CN114372652A - Urban ecological capacity assessment and development boundary simulation method - Google Patents
Urban ecological capacity assessment and development boundary simulation method Download PDFInfo
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Abstract
The invention discloses a method for evaluating urban ecological capacity and simulating development boundary, which comprises the following steps: obtaining basic rigid capacity according to regional resource environment bearing capacity and development suitability evaluation; taking important patches such as natural conservation lands, forest parks, cultural heritage and the like as ecological sources, combining an ecological corridor analysis model with minimum constraint accumulated resistance, constructing an ecological safety pattern according to a network communication rule, and obtaining structural rigidity capacity after space reduction; obtaining elastic ecological capacity through multi-scenario analysis according to various permanent basic farmland protection space game strategies such as all regulations and major project regulations and the like; and optimizing elastic ecological capacity, and simulating urban development boundary space-time change by utilizing a seed expansion patch type growth cellular automaton. The invention establishes a rigid-elastic combined urban ecological capacity evaluation multilevel coupling analysis strategy, realizes the space transmission from the capacity evaluation to the boundary control through an urban evolution simulation model, and has important significance for implementing scientific argument of the territorial space planning.
Description
Technical Field
The invention relates to a territorial space planning technology, in particular to a method for evaluating urban ecological capacity and simulating development boundaries.
Background
The urban ecological capacity is a planning concept after endowing the urban scale with ecological characteristics (agriculture also belongs to generalized ecology) according to the ecological civilized construction requirements. The urban ecological capacity simulation can be developed from three deep levels of basic rigid capacity, structural rigid capacity and elastic ecological capacity. The basic rigidity capacity is the maximum bearing capacity of a region determined according to the requirements of 'double evaluation' of the homeland space and the like, and is the maximum upper limit of a region development theory; the structure rigidity capacity further considers the space appeal of the ecological safety pattern, the basic rigidity capacity is reduced by nuclear power, and the sustainable ecological safety of the region is guaranteed; the elastic ecological capacity is characterized by considering various spatial uncertainty influences such as permanent basic farmland protection and the like, and the elasticity and diversity of urban ecological capacity are described. Therefore, the urban ecological capacity is used as an entry point, and a control boundary is constructed through multi-scenario ecological capacity simulation, so that the method is an important path for realizing the national and soil space planning and conduction. At present, a plurality of technical methods for urban development boundary planning exist, but analysis of a certain technical angle is often emphasized, the internal logic of space planning is not strong, and the actual application requirements of homeland space planning cannot be well met. Thus, there is still a need for improvement and development of the prior art.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for evaluating urban ecological capacity and simulating development boundaries, and the method can be used for analyzing and evaluating the optimal capacity of regional urbanization and development so as to improve the scientificity of homeland space planning and compilation.
In order to realize the task, the invention adopts the following technical scheme:
a method for evaluating urban ecological capacity and simulating development boundary comprises the following steps:
according to the requirements of landform suitability and geological disaster risk prevention and control, carrying out threshold value grading on core space factors supporting and restricting urban industrial construction, and determining the construction suitability or risk of a single factor on each evaluation unit; comprehensively integrating the single-factor evaluation result, dividing the territorial space into high-suitability, medium-suitability and low-suitability space types, and directly deducting the legally prohibited construction area according to the low-suitability type; calculating the areas of different space types by using a geospatial statistical analysis tool, and counting the space scale with high suitability and medium suitability as basic rigid ecological capacity;
comprehensively considering the ecological environment characteristics of a planning area, and taking a legal important ecological patch as an important ecological source area of the area; setting an ecological migration standard resistance surface according to the earth surface coverage type, and correcting the ecological migration standard resistance surface by using a digital earth surface model to generate an adjustment coefficient; according to the regional ecological environment characteristics, establishing the link relation and the basic trend of an important ecological corridor, and then calculating the ecological corridor by using a minimum accumulated resistance model; combining an ecological source and an ecological corridor space to construct a regional ecological safety pattern according to the connectivity requirement of an ecological network; carrying out space reduction on the basic rigid capacity by using the ecological safety pattern, and calculating the structural rigid capacity meeting the requirements of ecological safety bottom lines;
