An Irregular Urban Heat Island Footprint Extraction Method Based on Angle Segmentation

Abstract

The present invention provides a method for extracting irregular urban heat island footprints based on angular segmentation. First, based on multi-source remote sensing images, the land surface temperature is inverted, and the urban built-up area is extracted using the dynamic threshold dichotomy method, and then the urban morphology is measured. Secondly, starting from the boundary of the urban built-up area, multiple buffer rings with an interval of 1 km are drawn, and the built-up area and its buffer rings are equally angularly divided into sixteen quadrants. Furthermore, the average temperature on each ring is statistically calculated, the temperature curve is drawn, and the abnormal quadrants are eliminated. Thirdly, the temperature curves of the remaining quadrants are integrated, and the footprint extension distance and the background temperature value are fitted using the exponential decay model. Finally, the heat island influence range is jointly constrained according to the fitted extension distance and background temperature value to obtain the urban heat island footprint. This method minimizes the influence of urban morphology and the landscape outside the built-up area, obtains a more accurate heat island footprint, and provides suggestions for urban thermal environment research and urban planning management.

Description

Technical Field

[0001] The present invention relates to a method for extracting urban heat island footprints based on angle segmentation, and particularly to a method for extracting urban heat island footprints for irregularly shaped cities. Background Art

[0002] Urban heat island refers to the phenomenon that the air and surface temperatures in urban areas are significantly higher than those in suburban areas. With the acceleration of urbanization, the surface urban heat island phenomenon has a negative impact on the health and comfort of urban residents and greatly increases energy consumption, which has become an important research topic in various fields. Some scholars have proposed the heat island footprint index, which quantifies the area affected by the heat island effect and comprehensively considers the size and spatial extent of the heat island effect. Currently, the methods for determining the heat island footprint are generally divided into two categories. One category uses the Gaussian model to obtain the footprint. Although this method can comprehensively represent the urban heat distribution, the obtained footprint shape is oval and very rough. The other category uses the radius method to obtain the footprint, but this method is not applicable to some special cities with complex spatial forms. Therefore, it is necessary to design a method for extracting heat island footprints for irregularly shaped cities to extract accurate heat island footprints. Summary of the Invention

[0003] In view of the above problems, the purpose of the present invention is to provide a method for extracting urban heat island footprints based on angle segmentation to solve the problem that the heat island footprints of irregular cities cannot be accurately extracted at present.

[0004] To solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A method for extracting urban heat island footprints based on angle segmentation, which mainly comprises the following steps:

[0006] Step 1: Based on remote sensing images, use the single-window algorithm to invert the surface temperature;

[0007] Step 2: Extract the urban built-up area based on night light images and built-up area data, and use the Boyce-Clark index to measure the urban form;

[0008] Step 3: Draw a buffer ring from the built-up area boundary and perform angle segmentation;

[0009] Step 4: Statistically analyze the temperature of each ring, draw a temperature curve, and eliminate abnormal situations;

[0010] Step 5: Integrate the remaining part of the temperature curve and perform exponential fitting;

[0011] Step 6: Extract the heat island footprint according to the heat island extension distance and regional background temperature obtained by fitting.

[0012] Furthermore, the step 1 specifically involves obtaining Landsat8 remote sensing image data, and using a single window algorithm to express the relationship between TOA brightness temperature and surface temperature through a linear relationship, thereby calculating the surface temperature. The calculation formula is:

[0013]

[0014] Where LST is the surface temperature, Tb is the TOA brightness temperature in the TIR channel, and ε is the surface emissivity in the same channel. i 、B i and C i Determined by linear regression of radiative transfer simulations performed on 10 categories of atmospheric column water vapour (I = 1, ..., 10).

[0015] Furthermore, the second step is to extract built-up areas from the NPP-VIIRS image based on the dynamic threshold dichotomy method:

[0016]

[0017] Where H(i,j) is the pixel value in the i-th row and j-th column of the original image, θ is the set threshold, and h(i,j) is the binary image after segmentation. The threshold is continuously adjusted to make the extracted built-up area closest to the area in the statistical yearbook, obtaining the precise built-up area range while retaining only the main built-up area with the largest area.

[0018] 2.2. Use the Boyce-Clark index to measure urban form and determine its complexity. Compare the city shape to a standard circle to obtain a relative value. The larger the shape index, the more complex the shape. The calculation formula is as follows:

[0019]

[0020] Among them, k sbc is the shape index; r i is the radius, which represents the distance from the center of mass of the figure to the periphery of the figure, and n is the number of radiation radii. In this method, n is 32.

