CN117541114A

CN117541114A - Method for rapidly evaluating high spatial resolution thermal comfort of urban outdoor scene

Info

Publication number: CN117541114A
Application number: CN202311494159.9A
Authority: CN
Inventors: 任鹏; 钟雪; 赵立华
Original assignee: South China University of Technology SCUT
Current assignee: South China University of Technology SCUT
Priority date: 2023-11-10
Filing date: 2023-11-10
Publication date: 2024-02-09
Anticipated expiration: 2043-11-10
Also published as: CN117541114B

Abstract

The invention discloses a method for rapidly evaluating high spatial resolution thermal comfort of urban outdoor scenes, which relates to the field of outdoor thermal environment detection and comprises the following steps of: s1: pre-flight environmental investigation, parameter determination and path planning; s2: arranging a weather station and a near-surface real measurement point; s3: collecting position coordinates of a ground control point; s4: preprocessing thermal infrared images in batches, and establishing a three-dimensional point cloud model with bright temperature; s5: establishing a three-dimensional point cloud model with surface temperature and long-wave radiation; s6: preprocessing multispectral images in batches, and establishing a mapping relation between five channel digital quantized values and short wave radiation quantities; s7: establishing a three-dimensional point cloud model with short wave radiation; s8: mapping the point cloud data to a triangular surface, and establishing a real three-dimensional long-short wave radiation field; s9: sampling to obtain MRT of high spatial resolution of a scene; s10: and calculating and verifying the thermal comfort index of the scene with high spatial resolution. The invention reflects the geometric structure, surface thermal engineering and position parameters of the observed scene.

Description

Method for rapidly evaluating high spatial resolution thermal comfort of urban outdoor scene

Technical Field

The invention relates to the field of outdoor thermal environment detection, in particular to a method for rapidly evaluating high spatial resolution thermal comfort of urban outdoor scenes.

Background

In the context of global warming, rapid urban ization not only exacerbates the frequency and severity of heat waves, but also exacerbates urban heat island phenomena. In recent decades, heat exposure affecting urban residents has increased by a factor of two due to the gradual deterioration of urban heat environments. More evidence suggests that weather related hazards continue to increase, thereby presenting health risks. The non-ideal urban thermal environment limits the time and space for humans to perform outdoor activities in summer, further compromising their thermo-adaptive capacity and physiological resistance. Along with the development targets of healthy China, healthy cities, healthy communities and the like, more and more activities such as social activities, entertainment activities, rest activities and the like in the cities are carried out outdoors. Urban micro-scale living area groups, industrial parks, courts, valleys and the like are taken as basic units of urban spaces, and microclimate of the urban micro-scale living area groups is closely related to resident outdoor activities. The internal thermal environment condition and the thermal comfort level of the system directly influence the health condition, the behavior mode and the working efficiency of residents and are influenced by factors such as weather conditions, building trend and layout, small-scale underlying pad surface properties, infrastructure configuration patterns and the like. Compared with urban thermal environment regulation and control of a mesoscale and a local scale, the micro-scale level is more critical to the regulation of outdoor thermal comfort.

Currently, methods for obtaining outdoor thermal comfort on a microscopic scale include field measurement, reduced scale model research and numerical simulation. The on-site actual measurement is generally to set measuring points at the pedestrian height to acquire relevant meteorological parameters, and is the most direct and reliable method for researching the micro-scale outdoor thermal comfort. Although the on-site actual measurement can truly reflect the thermal environment characteristics and the thermal comfort status quo of the measurement site, the on-site actual measurement is limited by the distribution quantity of the measurement points, and the thermal comfort status of the high-heterogeneity outdoor space cannot be comprehensively evaluated. In addition, the reduced scale model research is carried out based on outdoor sites or climate wind tunnels, so that the urban complex real scene is difficult to accurately reproduce, and the evaluation accuracy of the outdoor thermal comfort is further affected. Although the wind-heat environment simulation software represented by FLUENT, PHOENICS, ENVI-met and the like can realize the efficient simulation research of the outdoor heat environment and the heat comfort degree of the urban complex scene, the theoretical model of numerical simulation is only established under ideal conditions because the influence factors of the indoor heat environment of the outdoor scene are complex and changeable, and the real problems of the outdoor heat environment and the heat comfort degree of the scene are difficult to reflect. Aiming at the method that the quality of the outdoor thermal comfort level is still limited to adopting wind-heat environment simulation and site observation based on measuring points in the analysis and evaluation at home and abroad at present, a path and an evaluation method for rapidly and real-timely observing the high-spatial resolution outdoor thermal comfort level of the urban complex scene are urgently needed to be explored.

The emerging low-altitude remote sensing technology represented by rotor unmanned aerial vehicles brings a trigger for the technology. In recent years, unmanned aerial vehicles are provided with various imaging instruments and probes to comprehensively observe urban microscale outdoor space, and the unmanned aerial vehicle has the technical characteristics of high convenience, high reliability, wide coverage range and the like. However, the current unmanned aerial vehicle low-altitude remote sensing technology is limited to shooting shallow applications such as radiation bright temperature of a natural underlying surface and a structure surface. The reason for this is that long wave radiation from the three-dimensional surface of the outdoor scene cannot be accurately obtained due to the lack of emissivity and temperature inversion mechanisms. In addition, for short wave radiation from three-dimensional surfaces that affects outdoor thermal comfort, no mature method currently exists to fully acquire this data based on unmanned aerial vehicles. In conclusion, the factors greatly limit the application of the unmanned aerial vehicle low-altitude remote sensing technology in the aspects of outdoor thermal comfort observation and evaluation.

Therefore, there is a need to provide a method for rapidly evaluating the high spatial resolution thermal comfort of urban outdoor scenes to solve the above-mentioned problems.

