Regional thermal environment analysis implementation method and device and storage medium

Abstract

The invention discloses a regional thermal environment analysis implementation method and device and a storage medium, and relates to the technical field of thermal environment analysis. According to the regional thermal environment analysis implementation method, the change trends corresponding to all adjacent positions of different land cover types in remote sensing data can be mined by lengthening the time dimension, and the weight parameter corresponding to each land cover is determined by combining all the change trends; the weight parameter can measure the influence degree of the earth surface coverage on the thermal environment of the target area. And finally, analyzing the thermal environment corresponding to the target area according to all the land surface coverage and the weight parameter corresponding to each land surface coverage. Therefore, the effective content of the remote sensing data can be fully mined, so that the accuracy and reliability of regional thermal environment analysis are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal environment analysis, and particularly relates to a method and device for realizing regional thermal environment analysis, and a storage medium. Background Art

[0002] With the acceleration of the urbanization process, the regional thermal environment problem has had a significant impact on human health, urban ecosystem and energy consumption. Regional thermal environment analysis refers to the comprehensive study of environmental data within a certain region to reveal the spatio-temporal distribution characteristics of the regional thermal environment and its influencing factors. Accurately analyzing the regional thermal environment is crucial for formulating effective urban planning and improvement strategies.

[0003] The main analyses of regional thermal environment analysis generally include spatio-temporal distribution characteristic analysis, thermal environment difference analysis of different functional areas (such as industrial areas, residential areas, green spaces), thermal environment influencing factor analysis, urban functional area influence analysis, etc. Practice has shown that there are still many deficiencies in the existing technology in terms of data sources and analysis methods, which limit the accuracy and reliability of regional thermal environment analysis. For example, currently, regional thermal environment analysis mainly relies on remote sensing data, such as Landsat satellite images, whose spatial resolution (for example, the 30-meter resolution of Landsat 8) is limited, and the effective data basis for providing thermal environment analysis is limited. In recent years, some studies have also tried to improve the accuracy of regional thermal environment analysis by multi-source data fusion, improving model algorithms or introducing new analysis frameworks. For example, studies based on the local climate zone (LCZ) framework can better reflect the impact of urban morphology on the thermal environment; while the SOLWEIG model provides ideas for thermal environment analysis in complex urban environments through high-spatial-resolution three-dimensional radiation calculations. However, the excavation of the effective content of data in the existing technology is still not sufficient, which limits the accuracy and reliability of regional thermal environment analysis. Summary of the Invention

[0004] The present invention provides a method and device for realizing regional thermal environment analysis, and a storage medium, which are used to improve the accuracy and reliability of regional thermal environment analysis.

[0005] To solve the above technical problems, in the first aspect of the present invention, a method for realizing regional thermal environment analysis is disclosed, and the method includes:

[0006] Obtaining remote sensing data corresponding to a target region at multiple preset time points;

[0007] For each of the preset time points, according to the remote sensing data corresponding to the preset time point, determining the boundary line between different types of surface coverages, where the types of surface coverages include building types, water body types and vegetation types; determining the area within a preset range around each boundary line as a boundary region;

[0008] For each of the preset time points, filter out the remote sensing spectral data corresponding to each demarcation area from the remote sensing data corresponding to the preset time point, and generate a demarcation area spectrogram corresponding to each demarcation area based on the remote sensing spectral data;

[0009] For the first surface cover and the second surface cover adjacent to each other in the target area, determine the change trend corresponding to the adjacent position of the first surface cover and the second surface cover according to the demarcation area spectrograms corresponding to the first surface cover and the second surface cover at all the preset time points, where the change trend includes an erosion trend, an expansion trend, a degradation trend, and a maintenance trend;

[0010] Determine the weight parameter corresponding to each surface cover according to the change trend corresponding to each surface cover at all adjacent positions, and analyze the thermal environment corresponding to the target area according to all the surface covers and the weight parameter corresponding to each surface cover.

[0011] As an optional implementation manner, in the first aspect of the present invention, the analyzing the thermal environment corresponding to the target area according to all the surface covers and the weight parameter corresponding to each surface cover includes:

[0012] Determine the building index corresponding to the target area according to all the building-type surface covers in the target area and the weight parameter corresponding to each building-type surface cover;

[0013] Determine the water body index corresponding to the target area according to all the water body-type surface covers in the target area and the weight parameter corresponding to each water body-type surface cover;

[0014] Determine the vegetation index corresponding to the target area according to all the vegetation-type surface covers in the target area and the weight parameter corresponding to each vegetation-type surface cover;

[0015] Analyze the thermal environment corresponding to the target area according to the building index, the water body index, and the vegetation index of the target area.

[0016] As an optional implementation manner, in the first aspect of the present invention, the analyzing the thermal environment corresponding to the target area according to the building index, the water body index, and the vegetation index of the target area includes:

[0017] Input the building index, the water body index, and the vegetation index of the target area into a pre-trained thermal environment analysis model to obtain the surface temperature distribution data output by the thermal environment analysis model, and the surface temperature distribution data is used to represent the surface temperature of each position in the target area.

[0018] As an alternative implementation, in the first aspect of the present invention, the obtaining of the remote sensing data corresponding to the target area at multiple preset time points includes:

[0019] For each preset time point, obtain the reference remote sensing data corresponding to the target area, where the reference remote sensing data includes the second-hand remote sensing data corresponding to the target area that can be directly obtained; according to the reference remote sensing data, determine the reference demarcation lines between different types of surface coverages; for each reference demarcation line, determine a plurality of reference points on the reference demarcation line according to the preset reference point selection rule, and calculate the curvature radius corresponding to each reference point on the reference demarcation line;

[0020] For each preset time point, control the remote sensing detection device to sample along the reference demarcation line to obtain the demarcation remote sensing data, where during the sampling process of the remote sensing detection device, a higher sampling density corresponds to a preset range around the reference point with a larger curvature radius;

[0021] For each preset time point, obtain the remote sensing data corresponding to the target area at the preset time point according to the reference remote sensing data and the demarcation remote sensing data.

