Method for identifying and extracting urban characteristic landscape area based on spatial geographic information
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING SOUTHEAST UNIV URBAN PLANNING & DESIGN INST CO LTD
- Filing Date
- 2026-04-15
- Publication Date
- 2026-07-10
AI Technical Summary
Existing technologies cannot scientifically and accurately define the boundaries and scope of urban characteristic landscape areas, resulting in vague boundaries, insufficient targeting, and inability to meet the needs of urban planning.
Using a spatial geographic information-based approach, water system distribution data and topographic elevation data are acquired, the ratio of water surface area to mountain peak observation distance is calculated, water-characteristic areas and mountain-characteristic areas are identified, and spatial coupling and overlay are performed to extract characteristic landscape areas.
It achieves an organic integration of natural landscapes and urban spaces, accurately matches the unique geographical environment and cultural habits of each city, has high operability and practicality, supports flexible adjustments, and is suitable for large-scale and standardized urban planning.
Smart Images
Figure CN122365147A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of urban planning technology, specifically relating to a method for identifying and extracting urban characteristic landscape areas based on spatial geographic information. Background Technology
[0002] As an important planning carrier embodying the ecological, cultural, and spatial characteristics of a city, the scientific delineation and precise extraction of urban characteristic landscape areas are of significant practical importance. From an ecological perspective, these areas are a crucial component of the urban ecosystem, bearing key ecological functions such as water conservation, climate regulation, and biodiversity maintenance, and serving as core spaces for enhancing urban ecological resilience. In the field of urban planning, accurately defining the scope of characteristic landscape areas is the prerequisite and foundation for subsequent landscape protection, planning guidance, and management implementation. This can prevent the disorderly development of mountain and water resources and promote the realization of an ideal living environment where "mountains and water can be seen."
[0003] However, to date, although concepts related to the characteristics of mountain and water cities (mountain and water cities, urban natural landscape areas, urban cultural landscape areas, etc.) have received widespread attention in urban planning research and practice, how to scientifically and accurately define the boundaries and scope of mountain and water characteristic landscape areas has always been a core technical challenge in the fields of urban planning and geographic information identification, and has also become a key bottleneck restricting the implementation of the "mountain and water city" planning concept.
[0004] Currently, the common methods for defining scenic areas with distinctive mountain and water features in the industry mainly fall into two categories, both of which have significant shortcomings and cannot meet the actual needs of precise planning and scientific protection. Related research has also confirmed the prevalence of this problem: First, relying on the subjective judgment of practitioners, artificially dividing characteristic areas related to mountains and water in the city based on personal experience. This method lacks scientific and accurate quantitative definitions, resulting in unclear boundaries and scope of scenic areas with distinctive mountain and water features. It is highly subjective, lacks repeatability, and is difficult to adapt to the needs of large-scale and standardized urban planning. Related research on urban scenic area delineation methods clearly points out that subjective judgment methods have a high error rate and are prone to deviations in the scope of scenic areas, failing to provide reliable support for subsequent management. Second, using mechanical quantitative clauses for definition, such as uniformly stipulating areas at fixed distances along mountains and water (such as "XX meters along the mountain, XX meters along the water" in many local planning clauses) as scenic areas with distinctive mountain and water features, for subsequent protection or planning guidance. While this approach improves the objectivity and accuracy of the definition to some extent, it is too mechanical and fails to consider the spatial relationship and interaction in the core of "mountains and waters in harmony" in Chinese cities. The separation of mountains, waters and urban spaces makes it impossible to reflect the uniqueness of the mountain and water resources of different cities, and it is also difficult to accurately match the actual distribution characteristics of urban mountain and water landscapes. Ultimately, this results in some designated areas lacking actual mountain and water experience value, while some areas with important landscape value are overlooked.
[0005] The inherent flaws of existing traditional definition methods have led to widespread problems of vague boundaries and insufficient specificity in the delineation of scenic areas in most Chinese cities with mountainous landscapes. Therefore, there is an urgent need for a method to identify and extract distinctive urban scenic areas that can address these issues and adapt to the individual differences of different cities, thus filling a technological gap in the industry. Summary of the Invention
[0006] To address the shortcomings of existing technologies, the present invention aims to provide a method for identifying and extracting urban characteristic landscape areas based on spatial geographic information, thereby solving the problems in existing technologies.