Disclosure of Invention

The invention aims to provide a method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene, which not only can truly restore a three-dimensional long-short wave radiation field so as to accurately reflect geometric structures, surface thermal engineering and position parameters of an observation scene, but also provides a novel observation path and evaluation method of the outdoor thermal comfort.

In order to achieve the above purpose, the invention provides a method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene, which comprises hardware equipment and an evaluation method, wherein the hardware equipment comprises an unmanned aerial vehicle, a double-cradle head, a double-sensor, a ground positioning control system, a cradle head task execution system, a wireless transmission system and a remote control system, the unmanned aerial vehicle is provided with the double-sensor based on the double-cradle head, the double-cradle head realizes synchronous multi-angle observation of the double-sensor based on a synchronous control program developed by an SDK, and a working route of the unmanned aerial vehicle and a photographing task of the double-sensor are connected with the remote control system through the wireless transmission system and are matched with the ground positioning control system, and the double-sensor comprises a thermal infrared camera and a multispectral camera;

the evaluation method specifically comprises the following steps:

s1: pre-flight environmental investigation, parameter determination and path planning;

s2: arranging weather stations and near-surface real stations meteorological parameter recorders;

s3: and (3) collecting position coordinates of a ground control point: determining the number and the placement positions of the target cloths according to the scene size, and synchronously acquiring the coordinates of the center positions of the target cloths by using an RTK GPS measuring instrument on the ground when the task executes the flight;

S4: preprocessing thermal infrared images in batches, and establishing a three-dimensional point cloud model with bright temperature;

s5: establishing a three-dimensional point cloud model with surface temperature and long-wave radiation;

s6: preprocessing multispectral images in batches, and establishing a mapping relation between five channel digital quantized values and short wave radiation quantities;

s7: establishing a three-dimensional point cloud model with short wave radiation;

s8: mapping the point cloud data to a triangular surface, and establishing a real three-dimensional long-short wave radiation field by combining radiation data actually measured by a weather station;

s9: sampling to obtain MRT of high spatial resolution of the scene and verifying based on meteorological data measured on the near surface;

s10: and calculating and verifying the thermal comfort index of the scene with high spatial resolution by combining the meteorological data actually measured on the near surface.

Preferably, in step S1, the location and area of the observed scene are determined, and the location is determined to be a no-fly zone or a limited-fly zone, and the surrounding environment of the scene is surveyed; determining lens parameters of dual sensors: including pixels in the height, width, and both directions, lens focal length, horizontal and vertical angles of view, image capture format: the thermal infrared image is in the format of R-JPEG, the multispectral image is in the format of TIFF, shooting angles and shooting intervals, and the course track of the unmanned aerial vehicle is determined, wherein the course track comprises a course and side lap ratio, a flight altitude and a speed.

Preferably, in step S2, a weather station is selected to be located at the open scene or at the roof of the higher floors of the scene, including a radiometer measuring direct radiation (DNI), short wave diffuse horizontal radiation (GHI) and long wave horizontal radiation (LHI) from the sky and the sun, an air temperature humidity and wind speed measuring instrument; and uniformly arranging a plurality of near-surface real-time points in the scene, and synchronously measuring the air temperature and humidity, the air speed and the black ball temperature at the pedestrian height as input and verification data of the high-spatial-resolution outdoor thermal comfort index.

In step S3, it is determined that at least one control point is disposed at each of the fields Jing Sijiao, and the control points need to be made of tinfoil, and are square in shape, and have a side length at least three times the coarsest spatial resolution of the multi-mode image.

Preferably, in step S4, the method specifically includes the following steps:

s41: adopting an Exiftool kit and a flyback kit to decrypt and acquire camera parameters and pixel-level brightness and coordinates of each thermal infrared image in batches;

s42: according to the high-frequency interval of scene brightness temperature distribution, uniform brightness Wen Biaoche is determined, and all thermal infrared images are subjected to batch processing to obtain color thermal infrared images after uniform brightness temperature scales of different scenes;

S43: three-dimensional point cloud reconstruction is carried out on the image with the unified bright temperature scale by using photogrammetry software, puncture is carried out on the image by using the actually measured ground control points, a three-dimensional point cloud model with accurate coordinates and color information RGB values is generated, and a point cloud file with the accurate coordinates and RGB values is output

S44: and processing the point cloud file output by the photogrammetry software based on the mapping relation between the RGB value of the point cloud and the bright temperature after unifying the bright temperature scale to obtain the point cloud file with accurate coordinates and bright temperature.

Preferably, the step S5 specifically includes the following steps:

s51: based on the point cloud file obtained in the step S44, point cloud data capable of representing three-dimensional surface temperature and long-wave radiation is obtained by inversion of a Planck law, an observation corresponding radiation transmission equation and a Boltzmann formula, and the calculated surface temperature and long-wave radiation data are used as two new columns to be sequentially attached to the point cloud file in an XYZ format;

s52: and (3) performing visualization processing on the point cloud data obtained in the step (S51) to obtain a point cloud model for accurately representing the pixel-level coordinates, the temperature and the long-wave radiation of the three-dimensional surface of the scene.

The file is visualized by using FME, a field 'x y zcolor_red color_green color_ blue Tsensor Ts Elw' is added to the first row of the file in an XYZ format based on FME WorkBench, and is input into FME Data Inspector, so that conversion parameters are ensured to be 'x y z color_red color_green color_ blue TsensorTs Elw', and a coordinate system is EPSG (point cloud model) 32649, and the three-dimensional surface pixel level coordinates, temperature and long-wave radiation of a scene can be accurately represented.