superposing permanent basic farmland protection pattern spots on the structural rigidity capacity, determining the conflict level of each permanent basic farmland protection pattern spot and the construction requirement one by one, and mainly identifying the Yongnong pattern spots which must be called out for a major project and the Yongnong pattern spots which must be protected by opening a skylight; according to the basic requirement of the balance of the total amount of the permanent basic farmland protection, determining which permanent farmland patches in the region can be subjected to allopatric additional drawing or allopatric conservation, and generating various permanent basic farmland protection schemes such as full regulation and conservation or partial regulation and conservation; comprehensively considering the ecological safety pattern requirements and the permanent basic farmland regulation and protection multi-scenario scheme to obtain the floating range of the regional urban ecological capacity, and taking the floating range as the elastic ecological capacity;
optimizing a multi-scenario scheme of elastic ecological capacity according to a regional socioeconomic development strategy and a territorial space development positioning, and establishing an optimal capacity scenario meeting the regional socioeconomic development according to a permanent basic farmland regulation and protection index issued by superior planning; taking the optimal capacity scene as a basic constraint, combining the planning of the scale requirement of the social and economic development and construction land of the target year, and adopting a plaque cellular automaton model to simulate the urban growth space-time sequence evolution scene from the current situation to the target year; and smoothing and simplifying the simulated town growth plaque based on the simulated town growth pattern, and finally generating a regional town development boundary suggestion scheme.
Further, the threshold classification of the core space factors refers to setting different thresholds according to the importance of a certain factor on construction and development, and then classifying the single-factor space data under the support of GIS software to obtain a single-factor evaluation graph.
Furthermore, in the aspect of ecological corridor calculation, a connection trend buffer zone between ecological sources is fused into a minimum accumulated resistance model to construct a constraint minimum accumulated resistance model;
the constraint minimum accumulated resistance model has the following calculation formula:
wherein: m is the minimum accumulated resistance value; dcsRepresents the distance of the spatial element c from the source s; rcRepresenting the coefficient of resistance of the spatial unit c to the diffusion of the ecological process, which is the earth covering type resistance KcAnd regulatory factor TcSynthesizing; b represents the trend bandwidth constraint of the ecological corridor, so that excessive roundabout of the corridor calculation result is avoided; f represents the positive correlation of the minimum cumulative resistance and the ecological process; the communication path formed in the area with the lower M value between any two ecological sources is the ecological corridor.
Further, the adjustment coefficient T is calculated by normalization of the digital surface model DSM, and is expressed as T ═ H/HmaxWhere H represents the DSM value of the cell, HmaxRepresenting the maximum of all DSM units.
Furthermore, the elasticity lower limit of the elasticity ecological capacity is that permanent basic farmland pattern spots are required to be completely protected, and town development is strictly limited; the upper elastic limit is the permanent basic farmland pattern spot regulation and protection, and the urban development requirement is completely guaranteed; different permanent basic farmland regulations generate different elastic ecological capacity multi-scenario schemes.
Further, basic guidance and space constraint of a regional construction space are determined through elastic ecological capacity optimization, then major project site selection is used as a known seed point, a seed expansion mode is adopted to realize a plaque cellular automaton model, and then regional town growth space-time sequence change is simulated according to regional socioeconomic development construction land requirements.
Further, the selection strategies of the seed units of the plaque cellular automata model Patch-CA are respectively as follows: the initial seed position is based on a regional project addressing library, a plot with addressing requirements within an elastic ecological capacity range is recorded as fixed seeds of Patch-CA, meanwhile, random seeds are generated according to the expansion probability, and Patch expansion is carried out on the Patch-CA model based on the initial seeds during evolution iteration; the updating of the seed position is to randomly generate a batch of new seeds in a certain buffer area of the last iteration seed patch expansion area, the position of the new seeds should be prevented from being too far away or too close to the current town, and the size of the buffer area is defaulted to be the maximum outer diameter of the expansion patch.
Furthermore, the Patch-CA does not update one by one according to the unit when executing the cellular state evolution, but adopts a seed expansion strategy to carry out Patch type growth; the seed unit is selected according to a mixed mode of major item addressing and random addressing, and the patch type growth is carried out by filling the copy stamp by taking the seed unit as the center.