[0022] As an alternative implementation, in the first aspect of the present invention, for each reference demarcation line, determining a plurality of reference points on the reference demarcation line according to the preset reference point selection rule and calculating the curvature radius corresponding to each reference point on the reference demarcation line includes:

[0023] For each reference demarcation line, select a point as a reference point at every fixed distance interval, and calculate the curvature radius corresponding to the reference demarcation line at the reference point.

[0024] As an alternative implementation, in the first aspect of the present invention, the controlling the remote sensing detection device to sample along the reference demarcation line includes:

[0025] Control the remote sensing detection device to move along the reference demarcation line. When the distance between the remote sensing detection device and the next reference point is less than or equal to the preset distance, control the sampling density of the remote sensing detection device to be adjusted to the sampling density corresponding to the next reference point, where the reference point with a larger curvature radius corresponds to a larger sampling density.

[0026] As an alternative implementation, in the first aspect of the present invention, the determining the change trend corresponding to the adjacent positions of the first surface coverage and the second surface coverage according to the demarcation area spectrogram corresponding to the first surface coverage and the second surface coverage at all the preset time points includes:

[0027] For each of the preset time points, according to the spectral map of the boundary region corresponding to the preset time point, determine the proportion of the band amplitudes corresponding to the first surface coverage and the second surface coverage respectively;

[0028] According to the proportion of the band amplitudes corresponding to the first surface coverage at all the preset time points, determine the change trend of the first amplitude proportion corresponding to the first surface coverage, where the change trend of the amplitude proportion is used to represent the change of the corresponding amplitude proportion with the change of the order of the preset time points; according to the proportion of the band amplitudes corresponding to the second surface coverage at all the preset time points, determine the change trend of the second amplitude proportion corresponding to the second surface coverage

[0029] According to the change trend of the first amplitude proportion corresponding to the first surface coverage, determine the change trend corresponding to the adjacent positions of the first surface coverage, and according to the change trend of the second amplitude proportion corresponding to the second surface coverage, determine the change trend corresponding to the adjacent positions of the second surface coverage.

[0030] A second aspect of the present invention discloses a device for realizing regional thermal environment analysis, and the device includes:

[0031] A data acquisition module, configured to acquire remote sensing data corresponding to a target area at multiple preset time points;

[0032] A boundary analysis module, configured to, for each of the preset time points, according to the remote sensing data corresponding to the preset time point, determine the boundary between different types of surface coverages, where the types of the surface coverages include building types, water body types, and vegetation types; determine the area within a preset range around each boundary as a boundary region;

[0033] A spectral map determination module, configured to, for each of the preset time points, screen out the remote sensing spectral data corresponding to each boundary region from the remote sensing data corresponding to the preset time point, and generate a spectral map of the boundary region corresponding to each boundary region based on the remote sensing spectral data;

[0034] A trend analysis module, configured to, for the adjacent first surface coverage and second surface coverage in the target area, according to the spectral maps of the boundary regions corresponding to the first surface coverage and the second surface coverage at all the preset time points, determine the change trend corresponding to the adjacent positions of the first surface coverage and the second surface coverage, where the change trend includes an erosion trend, an expansion trend, a degradation trend, and a maintenance trend;

[0035] A thermal environment analysis module, configured to determine the weight parameter corresponding to each surface coverage according to the change trend corresponding to all adjacent positions of each surface coverage, and analyze the thermal environment corresponding to the target area according to all the surface coverages and the weight parameters corresponding to each surface coverage.

[0036] As an alternative implementation manner, in the second aspect of the present invention, the specific operation mode of the thermal environment analysis module for analyzing the thermal environment corresponding to the target area according to all the surface coverages and the weight parameters corresponding to each surface coverage includes:

[0037] Determine the building index corresponding to the target area according to all the building-type surface coverages in the target area and the weight parameters corresponding to each building-type surface coverage;

[0038] Determine the water body index corresponding to the target area according to all the water body-type surface coverages in the target area and the weight parameters corresponding to each water body-type surface coverage;

[0039] Determine the vegetation index corresponding to the target area according to all the vegetation-type surface coverages in the target area and the weight parameters corresponding to each vegetation-type surface coverage;

[0040] Analyze the thermal environment corresponding to the target area according to the building index, the water body index and the vegetation index of the target area.

[0041] As an alternative implementation manner, in the second aspect of the present invention, the specific operation mode of the thermal environment analysis module for analyzing the thermal environment corresponding to the target area according to the building index, the water body index and the vegetation index of the target area includes:

[0042] Input the building index, the water body index and the vegetation index of the target area into a pre-trained thermal environment analysis model to obtain the surface temperature distribution data output by the thermal environment analysis model, and the surface temperature distribution data is used to represent the surface temperature of each position in the target area.