Preferably, in step S6, the secondary development package for image processing of the multispectral camera is used to process the original multispectral image with five channels, and specifically includes the following steps:

s61: extracting metadata in batches from the image header file, and correcting distortion of the lens by using the position, UTC time and camera parameters (camera exposure and gain);

s62: performing radiation correction, and batch reading downlink short wave radiation DLS acquired by each channel and reflectance undisposed_reflectance obtained after pixel level correction, wherein the downlink short wave radiation DLS and the reflectance undisposed_reflectance are multiplied to obtain short wave radiation quantity which is reflected by a target and enters a sensor;

s63: converting the digital quantized value of each channel pixel level into a corresponding pixel level shortwave radiation value;

s64: summarizing the short-wave radiation values of the five channels to obtain a short-wave radiation value of a three-dimensional surface pixel level complete wave band;

s65: and (3) establishing a multiple regression equation between the short wave radiation value of the complete wave band obtained in the step S64 and the pixel digital quantized values of the five corresponding channels.

Preferably, in step S7, a three-dimensional point cloud model with short-wave radiation is built based on the mapping relationship between the short-wave radiation value obtained in step S6 and the pixel digital quantized values of the five corresponding channels, and the method specifically includes the following steps:

S71: based on photogrammetry software Agisoft PhotoScan, an original multi-channel TIFF gray multi-spectral image is input to perform three-dimensional point cloud reconstruction, an aerial triangulation result is optimized based on control point puncturing, then dense point cloud data are constructed, a point cloud file with accurate coordinate information of a three-dimensional surface and five-channel digital quantized values is generated and output, the output format is TXT, and a space reference system is WGS84/UTM-49N (EPSG: 32649);

s72: processing the point cloud file output in the step S71 based on the mapping relation between the digital quantized value of each channel and the total short-wave radiation value established in the step S65 to obtain point cloud data with accurate coordinates and short-wave radiation;

s73: and (3) carrying out visualization processing on the point cloud data obtained in the step (S72) to obtain a point cloud model for accurately representing the pixel-level coordinates of the three-dimensional surface of the scene and the short-wave radiation.

The FME WorkBench is utilized to convert the point cloud data in the TXT format into the point cloud data in the XYZ format, then a field 'x y z DN_1DN_2DN_3DN_4DN_5Esw' is added to the first row of the file in the XYZ format, the modified file in the XYZ format is input into FME Data Inspector, the conversion parameter is ensured to be 'x y z DN_1DN_2DN_3DN_4DN_5Esw', the coordinate system is EPSG:32649, and then the point cloud model capable of accurately representing the pixel-level coordinates of the three-dimensional surface of a scene and short wave radiation can be visualized.

Preferably, in step S8, a real three-dimensional long-short wave radiation field is established, specifically comprising the following steps:

s81: based on the original multispectral image and the ground control point, generating a three-dimensional vector model which has accurate coordinates and is subjected to fine triangularization by using photogrammetry software, wherein the output format is OBJ;

s82: according to the principle of the nearest distance between the space point and the surface, mapping the point cloud data capable of representing accurate coordinates and the short-wave radiation onto the nearest triangular surface, and calculating the short-wave radiation quantity from the three-dimensional surface received at the height of a scene pedestrian;

s83: and establishing a real three-dimensional long-short wave radiation field by combining direct radiation, short wave diffusion horizontal radiation and long wave horizontal radiation from the sun and the sky, which are synchronously acquired by a scene weather station, and calculating the MRT of the scene pedestrian height.

Preferably, in step S9, the method includes the steps of sampling and acquiring MRT with high spatial resolution of the scene and verifying based on meteorological data actually measured on the near-surface, and specifically includes the following steps:

s91: based on multispectral three-dimensional point cloud data processed by a photogrammetry means, extracting ground point cloud data, and generating an independent ground model;

s92: and (3) dividing the ground model obtained in the step S91 into triangular surfaces with the same area size (0.5 square meter) by utilizing an FME workbench, and extracting the three-dimensional coordinates of the mass center of each triangular surface. Calculating MRT of the height of the pedestrian in the scene, and increasing the Z coordinate of the centroid of the surface triangular surface by 1.1 meters to represent the potential position of the gravity center of the pedestrian;

S93: based on a real three-dimensional long-short wave radiation field, isotropic sampling is carried out on the long-short wave radiation received at the height of an outdoor space human body through a IndexedView Sphere (IVS) method and a ray tracing technology, and the average radiation temperature MRT distribution condition with high spatial resolution is obtained.

S94: the MRT is calculated based on the near-surface measured air temperature, wind speed and black ball temperature as verification data of sampling the MRT in step S92.

Preferably, in step S10, outdoor thermal comfort indicators with high spatial resolution including SET, PET and UTCI are calculated and obtained by spatially sampled MRT and in-situ measured meteorological parameters including air temperature, relative humidity and wind speed. And verifying the outdoor thermal comfort index obtained by sampling based on the outdoor thermal comfort index calculated by the meteorological data measured on the near surface.

The visualization method further comprises the steps of displaying and clicking and reading a three-dimensional color point cloud model attached with geographic and thermal information, and obtaining accurate coordinate information and thermal information of pixel level; the verification method comprises the step of judging the applicable precision of the method based on the absolute difference value between 8 verification point sampling values and calculated values and the Root Mean Square Error (RMSE).

Therefore, the method for rapidly evaluating the high spatial resolution thermal comfort of the urban outdoor scene can truly restore the three-dimensional long-short wave radiation field, so that the geometric structure, the surface thermal engineering and the position parameters of the observation scene are accurately reflected, and a novel observation path and evaluation method are provided for the outdoor thermal comfort.

The technical scheme of the invention is further described in detail through the drawings and the embodiments.

