Urban heat island intensity and footprint measuring method and system, terminal and medium

Abstract

The invention discloses an urban heat island intensity and footprint measurement method and system, a terminal and a medium. The method comprises the following steps: estimating an initial urban heat island intensity value based on an initial reference temperature value, drawing an initial heat island intensity curve changing along urban and rural gradient, and identifying an urban cold and heat island effect; for the city with the heat island effect, error correction is carried out on the city heat island intensity value based on the ground temperature value of the critical circle or the initial heat island intensity value; estimating an urban heat island influence range of each urban built-up area patch, and identifying an area in which the urban heat island intensity value is greater than zero as an urban heat island footprint; and calculating the statistical index of the urban heat island based on the corrected urban heat island intensity value and the urban heat island footprint. According to the method, the generality and personality differences of different city temperature curves are considered, and objective unbiased estimation of the SUHI intensity and range under different geographical backgrounds is realized.

Description

Technical Field

[0001] The present invention relates to the field of urban heat island intensity and footprint measurement, and in particular to a method, system, terminal and medium for measuring urban heat island intensity and footprint based on an urban-rural temperature gradient change curve and an estimated urban heat island impact range. Background Art

[0002] Rapid urbanization and extensive human activities have greatly changed the characteristics of the Earth's atmosphere and surface, thus affecting the surface energy balance and urban thermal environment. The urban heat island effect, in which the temperature in the city center is significantly higher than that in the surrounding underdeveloped suburbs and rural areas, is one of the most significant manifestations and has become a focal issue worldwide. The urban heat island effect not only poses great challenges to the sustainable development of urban systems, but also poses a serious threat to human health. It has a significant negative impact on air quality and water quality, is closely related to increased energy consumption, rising heat mortality and frequent diseases, and greatly exacerbates the frequency of global warming and extreme high temperature events. In view of this, it is crucial to strengthen the understanding of the urban heat island effect, especially to accurately identify the urban heat island effect and measure its scale and spatial extent.

[0003] At present, there have been a large number of quantitative studies on the urban heat island effect based on the air temperature data of ground monitoring stations and the land surface temperature data (LST) inverted from satellite images. Among them, LST is currently the most important data source for evaluating the spatiotemporal pattern of urban heat island effects in different cities or regions. On the one hand, although LST is usually higher than air temperature and fluctuates more significantly, LST is more directly related to changes in the surface environment and the urbanization process. On the other hand, the ground monitoring stations are sparsely distributed and local climate conditions will greatly enhance the uncertainty of the observations, while the LST data acquired by satellites have the characteristics of spatial continuous coverage, high resolution and easy acquisition. In view of this, the present invention aims to propose a scheme for identifying the urban surface heat island effect (SUHI) based on LST data, measuring the intensity and impact range of the heat island, in order to provide strong support for urban planning, environmental management and climate change research.

[0004] When analyzing the spatiotemporal heterogeneity of SUHI, we face a major challenge: the diversity of SUHI definitions and the ambiguity of urban-rural boundaries. Due to the lack of a unified and widely recognized benchmark to define the reference temperature or area that is not affected by urban heat disturbance, different studies often show significant inconsistency in estimating the intensity and range of SUHI. Specifically, SUHI defined by the temperature difference between urban and suburban areas may show lower intensity and smaller range than SUHI defined by the temperature difference between urban and rural areas. Therefore, it is crucial to clearly define the non-urban area and determine a reasonable reference temperature standard to accurately identify the SUHI phenomenon and assess its impact. In addition, the diverse land use types and their thermal environmental effects in non-urban areas also cannot be ignored. The impact of the measurement of the intensity and scale of urban heat islands cannot be ignored. In particular, in some scenarios, such as cities in arid and semi-arid climate zones, there may be high-temperature heat sources such as deserts and bare land around them, resulting in lower temperatures inside the city relative to the surrounding environment, forming the so-called "urban cold island" phenomenon (SUCI). This phenomenon further highlights the complexity and challenge of accurately evaluating and comparing urban heat island effects in complex geographical environments. In summary, these factors together constitute a significant obstacle to the effective estimation and comparison of SUHI in different geographical contexts, emphasizing that future research needs to be committed to developing a standardized and adaptable methodological framework to overcome the limitations of existing definitions and measurements, thereby achieving a more comprehensive and accurate scientific understanding of the UHI phenomenon.

