CN111637972A - Remote sensing definition method for industrial heat island effect - Google Patents

Abstract

Thermal pollution from industrial activities has caused serious negative impacts on the urban ecological environment, but there is still a lack of quantitative measurement methods and processes for thermal environmental effects in industrial areas. Aiming at the above problems, the present invention discloses a remote sensing definition method for industrial heat island effect. The method includes the following steps: step 1) using Google Earth to frame the vector boundary of the industrial target area; step 2) performing data preprocessing on the Landsat8 image of the target industrial area , and invert the surface temperature; step 3) build a 5-kilometer buffer zone at the periphery of the industrial area, and divide it into 100 equal parts to generate 100 layer-by-layer buffers of 50 meters; step 4) calculate the average surface of each layer of buffer zone temperature, draw a scatter plot of the average surface temperature with distance, and use the B-spline curve to interpolate; step 5) According to the surface temperature change curve, find the first change critical point, and then calculate the response range (km), the response temperature difference ( °C) and response intensity (°C/km).

Description

A Remote Sensing Definition Method of Industrial Heat Island Effect

technical field

The invention relates to a remote sensing definition method of industrial heat island effect. Aiming at the problem of thermal environment effect of industrial parks in cities, a remote sensing calculation method of heat island effect suitable for thermal emission objects is proposed, combined with the surface temperature change curve of the surrounding area of the industrial park. , three response indicators for industrial features were established to clearly quantify the impact of such large-scale urban targets with heat emissions on the local geothermal environment, in order to further understand the impact mechanism of urban industrial heat sources on the microclimate.

Background technique

Worldwide, rapid urbanization has led to major changes in urban climate and surface biochemical processes. Among them, the urban heat island effect (UHI effect) is one of the most typical urban ecological environmental problems, that is, the air temperature and surface temperature (LST) in urban areas are higher than those in the surrounding suburbs. Rising urban temperatures affect the livability of urban residents, exacerbate air pollution, increase cooling energy consumption, and harm human health. In response to these questions, urban researchers are eagerly evaluating strategies that could mitigate further warming in urban areas.

Current studies have broadly concluded that anthropogenic waste heat from industry, transport and building energy is one of the important causes of the urban heat island effect (Kato and Yamaguchi 2005, Kotharkar and Surawar 2016, Papadopoulos and Moussiopoulos 2004, Han and Taylor 2015). In the process of resource development and utilization, the basic materials and energy consumption required for the development of industrial production have caused a series of environmental problems (Rao et al. 2018), the redistribution of urban heat and the fluctuation of surface energy (Chakraborty, Kant and Mitra 2015). According to previous studies, industrial land plays a leading role in the formation of high surface temperature (Li et al., 2011), and urban high temperature areas are highly concentrated in industrial areas (Pearsall 2017, Tran et al. 2017). In addition, if the impact of industrial production activities on the environment is ignored, the human, material and financial resources used to alleviate environmental degradation will even be doubled (Wan, Shenand Choi 2017). In addition, artificial surfaces (i.e., man-made areas), such as commercial, residential, and industrial areas, are often used as a whole to study changes in the urban thermal environment (Li et al. 2011, Chakraborty et al. 2015). Therefore, taking the industrial park as a separate research target and focusing on the relationship between the thermal response and heat emission of the industrial feature target needs to be further explored.

Previous studies have also paid attention to the impact of urban climate regulation targets on the thermal environment, such as the cold island effect of urban green space (large parks), urban water bodies, etc. (Yan, Wu and Dong 2018, Cao et al. 2010, Bowler et al. 2010 , Bartesaghi-Koc, Osmond and Peters 2019). Early studies were based on measured data at fixed points to estimate the extent of the cold island effect in urban water bodies (Chang, Li and Chang 2007). In order to adopt a more convenient data acquisition method, (Du et al. 2016) used Google Earth and landsat-8 satellite image data to quantitatively detect the cold island effect of water bodies in Shanghai. In conclusion, a large number of studies have proved that the accurate and real-time extraction of dynamic thermal radiation information using remote sensing technology can provide strong support for regional thermal environment optimization (Wilson et al. 2003, Stone and Rodgers 2001, Meng et al. 2018, Dos Santos et al. al. 2017, Powers et al. 2015, Feng et al. 2019).