Drawings

FIG. 1 is a workflow diagram of the present invention;

FIG. 2 is a schematic illustration of an orthographic image, near-surface real-world measurement point and a device for use in accordance with an embodiment of the present invention;

FIG. 3 is a three-dimensional geometric model and a three-dimensional model capable of characterizing long and short wave radiation of an embodiment of the present invention;

FIG. 4 is a schematic illustration of spatially sampled average radiation temperature MRT at pedestrian height in accordance with an embodiment of the present invention;

FIG. 5 is a schematic illustration of the results of MRT verification of the average radiation temperature sampled at pedestrian height in accordance with an embodiment of the invention;

FIG. 6 is a schematic illustration of an outdoor thermal comfort index calculated at pedestrian height in accordance with an embodiment of the invention;

fig. 7 is a schematic diagram of an outdoor thermal comfort index verification result calculated at pedestrian height according to an embodiment of the present invention.

Detailed Description

The technical scheme of the invention is further described below through the attached drawings and the embodiments.

Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs.

As used herein, the word "comprising" or "comprises" and the like means that elements preceding the word encompass the elements recited after the word, and not exclude the possibility of also encompassing other elements. The terms "inner," "outer," "upper," "lower," and the like are used for convenience in describing and simplifying the description based on the orientation or positional relationship shown in the drawings, and do not denote or imply that the devices or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the invention, but the relative positional relationship may be changed when the absolute position of the object to be described is changed accordingly. In the present invention, unless explicitly specified and limited otherwise, the term "attached" and the like should be construed broadly, and may be, for example, fixedly attached, detachably attached, or integrally formed; can be directly connected or indirectly connected through an intermediate medium, and can be communicated with the inside of two elements or the interaction relationship of the two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.

Examples

As shown in fig. 1, the invention provides a method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene, which comprises hardware equipment and an evaluation method, wherein the hardware equipment comprises an unmanned aerial vehicle, a double-cradle head, a double-sensor, a ground positioning control system, a cradle head task execution system, a wireless transmission system and a remote control system, the unmanned aerial vehicle is based on the double-cradle head carrying double-sensor, the double-cradle head realizes synchronous multi-angle observation of the double-sensor based on a synchronous control program developed by an SDK, and a working route of the unmanned aerial vehicle and a photographing task of the double-sensor are connected with the remote control system through the wireless transmission system and are matched with the ground positioning control system, and the double-sensor comprises a thermal infrared camera and a multispectral camera; unmanned aerial vehicle cloud platform subassembly (including with the compatible two cloud platform subassemblies in Xinjiang of Xinjiang M300 RTK and mount Micasense Rededge-MX multispectral camera and with compatible X-Port standard load cloud platform of two cloud platforms and the collaborative control procedure of development), guarantee that the dual sensor of unmanned aerial vehicle carrying can carry out the multi-angle and observe in step.

The evaluation method specifically comprises the following steps:

s1: pre-flight environmental investigation, parameter determination and path planning; in step S1, determining the position and the area of an observation scene, judging that the ground is a no-fly zone or a limited-fly zone, and surveying the surrounding environment of the scene; determining lens parameters of dual sensors: including pixels in the height, width, and both directions, lens focal length, horizontal and vertical angles of view, image capture format: the thermal infrared image is in the format of R-JPEG, the multispectral image is in the format of TIFF, shooting angles and shooting intervals, and the course track of the unmanned aerial vehicle is determined, wherein the course track comprises a course and side lap ratio, a flight altitude and a speed.

S2: arranging weather stations and near-surface real stations meteorological parameter recorders; in step S2, a weather station is arranged at the open place of the scene or at the roof of the floor higher than the scene, including radiometers Long-and short-wave irradiance recorders for measuring direct radiation, short-wave diffuse horizontal radiation and Long-wave horizontal radiation from the sky and the sun, air temperature humidity and wind speed measuring instruments, and the measured data include direct radiation (DNI) and short-wave horizontal radiation (GHI, LHI) from the sky; and uniformly arranging a plurality of near-surface real-time points in the scene, synchronously measuring the air temperature and humidity, the wind speed and the black ball temperature at the pedestrian height, and verifying the calculation result of the outdoor thermal comfort index with high spatial resolution.

S3: and (3) collecting position coordinates of a ground control point: in consideration of the specificity of the thermal infrared image, special targets are required to be made into square cloth shapes by using tinfoil, and the side length is at least three times of the coarsest spatial resolution of the multi-mode image. The number and placement positions of the target cloths are determined according to the scene size, and at least one control point is determined to be arranged at each of the fields Jing Sijiao. When the task executes the flight, the ground synchronously uses the RTK GPS measuring instrument to collect the coordinates of the center position of the target cloth;

S4: preprocessing thermal infrared images in batches, and establishing a three-dimensional point cloud model with bright temperature; in step S4, the method specifically includes the following steps:

S5: establishing a three-dimensional point cloud model with surface temperature and long-wave radiation; the step S5 specifically includes the following steps:

S52: and (3) carrying out visualization processing on the point cloud data obtained in the step (S51), and obtaining a point cloud model accurately representing the pixel-level coordinates, the temperature and the long-wave radiation of the three-dimensional surface of the scene as shown in fig. 3.

The file is visualized by using FME, a field 'x y zcolor_red color_green color_ blue Tsensor Ts Elw' is added to the first row of the file in an XYZ format based on FME WorkBench, and is input into FME Data Inspector, so that conversion parameters are ensured to be 'x y z color_red color_green color_ blue Tsensor Ts Elw', and a coordinate system is EPSG (point cloud model) 32649, and the three-dimensional surface pixel level coordinates, temperature and long-wave radiation of a scene can be accurately represented.