[0043] As an alternative implementation manner, in the second aspect of the present invention, the specific operation mode of the data acquisition module for acquiring the remote sensing data corresponding to the target area at multiple preset time points includes:

[0044] For each preset time point, acquire the reference remote sensing data corresponding to the target area, where the reference remote sensing data includes the second-hand remote sensing data corresponding to the target area that can be directly obtained; according to the reference remote sensing data, determine the reference demarcation lines between different types of surface coverages; for each reference demarcation line, determine a plurality of reference points on the reference demarcation line according to the preset reference point selection rule, and calculate the curvature radius corresponding to each reference point on the reference demarcation line;

[0045] For each preset time point, control the remote sensing detection device to sample along the reference demarcation line to obtain demarcation remote sensing data. During the sampling process of the remote sensing detection device, a higher sampling density corresponds to a preset range around a reference point with a larger radius of curvature.

[0046] For each preset time point, obtain the remote sensing data corresponding to the target area at this preset time point according to the reference remote sensing data and the decomposed remote sensing data.

[0047] As an alternative implementation, in the second aspect of the present invention, the specific operation method of the data acquisition module for determining multiple reference points on each reference demarcation line according to a preset reference point selection rule and calculating the radius of curvature corresponding to each reference point on this reference demarcation line includes:

[0048] For each reference demarcation line, select a point as a reference point at a fixed distance interval, and calculate the radius of curvature corresponding to this reference point on this reference demarcation line.

[0049] As an alternative implementation, in the second aspect of the present invention, the specific operation method of the data acquisition module for controlling the remote sensing detection device to sample along the reference demarcation line includes:

[0050] Control the remote sensing detection device to move along the reference demarcation line. When the distance between the remote sensing detection device and the next reference point is less than or equal to the preset distance, control the sampling density of the remote sensing detection device to be adjusted to the sampling density corresponding to the next reference point, where the larger the radius of curvature of the reference point, the greater the corresponding sampling density.

[0051] As an alternative implementation, in the second aspect of the present invention, the specific operation method of the trend analysis module for determining the change trend corresponding to the adjacent positions of the first land cover and the second land cover according to the demarcation area spectrograms corresponding to the first land cover and the second land cover at all the preset time points includes:

[0052] For each of the preset time points, determine the respective band amplitude ratios corresponding to the first land cover and the second land cover according to the demarcation area spectrogram corresponding to this preset time point.

[0053] According to the band amplitude ratios corresponding to the first land cover at all the preset time points, determine the first amplitude ratio change trend corresponding to the first land cover. The amplitude ratio change trend is used to represent the change in the corresponding amplitude ratio as the order of the preset time points changes; according to the band amplitude ratios corresponding to the second land cover at all the preset time points, determine the second amplitude ratio change trend corresponding to the second land cover.

[0054] Determine the change trend corresponding to the first surface cover at adjacent locations according to the change trend of the first amplitude ratio corresponding to the first surface cover, and determine the change trend corresponding to the second surface cover at adjacent locations according to the change trend of the second amplitude ratio corresponding to the second surface cover.

[0055] The third aspect of the present invention discloses another system for realizing regional thermal environment analysis, and the system includes:

[0056] A memory storing executable program code;

[0057] A processor coupled to the memory;

[0058] The processor calls the executable program code stored in the memory and executes the method for realizing regional thermal environment analysis disclosed in the first aspect of the present invention.

[0059] The fourth aspect of the present invention discloses a computer storage medium, and the computer storage medium stores computer instructions, which are used to execute the method for realizing regional thermal environment analysis disclosed in the first aspect of the present invention when called.

[0060] In the prior art, remote sensing data is directly used for regional thermal environment analysis, and the connotation of the data fails to be fully explored. The present invention can, by extending the time dimension, explore the change trends corresponding to different surface cover types in all adjacent locations in the remote sensing data, and determine the weight parameters corresponding to each surface cover by combining all the change trends. The weight parameter can measure the influence of the surface cover on the thermal environment of the target area. Finally, according to all the surface covers and the weight parameters corresponding to each surface cover, the thermal environment corresponding to the target area is analyzed. It can be seen that the present invention can fully explore the effective content of remote sensing data, thereby improving the accuracy and reliability of regional thermal environment analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings without creative efforts based on these drawings.

[0062] Figure 1 is a schematic flowchart of a method for realizing regional thermal environment analysis disclosed in an embodiment of the present invention;

[0063] Figure 2 is a schematic structural diagram of a device for realizing regional thermal environment analysis disclosed in an embodiment of the present invention;

[0064] Figure 3It is a schematic structural diagram of a system for realizing regional thermal environment analysis disclosed in an embodiment of the present invention. Detailed implementation manners

[0065] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0066] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or terminal including a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or terminals.

[0067] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0068] The present invention discloses a method, device and storage medium for realizing regional thermal environment analysis, which are used to improve the accuracy and reliability of regional thermal environment analysis.

[0069] Embodiment 1

[0070] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a method for realizing regional thermal environment analysis disclosed in an embodiment of the present invention. Among them, Figure 1 the described method for realizing regional thermal environment analysis can be integrated in a device for realizing regional thermal environment analysis, and the device for realizing regional thermal environment analysis can be integrated in a cloud server or a local server. As Figure 1 shown, the method for realizing regional thermal environment analysis may include the following operations:

[0071] Step 101, obtain remote sensing data corresponding to a target area at multiple preset time points.

[0072] In the embodiments of the present invention, remote sensing data refers to information about a region obtained through remote sensing technology. This data is collected from a distance by various sensors and is generally classified into the following categories:

[0073] (1) Classification by the range of the electromagnetic spectrum:

[0074] Optical remote sensing data: including panchromatic images, multispectral images, and hyperspectral images. Panchromatic images usually record only one band and have high spatial resolution; multispectral images record multiple bands, such as red, green, blue, and near-infrared bands, for identifying features such as vegetation and water bodies; hyperspectral images record hundreds of continuous bands, providing more detailed spectral information for material composition analysis.