To sum up, accurately quantifying the impact of industrial parks on the thermal environment is an urgent task for industrial thermal pollution control. Therefore, the present invention focuses the research on large-scale urban industrial parks, aiming to establish a quantitative calculation method of industrial heat island effect. Environmental departments and urban planners can adjust the deployment of production tasks according to the intensity of the industrial heat island effect in different seasons, aiming to reduce the adverse impact of industrial production activities on the local geothermal environment.

SUMMARY OF THE INVENTION

Aiming at the technical lack of industrial heat island effect in existing research, the purpose of the present invention is to propose a remote sensing definition method of industrial heat island effect, and use thermal infrared remote sensing images to quantitatively measure the local geothermal environmental effect of urban industrial areas.

The object of the present invention is achieved through the following technical steps:

Step 1) utilize Google Earth to frame the vector boundary of the industrial target area;

Step 2) Data preprocessing is performed on the Landsat8 image of the target industrial area, and the surface temperature is inverted;

Step 3) Build a 5-kilometer buffer zone on the periphery of the industrial area, and divide it into 100 equal parts to generate 100 layer-by-layer buffer zones of 50 meters;

Step 4) Calculate the average surface temperature of each layer of buffer zone, draw a scatter diagram of the average surface temperature changing with distance, and use B-spline curve to interpolate;

Step 5) According to the surface temperature change curve, find the first change critical point, and then calculate the response range (km), the response temperature difference (°C) and the response intensity (°C/km).

Description of drawings

Fig. 1 Analytical diagram of the average surface temperature change curve based on the continuous buffer zone in the industrial zone;

Fig. 2 Inversion result of surface temperature of sample iron and steel plant;

Fig. 3 The fitting result of the average surface temperature change curve of the sample iron and steel plant;

Detailed ways

The following describes "a remote sensing definition method for industrial heat island effect" of the present invention in conjunction with the accompanying drawings.

(1) Vector bounding box of the study area

First, use Google Earth to determine the basic position of the target area through visual interpretation, use the "Add Polygon" tool to frame the vector boundary of the industrial target area, and save it in kml or kmz format, and then use ArcGIS's "convert from kml" tool to convert the vector The data is converted to shp format and saved again.

(2) Data preprocessing and remote sensing inversion of surface temperature

First, the original Landsat8 primary data products are preprocessed by radiometric calibration and atmospheric correction, and then the surface temperature is inverted using the Band10 data of Landsat8 based on the radiative transfer equation. The radiative transfer equation is:

和

分别指代大气的上行辐射和下行辐射；τ为大气透过率；上述的数据预处理过程可以通过ENVI的辐射校正工具与大气校正工具实现，地表温度反演的计算过程可通过ENVI的波段运算工具实现，样本区的地表温度反演结果如图2所示。In the above formula, T _s represents the surface temperature to be calculated; L _sensor is the radiance value calibrated by radiation; B(T _s ) is the black body radiation value when the temperature is T _s ;

and

respectively refer to the upward and downward radiation of the atmosphere; τ is the atmospheric transmittance; the above data preprocessing process can be realized by the radiation correction tool and atmospheric correction tool of ENVI, and the calculation process of the surface temperature inversion can be performed by the band calculation of ENVI The tool is implemented, and the inversion results of the surface temperature in the sample area are shown in Figure 2.

(3) Layer-by-layer buffer construction

Construct a 5-kilometer buffer at the periphery of the industrial area, and divide it into 100 equal parts to generate 100 layer-by-layer buffers of 50 meters; this step can be realized by the batch method of ArcGIS's buffer tool.

