CN-121982159-A - Urban growth simulation form correction method and system based on grid-vector cooperation

CN121982159ACN 121982159 ACN121982159 ACN 121982159ACN-121982159-A

Abstract

The invention discloses a grid-vector synergy-based city growth simulation form correction method and system, wherein the method comprises the steps of dividing remote sensing image data to obtain dividing patches, combining street block units obtained by processing vector road data to form fused space units, inputting land utilization and driving factor data into a grid CA model to obtain converted city cells, obtaining a city growth simulation result graph of the grid CA, and correcting the city growth simulation result graph of the grid CA by using a form correction strategy to obtain a corrected final city growth simulation result graph. According to the invention, the fused composite space unit is obtained by combining the segmentation patches and the neighborhood units, so that the fineness of the segmentation space unit is improved, a more accurate space base is provided for morphological correction, and an effective balance among the calculation efficiency, the process rationality and the morphological authenticity is realized by utilizing a cooperative mechanism of grid simulation-vector correction.

Inventors

ZENG HAORAN
HU SHOUGENG
ZHANG BIN

Assignees

中国地质大学（武汉）

Dates

Publication Date: 20260505
Application Date: 20260115

Claims (10)

1. The city growth simulation morphology correction method based on grid-vector cooperation is characterized by comprising the following steps of: dividing the remote sensing image data to obtain a dividing patch, and combining the block units obtained by processing the vector road data to form a fused space unit; Inputting land utilization and driving factor data into a grid CA model to obtain converted urban cells and obtain an urban growth simulation result diagram of the grid CA; and correcting the urban growth simulation result diagram of the grid CA by using a morphological correction strategy to obtain a corrected final urban growth simulation result diagram, wherein the morphological correction strategy carries out space division and coding linking on the urban growth simulation result diagram of the grid CA according to the fused space unit to obtain each plaque containing unique codes, calculates the urban land area occupation ratio of each plaque, and carries out morphological correction on the cell in the corresponding plaque according to the calculation result.
2. The urban growth simulation morphological correction method based on grid-vector cooperation according to claim 1, wherein land utilization, driving factors and remote sensing image data are specifically preprocessed data, and the preprocessing specifically comprises: acquiring land utilization data at an initial stage and an end stage, and classifying the land utilization data into a city class and a non-city class respectively; Selecting city growth driving factors, and carrying out standardized processing on driving factor data; And (3) deriving the acquired remote sensing image data in an RGB three-band TIFF format, and unifying a projection coordinate system, a geographic range and spatial resolution of all the data.
3. The urban growth simulation morphological correction method based on grid-vector cooperation according to claim 1, wherein the fused space unit is obtained specifically by the following way: Distributing seed points on the remote sensing image data, and distributing each pixel in the image data to the seed point closest to the seed point by optimizing a distance function to obtain a segmentation patch; Trimming, extending and cleaning suspension lines of the vector road data, and constructing a road buffer area and performing space division operation according to the processed vector road data to obtain a block unit surrounded by a road; And carrying out space superposition analysis on the segmentation patches and the neighborhood units, and carrying out optimization recombination on the super-pixel boundaries by using a road network as a structural frame to form a fused space unit.
4. The urban growth simulation morphological correction method based on grid-vector cooperation according to claim 1, wherein the grid CA model is specifically constructed based on a preset conversion rule, and specifically comprises: The land utilization and driving factor data are input into a grid CA model for iteration, the urban conversion probability of each non-urban cell is calculated in each iteration, and the non-urban cells with the probability larger than a certain threshold value are converted into urban cells until the newly added land utilization area reaches a preset threshold value, so that a simulation result diagram of the grid CA is obtained; the city transition probability is calculated by multiplying the development suitability probability, the neighborhood effect value and the development limit state of each cell.
5. The grid-vector synergy-based city growth simulation morphological correction method of claim 4, wherein the development suitability probability is calculated by a random forest model, and the construction process of the random forest model is as follows: acquiring initial and final land utilization data, preprocessing, performing superposition analysis on the preprocessed initial and final land utilization data, and identifying and dividing the preprocessed initial and final land utilization data into an urban growing area and an unchanged area; Extracting positive samples from the urban growing area according to a certain sampling rate, extracting equivalent negative samples from the unchanged area, obtaining driving factor values of all sample points, and constructing a sample set; And inputting the sample set into a random forest model for training, and obtaining the relation between the city growth and the driving factor to obtain the trained random forest model.
6. The grid-vector synergy-based city growth simulation morphological correction method according to claim 4, wherein the neighborhood effect value is calculated according to the total number of cells in the neighborhood, the city state of the adjacent cells at the time, and the weight of the adjacent cells, wherein the weight of the adjacent cells is calculated by a distance decay function.
7. The grid-vector synergy-based city growth simulation morphological correction method according to claim 4, wherein the performing of the correction by using the morphological correction strategy comprises a static correction strategy and a dynamic correction strategy, wherein the static correction strategy performs morphological correction on cells in each plaque based on a simulation result graph of the grid CA at the moment after the newly added city floor area reaches a preset threshold and stops iteration, and the dynamic correction strategy performs morphological correction on cells in each plaque in real time based on a simulation result graph of the grid CA at each iteration and takes the corrected result as an input of the next iteration.
8. The urban growth simulation morphological correction method based on grid-vector cooperation according to claim 7, wherein the static correction strategy is specifically: Space division is carried out on the city growth simulation result graph of the grid CA after iteration is completed by utilizing a space unit, and each divided plaque is encoded; Traversing each plaque, and calculating the urban land area occupation ratio in each plaque; setting a filling threshold and a pruning threshold, if the area ratio of the urban land is larger than or equal to the filling threshold, converting all non-urban cells in the plaque into urban cells, if the area ratio of the urban land is smaller than or equal to the pruning threshold, converting all the urban cells in the plaque into non-urban cells, otherwise, maintaining the original state.
9. The urban growth simulation morphological correction method based on grid-vector cooperation according to claim 7, wherein the dynamic correction strategy is specifically: Carrying out space division on the simulation result graph of the grid CA of each iteration by utilizing a space unit, and coding each divided plaque; after each iteration, identifying a new region of the iteration, linking the new region with plaque codes, traversing each plaque containing the new region, and calculating the urban land area occupation ratio in each plaque; Setting a filling threshold and a pruning threshold, and converting all non-urban cells in the plaque into urban cells if the urban land occupation ratio is larger than or equal to the filling threshold, and converting all the urban cells in the plaque into non-urban cells if the urban land occupation ratio is smaller than or equal to the pruning threshold, otherwise, maintaining the original state; stopping iteration when the maximum iteration number is reached, and outputting a final city growth simulation result graph.
10. A grid-vector synergy-based city growth simulation morphology correction system, the system comprising: The space unit fusion module is used for dividing the remote sensing image data to obtain a division patch, and combining the block units obtained by processing the vector road data to form a fused space unit; The grid simulation module is used for inputting land utilization and driving factor data into a grid CA model to obtain converted urban cells and obtain an urban growth simulation result diagram of the grid CA; The system comprises a correction module, a form correction module and a cell management module, wherein the correction module is used for correcting the urban growth simulation result diagram of the grid CA by using a form correction strategy to obtain a corrected final urban growth simulation result diagram, the form correction strategy is used for carrying out space division and coding linking on the urban growth simulation result diagram of the grid CA according to the fused space unit to obtain each plaque containing unique codes, calculating the urban area occupation ratio of each plaque and carrying out form correction on the cell in the corresponding plaque according to the calculation result.