[0075] Infrared remote sensing data: including thermal infrared images, which record the thermal radiation information of the earth's surface and are used for analyzing temperature distribution, vegetation health, etc.

[0076] Microwave remote sensing data: including passive microwave remote sensing and active microwave remote sensing. Passive microwave remote sensing receives the microwave radiation naturally emitted by the earth's surface and is used for monitoring the ocean, atmosphere, and surface humidity; active microwave remote sensing emits microwaves and receives the reflected signals, which is used to penetrate clouds and vegetation to obtain surface information.

[0077] (2) Classification by sensor type

[0078] Optical sensor data: Obtain data by detecting electromagnetic waves such as reflected or emitted visible light and infrared rays, and are widely used in fields such as vegetation monitoring and urban planning.

[0079] Radar sensor data: including synthetic aperture radar (SAR) and interferometric synthetic aperture radar (InSAR). SAR uses the phase difference of radar waves to obtain high-resolution images and is not limited by lighting and weather conditions; InSAR is used for surface deformation monitoring by comparing the phase differences of two SAR data.

[0080] Light detection and ranging (LiDAR) data: Generate a high-precision three-dimensional terrain model by emitting laser pulses and receiving the reflected signals, and are used for topographic mapping, forest structure analysis, etc.

[0081] Step 102: For each preset time point, determine the boundary between different types of land cover according to the remote sensing data corresponding to the preset time point; and determine the area within a preset range around each boundary as the boundary area.

[0082] In the embodiments of the present invention, the types of surface coverings may include building types, water body types, and vegetation types; building types correspond to high-density buildings and impervious surfaces, which are likely to trigger the heat island effect in local spaces; the lush vegetation indicated by the vegetation type effectively alleviates the surface temperature rise by means of transpiration and shading; the water bodies depicted by the water body type contribute to reducing the local surface temperature under the effects of evaporation and high heat capacity.

[0083] In the embodiments of the present invention, according to the remote sensing data corresponding to the preset time point, the boundaries between different types of surface coverings are determined. For image data, the boundaries are directly judged through image analysis; for spectral data, the analysis of the spectrum can be combined, for example, the spectral data is analyzed by a trained artificial intelligence model to determine the boundaries.

[0084] In the embodiments of the present invention, in order to fully explore the connotations of remote sensing data, a boundary area within a preset range around the boundary is determined at each time point. Through the variation of the remote sensing spectral data within the boundary area over time, the change trends corresponding to different types of surface coverings can be judged. Among them, the change trends may include erosion trends, expansion trends, degradation trends, and maintenance trends. The embodiments of the present invention find that the change trends measure the influence degree of a surface covering on the thermal environment of the target area. For example, building types correspond to high-density buildings and impervious surfaces, which are likely to trigger the heat island effect in local spaces. A surface covering of the building type with an expansion trend often represents that the buildings, population density, etc. within the surface covering are gradually approaching saturation and are in a growth state; while a surface covering of the building type with a degradation trend often represents that the buildings, population density, etc. within the surface covering are decreasing and are in a decreasing state. Although the areas and remote sensing spectral data of surface coverings in different change trends are not different, in fact, their influences on the regional thermal environment are different. Therefore, the present invention further explores the remote sensing data through the change trends, thereby improving the reliability of data analysis.

[0085] Step 103: For each preset time point, screen out the remote sensing spectral data corresponding to each boundary area from the remote sensing data corresponding to the preset time point, and generate a boundary area spectral map corresponding to each boundary area based on the remote sensing spectral data.

[0086] In the embodiments of the present invention, the remote sensing spectral data refers to the electromagnetic wave radiation information of the surface of the target area obtained through remote sensing technology within different spectral ranges. These data can be used to analyze the spectral characteristics of the surface covering, and further identify and classify the surface covering. In the embodiments of the present invention, it is necessary to analyze the spectral data of the boundary area to judge the respective change trends of the surface covering types on both sides of the boundary within the boundary area.

[0087] Step 104: For the adjacent first surface cover and second surface cover in the target area, determine the corresponding change trend at the adjacent position of the first surface cover and the second surface cover according to the boundary area spectrogram corresponding to the first surface cover and the second surface cover at all preset time points.

[0088] In the embodiment of the present invention, the change trend may include an erosion trend, an expansion trend, a degradation trend, and a maintenance trend; the change trend corresponding to different surface covers can be analyzed through the change of the boundary area spectrogram over time.

[0089] Step 105: Determine the weight parameter corresponding to each surface cover according to the change trend corresponding to each surface cover at all adjacent positions, and analyze the thermal environment corresponding to the target area according to all surface covers and the weight parameter corresponding to each surface cover.

[0090] In the embodiment of the present invention, the change trend in Step 104 can only measure the change trend of a certain surface cover at a boundary area. In actual situations, a surface cover is often adjacent to multiple other surface covers, and a surface cover may be in an expansion trend in a certain boundary area but in a degradation trend in another boundary area. Therefore, in Step 105, for each surface cover, it is also necessary to comprehensively consider the change trends corresponding to the surface cover at all adjacent positions to measure the impact of the surface cover on the thermal environment of the target area.