S6: preprocessing multispectral images in batches, and establishing a mapping relation between five channel digital quantized values and short wave radiation quantities; in step S6, the secondary development package for image processing of the multispectral camera is used to process the original multispectral image with five channels, and specifically includes the following steps:

S7: establishing a three-dimensional point cloud model with short wave radiation; in step S7, based on the mapping relationship between the short-wave radiation value obtained in step S6 and the pixel digital quantized values of the five corresponding channels, a three-dimensional point cloud model with short-wave radiation is built, which specifically includes the following steps:

S8: mapping the point cloud data to a triangular surface, and establishing a real three-dimensional long-short wave radiation field by combining radiation data actually measured by a weather station; in step S8, the method specifically includes the following steps:

s81: based on the original multispectral image and the ground control point, generating a three-dimensional vector model which has accurate coordinates and is subjected to fine triangularization by using photogrammetry software Agisoft PhotoScan, wherein the output format is OBJ;

S9: sampling to obtain MRT of high spatial resolution of the scene and verifying based on meteorological data measured on the near surface; in step S9, the method specifically includes the following steps:

s93: based on a real three-dimensional long-short wave radiation field, isotropic sampling is carried out on the long-short wave radiation received at the height of an outdoor space human body through a IndexedView Sphere (IVS) method and a ray tracing technology, and the average radiation temperature MRT distribution condition with high spatial resolution is obtained, as shown in fig. 4. The IVS method and the ray tracing technology both treat the human body as a microsphere which uniformly emits rays in all directions, and the face hit by the rays is stored as a pointer for deducing the corresponding radiation information of the first face hit by the rays.

S94: the MRT is calculated based on the near-surface measured air temperature, wind speed and black ball temperature as verification data of sampling the MRT in step S92. Further verifying the accuracy of the sampled MRT, calculating the MRT under the forced convection condition by using the air temperature and humidity, the wind speed and the black ball temperature measured by the near surface, and taking the calculated value as a verification reference of the MRT sampling value, wherein the verification result is shown in figure 5.

S10: and calculating and verifying the thermal comfort index of the scene with high spatial resolution. In step S10, outdoor thermal comfort indexes with high spatial resolution are calculated and obtained by spatially sampled MRT and in-situ measured meteorological parameters including air temperature, relative humidity and wind speed, wherein (a) is SET, PET and UTCI, and (b) is PET, and (c) is UTCI, as shown in fig. 6. Finally, sampling by using near-surface actual measurement dataThe data are verified, namely the outdoor heat comfort index calculated by the method is comparedPET _sampled ，UTCI _sampled ) And an outdoor thermal comfort index (++f) calculated based on the near-surface measured meteorological parameters and the black ball temperature>PET _measured ，UTCI _measured ) As shown in fig. 7, (a) is SET, (b) is PET, and (c) is UTCI.

Example 1

As shown in fig. 2-7, with a Guangzhou Yu silver science and technology garden in an office park as an experimental object, the unmanned aerial vehicle is adopted to adopt the Dajiang longitude and latitude M300 RTK, a high-performance RTK module is built in, and a thousands of seeking service is started on the premise of unobstructed network to realize high-precision positioning. The maximum load of the aircraft after the aircraft is fully loaded with two batteries is 2.7kg, the longest endurance mileage is about 55min, and the working environment temperature is-20-50 ℃; the double cradle head is a Xinjiang double cradle head component compatible with the Xinjiang longitude and latitude M300 RTK; the thermal infrared camera selects FLIR Zenmose XT2 compatible with the Dajiang longitude and latitude M300 RTK, the focal length of the lens is 19 mm, the angle of view is 32 degrees by 26 degrees, the focal plane array is 640 by 512, and the thermal radiation response wave band range is 7.5-13.5 microns; the multispectral camera selects Micasense Rededge-MX, the focal length of the lens is 5.4 millimeters, the angle of view is 47.2 degrees and 35.4 degrees, the focal plane array is 1280X 960, the response wave band range is 0.4-0.9 micrometers, the multispectral camera is divided into 5 narrow wave bands (corresponding center wavelengths are 475, 560, 668, 717 and 840 nanometers respectively) in the range, and the multispectral camera is compatible with a double holder through a large-area X-Port standard load holder. The thermal infrared camera needs to be connected with a main holder (No. 1) in the double holder, and the multispectral camera and the X-Port standard load holder need to be connected with a secondary holder (No. 2) in the double holder.

After planning five-way routes (the five-way pitch angles are respectively 60 DEG for downward normal incidence angle, north direction, south direction, west direction and east direction) and photographing modes, the airplane adopts an automatic mode to simultaneously capture multispectral images and thermal infrared images. In order to ensure the stability of solar radiation and environmental radiation, the unmanned aerial vehicle is selected to fly in noon with stable weather, and the total time for collecting five-way data is about one hour; the fly height is kept at 100 meters, the speed is kept at 1.7 meters per second, and the overlapping rate of heading and sideways is 90%; the dual sensor captures images at 2.0 second intervals and the thermal infrared image output format is R-JPEG.

In the aspect of near-surface synchronous measurement, 8 measuring points are uniformly arranged in a research area, each measuring point is provided with a sensor (namely HOBO MX2302A, delta AP3203.2 and Delta TP 3276.2) for measuring air temperature and humidity, wind speed and black ball temperature, and the data acquisition and recording interval is uniformly set to be 30 seconds once. In addition, a weather station closer to the investigation region was selected, which was equipped with a short wave radiometer (Kipp & Zonen SOLYS2 and Kipp & Zonen CMP 3) and a long wave radiometer (Kipp & Zonen CGR 3) in the horizontal direction, measuring direct radiation, short wave diffuse horizontal radiation and long wave horizontal radiation from the sky and the sun, respectively, and the data acquisition and recording interval was once again 30 seconds.

The method comprises the following steps:

s1: acquiring 1407 Zhang Regong external images and 1469 multispectral images;

s2: the near-surface weather station and the real-world points acquired 145 sets of data in total over the time of flight, and the average of these data was used to calculate the high spatial resolution MRT and outdoor thermal comfort index.

