GIS tool to obtain an optimizable area, wherein the method comprises the following steps:
based on the planning index and the space limitation condition set in the S2, carrying out space analysis on different geographic data by using a GIS tool:
space inquiry is carried out on the planning index set, land areas are selected according to inquiry conditions, and the land areas are output as inquiry data;
performing buffer area analysis on the space limiting condition set, performing space combination on the obtained multiple buffer areas, and outputting the buffer areas as buffer area data;
performing space erasure analysis on the query data and the buffer data, and outputting an optimizable area;
s4: planning an optimizable area based on a genetic algorithm to obtain an optimal planning scheme for land utilization type combination and distribution;
s5: and drawing the generated planning scheme by using a GIS tool, wherein GIS software provides symbols, labels and colors required by drawing.
2. The GIS-based territorial space planning and drafting method according to claim 1, wherein in step S4, the optimizable area is planned based on a genetic algorithm to obtain an optimal planning scheme for land use type combination and distribution, comprising:
based on the optimizable area obtained in the step S3, the process of obtaining the optimal planning scheme for the land use type combination and distribution is as follows:
s41: constructing an optimization objective function:
；
wherein , and />Respectively refers to the economic benefit of land and the ecological benefit of land utilization; />Refers to the i-th land economic benefit coefficient; />Refers to the area occupied by the i-th land; />Refers to the i-th land ecological benefit coefficient; n is the number of land utilization category types;
s42: initializing a population in a genetic algorithm and calculating population fitness, and selecting excellent individuals:
the initialization mode of the population is random initialization, and the calculation mode of the population fitness is as follows:
；
the selection mode of the excellent population is as follows:
；
wherein M is the total number of the population;indicating fitness of the jth population; according to the size of v, selecting the first 20% of population as the excellent population;
s43: in selected excellent populations, the introduction of crossover and mutation operations increases the diversity of the population:
the crossing operation is as follows:
；
wherein , and />Is a randomly selected population among the excellent populations, and +.>；/>A random number between 0 and 1;
the mutation operation is as follows:；
wherein ,the variation step length is randomly generated;
and (3) increasing the population quantity to 40% of the population quantity before the excellent population is selected by using the crossover and mutation operation, repeating the steps S42-S43 until the selected excellent population is less than 3, and selecting the population with the highest fitness value from the final population as the optimal solution, thereby obtaining the optimal planning scheme for the combination and distribution of the land utilization types.
3. The method for planning and drawing a homeland space based on GIS according to claim 2, wherein in step S5, the generated planning scheme is drawn by using GIS tools, and the GIS software provides symbols, labels, colors required for drawing, comprising:
and (3) based on the optimal planning scheme of land utilization type combination and distribution obtained in the step (S4), a GIS tool is used for drawing the planning scheme, and drawing elements are as follows:
symbol and legend: using rich symbol libraries provided in a GIS tool, selecting symbols corresponding to land utilization types, and simultaneously adding legends to explain meanings of different symbols and corresponding land utilization types;
labeling and annotation: adding text elements in the graph by using a GIS tool for marking geographic elements, planning indexes and important descriptions, and setting fonts, font sizes, colors and alignment modes at the same time so that marking information is clear and readable;
color: color libraries provided by GIS tools are used, colors are given to different land utilization types from the viewpoint of visual balance, and the visual balance is expressed in the following way:
；
wherein ,define the visual center of the picture,/->Is the q-th land use type; /> and />Respectively the barycentric coordinates of the q-th land utilization type; />The total number of land utilization types; />The calculation mode of (a) is as follows:
；
wherein ,the brightness value of the color of the q-th land use type in the CIELab color space is in the range of [0,100]；
The degree of visual balance is expressed in terms of the distance of the theoretical visual center from the visual center of the drawing:
；
wherein ,is a theoretical visual center;
generating different color collocations based on weighted random sampling, selecting the collocation with the closest distance between a theoretical visual center and a drawing visual center as the color of different land utilization types, wherein the weighted random sampling process comprises the following steps:
s51: putting the first m colors in the color library into a sampling result set R, calculating the characteristic value of each color in the sampling result set, and finally recording the minimum characteristic value in the color characteristic values in the sampling result set:
；
wherein ,a random number in the range of 0 to 1; />The weight of the kth color in the sampling result set; at the same time, the smallest characteristic value in the sampling result set is marked as a threshold value +.>；
S52: calculating characteristic values of the residual colors in the color library and determining whether to replace the colors in the sampling result set according to a threshold value:
selecting a color meeting a replacement condition, wherein the replacement condition is as follows:
；
；
wherein r is a random number in the range of 0 to 1; d is a color number satisfying the replacement condition;
replacing the color with the smallest characteristic value in the sampling result set by using the d-th color in the color library, and calculating the corresponding characteristic value:
；
wherein ,is->Random numbers in the range of up to 1; at the same time, the smallest characteristic value in the updated sampling result set is recorded as a threshold value +.>；
S53: repeating S52 until the number of color types in the sampling result set is。
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