Further, the generation strategy of the simulated stamp is to randomly extract a plurality of patch growth samples from the historical change process according to the size of a patch growth window; in order to guarantee the diversity of the patch type growth, thousands of simulated stamps are extracted, and the seed unit randomly selects one type of stamp from the simulated stamp library to fill the stamp during filling.
Compared with the prior art, the invention has the following beneficial effects:
1. the multi-scenario simulation method for urban ecological capacity, which is constructed by the invention, establishes a multi-path coupling analysis strategy from basic rigid capacity, structural rigid capacity and elastic ecological capacity, and improves the controllability of the implementation of the urban ecological capacity evaluation technology.
2. According to the method, the digital earth surface model is merged into the minimum accumulated resistance model, and meanwhile, the connection trend of the ecological corridor is used as a space constraint condition, so that the defect of a circuitous line in the calculation of the ecological corridor is effectively avoided, and the development of urban design is facilitated by a smooth corridor passing through a high-density construction area.
3. The invention takes the ecological safety pattern (the expanded version of ecological protection red line) as the structural rigidity for constraint, forms the space conflict between farmlands and towns into a multi-scenario scheme through the protection game strategy (such as local regulation and protection, allopatric generation and protection and the like), and provides a judgment basis for analyzing the development boundary elasticity of towns.
4. On the basis of urban ecological capacity multi-scenario simulation, the method further utilizes the seed expansion patch type growth cellular automaton to simulate an urban growth spatial-temporal evolution sequence, can realize accurate conduction from urban ecological capacity multi-scenario simulation to urban development boundaries, and further better meets the dividing requirement of national soil space planning on three-area three-line.
Drawings
FIG. 1 is a flow chart of the urban ecological capacity assessment and development boundary simulation method of the present invention;
FIG. 2 is a schematic diagram of the ecological corridor identification based on the constrained minimum cumulative resistance model according to the present invention;
FIG. 3 is a schematic diagram of town development boundary simulation based on a seed plaque cellular automaton according to the present invention;
FIG. 4 is a schematic diagram of extracting a dummy stamp according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
Referring to fig. 1, the method for evaluating urban ecological capacity and simulating development boundary of the invention comprises the following steps:
step 1, according to requirements of landform and landform suitability and geological disaster risk prevention and control, performing threshold value grading on core space factors supporting and restricting urban industrial construction, and determining construction suitability or risk of a single factor on each evaluation unit; a decision tree multi-factor space superposition comprehensive discrimination method is adopted to carry out comprehensive integration on the single-factor evaluation result, the territorial space is divided into high-suitability, medium-suitability, low-suitability and other space types, and areas forbidden to be constructed by law, such as a natural protected area, and the like are directly deducted according to the low-suitability type; and calculating three types of areas of high suitability, medium suitability and low suitability by using a geospatial statistical analysis tool, and counting the space scales (areas) of the high suitability and the medium suitability as basic rigid ecological capacity.
Wherein, the single factor can be selected according to specific requirements, for example, the single factor can be the terrain flatness, the disaster risk and the like; the size of the evaluation unit is set according to actual requirements, and a 100m × 100 grid is adopted in the embodiment.
The basic rigidity capacity measurement and calculation only considers the supporting and restricting effects of the most basic space influence factors (namely, terrain flatness and geological disaster risks) influencing construction and development, wherein the terrain flatness and the geological disaster risks are evaluated by adopting three levels of high fitness (high risk), medium fitness (medium risk) and low fitness (low risk) respectively. The dynamic human factors which change along with the development of time, such as the distance development center and the distance of a road network and the like adopted by the traditional land utilization construction suitability evaluation are not adopted, so that the stability of the evaluation result is enhanced. The basic rigidity capacity expands the evaluation connotation of the suitability of the construction land, and can better support the construction evaluation requirements of rapidly-growing areas, particularly new areas.