[0021] Furthermore, the step three is specifically as follows:

[0022] 3.1. In ArcGIS software, draw 20 buffer rings with an interval of 1 km from the built-up area boundary;

[0023] 3.2. Taking the center of the built-up area as the origin and due north as the starting direction, the built-up area and its multiple buffer zones are divided into sixteen quadrants in a clockwise direction.

[0024] Furthermore, the step 4 is specifically as follows:

[0025] 4.1. Exclude temperature pixel points in water bodies and those with an altitude more than 50 m above the highest point in the urban area, because water bodies and terrain may mask the impact of urbanization on temperature;

[0026] 4.2. Statistically analyze the temperature of each ring at each angle and plot it into a temperature curve;

[0027] 4.3. Eliminate the curves corresponding to the quadrants with a large area falling into water bodies and the quadrants affected by other built-up areas around.

[0028] Further, the specific content of step five is as follows

[0029] 5.1. Integrate the remaining temperature curves;

[0030] 5.2. Fit the integrated temperature curve, and its fitting formula is as follows:

[0031] [[ID=I9]]

[0032] Among them, y is the surface temperature, A represents the heat island intensity, t is the exponential decay rate, d is the extension distance of the footprint, that is, the distance from the built-up area boundary to the buffer ring, and T0 is the fitted regional background temperature.

[0033] Further, the specific content of step six is as follows

[0034] 6.1. Draw a buffer ring from the built-up area boundary, and the buffer distance is the footprint extension distance;

[0035] 6.2. Within the buffer ring range, extract the pixel points with a temperature higher than the regional background temperature;

[0036] 6.3. Convert the extracted temperature pixel points into vectors and aggregate them into a continuous range, that is, the final heat island footprint.

[0037] Beneficial effects: Through the above urban heat island footprint extraction method, the present invention can minimize the influence of urban form and the landscape outside the built-up area to obtain a more accurate heat island footprint, providing suggestions for urban thermal environment research and urban planning management. Description of the Drawings

[0038] Figure 1 It is a flowchart of an embodiment of an urban heat island footprint extraction method based on angle segmentation according to the present invention;

[0039] Figure 2 It is a schematic diagram of angle segmentation according to the present invention;

[0040] Figure 3 It is a schematic diagram of abnormal situations to be eliminated according to the present invention;

[0041] Figure 4 It is a graph of the exponential fitting result of the temperature curve according to the present invention;

[0042] Figure 5 This is the heat island footprint extraction result map of the present invention; DETAILED DESCRIPTION

[0043] The present invention will be further described in detail below by way of examples. The following examples are intended to explain the present invention but the present invention is not limited to the following examples.

[0044] The method for extracting urban heat island footprints based on angle segmentation of the present invention comprises the following steps:

[0045] Step 1: Obtain Landsat remote sensing image data and use the single window algorithm to calculate the surface temperature formula (Tb is the TOA brightness temperature in the TIR channel, ε is the surface emissivity in the same channel. The algorithm coefficient A i 、B i and C i The surface temperature is calculated from a linear regression of radiative transfer simulations performed on 10 categories of atmospheric column water vapour totals (I = 1, ..., 10).

[0046] Step 2: Obtain NPP-VIIRS images and extract built-up areas based on the dynamic threshold dichotomy method. The formula is: (Where H(i,j) is the pixel value in the i-th row and j-th column of the original image, θ is the set threshold, and h(i,j) is the binary image after segmentation). Continuously adjust the threshold to make the extracted built-up area closest to the area in the statistical yearbook, and obtain the precise built-up area range, while only retaining the main built-up area with the largest area. Use the shape index calculation formula (k sbc is the shape index; r i is the radius, which represents the distance between the centroid of the figure and the periphery of the figure, and n is the number of radiation radii) to calculate the city shape index and determine the complexity of the urban form.

[0047] Step 3: If Figure 2 As shown in the figure, 20 buffer rings with an interval of 1 km are drawn from the boundary of the built-up area in ArcGIS, and 16 rays are drawn clockwise with equal angles from the center of the built-up area as the origin and the north direction as the starting direction, dividing the built-up area and its multi-ring buffer zone into 16 quadrants.