[0007] The objective of this invention can be achieved through the following technical solutions: Methods for identifying and extracting distinctive urban landscape features based on spatial geographic information include: The water system distribution data of the urban spatial area to be processed is obtained, and the urban spatial area is divided into multiple uniform planar grids; the proportion of the water surface area in each planar grid to the total area of the planar grid is calculated to obtain the water surface ratio of each planar grid; the planar grids with the water surface ratio greater than a set water surface ratio threshold are identified as water feature units, and the collection of water feature units forms a water feature region. Obtain the topographic elevation data of the urban spatial area, and based on the topographic elevation data, obtain the actual height of each mountain peak in the area. Several classic mountain scenic spots were selected as examples within the urban spatial area. For each example, several unobstructed optimal observation points were selected. The ratio of the planar distance from each optimal observation point to the corresponding mountain peak to the actual height of the peak was calculated. Statistical analysis was performed on all calculated ratios to obtain the city's exclusive observation distance ratio. ; For each of the mountain peaks within the region, based on the formula The optimal observation distance for each of the aforementioned peaks is calculated by reverse calculation. Using the apex of each of the aforementioned peaks as the center, and the corresponding optimal observation distance... A circular planar region with a radius is drawn as a mountain feature unit, and the collection of all mountain feature units forms a mountain-featured region; The extracted water-feature areas and mountain-feature areas are spatially coupled and superimposed, and the intersection area after superposition is extracted to form the city's distinctive mountain and water landscape area.
[0008] Furthermore, before calculating the water surface ratio of each planar grid, the method further includes: preprocessing the water system distribution data, removing invalid data from the water system distribution data, and retaining valid water system data of natural rivers, lakes and artificial canals; the invalid data includes: temporary water accumulation areas and abandoned dried-up water systems.
[0009] Furthermore, the set water surface ratio threshold is determined based on the proportion distribution of the total water surface ratio of the city to be treated; when the city to be treated is a region with abundant water systems, the set water surface ratio threshold is configured to be greater than 20%.
[0010] Furthermore, the urban spatial area is divided into multiple uniform planar grids, including: dividing the entire urban spatial area into uniform planar grids of 100m×100m.
[0011] Furthermore, the dedicated observation distance is compared to The calculation method is as follows: Calculate the average of all the ratios, and use the average as the city's exclusive observation distance ratio. ; Alternatively, the ratio that appears most frequently in a normal distribution can be used as the city's specific observation distance ratio. .
[0012] Furthermore, five classic mountain scenic spots were selected as examples within the urban spatial area; for each example, eight unobstructed optimal observation points were selected.
[0013] A system for identifying and extracting distinctive urban landscape areas based on spatial geographic information, employing the methods described above, includes: The water feature area identification module is used to acquire water system distribution data of the urban spatial area to be processed, and divide the urban spatial area into multiple uniform planar grids; calculate the proportion of water surface area in each planar grid to the total area of the planar grid to obtain the water surface ratio of each planar grid; determine the planar grids with water surface ratio greater than a set water surface ratio threshold as water feature units, and the collection of water feature units forms a water feature area. The height and specificity ratio calculation module is used to obtain the topographic elevation data of the urban spatial area, and to obtain the actual height of each mountain peak in the area based on the topographic elevation data. Several classic mountain scenic spots were selected as examples within the urban spatial area. For each example, several unobstructed optimal observation points were selected. The ratio of the planar distance from each optimal observation point to the corresponding mountain peak to the actual height of the peak was calculated. Statistical analysis was performed on all calculated ratios to obtain the city's exclusive observation distance ratio. ; The mountain-specific region identification module is used to identify each mountain peak within the region based on a formula. The optimal observation distance for each of the aforementioned peaks is calculated by reverse calculation. Using the apex of each of the aforementioned peaks as the center, and the corresponding optimal observation distance... A circular planar region with a radius is drawn as a mountain feature unit, and the collection of all mountain feature units forms a mountain-featured region; The overlay extraction module is used to spatially couple and overlay the extracted water-feature areas with the mountain-feature areas, and extract the intersection area after overlay to form the city's characteristic landscape area.
[0014] A computer storage medium storing a readable program, which, when run, instructs a computing device to perform the above-described method for identifying and extracting urban characteristic landscape areas based on spatial geographic information.