In step 1 of this embodiment, the threshold classification of the core space factor refers to setting different thresholds according to the importance of a certain factor to the construction and development, and then classifying the single-factor space data under the support of the GIS software to obtain a single-factor evaluation graph. Taking the flatness of the terrain as an example, the threshold value is divided as shown in the following table:
TABLE 1 terrain flatness threshold partition Table
| Flatness of topography | Rating of evaluation | Area (ha) | Ratio (%) |
| <E1 | High suitability | A1 | P1％ |
| E1-E2 | Is suitable for the middle | A2 | P2％ |
| E2-E3 | Is not suitable for | A3 | P3％ |
| E3-E4 | Is not suitable for | A4 | P4％ |
| >E2 | Low suitability | A3 | P3％ |
In step 1 of this embodiment, the decision tree multi-factor spatial overlap synthesis determination method is a process of synthesizing a plurality of single-factor evaluation levels of an evaluation unit into one suitability level. Because the influence and the utility of different factors are different, a screening integration method of a decision tree is suitable for the comprehensive evaluation, and the multi-factor comprehensive evaluation example based on the decision tree is as follows:
step 2, comprehensively considering the ecological environment characteristics of a planning area, and taking the legal important ecological patches of a natural conservation place, a forest park, a wetland park and the like as important ecological source places of the area; setting an ecological migration standard resistance Surface according to the earth Surface coverage type, and generating an adjusting coefficient by using a Digital earth Surface Model (DSM) to correct the ecological migration standard resistance Surface; according to the regional ecological environment characteristics, determining the link relation and the basic trend of an important ecological corridor, and then calculating the ecological corridor by using a Minimum Cumulative Resistance Model (MCR) under the support of GIS software; combining an ecological source and an ecological corridor space to construct a regional ecological safety pattern according to the connectivity requirement of an ecological network; and carrying out space reduction on the basic rigidity capacity by utilizing the ecological safety pattern, and calculating the structural rigidity capacity meeting the requirements of the ecological safety bottom line.
Wherein the planning area refers to an administrative scope, such as Guangzhou city, Huangpu district, etc.; in the aspect of ecological resistance surface setting, a digital earth surface model is introduced to correct an ecological migration standard resistance surface set based on earth surface coverage data (such as land utilization and the like). The digital earth surface model contains height information of earth surface buildings, trees and the like, and can correct resistance dissimilarity (such as a high-rise building area has larger influence on bird migration) caused by different heights of the same type of earth surface coverage types.
In the aspect of ecological corridor calculation, a connection trend buffer zone between ecological sources and places is merged into a minimum Cumulative Resistance model to construct a Constrained minimum Cumulative Resistance model (CMCR), and various circuitous routes can be avoided when the minimum Cumulative Resistance model walks on an ecological Resistance surface through corridor trend constraint. The smoothness of the ecological corridor can avoid the fragmentation of the construction land patches and can better support the ground of the urban planning and design scheme.
In the step, the calculation principle of the constrained minimum accumulated resistance model is as follows
Wherein: m is the minimum accumulated resistance value; dcsRepresents the distance of the spatial element c from the source s; rcRepresenting the coefficient of resistance of the spatial unit c to the diffusion of the ecological process, which is the earth covering type resistance KcAnd regulatory factor TcSynthesizing; b represents the trend bandwidth constraint (represented as a buffer zone) of the ecological corridor, so that excessive roundabout of the corridor calculation result is avoided; f represents the positive correlation of the minimum cumulative resistance and the ecological process; the communication path formed in the area with the lower M value between any two ecological sources is the ecological corridor.
In step 2 of this embodiment, the ecological migration standard resistance surface is an ecological migration energy dissipation value determined according to a ground surface coverage type and by combining with expert scoring and other methods, and the larger the value is, the larger the resistance encountered in the ecological diffusion process of the animals and plants is. The setting mode of the value K of each unit on the ecological migration standard resistance surface based on the earth surface coverage type (such as the classification standard of the land utilization status of national soil survey for the third time) is as follows:
TABLE 2 minimum cumulative resistance value of cell on ecological migration standard resistance surface
In the step, a digital earth model is used for generating the regulating coefficient, and the influence of the earth morphology on the biological diffusion is mainly considered. For example, with the same type of forest land coverage, the forest land in plain areas has greater resistance than the forest land in mountain areas; same commercial land, high-rise buildings are compared with low-rise buildingsBirds are more affected. The digital earth surface model not only contains topographic information, but also contains height information such as buildings, trees and the like, and can reflect the three-dimensional space characteristics of the earth surface. The adjustment coefficient T can be calculated by the DSM by normalization and is expressed as T ═ H/HmaxWhere H represents the DSM value of the cell, HmaxRepresenting the maximum of all DSM units.