[0091] The main analysis of regional thermal environment analysis generally includes the analysis of spatio-temporal distribution characteristics, the analysis of thermal environment differences, the analysis of thermal environment influencing factors, the analysis of the impact of urban functional areas, etc. In the prior art, remote sensing data is directly used for regional thermal environment analysis, and the connotation of the data cannot be fully explored. The embodiment of the present invention can stretch the time dimension, explore the change trends corresponding to different surface cover types at all adjacent positions in the remote sensing data, and determine the weight parameter corresponding to each surface cover in combination with all the change trends. The weight parameter can measure the impact of the surface cover on the thermal environment of the target area. Finally, the thermal environment corresponding to the target area is analyzed according to all surface covers and the weight parameter corresponding to each surface cover. It can be seen that the embodiment of the present invention can fully explore the effective content of remote sensing data, thereby improving the accuracy and reliability of regional thermal environment analysis.

[0092] In an optional embodiment, the building type corresponds to high-density buildings and impervious surfaces, which are likely to cause the heat island effect in local spaces and can be specifically measured by a building index; the lush vegetation indicated by the vegetation type can effectively relieve the surface temperature rise through transpiration and shading effects and can be specifically measured by a vegetation index; the water body depicted by the water body type can help reduce the local surface temperature under the action of evaporation and high heat capacity and can be specifically measured by a water body index.

[0093] Optionally, the analysis of the thermal environment corresponding to the target area based on all surface coverages and the weight parameters corresponding to each surface coverage may include:

[0094] Determine the building index corresponding to the target area according to all building-type surface coverages in the target area and the weight parameters corresponding to each building-type surface coverage; specifically, the basic influence factor of the building-type surface coverage can be measured by the ratio of the reflectance of the band related to the building-type surface coverage in the remote sensing spectral data to the total spectral band reflectance. This basic influence factor is then combined with the weight parameter, such as by multiplication, to finally obtain the building index. The following water body index and vegetation index can also be determined based on the same principle.

[0095] Determine the water body index corresponding to the target area according to all water body-type surface coverages in the target area and the weight parameters corresponding to each water body-type surface coverage; determine the vegetation index corresponding to the target area according to all vegetation-type surface coverages in the target area and the weight parameters corresponding to each vegetation-type surface coverage; analyze the thermal environment corresponding to the target area based on the building index, water body index, and vegetation index of the target area. Thus, the thermal environment analysis can be more reliably achieved.

[0096] In an optional embodiment, there are many results of the thermal environment analysis, but the surface temperature data is a very direct and concise analysis result. For example, the surface temperature distribution is analyzed based on remote sensing data to achieve the prediction of the surface temperature. Therefore, the analysis of the thermal environment corresponding to the target area based on the building index, water body index, and vegetation index of the target area may include:

[0097] Input the building index, water body index, and vegetation index of the target area into a pre-trained thermal environment analysis model to obtain the surface temperature distribution data output by the thermal environment analysis model. The surface temperature distribution data is used to represent the surface temperature at each location in the target area.

[0098] In this optional embodiment, the thermal environment analysis model is a model trained based on the training dataset of the target area. It can analyze the surface temperature distribution of the target area according to the building index, water body index, and vegetation index on the target area. For example, the surface temperature distribution can be the average temperature of the building-type surface coverage, the average temperature of the vegetation-type surface coverage, and the average temperature of the water body-type coverage. It can be seen that this optional embodiment can determine the surface temperature distribution of the target area according to the building index, water body index, and vegetation index of the target area.

[0099] In an alternative embodiment, the thermal environment analysis of the target area relies on remote sensing data, such as Landsat satellite images, which have limited spatial resolution (e.g., 30-meter resolution of Landsat 8), and can provide a limited effective data basis for thermal environment analysis. That is to say, if the remote sensing data is from the existing remote sensing data of relevant institutions or personnel, it actually belongs to second-hand remote sensing data. Since second-hand remote sensing data is often not specifically obtained for the thermal environment analysis of the target area, the effective data related to the regional thermal environment analysis it contains is even less.

[0100] To solve the above problems, in this alternative embodiment, obtaining the remote sensing data corresponding to the target area at multiple preset time points may include:

[0101] For each preset time point, obtain the reference remote sensing data corresponding to the target area. The reference remote sensing data may include the second-hand remote sensing data directly obtained for the target area. According to the reference remote sensing data, determine the reference demarcation lines between different types of surface coverages. For each reference demarcation line, determine multiple reference points on the reference demarcation line according to the preset reference point selection rule, and calculate the curvature radius corresponding to each reference point on the reference demarcation line.

[0102] For each preset time point, control the remote sensing detection device to sample along the reference demarcation line to obtain the demarcation remote sensing data. Among them, during the sampling process of the remote sensing detection device, a higher sampling density corresponds to the preset range around the reference point with a larger curvature radius. The curvature radius is an important parameter for measuring the degree of curvature of the demarcation line. Generally, the more curved the demarcation line, the more complex its demarcation situation is. Correspondingly, the sampling points should be denser to sample more accurately. For a demarcation line with a lower degree of curvature, such as a straight demarcation line, this kind of demarcation line is relatively clear and the situation is simple. In order to reduce the workload, it corresponds to a lower sampling density.

[0103] For each preset time point, obtain the remote sensing data corresponding to the target area at this preset time point according to the reference remote sensing data and the demarcation remote sensing data.

[0104] In this alternative embodiment, in order to obtain more effective remote sensing data, a remote sensing detection device such as a low-altitude detector is used to detect remote sensing data specifically for thermal environment analysis. However, if the remote sensing detection device is used to detect the entire target area, the workload is also huge. Therefore, this alternative embodiment adopts a combination of second-hand remote sensing data and first-hand remote sensing data. For important demarcation lines, a remote sensing detection device is used to sample to obtain more accurate first-hand data. For other parts, second-hand remote sensing data is used, thus ensuring work efficiency on the basis of improving the effectiveness of remote sensing data.