[0015] An electronic device includes: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction, which causes the processor to perform operations corresponding to the above-described method for identifying and extracting urban characteristic landscape areas based on spatial geographic information.
[0016] A computer program product includes computer instructions that instruct a computing device to perform operations corresponding to the above-described method for identifying and extracting urban characteristic landscape areas based on spatial geographic information.
[0017] The beneficial effects of this invention are: 1. This invention uses "water surface ratio" as an evaluation index to reflect the experiential nature of water features, and employs a "mountain viewing line" model that quantifies the relationship between mountain peak height and observation distance to reflect the perceptible nature of mountain features. Both are identified independently before being spatially coupled and superimposed. This identification logic, based on scientific quantitative indicators and spatial geographic calculations, completely eliminates the boundary ambiguity caused by traditional subjective judgments based on experience. Simultaneously, it avoids the drawback of using mechanical quantitative clauses like "fixed buffer distances" that sever the cultural core of "mountain and water integration" in cities, achieving an organic integration of mountain and water landscapes with urban space, and making the extracted scenic areas more valuable in terms of humanities and ecology.
[0018] 2. The core identification parameters of this invention support flexible adjustment. For example, the "water surface ratio threshold" can be adjusted according to different geographical environments; by selecting classic local mountain examples and conducting statistical analysis, the city-specific observation distance ratio t, reflecting the observation habits of local citizens, can be derived in reverse. This tailored parameter technology ensures that the extraction results can accurately match the unique geographical environment, landscape resource characteristics, and cultural habits of each city. It effectively breaks the traditional "one-size-fits-all" identification mode and achieves truly "tailor-made and relatively accurate" capture of landscape features.
[0019] 3. The entire identification process of this invention is based on existing, mature geographic information data (such as the current land use data from the Third National Land Survey and topographic elevation data) for raster division and spatial calculation. This feature makes data acquisition very convenient in practical applications, and the calculation logic is clear and simple, completely eliminating the need for complex professional detection equipment. Therefore, this solution has strong practicality and high operability, enabling rapid large-scale and standardized extraction of landscape areas. The results can be directly applied to spatial guidance and control in subsequent urban planning and construction. Attached Figure Description
[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0021] Figure 1 This is a map of urban water features from Embodiment 2 of the present invention; Figure 2 This is a data map of urban mountain elements in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of the water density of urban statistical units in Embodiment 2 of the present invention; Figure 4 This is a schematic diagram of the mountain surface for city identification in Embodiment 2 of the present invention; Figure 5 This is a schematic diagram of the standardized water density of the city in Embodiment 2 of the present invention; Figure 6 This is a schematic diagram of the urban buffer mountain impact surface in Embodiment 2 of the present invention; Figure 7 This is the identification result image of the urban landscape area in Embodiment 2 of the present invention. Detailed Implementation
[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0023] Example 1 The core of the method for identifying and extracting urban characteristic landscape areas based on spatial geographic information is to independently identify water-characteristic areas and mountain-characteristic areas, and then couple and overlay them to finally obtain urban characteristic landscape areas where mountains and water complement each other. The specific steps are as follows: Step 1: Identification of water-featured areas 1.1 Grid Division: The city area to be studied is divided into several uniform planar grids. The size of the grids can be flexibly adjusted according to the city scale and the research accuracy requirements to ensure that the spatial distribution characteristics of the city's water surface can be accurately reflected, while taking into account the computational efficiency.
[0024] 1.2 Data Acquisition and Processing: Acquire the latest land survey data and other relevant water system vector data of the city to be studied (including but not limited to spatial distribution data of various water systems such as natural rivers, lakes, reservoirs, and artificial canals), and preprocess the water system data, specifically including: (1) extracting only patches with stable landscape characteristics such as land type names such as "river water surface", "lake water surface" and "reservoir water surface", and automatically filtering out other non-water system land types; (2) setting a minimum water area threshold T according to the current water system characteristics of the city to be studied, identifying and deleting isolated vector water surface patches with an area less than T, thereby eliminating temporary water accumulation or small polygons caused by data errors, and ensuring the accuracy and integrity of the water system data.
[0025] 1.3 Water surface ratio calculation: For each planar grid after division, calculate the proportion of water surface area in the grid to the total area of the grid, i.e., water surface ratio. The formula for calculating water surface ratio is: Water surface ratio = (Water surface area in the grid / Total area of the grid) × 100%.
