A method for confirming the width of heat island corridors in an urban heat island network

Abstract

The present invention discloses a method for confirming the width of heat island corridors in an urban heat island network, belonging to the technical field of urban ecological intelligent analysis. The method includes: inverting the surface temperature of the study area; screening heat island source areas and generating a resistance surface by combining morphological spatial pattern analysis, landscape connectivity index and circuit theory, and constructing a multi-level urban heat island corridor network; constructing multi-level buffer zones for different levels of corridors and respectively extracting the average surface temperature; extracting the extreme temperature values of the buffer zones of each level of corridors and calculating the temperature difference parameters to quantify the heat exchange intensity; calculating the heat transfer efficiency per unit area in combination with the buffer zone area; analyzing the non-linear attenuation characteristics of the heat transfer efficiency with the buffer zone offset distance, extracting the inflection point of the heat transfer efficiency, and taking the buffer zone offset distance corresponding to the inflection point as the spatial action width of the heat island corridor, so as to scientifically define the spatial action boundary of the heat island network. The present invention can also provide a scientific basis for alleviating the urban heat island effect, optimizing the green space layout, etc.

Description

Technical Field

[0001] The present invention relates to the cross - technical field of urban ecological research and artificial intelligence, and particularly to a method for confirming the width of a heat island corridor in an urban heat island network. Background Art

[0002] In recent years, factors such as global warming have triggered the degradation of urban ecosystems, intensified the urban heat environment problems characterized by the heat island effect, led to frequent occurrence of extreme high - temperature weather represented by heatwaves globally, and posed serious adverse impacts on human health, agriculture, social economy and ecosystems. Therefore, how to alleviate urban heat environment problems through reasonable planning and layout is a widely concerned issue currently. The academic community has gradually recognized the important role of urban heat environment connectivity in alleviating heat environment problems, and has explored the identification of urban heat island corridors, the construction of heat island networks, and the possibility of alleviating the heat island effect by setting obstacle points in the network structure.

[0003] Current research on urban heat island networks mostly focuses on the identification of linear structures and important nodes, but it is unable to scientifically determine the width of the heat island network. Therefore, it is impossible to reasonably optimize the heat environment pattern according to the specific scope of action of the corridors in the heat island network; or it can only obtain qualitative optimization strategies based on the linear structure of the heat island network, and the output results are relatively subjective. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for confirming the width of a heat island corridor in an urban heat island network, which can systematically analyze the key parameters of the width of the urban heat island corridor, realize the quantification of the heat transfer efficiency of the heat island corridor, and then determine the width of the urban heat island corridor according to the heat transfer efficiency, providing a scientific basis for alleviating the urban heat island effect and optimizing the heat environment. The technical solution adopted by the present invention is as follows.

[0005] On the one hand, the present invention provides a method for confirming the width of a heat island corridor in an urban heat island network, including:

[0006] Obtaining the atmospheric parameter data, remote sensing image data and resistance surface correlation data of the analysis area;

[0007] Based on the atmospheric parameter data and remote sensing image data, performing land surface temperature inversion to obtain the land surface temperature data of the analysis area;

[0008] Based on the land surface temperature data and the resistance surface correlation data, constructing a multi - level heat island corridor network of the analysis area;

[0009] Corresponding to each heat island corridor of different levels in the multi - level heat island corridor network, respectively constructing multi - level buffer zones, and respectively statistically analyzing the temperature data sets for each level of buffer zones at each level;

[0010] Based on the temperature dataset, obtain the temperature difference parameters characterizing the heat exchange intensity of each layer of the buffer zone;

[0011] According to the area of each layer of the buffer zone and the temperature difference parameters, calculate the heat transfer efficiency of each layer of the buffer zone of each grade of the heat island corridor;

[0012] For each grade of the heat island corridor, fit the relationship curve between the offset distance and the heat transfer efficiency of all layers of the buffer zone to characterize the non-linear attenuation characteristics of the heat transfer efficiency with the expansion of the buffer zone offset distance;

[0013] For each grade of the heat island corridor, based on the relationship curve between the buffer zone offset distance and the heat transfer efficiency, extract the inflection point of the heat transfer efficiency, and determine the corresponding buffer zone offset distance as the spatial action width of the corresponding grade of the heat island corridor.

[0014] Optionally, the surface temperature inversion based on the atmospheric parameter data and the remote sensing image data to obtain the surface temperature data of the analysis area includes:

[0015] According to the thermal infrared radiation value of each temperature grid in the remote sensing image data, as well as the surface emissivity, atmospheric radiation intensity, and atmospheric transmittance in the thermal infrared band in the atmospheric parameters, calculate the blackbody radiation brightness, and the formula is:

[0016]

[0017] Calculate the surface temperature of each temperature grid according to the blackbody radiation brightness and the calibration constant in the thermal infrared band, and the formula is:

[0018]

[0019] In the formula, represents the blackbody radiation brightness, represents the thermal infrared radiation value of the temperature grid, represents the atmospheric transmittance in the thermal infrared band, represents the surface emissivity, represents the upward atmospheric radiation intensity, represents the downward atmospheric radiation intensity, represents the surface temperature of the temperature grid, and represents the calibration constant in the thermal infrared band. For example, in Landsat-8 OLI / TIRS, , .

[0020] Optionally, in order to more clearly express the spatial pattern of the urban thermal environment, the present invention uses the relative land surface temperature to characterize the contribution value of different regions to the overall environment, that is, the land surface temperature of the analysis region is retrieved based on the atmospheric parameter data and remote sensing image data, and further includes: calculating the relative land surface temperature of each temperature grid according to the land surface temperature of each temperature grid, and the formula is:

[0021]

[0022] In the formula: represents the relative land surface temperature at temperature grid i, represents the actual land surface temperature at temperature grid i obtained by inversion, represents the average value of the actual land surface temperatures obtained by inversion of all temperature grids in the analysis region.

[0023] Optionally, based on the land surface temperature data and the resistance surface correlation data, a multi-level heat island corridor network of the analysis region is constructed, including:

[0024] Classify the land surface temperatures of all temperature grids by the mean standard deviation classification method, and the land surface temperature can be taken as the aforementioned relative land surface temperature;

[0025] Based on the land surface temperature classification results, combined with the MSPA model and the landscape connectivity index, determine the heat island source areas of the analysis region; and, based on the land surface temperature data and the resistance surface correlation data, analyze and obtain the heat island resistance surface of the analysis region;

[0026] According to the heat island source areas and the heat island resistance surface, apply circuit theory to construct the thermal environment network of the analysis region, and obtain the importance classification results of the heat island corridors through the centrality mapper module in the Linkage Mapper toolkit of ArcGIS, and classify the heat island corridors into first-level heat island corridors and second-level heat island corridors according to their centrality in the thermal environment network.