[0005] Previous studies on SUHI have mostly used the impervious surface coverage or a pre-set buffer zone that is equivalent to or slightly larger than the urban built-up area as the standard for demarcating the urban area and its thermal effect boundary. At the same time, the area where the local LST is significantly higher than the background temperature (such as the natural temperature in rural areas or the specified type in the local climate zone LCZ) is taken as the footprint range of SUHI. However, the inherent limitation of this method is that the temperature difference between the city and the adjacent non-urban area is significantly affected by the selection of the buffer zone radius and the setting of the background temperature reference value. Furthermore, many academic achievements have revealed that the SUHI footprint range can far exceed the geographical boundaries of the city, and its spatial extension can even reach more than three times the area of ​​the city itself. In view of this, ignoring the SUHI footprint range in SUHI intensity estimation and simply setting the analysis boundary based on a buffer zone that is equivalent to or slightly larger than the urban area often fails to fully capture the natural areas that are completely unaffected by the urban heat island effect, thereby weakening the reliability of the research results. At the same time, due to the diversity and complexity of the geographical environment, it is difficult to establish a universally applicable and standardized buffer zone delineation criterion, which further increases the inconsistency and uncertainty of SUHI intensity assessment results between different studies. Therefore, in order to comprehensively and accurately evaluate the SUHI phenomenon, a comprehensive approach must be adopted that not only focuses on the intensity measurement of SUHI, but also accurately defines its spatial footprint, providing a more solid scientific basis for the formulation of urban planning, environmental protection, and climate adaptation strategies.

[0006] The variation of SUHI intensity (or LST) along the urban-rural gradient has been shown to be mainly regulated by surface characteristics, especially land use type and distance from the city center. Specifically, SUHI intensity reaches a peak in the city center and then gradually decreases as it extends to the periphery of the city, until a sharp drop occurs at the urban-rural boundary, and then stabilizes. In view of this, the urban-rural gradient temperature curve has great potential in estimating SUHI intensity and footprint, and many studies have explored this in recent years. Zhou et al. (Zhou, D., Zhao, S., Zhang, L., Sun, G., & Liu, Y. (2015). The footprint of urbanheat island effect in China. Scientific Reports, 5(1), 1–11) created 12 buffer zones radiating outward from the city center to draw temperature curves, covering a spatial range of 7 times the actual urban area, and quantified the SUHI footprint as a concentrated and contiguous area with a temperature higher than the background temperature. However, the limitation of this method is that it assumes that the SUHI footprint must exceed the physical boundaries of the city, and there is a certain degree of subjectivity in the definition of the background temperature, which affects the accuracy of the estimation. Zhang et al. (Zhang, X., Friedl, MA, Schaaf, CB, Strahler, AH, & Schneider, A. (2004). The footprint of urban climates on vegetation phenology. Geophysical Research Letters, 31(12), L12209) and Yang et al. (Yang, K., Zhou, T., Wang, C., Wang, Z., Han, Q., & Tao, F. (2022). RSEDM: A New Rotational-Scan Exponential Decay Model for Extracting the Surface Urban Heat Island Footprint. Remote Sensing, 14(14), 3505) proposed a strategy to fit the temperature curve based on an exponential model and estimate the SUHI footprint. The strategy determines the SUHI footprint based on the distance corresponding to the 95% asymptotic value of the urban and rural temperature curve. However, the model only considers cities where the temperature curve shows a significant downward trend.

[0007] At present, there is still a lack of a method to effectively integrate urban and rural temperature change curves and SUHI estimation, taking into account the commonalities and individual differences of temperature curves in different cities, and achieving objective and unbiased estimation of SUHI intensity and range under different geographical backgrounds, thereby laying a solid theoretical foundation and data support for subsequent in-depth analysis of the formation mechanism, dynamic changes and environmental effects of SUHI. Summary of the invention

[0008] In view of the shortcomings of the prior art, the present invention provides a method, system, terminal and medium for measuring the intensity and footprint of urban heat islands. Based on the general definition of urban heat island intensity, the background temperature reference value is determined and the impact range of urban heat islands is estimated based on the critical points and critical circles of the initial heat island intensity curve along the urban-rural gradient, and finally the intensity and footprint of urban heat islands are measured. This method can measure the SUHI effect more objectively and accurately.