[0105] Further, for the calculation of the curvature radius of the demarcation line, the demarcation line is a virtual line in the computer system, and there are countless points on it. It is impossible to calculate the curvature radius for each point on it.

[0106] To solve the above problems, in an alternative embodiment, for each reference demarcation line, a plurality of reference points are determined on the reference demarcation line according to a preset reference point selection rule, and the curvature radius corresponding to each reference point on the reference demarcation line is calculated, which may include:

[0107] For each reference demarcation line, a point is selected as a reference point at a fixed interval, and the curvature radius corresponding to the reference demarcation line at the reference point is calculated.

[0108] It can be seen that this alternative embodiment adopts the scheme of selecting a point as a reference point at a fixed interval and calculating the curvature radius corresponding to the reference demarcation line at the reference point to implement the calculation of the curvature radius of each reference point on the demarcation line.

[0109] In yet another alternative embodiment, controlling the remote sensing detection device to sample along the reference demarcation line may include:

[0110] Controlling the remote sensing detection device to move along the reference demarcation line. When the distance between the remote sensing detection device and the next reference point is less than or equal to a preset distance, the sampling density of the remote sensing detection device is adjusted to the sampling density corresponding to the next reference point, where the larger the curvature radius of the reference point, the larger the corresponding sampling density, so as to sample more accurate remote sensing data at the demarcation line with more complex conditions.

[0111] In yet another alternative embodiment, according to the demarcation area spectrograms corresponding to the first surface coverage and the second surface coverage at all preset time points, determining the change trend corresponding to the adjacent positions of the first surface coverage and the second surface coverage may include:

[0112] For each preset time point, according to the demarcation area spectrogram corresponding to the preset time point, determining the band amplitude ratios respectively corresponding to the first surface coverage and the second surface coverage; this alternative embodiment only selects the spectrograms within the demarcation area for analysis, and can most efficiently obtain the change information of different surface coverages at the corresponding adjacent positions.

[0113] According to the proportion of the band amplitudes corresponding to the first land cover at all preset time points, determine the first amplitude proportion change trend corresponding to the first land cover. The amplitude proportion change trend is used to represent the change of the corresponding amplitude proportion as the preset time points change in sequence; according to the proportion of the band amplitudes corresponding to the second land cover at all preset time points, determine the second amplitude proportion change trend corresponding to the second land cover. Different types of land covers correspond to different spectral bands, and the amplitudes of different bands, that is, the reflectivities, can reflect the proportion of the land cover corresponding to each band.

[0114] According to the first amplitude proportion change trend corresponding to the first land cover, determine the change trend corresponding to the adjacent positions of the first land cover. According to the second amplitude proportion change trend corresponding to the second land cover, determine the change trend corresponding to the adjacent positions of the second land cover.

[0115] In this optional embodiment, first determine the different bands corresponding to different land covers, and then analyze the change of the band amplitude proportion of each land cover over time, so as to analyze the change trend of the corresponding land cover.

[0116] Embodiment 2

[0117] Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a device for realizing regional thermal environment analysis disclosed in an embodiment of the present invention. As Figure 2 shown, the device for realizing regional thermal environment analysis may include:

[0118] A data acquisition module 201, configured to acquire remote sensing data corresponding to a target area at multiple preset time points;

[0119] A boundary analysis module 202, configured to, for each preset time point, determine the boundary line between different types of land covers according to the remote sensing data corresponding to the preset time point, where the types of land covers may include building types, water body types, and vegetation types; determine the area within a preset range around each boundary line as a boundary area;

[0120] A spectrogram determination module 203, configured to, for each preset time point, screen out the remote sensing spectral data corresponding to each boundary area from the remote sensing data corresponding to the preset time point, and generate a boundary area spectrogram corresponding to each boundary area based on the remote sensing spectral data;

[0121] A trend analysis module 204, configured to determine, for adjacent first and second surface coverages in a target area, a change trend corresponding to the adjacent position of the first and second surface coverages according to boundary area spectrograms corresponding to the first and second surface coverages at all preset time points, where the change trend may include an erosion trend, an expansion trend, a degradation trend, and a maintenance trend;

[0122] A thermal environment analysis module 205, configured to determine a weight parameter corresponding to each surface coverage according to the change trend corresponding to each surface coverage at all adjacent positions, and analyze the thermal environment corresponding to the target area according to all surface coverages and the weight parameters corresponding to each surface coverage.

[0123] In an optional embodiment, the specific operation mode for the thermal environment analysis module 205 to analyze the thermal environment corresponding to the target area according to all surface coverages and the weight parameters corresponding to each surface coverage may include:

[0124] Determine a building index corresponding to the target area according to all building-type surface coverages in the target area and the weight parameters corresponding to each building-type surface coverage;

[0125] Determine a water body index corresponding to the target area according to all water body-type surface coverages in the target area and the weight parameters corresponding to each water body-type surface coverage;

[0126] Determine a vegetation index corresponding to the target area according to all vegetation-type surface coverages in the target area and the weight parameters corresponding to each vegetation-type surface coverage;

[0127] Analyze the thermal environment corresponding to the target area according to the building index, water body index, and vegetation index of the target area.

[0128] In another optional embodiment, the specific operation mode for the thermal environment analysis module 205 to analyze the thermal environment corresponding to the target area according to the building index, water body index, and vegetation index of the target area may include:

[0129] Input the building index, water body index, and vegetation index of the target area into a pre-trained thermal environment analysis model to obtain surface temperature distribution data output by the thermal environment analysis model, where the surface temperature distribution data is used to represent the surface temperature of each position in the target area.