[0027] Optionally, for each heat island corridor corresponding to different levels in the multi-level heat island corridor network, construct multi-level buffer zones respectively, and statistically obtain the land surface temperature mean data sets for each level of buffer zones at each level, including:

[0028] According to the set single-layer width and maximum offset threshold, use the center line of each heat island corridor as the offset reference line to construct symmetric multi-level buffer zones on both sides of each heat island corridor;

[0029] Statistically obtain the land surface temperature mean values of the same-level buffer zones of all heat island corridors at the same level, and obtain the land surface temperature mean data sets of the buffer zones at each level of heat island corridors at each level.

[0030] It should be noted here that in the dataset of the average surface temperature, each heat island corridor buffer zone at each level corresponding to each level has one such average surface temperature, that is, the average surface temperature of each level buffer zone is the average value obtained from the surface temperatures of all buffer zones at the same level of all heat island corridors at the same level.

[0031] The above process of realizing visualization can be achieved by using the ArcGIS platform, specifically including:

[0032] Through the "Extract by Mask" tool, crop the corresponding surface temperature raster data according to the boundaries of each buffer zone in the multi-level buffer zone;

[0033] Calculate the temperature mean Mean and the temperature coefficient of variation Std / Mean of each level buffer zone through the "Zonal Statistics" tool; at this time, the dataset of the average surface temperature can be obtained;

[0034] For the convenience of subsequent calling and data processing, associate the zonal statistics results with the heat island corridor level, buffer zone level serial number, buffer zone offset distance, and surface temperature raster file path, and save them as a structured data table. The buffer zone offset distance refers to the distance between the outer edge line of a single-layer buffer zone and the center line of the heat island corridor.

[0035] Furthermore, for the convenience of data processing and comparison during subsequent temperature difference parameter calculation, the average surface temperature of the buffer zones at the same level of all heat island corridors at the same level is statistically calculated to obtain the dataset of the average surface temperature of the buffer zones at each level of the heat island corridors at each level, including:

[0036] Calculate the average surface temperature of all buffer zones at the same level of all heat island corridors at the same level;

[0037] Based on the average surface temperature of the buffer zones at each level of all heat island corridors at the same level, perform range normalization calculation to obtain the range-normalized average surface temperature of the buffer zones at each level of all heat island corridors at the same level, which constitutes the dataset of the average surface temperature.

[0038] The purpose of the above range normalization process to obtain the average surface temperature of each buffer zone after range normalization is to map all average surface temperatures to a specified range, such as [0, 1]), to eliminate the influence of different orders of magnitude. The range normalization formula can be:

[0039]

[0040] In the formula, represents the average surface temperature of the level buffer zone, represents the The average surface temperature of the hierarchical buffer zone and respectively represent the minimum and maximum values among the average surface temperatures of all hierarchical buffer zones of all heat island corridors at the current level.

[0041] Optionally, obtaining the temperature difference parameter characterizing the heat exchange intensity of each hierarchical buffer zone based on the average surface temperature dataset includes:

[0042] Based on the average surface temperature dataset, for heat island corridors of different levels, taking the average surface temperature and offset distance of different hierarchical buffer zones as the vertical and horizontal coordinates respectively, converting each hierarchical buffer zone into coordinate points including the average surface temperature and offset distance, and obtaining a temperature scatter dataset for reflecting the law of heat radiation attenuation of the heat island corridor to the surrounding environment;

[0043] According to the temperature scatter dataset, sorting the average surface temperature data corresponding to the buffer zones according to the buffer zone offset distance size, and obtaining the effective extreme values of the average surface temperature data therein;

[0044] According to the effective extreme values and the average surface temperature data of each hierarchical buffer zone, calculating the temperature difference parameters of each hierarchical buffer zone at the same level to characterize the heat exchange intensity of each hierarchical buffer zone.

[0045] So far, for each level of heat island corridor, a set of heat exchange intensity data corresponding to all hierarchical buffer zones can be obtained respectively, and further the heat exchange intensity range of each level of heat island corridor can be obtained.

[0046] Further, the step of sorting the average surface temperature data corresponding to the buffer zones according to the buffer zone offset distance size according to the temperature scatter dataset and obtaining the effective extreme values of the average surface temperature data therein includes:

[0047] For each level of heat island corridor, select the top k larger average surface temperatures among the average surface temperatures of all hierarchical buffer zones of the heat island corridor at the current level, and mark them as the extreme values to be verified;

[0048] For each extreme value to be verified, compare it with the average surface temperature of the adjacent hierarchical buffer zone respectively. If the extreme value to be verified is the maximum value among them, then take the extreme value to be verified as the effective extreme value to be confirmed;

[0049] Take the maximum value among the effective extreme values to be confirmed as the effective extreme value;

[0050] The formula for calculating the temperature difference parameters of each hierarchical buffer zone at the same level according to the effective extreme values and the average surface temperature data of each hierarchical buffer zone is:

[0051]

[0052] In the formula, represents the temperature difference parameter of the layer buffer zone, is the effective extreme value of the average surface temperature data, is the average surface temperature of the layer buffer zone, which can be the aforementioned , or the after range normalization.

[0053] The above can also be used to implement the visualization process display on the ArcGIS platform, specifically including:

[0054] In ArcGIS, through the "Select by Attributes" tool, filter and separate the average surface temperature of each layer buffer zone of each level of heat island corridors according to the corridor level field in the structured data table;

[0055] Through the "Feature to Point" tool, convert each layer buffer zone into coordinate points including corridor level, buffer zone layer serial number, and buffer zone offset distance attributes;

[0056] Through the "Join Attributes Table" tool, associate the average surface temperature with the buffer zone coordinate points of the corresponding layer;

[0057] Based on the buffer zone coordinate point data of each layer, through the "Summary Statistics" tool, obtain the temperature scatter dataset of the heat island corridor system corresponding to different levels, and the temperature scatter datasets of the heat island corridor systems of each level respectively include the average surface temperature data of all layer buffer zones at the corresponding level.

[0058] Optionally, calculating the heat transfer efficiency of each layer buffer zone of each level of heat island corridors according to the area of each layer buffer zone and the temperature difference parameter includes:

[0059] For each level of heat island corridors, use the following formula to calculate the heat transfer efficiency of each layer buffer zone:

[0060]

[0061] In the formula, is the heat transfer efficiency of the layer buffer zone, is the area of all layer buffer zones of all heat island corridors of the same level, is the temperature difference parameter of the layer buffer zone.