S3: after the hand book of the Zhonghaida V60 GNSS RTK system is adopted to connect thousands of seeking, the geographical coordinate system is set as WGS84 according to the actual position and area of a measuring area in this case, the projection coordinate system is set as UTM-49N, then the center position of a target cloth is vertically aligned, when the hand book displays a fixed solution, the coordinates of the control point are saved, and 4 control point coordinates are acquired in total in consideration of the influence of high-rise signal shielding and clutter;

s4: based on Jupytenobook, invoking Exiftool kit and Flyr kit, decrypting and batch reading the bright temperature data, camera parameters and coordinates encrypted by the original R-JPEG color thermal infrared image, and the statistics result shows that 99.5% of bright temperature data is located at 35-75 ℃, so that unified bright Wen Biaoche is determined to be 35-75 ℃, batch processing is carried out on all thermal infrared images based on IRON palette stretching, and color thermal infrared images with unified temperature scales of different scenes and accurate camera parameters and coordinates are configured; then, the preprocessed image is imported into photogrammetry software ContextCapture to reconstruct three-dimensional point cloud, and an initialized aerial triangulation result shows that a total of 1395 images can be used for reconstruction; then importing the earth surface control point coordinates measured in the step S3, puncturing points on the characteristic images, optimizing aerial triangulation based on puncturing point results, and finally, re-projecting the images with the error of 1.04 pixels (19.8 cm); then, producing a three-dimensional point cloud model, outputting point cloud data with accurate coordinates and color information (namely RGB values), wherein the total number of the point clouds is 215074, the format is LAS, and the space reference system is WGS84/UTM-49N (EPSG: 32649); then, converting the LAS format file into an XYZ format file by utilizing an FME WorkBench, and ensuring that the conversion parameter is 'x y z color_red color_green color_blue', wherein the coordinate system is EPSG 32649; and finally, processing the point cloud file in the XYZ format based on the mapping relation between the RGB value of the point cloud and the bright temperature after unifying the bright temperature scale to obtain the point cloud file with accurate coordinates and bright temperature.

S5: and (3) processing the point cloud file which is obtained in the step (S4) and can accurately represent coordinates and bright temperature by adopting a Jupyternobook. Firstly, adopting the Planckian law (formula 1) to convert the brightness temperature received by a sensor into radiation brightness; then, based on a sensor observation corresponding radiation transmission equation (formula 2) and combining the acquisition of low-altitude atmosphere parameters, inverting to obtain the point cloud data of the three-dimensional surface temperature; and finally, calculating based on a Boltzmann formula (formula 3) to obtain point cloud data capable of representing the three-dimensional surface long wave radiation, and sequentially attaching the calculated surface temperature and the calculated long wave radiation data as two new columns to the point cloud file in an XYZ format. The processed data is visualized by using FME, a field 'x y zcolor_red color_green color_ blue Tsensor Ts Elw' is added to the first row of a file in an XYZ format based on FME WorkBench, and is input into FME Data Inspector, so that conversion parameters are ensured to be 'x y z color_red color_green color_ blue Tsensor Ts Elw', and a coordinate system is EPSG (point cloud model) 32649, and the point cloud model capable of accurately representing the pixel-level coordinates, temperature and long wave radiation of the three-dimensional surface of a scene can be obtained.

Wherein T is _sensor Is bright temperature data (with the unit of K), Is the observed radiance (in W.m ^-2 ·μm ^-1 ·sr ^-1 )，λ _e Is the effective wavelength of the thermal infrared camera (unit is μm, the effective wavelength of FLIR XT2 is 11.092 μm), c ₁ And c ₂ Is Planck coefficient, 1.191 ×10 respectively ⁸ W·m ^-2 ·sr ^-1 ·μm ^-4 ，14388μm·K。

Wherein T is _s Is the surface temperature (i.e. thermodynamic temperature, in K) of the observed target, B ^-1 Is the inverse of the planck equation,and τ _8～14 Respectively, the atmospheric uplink radiation between the ground of the observation scene and the sensor (the calculated value of the present case is 0.55 W.m ^-2 ·μm ^-1 ·sr ^-1 ) Atmospheric downstream radiation (calculated value in this case is 5.07 W.m ^-2 ·μm ^-1 ·sr ^-1 ) And the atmospheric transmittance (calculated value in this case is 0.94), ε _bb Is the emissivity of the wide channel of the observation target (which is uniformly set to 0.93 in the present case).

Where σ is the boltzmann coefficient (σ=5.67×10 ^-8 W·m ^-2 ·K ^-4 )，E _{lw_3D_surface} The amount of long wave radiation (in W.m ^-2 )。

S6: similarly, based on Jupyternotebook, the secondary development program package of image processing of the multispectral camera is utilized to process five independent multispectral images (TIFF format) with five channels, and then a mapping relation between the digital quantized values of the five channels and the short wave radiation quantity is established. Firstly, extracting metadata (such as position, UTC time, camera exposure, gain and the like) from an image header file in batches, and carrying out distortion correction on each lens; then performing radiation correction, and batch reading downlink short wave radiation (DLS) acquired by each channel and reflectance (undischarged_reflectance) corrected by pixel level, and multiplying the DLS and the reflectance to obtain short wave radiation quantity which is reflected by a target and enters a sensor, so as to convert a digital quantized value of the pixel level of each channel into a corresponding pixel level short wave radiation value; and summarizing the short-wave radiation values of the five channels to obtain a short-wave radiation value of a complete wave band of a three-dimensional surface pixel level, and establishing a multiple regression equation with the corresponding pixel digital quantized values of the five channels for later establishing a three-dimensional point cloud model with short-wave radiation.