[0130] In yet another optional embodiment, the specific operation mode for the data acquisition module 201 to acquire remote sensing data corresponding to the target area at multiple preset time points may include:

[0131] For each preset time point, obtain the reference remote sensing data corresponding to the target area. The reference remote sensing data may include second-hand remote sensing data corresponding to the target area that can be directly obtained. According to the reference remote sensing data, determine the reference demarcation lines between different types of surface coverages. For each reference demarcation line, determine a plurality of reference points on the reference demarcation line according to the preset reference point selection rule, and calculate the radius of curvature corresponding to each reference point on the reference demarcation line.

[0132] For each preset time point, control the remote sensing detection device to sample along the reference demarcation line to obtain demarcation remote sensing data. Among them, during the sampling process of the remote sensing detection device, a higher sampling density corresponds to a preset range around the reference point with a larger radius of curvature.

[0133] For each preset time point, obtain the remote sensing data corresponding to the target area at the preset time point according to the reference remote sensing data and the demarcation remote sensing data.

[0134] In another optional embodiment, the specific operation mode for the data acquisition module 201 to determine a plurality of reference points on each reference demarcation line according to the preset reference point selection rule and calculate the radius of curvature corresponding to each reference point on the reference demarcation line may include:

[0135] For each reference demarcation line, select a point as a reference point at a fixed interval, and calculate the radius of curvature corresponding to the reference demarcation line at the reference point.

[0136] In another optional embodiment, the specific operation mode for the data acquisition module 201 to control the remote sensing detection device to sample along the reference demarcation line may include:

[0137] Control the remote sensing detection device to move along the reference demarcation line. When the distance between the remote sensing detection device and the next reference point is less than or equal to the preset distance, control the sampling density of the remote sensing detection device to be adjusted to the sampling density corresponding to the next reference point, where the larger the radius of curvature of the reference point, the larger the corresponding sampling density.

[0138] In another optional embodiment, the specific operation mode for the trend analysis module 204 to determine the change trend corresponding to the adjacent positions of the first surface coverage and the second surface coverage according to the demarcation area spectrogram corresponding to the first surface coverage and the second surface coverage at all preset time points may include:

[0139] For each preset time point, according to the demarcation area spectrogram corresponding to the preset time point, determine the proportion of the band amplitude corresponding to the first surface coverage and the second surface coverage respectively.

[0140] Determine the first amplitude ratio change trend corresponding to the first surface coverage according to the ratio of the band amplitudes corresponding to the first surface coverage at all preset time points. The amplitude ratio change trend is used to represent the change in the corresponding amplitude ratio as the order of the preset time points changes; determine the second amplitude ratio change trend corresponding to the second surface coverage according to the ratio of the band amplitudes corresponding to the second surface coverage at all preset time points.

[0141] Determine the change trend corresponding to the adjacent positions of the first surface coverage according to the first amplitude ratio change trend corresponding to the first surface coverage, and determine the change trend corresponding to the adjacent positions of the second surface coverage according to the second amplitude ratio change trend corresponding to the second surface coverage.

[0142] Embodiment III

[0143] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a system for realizing regional thermal environment analysis disclosed in an embodiment of the present invention. As Figure 3 shown, the system for realizing regional thermal environment analysis may include:

[0144] A memory 301 storing executable program code;

[0145] A processor 302 coupled to the memory 301;

[0146] The processor 302 invokes the executable program code stored in the memory 301 and executes the steps in the method for realizing regional thermal environment analysis described in Embodiment I of the present invention.

[0147] Embodiment IV

[0148] An embodiment of the present invention discloses a computer storage medium. The computer storage medium stores computer instructions, and when the computer instructions are invoked, they are used to execute the steps in the method for realizing regional thermal environment analysis described in Embodiment I of the present invention.

[0149] Embodiment V

[0150] An embodiment of the present invention discloses a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the method for realizing regional thermal environment analysis described in Embodiment I.

[0151] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules. That is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0152] Through the above specific descriptions of the embodiments, those skilled in the art can clearly understand that each implementation can be realized by means of software plus a necessary general hardware platform, and of course, it can also be realized by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium that can be used to carry or store data.

[0153] Finally, it should be noted that: The method and device for realizing regional thermal environment analysis and the storage medium disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than limiting them; Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for realizing regional thermal environment analysis, characterized in that, The method includes: Obtaining remote sensing data corresponding to a target area at multiple preset time points; For each of the preset time points, based on the remote sensing data corresponding to the preset time point, determining the demarcation lines between different types of surface coverages, where the types of surface coverages include building types, water body types, and vegetation types; determining the area within a preset range around each demarcation line as a demarcation area; For each of the preset time points, screening out the remote sensing spectral data corresponding to each demarcation area from the remote sensing data corresponding to the preset time point, and generating a demarcation area spectral map corresponding to each demarcation area based on the remote sensing spectral data; For the adjacent first surface coverage and second surface coverage in the target area, based on the demarcation area spectral maps corresponding to the first surface coverage and the second surface coverage at all the preset time points, determining the change trend corresponding to the adjacent part of the first surface coverage and the second surface coverage, where the change trend includes an erosion trend, an expansion trend, a degradation trend, and a maintenance trend; Based on the change trends corresponding to all adjacent parts of each surface coverage, determining the weight parameter corresponding to each surface coverage, and analyzing the thermal environment corresponding to the target area according to all the surface coverages and the weight parameters corresponding to each surface coverage.