[0062] Optionally, the relationship curve between the buffer zone offset distance and the heat transfer efficiency can be expressed as:

[0063]

[0064] In the formula, represents the heat transfer efficiency of the buffer zone, is the intercept term, is the error term, is the offset distance of the buffer zone, is for the smoothing spline function applied, and here the thin plate regression spline basis function can be used to capture and the complex non-linear relationship between them, and through smoothing to predict or describe the change trend of

[0065] Optionally, based on the relationship curve between the buffer zone offset distance and the heat transfer efficiency, the inflection point of the heat transfer efficiency is extracted, and the corresponding buffer zone offset distance is determined as the spatial action width of the corresponding level of the heat island corridor, including: for each level of the heat island corridor,

[0066] By calculating the first derivative of the relationship curve between the buffer zone offset distance and the heat transfer efficiency, the rate extreme point of the change of the heat transfer efficiency with the buffer zone offset distance is found as the candidate inflection point of the heat transfer efficiency;

[0067] The statistical significance of the candidate inflection point of the heat transfer efficiency is verified by calculating the second derivative to determine the effective inflection point of the heat transfer efficiency;

[0068] The minimum value among the buffer zone offset distances corresponding to all effective inflection points of the heat transfer efficiency is used as the spatial action width of the current level of the heat island corridor.

[0069] Beneficial effects

[0070] By constructing multi-level buffer zones for the heat island corridor and statistically analyzing the corresponding temperature changes, the present invention realizes the simulation of the heat change law inside the urban heat island corridor. Furthermore, by calculating the temperature difference parameters of different-level buffer zones, the characteristics of the change of the heat exchange intensity with the buffer zone offset distance are quantified. Finally, through curve fitting and inflection point identification techniques, the spatial action width of each level of the heat island corridor is obtained, realizing the accurate quantification of the critical spatial scale of heat transfer in the heat island corridor, and being able to effectively reveal the interaction law between the internal thermal environment of the heat island corridor and the surrounding matrix.

[0071] The present invention effectively solves the problems of fuzzy boundaries and experience-dependent determination of the action range in traditional heat island corridor identification technologies. It can not only scientifically define the core action range of the heat island effect, provide a direct basis for the design of ventilation corridor width, the optimization of green space layout, and the control of impervious surfaces, but more importantly, it can provide a scientific basis and method support for the optimization and adjustment of land resources and the mitigation of heat island effect problems in the built-up areas of high-density cities globally, and has the value of popularization and application. Brief Description of the Drawings

[0072] Figure 1 The figure shows a schematic flow chart of a method for confirming the width of a heat island corridor in an urban heat island network according to an embodiment of the present invention;

[0073] Figure 2 The figure shows a schematic diagram of temperature classification after surface temperature inversion according to an embodiment of the present invention;

[0074] Figure 3 The figure shows a schematic diagram of the identification results of heat island source areas and heat island corridors according to an embodiment of the present invention;

[0075] Figure 4 The figure shows a schematic diagram of constructing a buffer zone for a heat island corridor according to an embodiment of the present invention;

[0076] Figure 5 The figure shows a schematic diagram of the distribution of temperature scatter data obtained for a primary heat island corridor according to an embodiment of the present invention;

[0077] Figure 6 The figure shows a schematic diagram of the distribution of temperature scatter data obtained for a secondary heat island corridor according to an embodiment of the present invention;

[0078] Figure 7 The figure shows a schematic diagram of the smooth curve fitting result of the heat transfer efficiency analyzed for a primary heat island corridor according to an embodiment of the present invention;

[0079] Figure 8 The figure shows a schematic diagram of the smooth curve fitting result of the heat transfer efficiency analyzed for a secondary heat island corridor according to an embodiment of the present invention;

[0080] Figure 9 The figure shows a visualization schematic diagram of a heat island network carrying spatial action width information according to an embodiment of the present invention. Detailed Embodiments

[0081] The following is further described in conjunction with the accompanying drawings and specific embodiments.

[0082] Embodiment 1

[0083] This embodiment introduces a method for confirming the width of a heat island corridor in an urban heat island network. Referring to Figure 1 as shown, the method includes:

[0084] Obtain the atmospheric parameter data, remote sensing image data, and resistance surface correlation data of the analysis area;

[0085] Based on the atmospheric parameter data and remote sensing image data, perform surface temperature inversion to obtain the surface temperature data of the analysis area;

[0086] Based on the surface temperature data and the resistance surface correlation data, construct a multi-level heat island corridor network for the analysis area;

[0087] For each heat island corridor of different levels in the multi-level heat island corridor network, construct multi-level buffer zones respectively, and statistically analyze the temperature data sets for each level of buffer zones at each level;

[0088] Based on the temperature data sets, obtain the temperature difference parameters characterizing the heat exchange intensity of each level of buffer zones;

[0089] According to the area of each level of buffer zones and the temperature difference parameters, calculate the heat transfer efficiency of each level of buffer zones of each level of heat island corridors;

[0090] For each level of heat island corridors, fit the relationship curve between the offset distance and the heat transfer efficiency of all levels of buffer zones to characterize the non-linear attenuation characteristics of the heat transfer efficiency with the expansion of the buffer zone offset distance;

[0091] For each level of heat island corridors, based on the relationship curve between the buffer zone offset distance and the heat transfer efficiency, extract the inflection point of the heat transfer efficiency, and determine the corresponding buffer zone offset distance as the spatial action width of the corresponding level of heat island corridors.

[0092] In this embodiment, by systematically analyzing the key parameters of the urban heat island corridor width and constructing multi-level buffer zones for the heat island corridor, the simulation of the heat change law of the heat island corridor and the quantification of the heat transfer efficiency of the heat island corridor are realized. Furthermore, according to the heat transfer efficiency, the width of the urban heat island corridor is determined, which can effectively reveal the interaction law between the internal heat environment of the heat island corridor and the surrounding matrix, solve the problems of low recognition efficiency and fuzzy recognition results boundaries in traditional heat island corridor recognition technologies, and provide a scientific basis for the mitigation of the urban heat island effect and the optimization of the heat environment.

[0093] Embodiment 2

[0094] Refer again to Figure 1 , on the basis of Embodiment 1, in this embodiment, a specific introduction of the technical solution is carried out with a urban area within the range of 30.10°N to 30.35°N and 120.05°E to 120.30°E as the analysis area.

[0095] I. Simulate the heat change law of the urban heat island corridor

[0096] In this part of the content, in this embodiment, the land surface temperature of the analysis area is first retrieved using remote sensing and other data, and then based on the retrieved land surface temperature, the identification and classification of heat island corridors are carried out. Next, multi-level buffer zones are constructed for each heat island corridor to simulate the heat transfer and change rules of urban heat island corridors and obtain the corresponding temperature datasets for subsequent quantitative analysis of heat exchange intensity and heat transfer efficiency. The specific contents are as follows.