[0026] 1.4 Water Feature Area Determination: Based on the local geographical environment and the distribution of the total water surface ratio of the city under study, a water surface ratio threshold is determined (the threshold varies for different cities; for example, in the Jiangnan water town area, due to the abundance of water systems, a water surface ratio greater than 20% can be selected as the threshold; while in water-scarce cities in the north, the threshold can be appropriately lowered according to the actual distribution of the total water surface ratio). The grid area with a water surface ratio greater than the set threshold is determined as a water feature unit. The set of all water feature units is the water feature area of the city. This area has abundant water bodies, great potential for interaction between people and water space, and is the core water landscape carrier of the city's landscape.
[0027] Step 2: Identification of distinctive mountain areas This step uses "viewing distance" as the core basis for people to experience the characteristics of mountains in the city. By quantifying the relationship between mountain height and observation distance, and combining it with the city's own mountain features, the scope of areas with distinctive mountain features is determined, as follows: 2.1 Mountain Feature Identification and Extraction: Obtain the digital elevation model (DEM) data of the city to be studied. Based on the urban terrain features, the following automated extraction procedures were performed using GIS tools: (1) Baseline Threshold Extraction: Based on the terrain undulation characteristics of the study area, the mountain slope elevation threshold H was set. limit Using GIS spatial query tools, extract all elevation values greater than H. limit(2) Morphological correction and noise reduction: Using morphological algorithms such as opening and closing operations, the mountain edges are automatically smoothed and small, fragmented highlands with areas smaller than a preset threshold are removed to ensure that the extracted results are actual mountains with landscape significance. (3) Multi-source data verification: The extracted mountain surface is spatially intersected with relevant land types such as "forest land" and "orchard land" in the latest land survey data to retain mountain elements with vegetation cover characteristics, thereby automatically removing artificial noise interference such as building clusters and overpasses with high elevations to obtain the mountain surface of the city to be studied.
[0028] 2.2 Determination of core influencing factors: The actual height of the mountain in the city (denoted as H) and the planar distance from the best observation point to the mountain peak (denoted as D) are selected as core influencing factors. Among them, the local maximum point in the above-mentioned mountain surface is identified by the surface analysis tool of GIS as the mountain peak; the absolute elevation of the peak is extracted and the average surface elevation (or the average benchmark elevation of the city) within a certain buffer range around the mountain is subtracted, and the resulting relative height difference is taken as the actual height H of the mountain. The best observation point is an area in the city where the main body of the mountain can be clearly observed without obvious obstruction. Among them, in order to ensure that the best observation point has the characteristic of "no obvious obstruction", the following automated screening steps are performed by GIS: (1) Extract public open spaces (including but not limited to open squares, parks and green spaces, low-rise and multi-story building areas, and waterfront areas) from the urban vector data as candidate observation areas. (2) Using the extracted mountain peak as the target point and the height of existing urban buildings as the obstruction, the visual field analysis algorithm is used to calculate and automatically extract the set of elements that can directly see the mountain peak within the candidate observation area. (3) In the above set of visible elements, resampling is performed at equal intervals according to a preset step size (determined based on the spatial scale relationship between mountains and water in the city under study), or the geometric center point is selected as a representative classic mountain observation point sample set.
[0029] 2.3 Determination of the city-specific observation distance ratio t: 2.3.1 Example Selection: In the city to be studied, several classic mountain scenic spots that are widely recognized and representative by the public are selected as examples. These examples should be able to reflect the core characteristics of the city's mountains and have good observation conditions.
[0030] 2.3.2 Ratio Calculation and Statistics: For each classic mountain scenic spot, several optimal observation points are selected from a representative sample of classic mountain observation points. The D / H value (i.e., the ratio of the planar distance from the optimal observation point to the mountain peak to the actual height of the mountain peak) corresponding to each optimal observation point is calculated. All calculated D / H values are statistically analyzed, and the arithmetic mean (or the value with the highest frequency in the normal distribution) is taken as the exclusive observation distance ratio of the city, denoted as t. The t value can accurately reflect the city's citizens' optimal observation habits of mountain scenery and reflect the uniqueness of the city's mountains.