[0009] In the first aspect, a method for measuring the intensity and footprint of an urban heat island is provided, comprising the following steps:

[0010] S1: Estimate the initial urban heat island intensity value based on the initial reference temperature value, draw the initial heat island intensity curve along the urban-rural gradient, and identify the urban cold and heat island effect;

[0011] S2: For cities with heat island effect, error correction is performed on the urban heat island intensity value based on the ground temperature value of the critical circle or the initial heat island intensity value;

[0012] S3: Estimate the impact range of the urban heat island in each urban built-up area patch and identify the areas within it where the urban heat island intensity value is greater than zero as the urban heat island footprint;

[0013] S4: Calculate the UHI statistical indicators based on the corrected UHI intensity value and UHI footprint.

[0014] Furthermore, step S1 specifically includes:

[0015] S11: Calculate the initial reference temperature value LST using the average surface temperature of rural areas outside urban built-up areas, excluding mountains and water bodies r0 ;

[0016] S12: Establish multiple rings of equal-area buffer zones from the city center to the periphery;

[0017] S13: Use the surface temperature LST of each pixel and the initial reference temperature LST r0 The initial urban heat island intensity value of the pixel is calculated by the difference between Calculate the pixels within each buffer The median value of the group is used as the initial value of the heat island intensity in the buffer zone, and the initial heat island intensity curve along the urban-rural gradient is drawn;

[0018] S14: Determine whether a city has a heat island effect or a cold island effect based on the trend of the initial heat island intensity curve.

[0019] Furthermore, step S12 specifically includes:

[0020] Establish multiple equal-area buffer zones from the city center to the periphery, and set the area of ​​each buffer zone to the smaller value of S1 / A and S2 / B; S1 represents the built-up area of ​​the city, and S2 represents the urban area. In order to ensure sufficient sample size in the urban area and built-up area and avoid excessive calculation, the value range of A is [30,100], and the value range of B is [200,500]; for multi-center cities, the radius of the secondary center buffer zone is set to 1 / 2 of the radius of the primary center buffer zone;

[0021] Set the outermost radius of the buffer zone to C times the radius of the circle of equal area in the urban area or ensure that the number of buffer zones does not exceed B*5, so that the buffer zone can cover the entire urban area as much as possible without causing excessive calculation. The value range of C is [1.25,5].

[0022] Furthermore, step S14 specifically includes:

[0023] The peak, critical point and critical circle in the initial heat island intensity curve are dynamically identified by combining the piecewise linear regression method;

[0024] If the initial urban heat island intensity of the city center area (the central 1 / 4 area of ​​the urban built-up area) If the mean is greater than 0, the peak of the initial heat island intensity curve is within the urban area, and there is a significant downward trend after the peak (the slope of the piecewise linear regression fitting line is less than the set threshold), then it is determined that there is an urban heat island effect; conversely, if the initial urban heat island intensity in the central area of ​​the city is The mean is less than 0, and If the overall trend from the city center to the periphery is increasing, it is determined that the urban cold island effect occurs. Further, step S2 specifically includes:

[0025] For cities with heat island effect, the critical circle land surface temperature value LST is used. c or initial heat island intensity value Correct the initial reference temperature value and calculate the true urban heat island intensity value SUHII by the following formula:

[0026]

[0027] Where, LST represents the land surface temperature; Indicates the initial urban heat island intensity value, LST r0 Indicates the initial reference temperature value; The corrected reference temperature value is not restricted by the urban-rural dichotomy for the definition of urban and rural areas. The correction process can reduce temporal and spatial uncertainties and establish comparable standards for different time and space.

[0028] Furthermore, step S3 specifically includes:

[0029] The impact range of urban heat island in each urban built-up area can be estimated by the following formula:

[0030]

[0031] In the formula, BR i A represents the radius of the expected urban heat island impact range of urban built-up area patch i; i represents the area of ​​urban built-up area patch i; SUHIFPR represents the ratio of urban heat island footprint to urban built-up area, is the estimated value of SUHIFPR, calculated by the ratio of the total area of ​​the critical circle to the area of ​​the urban built-up area within it;

[0032] Identify the areas where the urban heat island intensity value SUHII is greater than zero within the influence range of all urban built-up patches as the urban heat island footprint. Identifying the heat island footprint within the estimated range can avoid overestimation of the urban heat island footprint under the influence of non-urban heat sources.

[0033] Furthermore, step S4 specifically includes:

[0034] Based on the corrected urban heat island intensity value, the maximum value SUHII_max and the average value SUHII_mean of the urban heat island intensity within the urban heat island range are calculated to characterize the urban heat island intensity;

[0035] Based on the urban heat island footprint, the heat island footprint area SUHIFP and its ratio to the urban built-up area SUHIFPR are calculated to represent the impact range of the urban heat island.