[0097] 1.1) Retrieval of land surface temperature

[0098] The present invention uses the atmospheric correction method to retrieve the land surface temperature of the study area, and obtains the land surface temperature status of the study scope according to the retrieval results, specifically including:

[0099] Acquisition and preprocessing of multi-source data: In this embodiment, the Landsat-9 remote sensing image on August 5, 2022 covering the analysis area is adopted, and the atmospheric correction parameters are set, where the atmospheric transmittance is obtained by simulating with the MODTRAN model, and the land surface emissivity is calculated by classification based on the NDVI threshold method; the calibration constant of the Landsat-9 thermal infrared band is , ;

[0100] According to the thermal infrared radiation values of each temperature grid in the remote sensing image data, as well as the surface emissivity, atmospheric radiation intensity, and atmospheric transmittance of the thermal infrared band in the atmospheric parameters, the blackbody radiation brightness is calculated, and the formula is:

[0101]

[0102] According to the blackbody radiation brightness and the calibration constant of the thermal infrared band, the land surface temperature of each temperature grid is calculated, and the formula is:

[0103]

[0104] In the formula, represents the blackbody radiation brightness, represents the thermal infrared radiation value of the temperature grid, represents the atmospheric transmittance of the thermal infrared band, represents the surface emissivity, represents the upward atmospheric radiation intensity, represents the downward atmospheric radiation intensity, represents the land surface temperature of the temperature grid.

[0105] In order to more clearly express the spatial pattern of the urban thermal environment, this embodiment uses the relative land surface temperature to characterize the contribution value of different regions to the overall environment. That is, the relative land surface temperature of each temperature grid is calculated according to the land surface temperature of each temperature grid, and the formula is:

[0106]

[0107] In the formula: represents the relative surface temperature at temperature grid i, represents the actual surface temperature at temperature grid i obtained by inversion, represents the average value of the actual surface temperatures obtained by inverting all temperature grids within the analysis area.

[0108] 1.2) Construct a multi-level heat island corridor network and multi-level buffer zones for each heat island corridor

[0109] The purpose of this part is to identify the linear structure of the urban heat island network, mainly including: First, classify the relative surface temperature by the mean-standard deviation method, combine morphological spatial pattern analysis (MSPA) and landscape connectivity index to identify the urban heat island source areas, then select urban spatial pattern factors according to Spearman correlation analysis to generate a heat island resistance surface, and then apply circuit theory to construct the linear structure of the urban heat island network, identify the priority levels of the heat island corridors inside the urban heat island network, and then construct multi-level buffer zones for each heat island corridor to simulate the heat change law.

[0110] Referring to Table 1, in this embodiment, the relative surface temperature is divided into 5 levels by the mean standard deviation method, Figure 2 showing the basic situation after grading the visualization expression of the thermal environment in the analysis area on the ArcGIS platform.

[0111] Table 1 Classification criteria for urban thermal environment

[0112]

[0113] In this embodiment, combining morphological spatial pattern analysis (MSPA), landscape connectivity index and circuit theory, screening heat island source areas and generating a resistance surface, constructing a multi-level urban heat island corridor network, specifically including:

[0114] S121, establish a model database and perform data preprocessing; the data is divided into two categories, which are respectively applied to source area extraction and resistance surface construction.

[0115] The data applied to source area extraction includes: surface temperature data, which is used to obtain the surface temperature classification. Subsequently, the high-temperature and sub-high-temperature areas are merged into the urban heat island area, and the Core area in it is identified as the alternative heat island source area by using MSPA. Further calculate the landscape connectivity index of each alternative heat island source area, and select the patches with high connectivity as the final heat island source areas.

[0116] The data applied to the construction of the resistance surface are as follows: (1) traffic location data; (2) DEM elevation data of the study area; (3) NDVI data of the study area; (4) water system data of the study area; (5) building data of the study area; (6) land use data of the study area; (7) Sentinel-2 images from the European Space Agency.

[0117] S122. Using the above model database, the identification of the urban heat island source areas and the construction of the resistance surface are carried out respectively:

[0118] Based on the relative surface temperature data, landscape pattern analysis and landscape connectivity analysis are carried out, and patches with strong heat dissipation contribution and strong connectivity can be obtained, which are considered as heat island source areas in this embodiment;

[0119] Taking the relative surface temperature as the independent variable and the index system of the urban resistance surface as the dependent variable, Spearman correlation analysis is carried out. According to the results of the correlation analysis, factors with a correlation higher than 0.3 are selected to obtain the key influencing factors of the relative surface temperature, which are also the key influencing factors affecting heat diffusion and conduction. After determining the weights of these key influencing factors through principal component analysis, a raster calculation tool is used for weighted overlay to construct the urban heat island resistance surface. The finally obtained urban heat island resistance surface is a two-dimensional spatial data layer. In this layer, each pixel corresponds to a resistance value, which comprehensively considers the influence of multiple key factors. Areas with lower resistance values have lower resistance to air flow and efficient heat diffusion ability, and may be potential source areas or key influencing regions of the urban heat island effect.

[0120] S123. Extracting and grading the heat island network: Applying circuit theory to construct a heat environment network, the current threshold can be set to 15000 in the Linkage Mapper toolbox of ArcGIS to determine the importance of the corridors. Only the corridors with current values, that is, the flow through the corridors reaching or exceeding 15000, will be regarded as important heat island corridors. In this embodiment, the heat island corridors are divided into first-level heat island corridors and second-level heat island corridors according to the centrality calculation results of the centrality mapper module, as Figure 3 shown. The centrality mapper module is used to calculate the centrality of each corridor in the network. Centrality reflects the importance of the corridor in the network, including its connection with other corridors and its relative position in the network. Corridors with high centrality have more extensive connections and greater influence in the network. The corridor current value generated based on circuit theory quantifies the transmission priority of the heat island effect, and the higher its value, the more urgent it is to block the heat island expansion risk.

[0121] The above methods for extracting heat island source areas, resistance surfaces, and grading heat island corridors can all refer to the prior art and will not be elaborated here.

[0122] Based on the above analysis of the heat island corridor classification results of the linear structure of the urban heat island network in the region, this embodiment constructs symmetrical multi-level buffer zones on both sides of each heat island corridor according to the set single layer width and maximum offset threshold, with the center line of each heat island corridor as the offset reference line. Figure 4 As shown in the figure, in this embodiment, the gradient interval of each level of buffer zone, i.e., the width of a single layer, is 30 meters, and the maximum offset threshold is set to 1000 meters. Therefore, for each heat island corridor, 33 layers of buffer zones can be formed symmetrically on both sides thereof.