Step 3, superposing permanent basic farmland protection patterns on the structural rigidity capacity, determining the conflict level between each permanent basic farmland protection pattern and the construction requirement one by one, and identifying the Yongnong pattern which needs to be called out for a major project and the Yongnong pattern which needs to be protected by opening a skylight; according to the basic requirement of the balance of the total amount of the permanent basic farmland protection, determining which permanent farmland patches in the region can be subjected to allopatric additional drawing or allopatric conservation, and generating various permanent basic farmland protection schemes such as full regulation and conservation or partial regulation and conservation; and comprehensively considering the ecological safety pattern requirements and the permanent basic farmland multi-situation-conservation scheme to obtain the floating range of the regional urban ecological capacity as the elastic ecological capacity.
Wherein, the elastic lower limit of the elastic ecological capacity is that the permanent basic farmland pattern spots must be completely protected, and the town development is strictly limited; and the upper elastic limit is the permanent basic farmland pattern spot regulation and protection, and the urban development requirement is completely guaranteed. Different permanent basic farmland regulations generate different elastic ecological capacity multi-scenario schemes.
In step 3 of this embodiment, the step of determining the conflict level between each permanent basic farmland protection pattern spot and the construction requirement one by one is to determine whether each land parcel can be adjusted and the corresponding adjustment path analysis problem according to the spatial conflict analysis of the permanent basic farmland cultivated land quality level and the construction requirement. Different permanent basic farmland protection conflict analysis can obtain multiple scenario schemes, and the multiple scenario schemes are important influencing factors for urban ecological capacity evaluation elasticity analysis. The collision determination can be performed in the following mode:
TABLE 3 conflict discrimination Table
In the step, the space game of permanent basic farmland protection is fully considered. Aiming at the space conflict between the urban development and the farmland protection, a plurality of game strategies such as major project adjustment and protection, high-quality farmland 'skylight opening' and the like are introduced, and the urban space has elastic characteristics by studying and judging the uncertainty (such as reduction and protection, adjustment and protection and the like) of the permanent farmland block protection and multi-scenario analysis, so that the elastic ecological capacity range is determined.
Step 4, optimizing the elastic ecological capacity multi-scenario scheme according to the regional socioeconomic development strategy and the territorial space development positioning, and establishing the optimal capacity scenario meeting the regional socioeconomic development according to the permanent basic farmland regulation and protection indexes issued by the superior planning; the optimal capacity scene is taken as basic constraint, and a Patch-based Cellular Automata (Patch-CA) is adopted to simulate the urban growth space-time sequence evolution scene from the current situation to the target year in combination with the planning of the target year social economic development construction land scale requirement; based on the town growth pattern simulated by Patch-CA, the simulated town growth patches are smoothed and simplified by using a GIS (geographic information system) map making comprehensive tool, and finally a regional town development boundary suggestion scheme is generated.
The multi-scenario scheme is generated according to different farmland protection requirements, the optimal capacity scenario is determined according to indexes issued by superior levels, and the town growth pattern is obtained by a patch expansion cellular automata model.
In the step, basic guidance and space constraint of a regional construction space are determined through elastic ecological capacity optimization, then major project site selection is used as a known seed point, a batch-CA mode is adopted to realize batch-CA, and regional town growth time-space sequence change is simulated according to regional socioeconomic development construction land requirements.
In step 4 of this embodiment, Patch-CA is a set of general grid dynamic model framework, that is, a region space is discretized into a plurality of standard grids (e.g., 100m × 100m), and then the evolution of the complex system of the whole city is simulated by simulating the state change of each grid (i.e., whether the ground type identifier is a city). The Patch-CA does not update one by one according to the unit when executing the cellular state evolution, but adopts a seed expansion strategy to carry out the Patch type growth. The seed unit is selected mainly according to a mixed mode of major item addressing and random addressing, and the patch type growth is to fill the copy stamp by taking the seed unit as the center.