[0036] Secondly, a measurement system for urban heat island intensity and footprint is provided, including:

[0037] The urban heat island effect identification module is used to estimate the initial urban heat island intensity value based on the initial reference temperature value, draw the initial heat island intensity curve along the urban-rural gradient, and identify the urban heat island effect;

[0038] The urban heat island intensity value correction module is used to correct the error of the urban heat island intensity value based on the ground temperature value of the critical circle or the initial heat island intensity value in cities with heat island effect;

[0039] The urban heat island footprint identification module is used to estimate the urban heat island impact range of each urban built-up area patch and identify the areas within it where the urban heat island intensity value is greater than zero as the urban heat island footprint;

[0040] The urban heat island statistical index calculation module is used to calculate the urban heat island statistical index based on the corrected urban heat island intensity value and urban heat island footprint.

[0041] In a third aspect, an electronic terminal is provided, comprising:

[0042] a memory having a computer program stored thereon;

[0043] A processor is used to load and execute the computer program to implement the above-mentioned method for measuring the intensity and footprint of urban heat island.

[0044] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the method for measuring the intensity and footprint of the urban heat island as described above is implemented.

[0045] The present invention proposes a method, system, terminal and medium for measuring the intensity and footprint of urban heat islands, which can achieve more robust results in estimating the intensity and footprint of SUHI, especially by predicting the impact range of SUHI and eliminating the interference of non-urban heat sources on SUHI identification; the present invention is also applicable to complex situations where there are other heat sources outside the urban built-up area, such as non-artificial heat sources such as sand, bare land and grassland with low vegetation coverage outside the urban built-up area, or affected by the SUHI effect of other surrounding large cities. The present invention takes into account the commonalities and individual differences of temperature curves in different cities, and realizes objective and unbiased estimation of SUHI intensity and range under different geographical backgrounds, thereby laying a solid theoretical foundation and data support for the subsequent in-depth analysis of the formation mechanism, dynamic changes and environmental effects of SUHI. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 It is a schematic diagram of the principle of a method for measuring the intensity and footprint of an urban heat island provided by an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of the ratio of cold and hot islands in large cities in different seasons provided by an embodiment of the present invention;

[0049] Figure 3is the median value of the urban heat island intensity and urban heat island footprint group of each city from 2005 to 2018 provided by the embodiment of the present invention (the size of the dot represents the administrative region level, the largest is the municipality, followed by sub-provincial cities and prefecture-level cities);

[0050] Figure 4 is a schematic diagram of quality assessment of heat island footprint identification results provided by an embodiment of the present invention;

[0051] Figure 5 The heat island measurement results based on three different methods provided by the embodiments of the present invention are as follows: taking the summer heat island of Beijing in 2005 as an example;

[0052] Figure 6 These are the heat island measurement results based on three different methods provided by the embodiments of the present invention: taking the summer heat island in Lanzhou in 2018 as an example. DETAILED DESCRIPTION

[0053] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0054] The present invention provides a method, system, terminal and medium for measuring the intensity and footprint of urban heat islands. On the basis of the general definition of urban heat island intensity, in order to avoid the estimation bias caused by the urban-rural dichotomy, the background temperature reference value is determined and the impact range of the urban heat island is estimated based on the critical points and critical circles of the initial heat island intensity curve that changes along the urban-rural gradient, and finally the intensity and footprint of the urban heat island are measured. The method can measure the SUHI effect more objectively and accurately. Below, 283 cities at the prefecture level and above in China in 2005, 2010, 2015 and 2018 are taken as examples, and the seasonal SUHI effects of these cities are identified and measured using the method of the present invention. The case cities include 4 municipalities, 15 sub-provincial cities and 264 prefecture-level cities. They are selected on the basis of the administrative divisions in 2018 after excluding cities with missing data. Their climate conditions, topography and development status are different. The research data mainly include 1km resolution LST data (MYD11A1V6) obtained by Google Earth Engine (GEE) platform, land use data of China National Land Use Cover Database (NLUD-C) and digital elevation model DEM data of NASA Shuttle Radar Topography Mission (SRTM) V4.1 product. LST data products provide daily daytime and nighttime temperature products during the research period, on which the average daytime and nighttime temperatures of different seasons and the whole year are calculated, where spring is defined as March to May, summer is June to August, autumn is September to November, and winter is December to February of the following year. Land use data comes from Landsat TM images, including 6 major categories and 25 minor categories. In addition, the data of urban centers and sub-centers come from the results of map-based POI recognition by Li et al. (Li, J., Long, Y., & Dang, A. (2018). Live-Work-Play Centers of Chinese cities: Identification and temporal evolution with emerging data. Computers, Environment and Urban Systems, 71, 58-66).