[0031] 2.4 Delineation of Mountain-Featured Areas: Based on the actual height H of all mountains within the city under study, and combined with the determined city-specific observation distance ratio t, the optimal observation distance D for each mountain is calculated using the formula D=t×H. A circular planar region is drawn with the apex of each mountain as the center and the calculated optimal observation distance D as the radius. This circular region is the optimal observation area for that mountain, which is the mountain feature unit corresponding to that mountain. The set of all mountain feature units corresponding to all mountains is the mountain-featured area of the city.
[0032] Step 3: Extraction of landscape features by coupling and overlaying Using GIS tools, the water-feature raster set extracted in step 1 is converted into vector area features. During the conversion, the cell boundaries are kept intact, and adjacent rasters with the same attributes are merged to form continuous water-feature vector areas. A Boolean intersection operation is then performed between these water-feature vector areas and the mountain-feature vector areas extracted in step 2. The resulting intersection area represents the city's distinctive mountain and water landscape area. This area possesses both excellent water and mountain landscapes, enabling a "seeing mountains and seeing water" urban landscape experience. It is a core potential area that requires key guidance, management, and protection in future urban planning and construction.
[0033] Furthermore, in the identification and extraction process of this invention, all key parameters (including planar grid size, water surface ratio threshold, city-specific observation distance ratio t, etc.) can be flexibly adjusted according to the individual differences of the city under study. For example, the grid size can be adjusted for cities of different sizes; smaller cities can use smaller grids to improve accuracy, while larger cities can appropriately increase the grid size to improve computational efficiency. Cities with different geographical environments and water system distributions can adjust the water surface ratio threshold to adapt to local water system characteristics. Cities with different mountain distributions and observation habits can optimize the city-specific observation distance ratio t by adjusting the number and statistical methods of classic mountain examples, thereby achieving "tailor-made and relatively accurate" capture of mountain and water characteristic areas.
[0034] Based on a similar inventive concept, embodiments of the present invention also provide a computer storage medium storing a readable program that, when run by a processor, can execute the above-described method for identifying and extracting urban characteristic landscape areas based on spatial geographic information.
[0035] Based on a similar inventive concept, this invention provides an electronic device, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-described method for identifying and extracting urban characteristic landscape areas based on spatial geographic information.
[0036] Based on a similar inventive concept, embodiments of the present invention also provide a computer program product, including computer instructions, which instruct a computing device to perform the operations corresponding to the above-described method for identifying and extracting urban characteristic landscape areas based on spatial geographic information.
[0037] Example 2 This embodiment uses a specific city as an example to introduce a method for identifying and extracting urban characteristic landscape areas based on spatial geographic information. This city has abundant water systems, and mountains are distributed both within and around the city. Citizens generally share a common understanding of mountain and water landscapes and have a high demand for developing urban landscape features. Therefore, the "mountain and water reflecting each other" landscape area is identified as a key focus of urban construction control and is extracted accordingly. The specific extraction steps are as follows: Step 1: Identification of water-featured areas 1.1 Data Acquisition and Processing: Water system data was acquired from the city's third national land survey's current land use data. Invalid data such as temporary flooding and abandoned ditches were removed, while valid water system data including natural rivers, lakes, and artificial ponds were retained, resulting in the following: Figure 1 The image shows a map of the city's water features.
[0038] 1.2 Raster Division: The entire city area is divided into uniform planar grids of 100m × 100m, balancing computational accuracy and efficiency, such as... Figure 3 As shown; 1.3 Water Surface Ratio Calculation: Calculate the ratio of the water surface area within each grid cell to the total area of the grid cells to obtain the water surface ratio of each grid cell, such as... Figure 5 As shown; 1.4 Water Feature Area Determination: Combining the geographical environment of the city as a water town in the Jiangnan region and the distribution of the total water surface ratio, a water surface ratio of >20% was selected as the threshold. All grid cells with a water surface ratio of >20% were aggregated to obtain the water feature areas of the city, which are mainly distributed along the riverbanks and around the lakes.
[0039] Step 2: Identification of distinctive mountain areas 2.1 Mountain Feature Identification and Extraction: Using the city's digital elevation model data and based on the city's topographic features, an automated extraction program was executed using GIS tools to obtain the following features: Figure 2 The image shows a map of the city's mountain features.