In step 4 of this embodiment, the selection strategies of the Patch-CA seed unit are respectively: the initial seed position is based on a regional project addressing library, a plot with addressing requirements within an elastic ecological capacity range is recorded as fixed seeds of Patch-CA, meanwhile, random seeds are generated according to the expansion probability, and Patch expansion is carried out on the Patch-CA model based on the initial seeds during evolution iteration; the updating of the seed position is to randomly generate a batch of new seeds in a certain buffer area of the last iteration seed patch expansion area, the position of the new seeds should be prevented from being too far away or too close to the current town, and the size of the buffer area can be generally defaulted to be the maximum outer diameter of the expansion patch.
In step 4 of this embodiment, the generation strategy of the dummy stamp is to randomly extract a plurality of patch growth samples from the history change process according to the size of the patch growth window (the larger the area of the planned area is, the larger the window size should be, and the default value may be set to 1000m × 1000 m). In order to ensure the diversity of the patch type growth, thousands of simulated stamps can be extracted, and the seed unit randomly selects one type of stamp from the simulated stamp library to fill the stamp during filling.
In conclusion, the invention constructs a complete analysis path from the basic rigid capacity to the structural rigid capacity and then to the elastic ecological capacity. The regional optimal town growth scheme is deduced from three ecological capacities from three visual angles according to a hierarchical progressive strategy, the rigidity and the elasticity characteristics of the urban ecological capacity are considered, and an operable path is provided for the national and local space planning and the implementation of grain safety (Yongnong protection), ecological safety (ecological pattern) and human development (development boundary).
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (9)
1. A method for evaluating urban ecological capacity and simulating development boundary is characterized by comprising the following steps:
according to the requirements of landform suitability and geological disaster risk prevention and control, carrying out threshold value grading on core space factors supporting and restricting urban industrial construction, and determining the construction suitability or risk of a single factor on each evaluation unit; comprehensively integrating the single-factor evaluation result, dividing the territorial space into high-suitability, medium-suitability and low-suitability space types, and directly deducting the legally prohibited construction area according to the low-suitability type; calculating the areas of different space types by using a geospatial statistical analysis tool, and counting the space scale with high suitability and medium suitability as basic rigid ecological capacity;
comprehensively considering the ecological environment characteristics of a planning area, and taking a legal important ecological patch as an important ecological source area of the area; setting an ecological migration standard resistance surface according to the earth surface coverage type, and correcting the ecological migration standard resistance surface by using a digital earth surface model to generate an adjustment coefficient; according to the regional ecological environment characteristics, establishing the link relation and the basic trend of an important ecological corridor, and then calculating the ecological corridor by using a minimum accumulated resistance model; combining an ecological source and an ecological corridor space to construct a regional ecological safety pattern according to the connectivity requirement of an ecological network; carrying out space reduction on the basic rigid capacity by using the ecological safety pattern, and calculating the structural rigid capacity meeting the requirements of ecological safety bottom lines;
superposing permanent basic farmland protection pattern spots on the structural rigidity capacity, determining the conflict level of each permanent basic farmland protection pattern spot and the construction requirement one by one, and mainly identifying the Yongnong pattern spots which must be called out for a major project and the Yongnong pattern spots which must be protected by opening a skylight; according to the basic requirement of the balance of the total amount of the permanent basic farmland protection, determining which permanent farmland patches in the region can be subjected to allopatric additional drawing or allopatric conservation, and generating various permanent basic farmland protection schemes such as full regulation and conservation or partial regulation and conservation; comprehensively considering the ecological safety pattern requirements and the permanent basic farmland regulation and protection multi-scenario scheme to obtain the floating range of the regional urban ecological capacity, and taking the floating range as the elastic ecological capacity;
optimizing a multi-scenario scheme of elastic ecological capacity according to a regional socioeconomic development strategy and a territorial space development positioning, and establishing an optimal capacity scenario meeting the regional socioeconomic development according to a permanent basic farmland regulation and protection index issued by superior planning; taking the optimal capacity scene as a basic constraint, combining the planning of the scale requirement of the social and economic development and construction land of the target year, and adopting a plaque cellular automaton model to simulate the urban growth space-time sequence evolution scene from the current situation to the target year; and smoothing and simplifying the simulated town growth plaque based on the simulated town growth pattern, and finally generating a regional town development boundary suggestion scheme.
2. The urban ecological capacity assessment and development boundary simulation method according to claim 1, wherein the threshold classification of the core space factors is to set different thresholds according to the importance of a certain factor to construction and development, and then classify single-factor space data under the support of GIS software to obtain a single-factor evaluation graph.