[0055] Specifically, Figure 1 As shown, a method for measuring the intensity and footprint of an urban heat island provided by an embodiment of the present invention includes the following steps:

[0056] S1: Estimate the initial urban heat island intensity value based on the initial reference temperature value, draw the initial heat island intensity curve along the urban-rural gradient, and identify the urban cold and heat island effect.

[0057] Specifically, step S1 includes:

[0058] S11: Calculate the initial reference temperature value LST using the average surface temperature of rural areas outside urban built-up areas, excluding mountains and water bodies r0 In this example, urban built-up areas are defined as urban and rural areas, industrial and mining areas, and residential land in the land cover data.

[0059] S12: Establish multiple equal-area buffer zones from the city center to the periphery, and set the area of ​​each buffer zone to the smaller value of S1 / A and S2 / B; where S1 represents the built-up area of ​​the city, and S2 represents the urban area. In order to ensure sufficient sample size in the urban area and built-up area and avoid excessive calculation, the value range of A is [30,100], and the value range of B is [200,500]. For multi-center cities, the radius of the secondary center buffer zone is set to 1 / 2 of the radius of the primary center buffer zone; the outermost radius of the buffer zone is set to C times the radius of the equal-area circle of the urban area or ensure that the number of buffer zones does not exceed B*5, so that the buffer zone covers the entire urban area as much as possible without excessive calculation, where the value range of C is [1.25,5]. In the example, the built-up area of ​​each city is based on the 2005 data to ensure that there are enough sample points in the initial year when the city area is the smallest, and to be able to compare across years with a unified standard; in this example, A is 30, B is 200, and C is 1.25.

[0060] S13: Use the surface temperature LST of each pixel and the initial reference temperature LST r0 The initial urban heat island intensity value of the pixel is calculated by the difference between Calculate the pixels within each buffer The median value of the group is taken as the initial value of the heat island intensity in the buffer zone, and the initial heat island intensity curve along the urban-rural gradient is drawn.

[0061] S14: Determine whether the city has a heat island effect or a cold island effect based on the trend of the initial heat island intensity curve. Use the piecewise linear regression method to dynamically identify the peak, critical point and critical circle in the initial heat island intensity curve; if the initial urban heat island intensity in the central area of ​​the city (the central 1 / 4 area of ​​the urban built-up area) is If the mean is greater than 0, and the peak of the initial heat island intensity curve is located within the urban area, and there is a significant downward trend after the peak (the slope of the piecewise linear regression fitting line is less than the set threshold, which can be set to different values ​​according to actual conditions), then it is determined that there is an urban heat island effect; conversely, if the initial urban heat island intensity in the city center is The mean is less than 0, and If there is an overall increasing trend from the city center to the periphery, it is determined that an urban cold island effect occurs.

[0062] Figure 2The results of identifying the urban cold-heat island effect in the example are shown. Among the 283 Chinese cities, more than 90% of the cities experienced SUHI effect in summer, followed by autumn, spring and winter, while the SUCI effect showed the opposite seasonal trend, with no more than 4% of cities experiencing SUCI effect in summer. In addition, the proportion of cities experiencing the cold-heat island effect also showed significant day-night differences. SUHI mostly occurred at night, while SUCI occurred more during the day, which was particularly obvious in winter. 34% and 82% of cities experienced SUHI phenomenon during the day and night, respectively, and 39% and 6% of cities experienced SUCI phenomenon. In terms of annual trends, the proportion of daytime SUHIs decreased slightly from 2005 to 2018, while the proportion of nighttime SUHIs increased and peaked in 2015.

[0063] From the spatial distribution characteristics of the cold-heat island effect in 283 cities, it can be seen that the proportion of daytime SUHI effect in southern Chinese cities is higher than that in northern cities, and the daytime SUCI effect in northern cities is more obvious. In contrast, the distribution pattern of nighttime SUCIs is the opposite, with almost all SUCIs occurring in central and southern China, especially in the Yangtze River Basin. In addition, some cities in North China show a SUCI effect during the daytime in spring, but turn to a SUHI effect during the daytime in summer. Many northern cities experience a transition from daytime SUHI to daytime SUCI from autumn to winter. However, cities in the northeast, southeast coastal and southwest regions always show a significant SUHI effect regardless of day or night, season or year.