[0040] 2.2 Determination of Core Influencing Factors: The actual height H of all mountain peaks in the entire region was obtained by calculating the difference between the city's topographic elevation data, the average elevation around the mountains, and the absolute elevation of the mountain peaks. The results are as follows: Figure 4 The map shows the surface data of the city's mountains; five classic mountain scenic spots widely recognized by the city's citizens were selected as examples, and eight unobstructed best observation points were selected for each example; 2.3 Determination of the city-specific observation distance ratio t: The D / H value of each optimal observation point was calculated, resulting in 40 D / H values. Statistical analysis was performed on these values, and the average value was taken as the city's specific observation distance ratio t=20. 2.4 Delineation of Mountain-Specific Areas: Based on the actual height H of each peak, the optimal observation distance D for each peak is calculated using the formula D=20×H. Circular areas are then drawn with each peak's apex as the center and D as the radius. After summing all circular areas, the following is obtained: Figure 6 The image shows the mountainous area of the city.
[0041] Step 3: Extraction of landscape features by coupling and overlaying The water-feature areas obtained in step 1 are vectorized and then spatially overlaid with the mountain-feature areas obtained in step 2. The intersection area after overlay represents the characteristic landscape area of this Jiangnan water town, such as... Figure 7 As shown, this area is mainly distributed in the overlapping part of the riverbank and the best observation area of the mountain, which can realize the landscape experience of "seeing the mountain and seeing the water", and provide a precise range basis for the subsequent planning, protection and landscape creation of this area.
[0042] Example 3 This embodiment proposes a system for identifying and extracting urban characteristic landscape areas based on spatial geographic information, specifically including: The water feature area identification module is used to acquire water system distribution data of the urban spatial area to be processed, and divide the urban spatial area into multiple uniform planar grids; calculate the proportion of water surface area in each planar grid to the total area of the planar grid to obtain the water surface ratio of each planar grid; determine the planar grids with water surface ratio greater than a set water surface ratio threshold as water feature units, and the collection of water feature units forms a water feature area. The height and specificity ratio calculation module is used to obtain the topographic elevation data of the urban spatial area, and to obtain the actual height of each mountain peak in the area based on the topographic elevation data. Several classic mountain scenic spots were selected as examples within the urban spatial area, and several unobstructed optimal observation points were selected for each example. The planar distance from each optimal observation point to the corresponding mountain peak of the example was calculated. Compared to the actual height of the mountain The ratio of the calculated ratios is statistically analyzed to obtain the city's exclusive observation distance ratio. ; The mountain-specific region identification module is used to identify each mountain peak within the region based on a formula. The optimal observation distance for each of the aforementioned peaks is calculated by reverse calculation. Using the apex of each of the aforementioned peaks as the center, and the corresponding optimal observation distance... A circular planar region with a radius is drawn as a mountain feature unit, and the collection of all mountain feature units forms a mountain-featured region; The overlay extraction module is used to spatially couple and overlay the extracted water-feature areas with the mountain-feature areas, and extract the intersection area after overlay to form the city's characteristic landscape area.
[0043] The methods of the present invention can be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium (such as a CD-ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code originally stored on a remote recording medium or a non-transitory machine-readable medium and subsequently stored on a local recording medium, downloaded via a network. Thus, the methods described herein can be processed by software stored on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components (e.g., RAM, ROM, flash memory, etc.) capable of storing or receiving software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the methods described herein. Furthermore, when a general-purpose computer accesses the code used to implement the methods shown herein, the execution of the code transforms the general-purpose computer into a dedicated computer for performing the methods shown herein.
[0044] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.
Claims
1. A method for identifying and extracting distinctive urban landscape areas based on spatial geographic information, characterized in that, include: Acquire water system distribution data for the urban spatial area to be processed, and divide the urban spatial area into multiple uniform planar grids; Calculate the ratio of the water surface area in each of the planar grids to the total area of the planar grids to obtain the water surface ratio of each planar grid; determine the planar grids with a water surface ratio greater than a set water surface ratio threshold as water feature units, and the collection of water feature units forms a water feature region; Obtain the topographic elevation data of the urban spatial area, and based on the topographic elevation data, obtain the actual height of each mountain peak in the area. Several classic mountain scenic spots were selected as examples within the urban spatial area. For each example, several unobstructed optimal observation points were selected. The ratio of the planar distance from each optimal observation point to the corresponding mountain peak to the actual height of the peak was calculated. Statistical analysis was performed on all calculated ratios to obtain the city's exclusive observation distance ratio. ; For each of the mountain peaks within the region, based on the formula The optimal observation distance for each of the aforementioned peaks is calculated by reverse calculation. Using the apex of each of the aforementioned peaks as the center, and the corresponding optimal observation distance... A circular planar region with a radius is drawn as a mountain feature unit, and the collection of all mountain feature units forms a mountain-featured region; The extracted water-feature areas and mountain-feature areas are spatially coupled and superimposed, and the intersection area after superposition is extracted as the city's distinctive landscape area.