3. The urban ecological capacity assessment and development boundary simulation method according to claim 1, wherein in terms of ecological corridor calculation, a connection trend buffer zone between ecological sources is merged into a minimum cumulative resistance model to construct a constrained minimum cumulative resistance model;
the constraint minimum accumulated resistance model has the following calculation formula:
wherein: m is the minimum accumulated resistance value; dcsRepresents the distance of the spatial element c from the source s; rcRepresenting the coefficient of resistance of the spatial unit c to the diffusion of the ecological process, which is the earth covering type resistance KcAnd regulatory factor TcSynthesizing; b represents the trend bandwidth constraint of the ecological corridor, so that excessive roundabout of the corridor calculation result is avoided; f represents the positive correlation of the minimum cumulative resistance and the ecological process; the communication path formed in the area with the lower M value between any two ecological sources is the ecological corridor.
4. The urban ecological capacity assessment and development boundary simulation method according to claim 1, wherein the adjustment coefficient T is expressed as T-H/H by standardized calculation of a digital surface model DSMmaxWhere H represents the DSM value of the cell, HmaxRepresenting the maximum of all DSM units.
5. The method for urban ecological capacity assessment and development boundary simulation according to claim 1, wherein the elasticity lower limit of the elastic ecological capacity is that permanent basic farmland patches must be completely protected, and town development is strictly limited; the upper elastic limit is the permanent basic farmland pattern spot regulation and protection, and the urban development requirement is completely guaranteed; different permanent basic farmland regulations generate different elastic ecological capacity multi-scenario schemes.
6. The urban ecological capacity assessment and development boundary simulation method according to claim 1, characterized in that basic guidance and space constraint of regional construction space are determined by elastic ecological capacity optimization, then major project site selection is taken as a known seed point, a plaque cellular automata model is realized by adopting a seed expansion mode, and then regional town growth space-time sequence change is simulated according to regional socioeconomic development construction land requirements.
7. The urban ecological capacity assessment and development boundary simulation method according to claim 1, wherein the selection strategies of the seed units of the plaque cellular automata model Patch-CA are respectively as follows: the initial seed position is based on a regional project addressing library, a plot with addressing requirements within an elastic ecological capacity range is recorded as fixed seeds of Patch-CA, meanwhile, random seeds are generated according to the expansion probability, and Patch expansion is carried out on the Patch-CA model based on the initial seeds during evolution iteration; the updating of the seed position is to randomly generate a batch of new seeds in a certain buffer area of the last iteration seed patch expansion area, the position of the new seeds should be prevented from being too far away or too close to the current town, and the size of the buffer area is defaulted to be the maximum outer diameter of the expansion patch.
8. The urban ecological capacity assessment and development boundary simulation method according to claim 1, wherein Patch-CA performs Patch growth by using a seed expansion strategy instead of updating one by one according to a unit when performing cellular state evolution; the seed unit is selected according to a mixed mode of major item addressing and random addressing, and the patch type growth is carried out by filling the copy stamp by taking the seed unit as the center.
9. The urban ecological capacity assessment and development boundary simulation method according to claim 8, wherein the generation strategy of the dummy stamp is to randomly extract a plurality of patch growth samples from the historical change process according to the size of the patch growth window; in order to guarantee the diversity of the patch type growth, thousands of simulated stamps are extracted, and the seed unit randomly selects one type of stamp from the simulated stamp library to fill the stamp during filling.
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| WO2024193147A1 (en) * | 2023-03-20 | 2024-09-26 | 东南大学建筑设计研究院有限公司 | Suitable construction scope grading method based on cold-island value evaluation |
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| WO2024193147A1 (en) * | 2023-03-20 | 2024-09-26 | 东南大学建筑设计研究院有限公司 | Suitable construction scope grading method based on cold-island value evaluation |
| CN116385062A (en) * | 2023-06-06 | 2023-07-04 | 和元达信息科技有限公司 | Store area site selection determining method and system based on big data |
| CN116385062B (en) * | 2023-06-06 | 2023-09-19 | 和元达信息科技有限公司 | Store area site selection determining method and system based on big data |
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