[0123] 1.3) Calculate the mean surface temperature for the same-level buffer zones of all heat island corridors at the same level, and obtain a dataset of mean surface temperature for each level of the heat island corridor buffer zones at each level. It should be noted that in this dataset, each level of the heat island corridor buffer zone has a mean surface temperature. In other words, the mean surface temperature for each level of the heat island corridor buffer zone is the average of the relative surface temperatures of all buffer zones at the same level for all heat island corridors at the same level.

[0124] To facilitate data processing and comparison in subsequent temperature difference parameter calculations, this embodiment performs the following processing when processing the surface temperature mean data set:

[0125] Calculate the mean surface temperature of all buffer zones at the same level for all heat island corridors at the same level;

[0126] Based on the surface temperature mean of each level buffer zone of all heat island corridors at the same level, the range normalization calculation is performed to obtain the surface temperature mean after range normalization of each level buffer zone of all heat island corridors at the same level, which constitutes the surface temperature mean dataset.

[0127] The above range normalization process obtains the mean surface temperature of each buffer zone after range normalization. The purpose is to map all surface temperature means to a specified range (e.g., [0, 1]) to eliminate the influence of different orders of magnitude. The range normalization formula can be:

[0128]

[0129] Where, Indicates the The mean surface temperature of the hierarchical buffer zone is selected as the mean relative surface temperature in this embodiment; Indicates the range after standardization The mean surface temperature of the hierarchical buffer zone, and They represent the minimum and maximum values of the mean surface temperature of all buffer zones of all heat island corridors at the current level.

[0130] The above process operations for visualization can be implemented using the ArcGIS platform, specifically including:

[0131] Set a fixed interval of 30 meters in ArcGIS, select the central axis of each heat island corridor as the offset reference line for the buffer zone, and generate multi-level buffer zones by expanding outward. The coordinate system is unified as WGS_1984_UTM_Zone_50N to ensure spatial consistency with the background data of the thermal environment;

[0132] Using the "Extract by Mask" tool, take the vector data of each buffer zone surface layer of the first-level and second-level heat island corridors as the mask boundary to partition and clip the relative surface temperature raster;

[0133] Calculate the mean temperature Mean and the coefficient of variation of temperature Std / Mean of each clipping result through the "Zonal Statistics" tool, and then the mean temperature and the coefficient of variation of temperature of all buffer zones at each level under the same level can be obtained; at this time, the dataset of the mean surface temperature can be obtained;

[0134] For subsequent calling and data processing, associate the zonal statistics results with the heat island corridor level, buffer zone level serial number, buffer zone offset distance, and the path of the surface temperature raster file, and save it as a structured data table. The buffer zone offset distance refers to the distance between the outer edge line of a single-layer buffer zone and the center line of the heat island corridor.

[0135] II. Quantify the heat transfer efficiency of each level of heat island corridor

[0136] In this part of the content, in this embodiment, first, based on the statistical results of the relative surface temperature means of the multi-level buffer zones obtained above, obtain the temperature difference parameters characterizing the heat exchange intensity of each level of buffer zone; then, according to the area of each level of buffer zone and the temperature difference parameters, calculate the heat transfer efficiency of each level of buffer zone of each level of heat island corridor.

[0137] 2.1) Calculation of temperature difference parameters

[0138] In this embodiment, based on the dataset of the mean surface temperature, obtain the temperature difference parameters characterizing the heat exchange intensity of each level of buffer zone, specifically including:

[0139] Based on the dataset of the mean surface temperature after range standardization processing, for different levels of heat island corridors, take the offset distance and the mean surface temperature of different levels of buffer zones as the abscissa and ordinate respectively, convert each level of buffer zone into coordinate points including the mean surface temperature and the offset distance, and obtain a temperature scatter dataset for reflecting the law of heat radiation attenuation of the heat island corridor to the surrounding environment;

[0140] According to the temperature scatter data set, sort the average surface temperature data corresponding to the buffer zones according to the buffer zone offset distance, and obtain the effective extreme values of the average surface temperature data among them.

[0141] According to the effective extreme values and the average surface temperature data of each level of buffer zones, calculate the temperature difference parameters of each level of buffer zones at the same level to characterize the heat exchange intensity of each level of buffer zones.

[0142] So far, for each level of heat island corridor, a set of heat exchange intensity data corresponding to all levels of buffer zones can be obtained respectively, and further the heat exchange intensity range of each level of heat island corridor can be obtained.

[0143] The acquisition of the above temperature scatter data set can also use the ArcGIS platform to realize the visualization process display, specifically including:

[0144] In ArcGIS, through the "Select by Attributes" tool, filter and separate the average surface temperature of each level of buffer zones of each level of heat island corridor according to the corridor level field in the structured data table.

[0145] Through the "Feature to Point" tool, convert each level of buffer zone into coordinate points including attributes such as corridor level, buffer zone level serial number, buffer zone offset distance, average surface temperature, temperature coefficient of variation, etc.

[0146] Through the "Join Attribute Table" tool, associate the average surface temperature with the buffer zone coordinate points of the corresponding level.

[0147] Based on the buffer zone coordinate point data of each level, through the "Summary Statistics" tool, obtain the heat island corridor system data set corresponding to different levels, that is, the temperature scatter data set. The heat island corridor system data sets of each level respectively include the average surface temperature data of all levels of buffer zones at the corresponding level.

[0148] The mapping relationship between the buffer zone offset distance and the average surface temperature can be visually constructed by using a spatial econometric model, specifically including: taking the buffer zone offset distance as the independent variable, that is, the X-axis variable, and the average surface temperature after range normalization as the dependent variable, that is, the Y-axis variable, and generating temperature scatter plots corresponding to two levels of heat island corridors respectively, and visually presenting as Figure 5 and Figure 6 , which characterize the differences in the heat radiation attenuation laws of different levels of heat island corridors to the surrounding environment. In the distance range of 0 - 1000m, the heat exchange peak value of the first-level corridor is 54.56 °C, and the heat exchange peak value of the second-level corridor is 50.87 °C.

[0149] According to the temperature scatter data sets of the first-level heat island corridor and the second-level heat island corridor obtained above, extract the buffer temperature extreme coordinate points for the first-level and second-level heat island corridors respectively, including:

[0150] For each level of the heat island corridor, select the top k surface temperature means with larger values among the mean surface temperatures of all hierarchical buffer zones of the current level of the heat island corridor, and mark them as the extreme values to be verified.

[0151] For each extreme value to be verified, compare it with the mean surface temperature of the adjacent hierarchical buffer zone respectively. If the extreme value to be verified is the maximum among them, then take this extreme value to be verified as the extreme value to be confirmed as valid.