2. The method for identifying and extracting urban characteristic landscape areas based on spatial geographic information according to claim 1, characterized in that, Before calculating the water surface ratio of each planar grid, the process further includes: preprocessing the water system distribution data, removing invalid data from the water system distribution data, and retaining valid water system data for natural rivers, lakes, and artificial canals; the invalid data includes: temporary water accumulation areas and abandoned dried-up water systems.
3. The method for identifying and extracting urban characteristic landscape areas based on spatial geographic information according to claim 1, characterized in that, The set water surface ratio threshold is determined based on the proportion distribution of the total water surface ratio of the city to be treated; when the city to be treated is a region with abundant water systems, the set water surface ratio threshold is configured to be greater than 20%.
4. The method for identifying and extracting urban characteristic landscape areas based on spatial geographic information according to claim 1, characterized in that, Dividing the urban spatial area into multiple uniform planar grids includes: dividing the entire urban spatial area into uniform planar grids of 100m × 100m.
5. The method for identifying and extracting urban characteristic landscape areas based on spatial geographic information according to claim 1, characterized in that, The specific observation distance ratio The calculation method is as follows: Calculate the average of all the ratios, and use the average as the city's exclusive observation distance ratio. ; Alternatively, the ratio that appears most frequently in a normal distribution can be used as the city's specific observation distance ratio. .
6. The method for identifying and extracting urban characteristic landscape areas based on spatial geographic information according to claim 1, characterized in that, Five classic mountain scenic spots were selected as examples in the urban spatial area; for each example, eight unobstructed best observation points were selected.
7. A system for identifying and extracting urban characteristic landscape areas based on spatial geographic information, comprising the method described in any one of claims 1-6, characterized in that, include: The water feature area identification module is used to acquire water system distribution data of the urban spatial area to be processed and divide the urban spatial area into multiple uniform planar grids. Calculate the ratio of the water surface area in each of the planar grids to the total area of the planar grids to obtain the water surface ratio of each planar grid; determine the planar grids with a water surface ratio greater than a set water surface ratio threshold as water feature units, and the collection of water feature units forms a water feature region; The height and specificity ratio calculation module is used to obtain the topographic elevation data of the urban spatial area, and to obtain the actual height of each mountain peak in the area based on the topographic elevation data. Several classic mountain scenic spots were selected as examples within the urban spatial area. For each example, several unobstructed optimal observation points were selected. The ratio of the planar distance from each optimal observation point to the corresponding mountain peak to the actual height of the peak was calculated. Statistical analysis was performed on all calculated ratios to obtain the city's exclusive observation distance ratio. ; The mountain-specific region identification module is used to identify each mountain peak within the region based on a formula. The optimal observation distance for each of the aforementioned peaks is calculated by reverse calculation. Using the apex of each of the aforementioned peaks as the center, and the corresponding optimal observation distance... A circular planar region with a radius is drawn as a mountain feature unit, and the collection of all mountain feature units forms a mountain-featured region; The overlay extraction module is used to spatially couple and overlay the extracted water-feature areas with the mountain-feature areas, and extract the intersection area after overlay to form the city's characteristic landscape area.
8. A computer storage medium storing a readable program, characterized in that, When the program is running, it can instruct the computing device to perform the method for identifying and extracting urban characteristic landscape areas based on spatial geographic information as described in any one of claims 1-6.
9. An electronic device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the method for identifying and extracting urban characteristic landscape areas based on spatial geographic information as described in any one of claims 1-6.
10. A computer program product comprising computer instructions, characterized in that, The computer instructions instruct the computing device to perform the operations corresponding to the method for identifying and extracting urban characteristic landscape areas based on spatial geographic information as described in any one of claims 1-6.