(4) Curve fitting of average surface temperature

Calculate the average surface temperature of each buffer layer, draw a scatter diagram of the average surface temperature changing with distance, and use the B-spline curve to fit to obtain the smoothed surface temperature change curve (the abscissa is the distance to the industrial zone boundary. , the ordinate is the surface temperature); among them, the average surface temperature of the layer-by-layer buffer can be obtained by using the "attribute" function of ArcGIS, and then imported into the origin and then used the nonlinear curve fitting tool to generate the surface temperature change curve.

(5) Calculation of quantitative indicators

According to the surface temperature change curve (Fig. 1), find the first critical point, and then calculate the response range (km), response temperature difference (°C) and response strength (°C/km). The turning critical point refers to the first point where the slope of the curve is a non-negative number, and the abscissa of this point is the response range (km); the ordinate of the turning critical point represents the surface temperature of the turning point. The response temperature difference (°C) can be obtained by calculating the surface temperature difference at the turning point; the response intensity (°C/km) is the ratio of the response temperature difference to the response range. The fitting results of the average surface temperature curve in the sample area are shown in Figure 3.

Claims (6)

1. a remote sensing definition method of industrial heat island effect, the monitoring method comprises the steps: Step 1) utilize Google Earth to frame the vector boundary of the industrial target area; Step 2) Data preprocessing is performed on the Landsat8 image of the target industrial area, and the surface temperature is inverted; Step 3) Build a 5-kilometer buffer zone on the periphery of the industrial area, and divide it into 100 equal parts to generate 100 layer-by-layer buffer zones of 50 meters; Step 4) Calculate the average surface temperature of each layer of buffer zone, draw a scatter diagram of the average surface temperature changing with distance, and use B-spline curve to interpolate; Step 5) According to the surface temperature change curve, find the first change critical point, and then calculate the response range (km), the response temperature difference (°C) and the response intensity (°C/km). 2. the method as claimed in claim 1 is characterized in that, described step 1): utilize Google Earth to determine the basic position of target area by visual interpretation, utilize " add polygon " tool to frame the vector boundary of industrial target area, and Save it in kml or kmz format, and then use ArcGIS's "Export from kml" tool to convert the vector data to shp format. 3. The method according to claim 1, characterized in that, in the step 2): firstly, the preprocessing of radiation correction and atmospheric correction is performed on the original Landsat8 primary data product, and then the Band10 data of Landsat8 is utilized based on the radiation transfer equation. To invert the surface temperature, the radiative transfer equation is:

In the above formula, T _s represents the surface temperature to be calculated; L _sensor is the radiance value calibrated by radiation; B(T _s ) is the black body radiation value when the temperature is T _s ;

and

Respectively refer to the upward and downward radiation of the atmosphere; τ is the atmospheric transmittance; the above data preprocessing process can be realized by the radiation calibration tool and atmospheric correction tool of ENVI, and the calculation process of the surface temperature inversion can be performed by the ENVI band Operation tool implementation. 4. The method according to claim 1, wherein the step 3): construct a 5-kilometer buffer zone at the periphery of the industrial area, and divide it into 100 equal parts to generate 100 layer-by-layer buffer zones of 50 meters ; This step can be achieved through the ArcGIS Buffer tool. 5. The method according to claim 1, wherein the step 4): calculate the average surface temperature of each layer of buffer zone, draw a scatter plot of the average surface temperature changing with distance, and use a B-spline curve Carry out fitting to obtain the smoothed surface temperature change curve (the abscissa is the distance to the boundary of the industrial area, and the ordinate is the surface temperature); the average surface temperature of the layer-by-layer buffer can be obtained by using the "attribute" function of ArcGIS. After importing to origin, use the nonlinear curve fitting tool to generate the surface temperature change curve. 6. The method according to claim 1, characterized in that, in the step 5): according to the surface temperature change curve, find the first turning critical point, and then calculate the response range (km), the response temperature difference (°C) and the response Strength (°C/km). The turning critical point refers to the first point where the slope of the curve is a non-negative number, and the abscissa of this point is the response range (km); the ordinate of the turning critical point represents the surface temperature of the turning point. The response temperature difference (°C) can be obtained by calculating the surface temperature difference at the turning point; the response intensity (°C/km) is the ratio of the response temperature difference to the response range.

Images