[0152] Take the maximum value among the extreme values to be confirmed as valid as the valid extreme value.

[0153] The above can also be implemented for visualization using ArcGIS. Specifically:

[0154] In ArcGIS, right-click on the attribute layers of the first-level and second-level heat island corridors, and output the scatter plot attribute table as a CSV format file through "Export Data". Among them, the file fields include three columns: "Corridor Level", "Buffer Zone Offset Distance (m)", and "Range-normalized Temperature Mean".

[0155] Import the CSV file into Excel, and extract the extreme coordinate points of the buffer zone temperature for the first-level and second-level heat island corridors respectively: sort in ascending or descending order according to the "Buffer Zone Offset Distance", and use "Conditional Formatting - Project Selection Rules - Top 10 Items with the Largest Values" to mark the first 10 candidate points of the temperature extreme values within each level of the heat island corridor, that is, the extreme values to be verified. Manually check the temperature change trends of the buffer zone coordinate points before and after the marked points for a total of 3 points. When the mean temperature of a certain point is higher than the adjacent front and back coordinate points, it is regarded as an extreme value to be confirmed as valid. For example, in the first-level heat island corridor of the analysis area in this embodiment, the temperature reaches 54.56 °C at an offset distance of 330 m, and the temperatures of its front and back buffer zones are 54.51 °C, 54.53 °C, and 54.55 °C respectively, meeting the extreme value determination conditions. Finally, select the maximum value from the possible multiple extreme values to be confirmed as valid as the final and only valid extreme value to ensure that each level of the corridor corresponds to a unique reference value for calculating the temperature difference.

[0156] Referring to the research paradigm of urban cooling effect, take the temperature difference as the core evaluation index to characterize the intensity of hot air exchange within the buffer range on both sides of the heat island corridor. The larger it is, the greater the heat transfer intensity between the heat island corridor and the surrounding environment.

[0157] Since the temperature change before the peak reflects the disordered accumulation of heat, and the downstream temperature decreasing interval after the peak marks the phase transition process of the heat island effect from the "accumulative state" to the "dissipative state", which conforms to the core mechanism of the ecological sink absorbing heat in the "source-sink" landscape theory, that is, the peak represents the output limit of the heat source, and the subsequent temperature gradient directly quantifies the cooling intensity of the landscape elements. Therefore, the range value of the heat exchange intensity is obtained by the following method: for each hierarchical buffer zone at each level, calculate the difference between its uniquely representative extreme temperature and the average temperature of the downstream buffer zone (the interval showing a decreasing trend after the peak along the temperature scatter curve), and then statistically calculate the temperature difference results of all hierarchical buffer zones at all levels, and extract the minimum and maximum values among them as the heat exchange intensity range of the corridor at this level.

[0158] In this embodiment, according to the effective extreme value and the surface temperature average data of each hierarchical buffer zone, calculate the temperature difference parameter of each hierarchical buffer zone at the same level, and the formula is:

[0159]

[0160] In the formula, represents the temperature difference parameter of the th hierarchical buffer zone, is the effective extreme value of the surface temperature average data, is the th surface temperature average of the hierarchical buffer zone, and in this embodiment, it is the after range normalization.

[0161] Within the offset range of 0 - 1000m in the analysis area of this embodiment, the heat exchange intensity range of the first-level corridor is from 0.01 to 0.15, and the heat exchange intensity range of the second-level corridor is from 0.09 to 0.49. Finally, a structured data set can be formed, and each piece of data contains four core parameters of each buffer zone: corridor level, buffer zone offset distance, , .

[0162] Based on the above process, calculate the ratio of the heat exchange intensity in the heat island network to the area of each hierarchical buffer zone to obtain the heat transfer benefit per unit area of each hierarchical buffer zone. Theoretically, the heat transfer benefit should be calculated separately for each hierarchical buffer zone of each heat island corridor. However, considering that the lengths of each heat island corridor are different, the buffer zone areas are also different. But for the same-level heat island corridors, the lengths of the hierarchical buffer zones are the same. Therefore, in this embodiment, the sum of the areas of all the same-level hierarchical buffer zones of all heat island corridors is used to relatively calculate the heat transfer benefit, which does not affect the comparison results of the heat transfer benefits between different hierarchical buffer zones at the same level.

[0163] When calculating the area of buffer zones at each level, the ArcGIS platform can also be used to achieve visualization operations, including:

[0164] In the ArcGIS platform, successively select "Attribute Table → Add Field → Double Precision" to create a new field "Area_ha". Obtain the area data of each buffer zone through the "Calculate Geometry" toolset, and then obtain the sum of the areas of all buffer zones at each level under the same-level heat island corridors;

[0165] Use the "Join Attributes by Table" tool to associate the area of each level of buffer zone with the temperature difference parameter through the "Buffer Zone Offset" field;

[0166] Construct an evaluation model of the Heat Transfer Efficiency per Unit Area ( ), as a heat environment index, and link it with the spatial scale to reflect the contribution efficiency of the buffer zone per unit area to heat transfer. Among them, according to the area of each level of buffer zone and the temperature difference parameter, calculate the heat transfer efficiency of each level of buffer zone of each level of heat island corridor, including:

[0167] For each level of heat island corridor, use the following evaluation model of heat transfer efficiency to calculate the heat transfer efficiency of each level of buffer zone:

[0168]

[0169] In the formula, is the heat transfer efficiency of the -th level buffer zone, is the area of all -th level buffer zones of all heat island corridors of the same level, is the temperature difference parameter of the -th level buffer zone.

[0170] Finally, a structured data set corresponding to the first-level heat island corridor and the second-level heat island corridor can be generated, including three parameters: corridor level, buffer zone offset distance, and heat transfer efficiency, providing a data basis for subsequent inflection point analysis.

[0171] III. Obtain the inflection points of the heat transfer efficiency of each level of heat island corridor

[0172] In this part of the content, in this embodiment, for each level of heat island corridor, first fit the relationship curve between the offset distance and the heat transfer efficiency of all levels of buffer zones to characterize the non-linear attenuation characteristics of the heat transfer efficiency with the expansion of the buffer zone offset distance;

[0173] For each level of the heat island corridor, based on the relationship curve between the buffer zone offset distance and the heat transfer efficiency, the inflection point of the heat transfer efficiency is extracted, and the buffer zone offset distance corresponding to this inflection point can be considered as the spatial action width of the heat island corridor at the corresponding level.