[0064] S2: For cities with heat island effect, the urban heat island intensity value is corrected based on the ground temperature value of the critical circle or the initial heat island intensity value.

[0065] Specifically, step S2 includes:

[0066] For cities with heat island effect, the critical circle land surface temperature value LST is used. c or initial heat island intensity value Correct the initial reference temperature value and calculate the true urban heat island intensity value SUHII by the following formula:

[0067]

[0068] Where, LST represents the land surface temperature; Indicates the initial urban heat island intensity value, LST r0 Indicates the initial reference temperature value; The corrected reference temperature value is not restricted by the urban-rural dichotomy for the definition of urban and rural areas. The correction process can reduce temporal and spatial uncertainties and establish comparable standards for different time and space.

[0069] S3: Estimate the UHI impact range of each urban built-up area patch and identify the areas within it with UHI intensity values ​​greater than zero as the UHI footprint.

[0070] Specifically, step S3 includes:

[0071] The impact range of urban heat island in each urban built-up area can be estimated by the following formula:

[0072]

[0073] In the formula, BR i A represents the radius of the expected urban heat island impact range of urban built-up area patch i; i represents the area of ​​urban built-up area patch i; SUHIFPR represents the ratio of urban heat island footprint to urban built-up area, is the estimated value of SUHIFPR, calculated by the ratio of the total area of ​​the critical circle to the area of ​​the urban built-up area within it;

[0074] Identify the areas where the urban heat island intensity value SUHII is greater than zero within the influence range of all urban built-up patches as the urban heat island footprint. Identifying the heat island footprint within the estimated range can avoid overestimation of the urban heat island footprint under the influence of non-urban heat sources.

[0075] S4: Calculate the UHI statistical indicators based on the corrected UHI intensity value and UHI footprint.

[0076] Specifically, step S4 includes:

[0077] Based on the corrected urban heat island intensity value, the maximum value SUHII_max and the average value SUHII_mean of the urban heat island intensity within the urban heat island range are calculated to characterize the urban heat island intensity;

[0078] Based on the urban heat island footprint, the heat island footprint area SUHIFP and its ratio to the urban built-up area SUHIFPR are calculated to represent the impact range of the urban heat island.

[0079] In the example, the mean and maximum values ​​of SUHI intensity in China's large cities (excluding outliers) range from 0 to 4°C and 0.5 to 14°C, respectively. The mean and maximum values ​​of SUHI intensity during the day are 0.58 and 1.75 higher than those at night. Figure 3 It can be seen that the high values ​​of SUHII_mean and SUHII_max during the day are mainly concentrated in cities in the northeast and southeast coastal areas, while at night they are mainly in North China, Northeast China and Northwest China. In addition, the daytime SUHI intensity in most cities in summer is higher than in other seasons, especially in cities in the south and northwest regions, but the nighttime SUHI intensity is just the opposite.

[0080] The SUHI footprint of most cities is between 0 and 6 times the urban area, and the daytime footprint is on average 0.55 times larger than the nighttime footprint. Figure 3 The high values ​​of daytime and nighttime SUHIFPR and SUHIFP are concentrated in southern and eastern China, respectively. This means that the overall impact area of ​​SUHI effect in eastern cities is larger, while the SUHI impact per unit urban area in southern China is wider. In addition, for different seasons, UHIFPR is not always the highest in summer. In fact, the daytime SUHI footprint in winter is larger than that in other seasons, while the seasonal difference of nighttime SUHI footprint is not significant.

[0081] By comparing the heat island intensity curves of 283 cities, it is found that the critical circles of urban and rural temperature transitions are in similar positions in different years, but there are significant differences between day and night. Therefore, the accuracy of the method proposed in the present invention can be evaluated by comparing the deviations of the critical circle positions identified in different years. Specifically, the normal distribution probability density function of the critical circle position can be obtained based on the mean and standard deviation of the critical circle positions identified in different years, and the probability Prob of each identification result can be calculated based on this function. A low Prob result means that the identification result may be unreliable and requires further manual interpretation. Figure 4 As shown in the figure, in the example, the accuracy of the daytime recognition result is lower than that of the nighttime and the accuracy is the lowest in the winter daytime. This may be because the SUHI footprint at night is more robust than that during the daytime, and the SUHI features in winter are the least obvious compared to other seasons. For cases with deviations greater than 1.5 times the standard deviation in the recognition results, they have been excluded in the above analysis of SUHI features and recorded as unclassified results.