Description

Urban growth simulation form correction method and system based on grid-vector cooperation Technical Field The invention relates to the technical field of urban space simulation and geographic information, in particular to a grid-vector cooperation-based urban growth simulation form correction method and system. Background At present, the technical scheme of CA modeling in the technical field of urban space simulation and geographic information mainly comprises two types of traditional grid CA models and vector CA models. The traditional grid CA model takes a regular grid as a unit, and has high calculation efficiency, but the simulation result is rough in form, and has obvious 'checkerboard' effect, so that continuous and reasonable city contours molded by real geographic elements cannot be accurately reflected. Although the vector CA model adopts an irregular polygon as a unit to improve the shape authenticity, two main defects generally exist, namely, firstly, the space unit divided by a single data source (such as a cadastre or a road only) has defects in data timeliness and fineness, particularly in data sparse division results are rough, secondly, the calculation load is obviously increased due to the fact that complex vector operation is embedded into an iterative process, the shape evolution rule in the iterative process is difficult to design, and effective balance among calculation efficiency, process rationality and shape authenticity is difficult to realize. Disclosure of Invention In order to solve the problems of dependence on a single data source and low calculation efficiency in the prior art, the invention provides a grid-vector cooperation-based city growth simulation form correction method and system, so as to improve the timeliness and accuracy of dividing space units and realize the effective balance among calculation efficiency, process rationality and form authenticity. The technical scheme adopted by the invention is as follows: the utility model provides a city growth simulation form correction method based on grid-vector cooperation, which comprises the following steps: dividing the remote sensing image data to obtain a dividing patch, and combining the block units obtained by processing the vector road data to form a fused space unit; Inputting land utilization and driving factor data into a grid CA model to obtain converted urban cells and obtain an urban growth simulation result diagram of the grid CA; and correcting the urban growth simulation result diagram of the grid CA by using a morphological correction strategy to obtain a corrected final urban growth simulation result diagram, wherein the morphological correction strategy carries out space division and coding linking on the urban growth simulation result diagram of the grid CA according to the fused space unit to obtain each plaque containing unique codes, calculates the urban land area occupation ratio of each plaque, and carries out morphological correction on the cell in the corresponding plaque according to the calculation result. According to the scheme, the remote sensing image data specifically is the preprocessed remote sensing image data, and the preprocessing specifically comprises: Land utilization grid data at the initial stage and the final stage are acquired and classified into urban categories and non-urban categories respectively; Selecting city growth driving factors, and carrying out standardized processing on driving factor data; And (3) deriving the acquired remote sensing image data in an RGB three-band TIFF format, and unifying a projection coordinate system, a geographic range and spatial resolution of all the data. According to the scheme, the fused space unit is specifically obtained by the following steps: Distributing seed points on the remote sensing image data, and distributing each pixel in the image data to the seed point closest to the seed point by optimizing a distance function to obtain a segmentation patch; trimming, extending and cleaning suspension lines of vector road data in the remote sensing image data, and constructing a road buffer area and performing space division operation according to the processed vector road data to obtain a block unit surrounded by a road; And carrying out space superposition analysis on the segmentation patches and the neighborhood units, and carrying out optimization recombination on the super-pixel boundaries by using a road network as a structural frame to form a fused space unit. According to the scheme, the grid CA model is specifically constructed based on a preset conversion rule, and specifically comprises the following steps: Inputting remote sensing image data into a grid CA model for iteration, calculating the urban conversion probability of each non-urban cell in each iteration, and converting the non-urban cells with the probability larger than a certain threshold value into urban cells until the newly added urban land area reaches a preset