S7: based on photogrammetry software AgisoftPhotoScan, inputting an original multi-channel TIFF gray multi-spectral image to perform three-dimensional point cloud reconstruction, automatically matching photos according to a structure of a motion technology, initializing an aerial triangulation result to show that 1458 images can be used for reconstruction, then puncturing the image through a Ground Control Point (GCP) measured by S3 to optimize the aerial triangulation result, obtaining a final re-projection error of 0.7 pixel (7.89 cm), constructing dense point cloud data through stereo matching, hole filling and the like, finally generating and outputting a point cloud file with accurate coordinates of a three-dimensional surface and five channel digital quantization values, wherein the output format is TXT, and a space reference system is WGS84/UTM-49N (EPSG: 32649); processing a TXT format point cloud file output by photographic measurement software based on the mapping relation between the digital quantized value of each channel and the total short wave radiation value established in the S6 to obtain point cloud data with accurate coordinates and short wave radiation, wherein the total number of the point clouds is 204809; the FME WorkBench is utilized to convert the point cloud data in the TXT format into the point cloud data in the XYZ format, then a field 'x y z DN_1DN_2DN_3DN_4DN_5Esw' is added to the first row of the file in the XYZ format, the modified file in the XYZ format is input into FME Data Inspector, the conversion parameter is ensured to be 'x y z DN_1DN_2DN_3DN_4DN_5Esw', the coordinate system is EPSG:32649, and then the point cloud model capable of accurately representing the pixel-level coordinates of the three-dimensional surface of a scene and short wave radiation can be visualized.

S8: based on the processing result of S7, the grid is continuously generated based on the multispectral point cloud data by using Agisoft PhotoScan, and then the three-dimensional vector model which has accurate coordinates and is subjected to fine triangulation is output, wherein the format is OBJ, and the number of the output triangular faces is 140382. According to the principle of the nearest distance between the space point and the surface, mapping the point cloud data capable of representing the accurate coordinates and the long-short wave radiation to the nearest triangular surface for calculating the long-short wave radiation quantity from the three-dimensional surface received at the height of the pedestrians in the scene; and establishing a real three-dimensional long-short wave radiation field by combining direct radiation, short wave diffusion horizontal radiation and long wave horizontal radiation from the sun and the sky, which are synchronously acquired by a scene weather station, and calculating the MRT of the scene pedestrian height.

S9: and (3) performing point cloud classification based on the processing result of S7, namely multispectral dense point cloud data, extracting ground point cloud data, generating grids, and outputting an independent ground model in an OBJ format. Then, the ground model is divided into triangular faces with the same area size (0.5 square meter) by utilizing an FME workbench, and the three-dimensional coordinates of the mass center of each triangular face are extracted. Considering that it is the MRT at the scene pedestrian height that needs to be calculated, the Z coordinate of the surface triangle centroid is raised by 1.1 meters to represent the potential location of the pedestrian's center of gravity. In order to quantify the radiation reaching the different components of the human body from the three-dimensional surface or the whole sky surface, the Indexed View Sphere (IVS) method is adopted, i.e. the human body is regarded as a microsphere which uniformly emits rays in all directions, a pointer of the face hit by the rays for the first time is saved, and then the corresponding radiation information of the face is deduced. For the direct radiation received by the human body, a ray tracing technology is adopted to determine whether the human body is irradiated by solar beams, and the angle coefficient and the projection area factor respectively determine the proportion of the solar radiation received by the human body from each surface, wherein the projection area factor is calculated according to a human body standing model (formula 4). Therefore, the MRT at the pedestrian height of each point is obtained by sampling in the above manner and calculating the radiation components absorbed by the human body by combining the absorption coefficient of the human body surface to the long-short wave radiation (formula 5). To optimize the computation speed, the sampling process described above is done using GPU parallel computation. The processing mode is a personal computer (CPU: intel processor i7-12700F CPU@2.10GHz,12 core; GPU: nvidia GeForce RTX 3060Ti,8GB,4864 core), and in the study, each microsphere is set to emit 401 rays, and the whole process takes about 197 seconds.

f _p ＝3.67·10 ^-7 θ ³ -6.74·10 ^-5 θ ² +8.49 (4)·10 ^-4 θ+0.297

Wherein f _p Is the projected area factor; θ represents the solar altitude.

Wherein MRT is _sampled Is the MRT sampling value; alpha _sw And alpha _lw Absorption coefficients (alpha) of short wave radiation and long wave radiation respectively of the human body surface after wearing the garment _sw ＝0.5，α _lw ＝0.9)；δ _shadow Is a binary value indicating whether the human body receives direct radiation (delta _shadow =0 indicates that the human body is irradiated by solar beam, δ _shadow =1 indicates that the human body is under shadow); i is the sequence number of the hit surface by the ray; DNI is direct radiation; e (E) _{sw_sky_i} And E is _{lw_sky_i} Short wave radiation and long wave radiation from the sky surface are received by the human body based on angle coefficient calculation respectively; e (E) _{sw_3D_surface_i} And E is _{lw_3D_surface__i} Short wave and long wave radiation from the three-dimensional surface, respectively, that impinges on the human body.

Further verifying the accuracy of the sampled MRT, calculating the MRT under the forced convection condition by using the air temperature and humidity, the wind speed and the black ball temperature measured on the near surface (formula 6), and taking the calculated value as a verification reference of the MRT sampling value.

Wherein MRT is _calculated The MRT reference value is calculated based on the near-surface measurement result; t (T) _a Is air temperature, RH is relative humidity, V is wind speed, T _g The temperature of the black ball; epsilon _g Is the surface emissivity (epsilon) of the black ball _g ＝0.95)；D _g Is the diameter of a black sphere (d=50 mm).