[0082] The proposed method can achieve more robust results in SUHI intensity and footprint estimation, especially by predicting the SUHI impact range and eliminating the interference of non-urban heat sources on SUHI identification. Therefore, the proposed method is applicable in most cases. Figure 5 and 6 The results of the proposed method and two other commonly used heat island estimation methods are compared, namely, the zero value extraction method (after step S11, all LST values ​​greater than LST values ​​are extracted). r0 The largest area of ​​concentrated contiguous areas is the heat island footprint) and the threshold extraction method (after step S14, all areas with LST greater than the critical point are directly extracted as heat island footprints). Taking Beijing as an example, the zero value extraction method usually misses the impact of some enclave areas outside the city center, such as Figure 5Yanqing District in the picture. However, the threshold extraction method often misidentifies some high-temperature areas far away from the city as SUHI footprints because it does not take into account the maximum impact range of SUHI. In addition, the method of the present invention is also applicable to complex situations where there are other heat sources outside the urban built-up area, such as non-anthropogenic heat sources such as sandy land, bare land and grassland with low vegetation coverage outside the urban built-up area, or the area is affected by the SUHI effect of other large cities in the surrounding area. In such cases, the commonly used methods in the past usually identify SUHI footprints that are much larger than the actual impact because they do not take into account the heat source and its impact range (such as Figure 6 Of course, the method of the present invention is not recommended in some special cases, such as when the urban built-up area is too small or the LST data accuracy is too low, resulting in too few valid sample points in the urban built-up area and difficulty in drawing an accurate urban-rural temperature gradient change curve; or when the temperature gradient change curve of some cities shows a linear change trend and there is no obvious temperature turning point.

[0083] It should be understood that parts not elaborated in detail in this specification belong to the prior art.

[0084] The embodiment of the present invention further provides a system for measuring the intensity and footprint of an urban heat island, including:

[0085] The urban heat island effect identification module is used to estimate the initial urban heat island intensity value based on the initial reference temperature value, draw the initial heat island intensity curve along the urban-rural gradient, and identify the urban heat island effect;

[0086] The urban heat island intensity value correction module is used to correct the error of the urban heat island intensity value based on the ground temperature value of the critical circle or the initial heat island intensity value in cities with heat island effect;

[0087] The urban heat island footprint identification module is used to estimate the urban heat island impact range of each urban built-up area patch and identify the areas within it where the urban heat island intensity value is greater than zero as the urban heat island footprint;

[0088] The urban heat island statistical index calculation module is used to calculate the urban heat island statistical index based on the corrected urban heat island intensity value and urban heat island footprint.

[0089] It should be understood that the functional unit modules in various embodiments of the present invention may be concentrated in one processing unit, or each unit module may exist physically separately, or two or more unit modules may be integrated in one unit module, and may be implemented in the form of hardware or software.

[0090] An embodiment of the present invention further provides an electronic terminal, including:

[0091] a memory having a computer program stored thereon;

[0092] A processor is used to load and execute the computer program to implement the above-mentioned method for measuring the intensity and footprint of urban heat island.

[0093] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for measuring the intensity and footprint of an urban heat island as described above is implemented.

[0094] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for measuring the intensity and footprint of urban heat islands, characterized in that: The steps include: S1: Estimate the initial urban heat island intensity value based on the initial reference temperature value, draw the initial heat island intensity curve along the urban-rural gradient, and identify the urban cold and heat island effect; S2: For cities with heat island effect, error correction is performed on the urban heat island intensity value based on the ground temperature value of the critical circle or the initial heat island intensity value; S3: Estimate the impact range of the urban heat island in each urban built-up area patch and identify the areas within it where the urban heat island intensity value is greater than zero as the urban heat island footprint; S4: Calculate the urban heat island statistical indicators based on the corrected urban heat island intensity value and urban heat island footprint.