[0174] 3.1) Fitting the relationship curve between the offset distance of the buffer zone and the heat transfer efficiency

[0175] In this embodiment, the buffer zone offset distance is used as the independent variable, and the heat transfer efficiency is used as the dependent variable. The relationship curve between the buffer zone offset distance and the heat transfer efficiency is fitted through a generalized additive model, and the overall significance of the model is evaluated using the F-test. Abnormal curves that do not pass the significance test are removed to ensure that only models with statistical explanatory power are retained, thus guaranteeing the reliability of the analysis of the spatial attenuation law. Finally, the attenuation law of the heat transfer efficiency of different levels of heat island corridors after fitting with a smooth curve is visually presented, as shown in Figure 7 and Figure 8 . The dashed lines in the figure are used to represent the confidence intervals of the fitted heat transfer efficiency.

[0176] Through the generalized additive model and the F-test, the non-linear attenuation characteristics of the heat transfer efficiency with respect to the buffer zone offset distance are analyzed, specifically including:

[0177] Clean and group the aforementioned structured data set, and call the dplyr package in R language to delete abnormal data to ensure data integrity;

[0178] Call the mgcv package in R language to perform model curve fitting. The formula is:

[0179]

[0180] In the formula, represents the heat transfer efficiency of the buffer zone, is the intercept term, is the error term, is the buffer zone offset distance, is the smooth spline function applied to . Here, a thin plate regression spline basis function can be used to capture the complex non-linear relationship between and , and to predict or describe the change trend of through smoothing.

[0181] Refer to Figure 7 and Figure 8, using Matplotlib to plot the fitting curve, under the buffer zones with different offset distances, all levels of heat island corridors show the law that the transmission efficiency first increases and then decreases. This indicates that as the offset distance of the buffer zone increases, the heat transmission efficiency of the heat island corridor begins to decline after reaching the maximum value. In addition, there are differences in the rate of change of efficiency among corridors at different levels, which is attributed to the different environmental matrices where the corridors are located.

[0182] 3.2) Extraction of the inflection point of heat transmission efficiency

[0183] Based on the relationship curve between the offset distance of the buffer zone and the heat transmission efficiency, extract the inflection point of the heat transmission efficiency, and determine the offset distance of the buffer zone corresponding to it as the spatial action width of the heat island corridor at the corresponding level, including: for each level of heat island corridor,

[0184] By calculating the first derivative of the relationship curve between the offset distance of the buffer zone and the heat transmission efficiency, find the extreme point of the rate of change of the heat transmission efficiency with the offset distance of the buffer zone, that is, the position where the curve slope changes most significantly, as the candidate inflection point of the heat transmission efficiency;

[0185] Verify the statistical significance of the candidate inflection point of the heat transmission efficiency through the calculation of the second derivative to determine the effective inflection point of the heat transmission efficiency;

[0186] Take the minimum value among the offset distances of the buffer zones corresponding to all effective inflection points of the heat transmission efficiency as the spatial action width of the heat island corridor at the current level.

[0187] By taking the derivative of the fitting function of the relationship curve, it is found that there are inflection points in the heat transmission efficiency curves of heat island corridors at each level. As shown in Table 2, where CI represents the confidence interval and P value is the P value, which is used to measure the probability that the observed effect size β, that is, the heat transmission efficiency, is caused by random error. For example, P < 0.001 indicates that the effect size is significant at the inflection point. When the width from the center line of the corridor reaches the corresponding value of the inflection point, significant changes occur in the internal components of the corridor, which is in line with the edge effect law of the corridor.

[0188] Table 2 Detection results of inflection points of heat island corridors

[0189]

[0190] Generally speaking, the finally selected inflection point of the heat transmission efficiency in this embodiment is actually the first-segment inflection point in the relationship curve. The determination of this first-segment inflection point needs to meet the following conditions:

[0191] (1) Before this point Remain relatively stable as the offset distance of the buffer zone increases;

[0192] (2) After this point A significant decrease occurs, that is, the attenuation rate exceeds a preset threshold, such as ≥10% / 100 m. The buffer zone offset distance corresponding to the first inflection point that meets the conditions can be interpreted as the spatial action width of the corresponding level of the heat island corridor, which represents the critical scale at which the heat transfer function transitions from the high-efficiency area to the low-efficiency area.

[0193] IV. Determine the spatial action width of each level of the heat island corridor

[0194] The above-mentioned inflection points of the heat transfer efficiency extracted for each level of the heat island corridor can be confirmed as the spatial action width of the corresponding level of the heat island corridor.

[0195] Figure 9 The visualized expression shown can be achieved through the ArcGIS platform, specifically including:

[0196] Load the vector of the center line of the heat island corridor in the analysis area, use the "Join Field" tool, and associate the inflection point offset distance field to the attribute table of the corresponding corridor line feature through the corridor ID. Call the "Buffer" tool and set the parameters as follows:

[0197] (1) Input feature: Center line of the heat island corridor

[0198] (2) Distance field: Select the associated "inflection point offset distance" field

[0199] (3) Side type: Both sides (FULL)

[0200] (4) End type: Round (ROUND)

[0201] (5) Dissolve type: Do not dissolve (ALL)

[0202] Thus, the heat island network analysis results of the analysis area can be obtained intuitively.

[0203] Example 3

[0204] Based on the same inventive concept as in Example 1 and Example 2, this example introduces a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the method for confirming the width of the heat island corridor of the urban heat island network as described in Example 1 or 2.

[0205] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0206] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one or more flows and / or blocks Figure 1 in one or more flows and / or blocks Figure 1 or in one or more blocks.

[0207] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means for implementing the functions specified in one or more flows and / or blocks Figure 1 in one or more flows and / or blocks Figure 1 or in one or more blocks.

[0208] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more flows and / or blocks Figure 1 in one or more flows and / or blocks Figure 1 or in one or more blocks.

[0209] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the present invention and the claims. All of these are within the protection scope of the present invention.