[0048] Step 4: Exclude water bodies and temperature pixels with an altitude of more than 50m above the highest point in the urban area, calculate the temperature of each ring in each quadrant, and draw a temperature curve. Eliminate the curves corresponding to quadrants with large areas falling into water bodies and quadrants affected by other built-up areas. The following situations need to be eliminated: Figure 3 shown.

[0049] Step 5: Integrate the remaining temperature curves, and fit the integrated curve according to the formula where y is the surface temperature, A represents the heat island intensity, t is the exponential decay rate, d is the extension distance of the footprint, i.e., the distance from the built-up area boundary to the buffer ring, and T0 is the fitted regional background temperature), and the fitted curve is as shown in Figure 4 Figure...

[0050] Step 6: Draw a buffer ring from the built-up area boundary, and the buffer distance is the extension distance of the footprint. Within the buffer ring range, extract the pixel points with temperatures higher than the regional background temperature, convert the extracted temperature pixel points into vectors, and aggregate them into a continuous surface, which is the final heat island footprint, as shown in Figure 5 Figure...

Claims

1. An extraction method for irregular urban heat island footprints based on angle segmentation, characterized in that It includes the following steps: Step 1: Invert the land surface temperature based on remote sensing images; Step 2: Extract urban built-up areas based on night-time light images and built-up area data, and measure the urban form; Step 3: Draw buffer rings starting from the built-up area boundary and perform angular segmentation; Step 4: Count the temperature of each ring, draw a temperature curve, and eliminate abnormal situations; Step 5: Integrate the remaining part of the temperature curve and perform exponential fitting; Step 6: Extract the heat island footprint according to the heat island extension distance and regional background temperature obtained by fitting; Specifically, Step 1 is to obtain Landsat8 remote sensing image data, use the single-window algorithm to represent the relationship between TOA brightness temperature and land surface temperature through a linear relationship, so as to calculate the land surface temperature. Its calculation formula is: where LST is the land surface temperature, Tb is the TOA brightness temperature in the TIR channel, and ε is the surface emissivity of the same channel; the algorithm coefficients A i , B i , and C i are determined by linear regression of radiative transfer simulations performed for 10 total atmospheric column water vapor amounts (I = 1, …, 10); Specifically, Step 2 is: 2.1 Extract built-up areas from NPP-VIIRS images based on the dynamic threshold bisection method: Among them, H(i,j) is the pixel value of the original image at the i-th row and j-th column, θ is the set threshold, and h(i,j) is the binary image after segmentation; continuously adjust the threshold to make the built-up area extracted closest to the area in the statistical yearbook, obtain the accurate built-up area range, and only retain the largest main built-up area; 2.2 Use the Boyce-Clark index to measure the urban form and judge the complexity of the urban form; compare the urban shape with a standard circle to obtain a relative value; the larger the shape index, the more complex the shape. Its calculation formula is as follows: where k sbc is the shape index; r i is the radius, representing the length from the centroid of the figure to the periphery of the figure. n is the number of radiation radii, and in this method, n is taken as 32; Specifically, Step 3 is: 3.1 In the ArcGIS software, draw multiple buffer rings with an interval of 1 km starting from the built-up area boundary; 3.2 Take the center of the built-up area as the origin, the due north direction as the starting direction, and divide the built-up area and its multi-ring buffer zones into sixteen quadrants clockwise at equal angles; Specifically, Step 4 is: 4.1 Exclude temperature pixel points of water bodies and those with an altitude more than 50 m higher than the highest point in the urban area, because water bodies and terrain may mask the impact of urbanization on temperature; 4.2 Count the temperature of each ring in each quadrant and draw it into a temperature curve; 4.3 Eliminate the curves corresponding to the quadrants with a large area falling into the water body and the quadrants affected by other built-up areas around; Specifically, Step 5 is: 5.1 Integrate the remaining temperature curves; 5.2 Fit the integrated temperature curve. Its fitting formula is as follows: Among them, y is the land surface temperature, A represents the heat island intensity, t is the exponential decay rate, d is the extension distance of the footprint, that is, the distance from the built-up area boundary to the buffer ring, and T0 is the fitted regional background temperature; Specifically, Step 6 is 6.1 Draw a buffer ring from the built-up area boundary, and the buffer distance is the footprint extension distance; 6.2 Extract the pixel points with a temperature higher than the regional background temperature within the buffer ring range; 6.3 Convert the extracted temperature pixel points into vectors and aggregate them into a continuous range, that is, the final heat island footprint.

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