2. The method for measuring the intensity and footprint of urban heat island according to claim 1, characterized in that: Step S1 specifically includes: S11: Calculate the initial reference temperature value LST using the average surface temperature of rural areas outside urban built-up areas, excluding mountains and water bodies r0 ; S12: Establish multiple rings of equal-area buffer zones from the city center to the periphery; S13: Use the surface temperature LST of each pixel and the initial reference temperature LST r0 The initial urban heat island intensity value of the pixel is calculated by the difference between Calculate the pixels in each buffer The median value of the group is used as the initial value of the heat island intensity in the buffer zone, and the initial heat island intensity curve along the urban-rural gradient is drawn; S14: Determine whether a city has a heat island effect or a cold island effect based on the trend of the initial heat island intensity curve.

3. The method for measuring the intensity and footprint of urban heat island according to claim 2, characterized in that: Step S12 specifically includes: Establish multiple equal-area buffer zones from the city center to the periphery, and set the area of ​​each buffer zone to the smaller value of S1 / A and S2 / B; where S1 represents the built-up area of ​​the city, S2 represents the urban area, A ranges from [30,100], and B ranges from [200,500]; for multi-center cities, the radius of the secondary center buffer zone is set to 1 / 2 of the radius of the primary center buffer zone; Set the outermost radius of the buffer zone to C times the radius of the circle of equal area in the urban area or ensure that the number of buffer zones does not exceed B*5, where the value range of C is [1.25,5].

4. The method for measuring the intensity and footprint of urban heat island according to claim 2, characterized in that: Step S14 specifically includes: The peak, critical point and critical circle in the initial heat island intensity curve are identified by combining piecewise linear regression method; If the initial urban heat island intensity in the city center If the mean is greater than 0, and the peak of the initial heat island intensity curve is located within the urban area, and there is a significant downward trend after the peak, then it is determined that there is an urban heat island effect; conversely, if the initial urban heat island intensity in the city center is The mean is less than 0, and If there is an overall increasing trend from the city center to the periphery, it is determined that an urban cold island effect occurs.

5. The method for measuring the intensity and footprint of urban heat island according to claim 1, characterized in that: Step S2 specifically includes: For cities with heat island effect, the critical circle land surface temperature value LST is used. c or initial heat island intensity value Correct the initial reference temperature value and calculate the true urban heat island intensity value SUHII by the following formula: Where, LST represents the land surface temperature; Indicates the initial urban heat island intensity value, LST r0 Indicates the initial reference temperature value; 6. The method for measuring the intensity and footprint of urban heat island according to claim 1, characterized in that: Step S3 specifically includes: The impact range of urban heat island in each urban built-up area can be estimated by the following formula: In the formula, BR i A represents the radius of the expected urban heat island impact range of urban built-up area patch i; i represents the area of ​​urban built-up area patch i; SUHIFPR represents the ratio of urban heat island footprint to urban built-up area, is the estimated value of SUHIFPR, calculated by the ratio of the total area of ​​the critical circle to the area of ​​the urban built-up area within it; The areas where the urban heat island intensity value SUHII is greater than zero within the influence range of the urban heat island of all urban built-up areas are identified as the urban heat island footprint.

7. The method for measuring the intensity and footprint of urban heat island according to claim 1, characterized in that: Step S4 specifically includes: Based on the corrected urban heat island intensity value, the maximum value SUHII_max and the average value SUHII_mean of the urban heat island intensity within the urban heat island range are calculated to characterize the urban heat island intensity; Based on the urban heat island footprint, the heat island footprint area SUHIFP and its ratio to the urban built-up area SUHIFPR are calculated to represent the impact range of the urban heat island.

8. A system for measuring the intensity and footprint of urban heat islands, characterized in that: include: The urban heat island effect identification module is used to estimate the initial urban heat island intensity value based on the initial reference temperature value, draw the initial heat island intensity curve along the urban-rural gradient, and identify the urban heat island effect; The urban heat island intensity value correction module is used to correct the error of the urban heat island intensity value based on the ground temperature value of the critical circle or the initial heat island intensity value in cities with heat island effect; The urban heat island footprint identification module is used to estimate the urban heat island impact range of each urban built-up area patch and identify the areas within it where the urban heat island intensity value is greater than zero as the urban heat island footprint; The urban heat island statistical index calculation module is used to calculate the urban heat island statistical index based on the corrected urban heat island intensity value and urban heat island footprint.

9. An electronic terminal, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to load and execute the computer program to implement the method for measuring the intensity and footprint of an urban heat island as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for measuring the intensity and footprint of an urban heat island as claimed in any one of claims 1 to 7 is implemented.

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