Claims

1. A method for confirming the width of a heat island corridor in an urban heat island network, characterized in that Including: Obtaining atmospheric parameter data, remote sensing image data, and resistance surface correlation data of the analysis area; Performing land surface temperature inversion based on the atmospheric parameter data and remote sensing image data to obtain land surface temperature data of the analysis area; Constructing a multi-level heat island corridor network of the analysis area based on the land surface temperature data and the resistance surface correlation data; For each heat island corridor of different levels in the multi-level heat island corridor network, constructing multi-level buffer zones respectively, and statistically obtaining a land surface temperature mean data set for each level of buffer zones at each level; Based on the land surface temperature mean data set, obtaining a temperature difference parameter characterizing the heat exchange intensity of each level of buffer zone; Calculating the heat transfer efficiency of each level of buffer zone of each level of heat island corridor according to the area of each level of buffer zone and the temperature difference parameter; For each level of heat island corridor, fitting a relationship curve between the offset distance and the heat transfer efficiency of all its levels of buffer zones to characterize the non-linear attenuation characteristics of the heat transfer efficiency with the expansion of the buffer zone offset distance; For each level of heat island corridor, based on the relationship curve between the buffer zone offset distance and the heat transfer efficiency, extracting the inflection point of the heat transfer efficiency, and determining the corresponding buffer zone offset distance as the spatial action width of the corresponding level of heat island corridor; The performing land surface temperature inversion based on the atmospheric parameter data and remote sensing image data to obtain land surface temperature data of the analysis area includes: Calculating the blackbody radiation brightness according to the thermal infrared radiation value of each temperature grid in the remote sensing image data, and the surface emissivity, atmospheric radiation intensity, and atmospheric transmittance in the thermal infrared band in the atmospheric parameters. The formula is: ； Calculating the land surface temperature of each temperature grid according to the blackbody radiation brightness and the calibration constant in the thermal infrared band. The formula is: ， In the formula, represents the blackbody radiation brightness, represents the thermal infrared radiation value of the temperature grid, represents the atmospheric transmittance in the thermal infrared band, represents the surface emissivity, represents the upward atmospheric radiation intensity, represents the downward atmospheric radiation intensity, represents the land surface temperature of the temperature grid, and represent the calibration constants in the thermal infrared band; Calculating the relative land surface temperature of each temperature grid according to the land surface temperature of each temperature grid. The formula is: ， In the formula: represents the relative surface temperature at temperature grid i, represents the actual surface temperature at temperature grid i obtained by inversion, represents the average value of the actual surface temperatures obtained by inversion of all temperature grids in the analysis area.

2. The method according to claim 1, characterized in that, The constructing a multi-level heat island corridor network of the analysis area based on the land surface temperature data and the resistance surface correlation data includes: Classifying the land surface temperature of all temperature grids by the mean standard deviation classification method; Based on the land surface temperature classification result, combining the MSPA model and the landscape connectivity index to determine the heat island source area of the analysis area; and, based on the land surface temperature data and the resistance surface correlation data, analyzing and obtaining the heat island resistance surface of the analysis area; According to the heat island source area and the heat island resistance surface, applying circuit theory to construct a heat environment network of the analysis area, obtaining the heat island corridor importance classification result through the centrality mapper module in the Linkage Mapper toolbox of ArcGIS, and classifying the heat island corridors into first-level heat island corridors and second-level heat island corridors according to their centrality in the heat environment network.

3. The method according to claim 1, wherein The corresponding to each heat island corridor of different levels in the multi-level heat island corridor network, constructing multi-level buffer zones respectively, and statistically obtaining a land surface temperature mean data set for each level of buffer zones at each level includes: Constructing symmetric multi-level buffer zones on both sides of each heat island corridor with the center line of each heat island corridor as the offset reference line according to the set single-layer width and maximum offset threshold; For all buffer zones of the same level of all heat island corridors at the same level, the average surface temperature is statistically calculated to obtain a dataset of the average surface temperature of the buffer zones of each level of the heat island corridors at each level.

4. The method according to claim 3, characterized in that, The statistical calculation of the average surface temperature for all buffer zones of the same level of all heat island corridors at the same level to obtain a dataset of the average surface temperature of the buffer zones of each level of the heat island corridors at each level includes: Calculating the average surface temperature of all buffer zones of the same level of all heat island corridors at the same level; Based on the average surface temperature of the buffer zones of each level of all heat island corridors at the same level, range normalization calculation is performed to obtain the range-normalized average surface temperature of the buffer zones of each level of all heat island corridors at the same level, which constitutes the dataset of the average surface temperature.

5. The method according to claim 3 or 4, characterized in that, Based on the dataset of the average surface temperature, obtaining a temperature difference parameter characterizing the heat exchange intensity of each buffer zone includes: Based on the dataset of the average surface temperature, for heat island corridors of different levels, taking the average surface temperature and offset distance of different-level buffer zones as the vertical and horizontal coordinates respectively, converting each buffer zone into coordinate points including the average surface temperature and offset distance, and obtaining a temperature scatter dataset for reflecting the law of heat radiation attenuation of the heat island corridor to the surrounding environment; According to the temperature scatter dataset, sorting the average surface temperature data corresponding to the buffer zones according to the buffer zone offset distance, and obtaining the effective extreme values of the average surface temperature data; According to the effective extreme values and the average surface temperature data of each buffer zone, calculating the temperature difference parameter of each buffer zone at the same level to characterize the heat exchange intensity of each buffer zone.

6. The method according to claim 5, characterized in that, The sorting of the average surface temperature data corresponding to the buffer zones according to the buffer zone offset distance according to the temperature scatter dataset to obtain the effective extreme values of the average surface temperature data includes: For each level of heat island corridors, selecting the top k larger average surface temperatures among the average surface temperatures of all buffer zones of the current level of heat island corridors, and marking them as the extreme values to be verified; For each extreme value to be verified, comparing it with the average surface temperature of the adjacent buffer zone. If the extreme value to be verified is the maximum among them, then taking this extreme value to be verified as the extreme value to be confirmed as valid; Taking the maximum value among the extreme values to be confirmed as valid as the valid extreme value; According to the valid extreme values and the average surface temperature data of each buffer zone, the formula for calculating the temperature difference parameter of each buffer zone at the same level is: ， In the formula, represents the temperature difference parameter of the layer buffer zone, is the effective extreme value of the average surface temperature data, is the average surface temperature of the layer buffer zone.

7. The method according to claim 6, characterized in that, Calculating the heat transfer efficiency of the buffer zones of each level of each heat island corridor according to the area of each buffer zone and the temperature difference parameter includes: For each level of heat island corridors, using the following formula to calculate the heat transfer efficiency of each buffer zone: ， In the formula, is the heat transfer efficiency of the layered buffer zone, is the area of all the layered buffer zones of all the heat island corridors of the same level, is the temperature difference parameter of the layered buffer zone.

8. The method according to claim 1 or 7, characterized in that, Based on the relationship curve between the buffer zone offset distance and the heat transfer efficiency, extracting the inflection point of the heat transfer efficiency and determining the buffer zone offset distance corresponding to it as the spatial action width of the heat island corridor of the corresponding level, including: for each level of heat island corridors, By calculating the first derivative of the relationship curve between the buffer zone offset distance and the heat transfer efficiency, find the rate extreme point of the change in heat transfer efficiency with the buffer zone offset distance, and use it as the candidate inflection point of heat transfer efficiency; Verify the statistical significance of the candidate inflection point of heat transfer efficiency through second derivative calculation to determine the effective inflection point of heat transfer efficiency; Take the minimum value among the buffer zone offset distances corresponding to all effective inflection points of heat transfer efficiency as the spatial action width of the current level heat island corridor.

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