S10: based on the sampling result of S9, in combination with meteorological parameters (including air temperature, relative humidity and wind speed) measured on the near-surface, outdoor thermal comfort indexes with high spatial resolution are calculated and obtained, including SET, PET and UTCI. And finally, verifying the outdoor thermal comfort index with high spatial resolution obtained by the method based on near-surface actual measurement data, namely comparing the outdoor thermal comfort index calculated by the method with the outdoor thermal comfort index calculated based on the near-surface actual measurement meteorological parameters and the black ball temperature. Based on the absolute difference value and the Root Mean Square Error (RMSE) between the sampling values and the calculated values of 8 verification points, the method can rapidly and accurately acquire the outdoor thermal comfort level with high spatial resolution in real time.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting it, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that: the technical scheme of the invention can be modified or replaced by the same, and the modified technical scheme cannot deviate from the spirit and scope of the technical scheme of the invention.

Claims

1. A method for rapidly evaluating high spatial resolution thermal comfort of urban outdoor scenes is characterized by comprising the following steps: the system comprises hardware equipment and an evaluation method, wherein the hardware equipment comprises an unmanned aerial vehicle, a double-holder, a double-sensor, a ground positioning control system, a holder task execution system, a wireless transmission system and a remote control system, the unmanned aerial vehicle is used for carrying the double-sensor based on the double-holder, the double-holder realizes synchronous multi-angle observation of the double-sensor based on a synchronous control program developed by an SDK, and a working route of the unmanned aerial vehicle and a photographing task of the double-sensor are connected with the remote control system through the wireless transmission system and are matched with the ground positioning control system, and the double-sensor comprises a thermal infrared camera and a multispectral camera;

The evaluation method specifically comprises the following steps:

2. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 1, wherein: in step S1, determining the position and the area of an observation scene, judging that the ground is a no-fly zone or a limited-fly zone, and surveying the surrounding environment of the scene; determining lens parameters of dual sensors: including pixels in the height, width, and both directions, lens focal length, horizontal and vertical angles of view, image capture format: the thermal infrared image is in the format of R-JPEG, the multispectral image is in the format of TIFF, shooting angles and shooting intervals, and the course track of the unmanned aerial vehicle is determined, wherein the course track comprises a course and side lap ratio, a flight altitude and a speed.

3. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 2, wherein: in step S2, a weather station is selected to be arranged at the open place of the scene or at the roof of the floor with higher scene, including a radiometer, an air temperature and humidity meter and a wind speed measuring instrument for measuring direct radiation, short wave diffusion horizontal radiation and long wave horizontal radiation from the sky and the sun, a plurality of near-surface real-world measuring points are uniformly arranged in the scene, and the air temperature and humidity, wind speed and black ball temperature at the pedestrian height are synchronously measured as input and verification data of the high-spatial-resolution outdoor thermal comfort index.

4. A method for rapidly assessing high spatial resolution thermal comfort of an urban outdoor scene according to claim 3, wherein: in step S4, the method specifically includes the following steps:

s43: carrying out three-dimensional point cloud reconstruction on the image with the unified bright temperature scale by using photogrammetry software, puncturing the image by using the actually measured ground control points, generating a three-dimensional point cloud model with accurate coordinates and color information RGB values, and outputting a point cloud file with the accurate coordinates and RGB values;

5. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 4, wherein: the step S5 specifically includes the following steps:

S51: based on the point cloud file obtained in the step S44, inversion is carried out by adopting the Planck law, an observation corresponding radiation transmission equation and a Boltzmann formula to obtain point cloud data capable of representing three-dimensional surface temperature and long-wave radiation;

6. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 5, wherein: in step S6, the secondary development package for image processing of the multispectral camera is used to process the original multispectral image with five channels, and specifically includes the following steps:

s61: extracting metadata in batches from the image header file, and correcting distortion of the lens by using the position, time and camera parameters;

7. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 6, wherein: in step S7, based on the mapping relationship between the short-wave radiation value obtained in step S6 and the pixel digital quantized values of the five corresponding channels, a three-dimensional point cloud model with short-wave radiation is built, which specifically includes the following steps:

s71: performing three-dimensional point cloud reconstruction based on an original multi-channel TIFF gray multi-spectral image by using a photogrammetry means, puncturing the image by using a ground control point which is actually measured, and generating and outputting a point cloud file with accurate coordinates of a three-dimensional surface and digital quantized values of five channels;

8. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 7, wherein: in step S8, a real three-dimensional long-short wave radiation field is established, which specifically includes the following steps:

9. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 8, wherein: in step S9, the high spatial resolution MRT is sampled and verified, specifically comprising the steps of:

S91: based on multispectral three-dimensional point cloud data processed by a photogrammetry means, extracting ground point cloud data, generating an independent ground model, dividing the ground model into triangular faces with the same size, and extracting three-dimensional coordinates of mass centers of each triangular face;

s92: for calculating MRT of the height of the pedestrian in the scene, the Z coordinate of the mass center of the surface triangular surface is increased by 1.1 meters, and the potential position of the gravity center of the pedestrian is represented;

s93: based on a real three-dimensional long-short wave radiation field, isotropic sampling is carried out on the short-wave radiation received at the height of an outdoor space human body by a IndexedView Sphere method and a ray tracing technology, so that the MRT distribution condition with high spatial resolution is obtained;

10. The method for rapidly evaluating high spatial resolution thermal comfort of an urban outdoor scene according to claim 9, wherein: in step S10, by spatially sampled MRT and on-site measured meteorological parameters, the meteorological parameters including air temperature, relative humidity and wind speed, outdoor thermal comfort indicators of high spatial resolution are calculated and obtained, the outdoor thermal comfort indicators including SET, PET and UTCI, and the outdoor thermal comfort indicators obtained by the sampling are verified based on the outdoor thermal comfort indicators calculated from the meteorological data measured on the near-surface.