2. The method for realizing regional thermal environment analysis according to claim 1, wherein The analyzing the thermal environment corresponding to the target area according to all the surface coverages and the weight parameters corresponding to each surface coverage includes: Determining the building index corresponding to the target area according to all the building-type surface coverages in the target area and the weight parameters corresponding to each building-type surface coverage; Determining the water body index corresponding to the target area according to all the water body-type surface coverages in the target area and the weight parameters corresponding to each water body-type surface coverage; Determining the vegetation index corresponding to the target area according to all the vegetation-type surface coverages in the target area and the weight parameters corresponding to each vegetation-type surface coverage; Analyzing the thermal environment corresponding to the target area according to the building index, the water body index, and the vegetation index of the target area.

3. The method for realizing regional thermal environment analysis according to claim 2, wherein The analyzing the thermal environment corresponding to the target area according to the building index, the water body index, and the vegetation index of the target area includes: Inputting the building index, the water body index, and the vegetation index of the target area into a pre-trained thermal environment analysis model to obtain the surface temperature distribution data output by the thermal environment analysis model, where the surface temperature distribution data is used to represent the surface temperature of each position in the target area.

4. The implementation method of regional thermal environment analysis according to claim 1, characterized in that The obtaining remote sensing data corresponding to a target area at multiple preset time points includes: For each preset time point, obtaining the reference remote sensing data corresponding to the target area, where the reference remote sensing data includes the second-hand remote sensing data corresponding to the target area that can be directly obtained; based on the reference remote sensing data, determining the reference demarcation lines between different types of surface coverages; for each reference demarcation line, determining multiple reference points on the reference demarcation line according to the preset reference point selection rule, and calculating the curvature radius corresponding to each reference point on the reference demarcation line; For each preset time point, control the remote sensing detection device to sample along the reference demarcation line to obtain demarcation remote sensing data. During the sampling process of the remote sensing detection device, a higher sampling density corresponds to a preset range around a reference point with a larger radius of curvature. For each preset time point, obtain the remote sensing data corresponding to the target area at this preset time point according to the reference remote sensing data and the demarcated remote sensing data.

5. The method for realizing regional thermal environment analysis according to claim 4, characterized in that, For each reference demarcation line, determine multiple reference points on this reference demarcation line according to the preset reference point selection rule, and calculate the radius of curvature corresponding to each reference point on this reference demarcation line, including: For each reference demarcation line, select a point as a reference point at a fixed distance interval, and calculate the radius of curvature corresponding to this reference demarcation line at this reference point.

6. The implementation method of regional thermal environment analysis according to claim 5, characterized in that, The control of the remote sensing detection device to sample along the reference demarcation line includes: Control the remote sensing detection device to move along the reference demarcation line. When the distance between the remote sensing detection device and the next reference point is less than or equal to the preset distance, control the sampling density of the remote sensing detection device to be adjusted to the sampling density corresponding to the next reference point. Among them, the larger the radius of curvature of the reference point, the larger the corresponding sampling density.

7. The method for realizing regional thermal environment analysis according to claim 1, characterized in that, The determination of the change trend corresponding to the adjacent positions of the first surface coverage and the second surface coverage according to the demarcation area spectrogram corresponding to the first surface coverage and the second surface coverage at all the preset time points includes: For each of the preset time points, determine the proportion of the band amplitude corresponding to the first surface coverage and the second surface coverage respectively according to the demarcation area spectrogram corresponding to this preset time point. According to the proportion of the band amplitude corresponding to the first surface coverage at all the preset time points, determine the change trend of the first amplitude proportion corresponding to the first surface coverage. The change trend of the amplitude proportion is used to represent the change of the corresponding amplitude proportion with the change of the preset time point sequence. According to the proportion of the band amplitude corresponding to the second surface coverage at all the preset time points, determine the change trend of the second amplitude proportion corresponding to the second surface coverage. According to the change trend of the first amplitude proportion corresponding to the first surface coverage, determine the change trend corresponding to the adjacent positions of the first surface coverage. According to the change trend of the second amplitude proportion corresponding to the second surface coverage, determine the change trend corresponding to the adjacent positions of the second surface coverage.

8. An apparatus for realizing regional thermal environment analysis, characterized in that The device includes: A data acquisition module for acquiring the remote sensing data corresponding to the target area at multiple preset time points. A boundary analysis module for, for each of the preset time points, determining the demarcation line between different types of surface coverages according to the remote sensing data corresponding to this preset time point, where the types of surface coverages include building types, water body types, and vegetation types; determining the area within a preset range around each demarcation line as the demarcation area. A spectrogram determination module for, for each of the preset time points, screening out the remote sensing spectrum data corresponding to each demarcation area from the remote sensing data corresponding to this preset time point, and generating a demarcation area spectrogram corresponding to each demarcation area based on the remote sensing spectrum data. A trend analysis module, configured to determine, for adjacent first and second surface coverages in a target area, a change trend corresponding to the adjacent position of the first and second surface coverages according to a boundary area spectrogram corresponding to the first and second surface coverages at all the preset time points, wherein the change trend includes an erosion trend, an expansion trend, a degradation trend, and a maintenance trend; A thermal environment analysis module, configured to determine a weight parameter corresponding to each surface coverage according to the change trend corresponding to each surface coverage at all adjacent positions, and analyze the thermal environment corresponding to the target area according to all the surface coverages and the weight parameter corresponding to each surface coverage.

9. A system for realizing regional thermal environment analysis, characterized in that, The system includes: a memory storing executable program codes; a processor coupled to the memory; the processor calling the executable program codes stored in the memory to execute the regional thermal environment analysis implementation method according to any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which are used to execute the regional thermal environment analysis implementation method according to any one of claims 1-7 when being called.

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