CN111637972A - Remote sensing definition method for industrial heat island effect - Google Patents
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Abstract
The heat pollution generated by industrial activities has serious negative influence on urban ecological environment, but a quantitative measuring and calculating method and a flow for industrial area heat environment effect are lacked at present. The invention aims at the problems and discloses a remote sensing definition method of an industrial heat island effect, which comprises the following steps: step 1) framing the vector boundary of an industrial target area by utilizing Google Earth; step 2) carrying out data preprocessing on the Landsat8 image of the target industrial area and inverting the earth surface temperature; step 3) constructing 5 kilometer buffer areas on the periphery of an industrial area, and dividing 100 kilometer buffer areas equally to generate 100 layer-by-layer buffer areas of 50 meters; step 4) calculating the average earth surface temperature of each layer of buffer area, drawing a scatter diagram of the average earth surface temperature along with the change of the distance, and performing interpolation by using a B-spline curve; and 5) finding a first change critical point according to the surface temperature change curve, and further calculating a response range (km), a response temperature difference (DEG C) and response intensity (DEG C/km).
Description
Technical Field
The invention relates to a remote sensing definition method of an industrial heat island effect, which provides a remote sensing measurement method of the heat island effect suitable for a heat emission ground object target aiming at the problem of the heat environment effect of an industrial park in a city.
Background
Worldwide, rapid urbanization has led to significant 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, i.e., the phenomenon that the air temperature and the surface temperature (LST) of an urban area are higher than those of suburbs around the urban area. The rise of the urban temperature affects the habitability of urban residents, aggravates air pollution, increases the consumption of cooling energy and damages human health. In response to the above problems, urban researchers are eagerly evaluating strategies that can mitigate further warming of urban areas.
Current research has extensively summarized that human waste heat from industrial, transportation and building energy sources is one of the major causes of urban heat island effects (Kato and Yamaguchi 2005, Kotharkar and surarwar 2016, Papadopoulos and Moussiopoulos 2004, Han and Taylor 2015). In the course of resource development and utilization, the basic materials and energy consumption required for industrial production development raise a series of environmental problems (Rao et al 2018), causing redistribution of urban heat and fluctuation of surface energy (Chakraborty, Kant and Mitra 2015). According to previous studies, industrial sites play a dominant role in the formation of high surface temperatures (Li et al, 2011), and urban high-temperature regions are highly concentrated in industrial areas (Pearsall 2017, Tran et al 2017). Furthermore, if the influence of industrial production activities on the environment is neglected, the investment of manpower, material resources, and financial resources for alleviating environmental deterioration is even doubled (Wan, Shenand Choi 2017). In addition, artificial surfaces (i.e., man-made areas), such as commercial, residential and industrial areas, often study the changes in urban thermal environment as a whole (Li et al 2011, Chakraborty et al 2015). Therefore, the industrial park, as a separate research target, is dedicated to the study of the relationship between the thermal response and the thermal emissions of the industrial landscape target, and is yet to be deeply explored.
Previous studies have also focused on the impact of urban climate control targets on thermal environments, such as the cold island effect in urban greenhouses (large parks), urban waters, etc. (Yan, Wu and Dong 2018, Cao et al 2010, Bowler et al 2010, Bartesaghi-Koc, Osmond and Peters 2019). Early studies estimated the cold island effect range of influence of urban waters based on measured data of fixed point locations (Chang, Li and Chang 2007). In order to adopt a more convenient data acquisition mode, (Du et al.2016) utilizes Google Earth and landsat-8 satellite image data to quantitatively detect the cold island effect of the water body in Shanghai city. In summary, a large number of studies prove that dynamic thermal radiation information can be accurately extracted in real time by using a remote sensing technology, and a powerful support can be provided for regional thermal environment optimization (Wilson et al 2003, Stone and Rodgers2001, Meng et al 2018, Dos Santos et al 2017, Powers et al 2015, Feng et al 2019).
In summary, accurately quantifying the influence of the industrial park on the thermal environment is an urgent task of industrial thermal pollution control at present. Therefore, the invention focuses on the research in the large-scale industrial park in the city, and aims to establish a quantitative measuring and calculating method for the industrial heat island effect. Environmental departments and city planners can adjust the deployment of production tasks according to the intensity of industrial heat island effect in different seasons, and aim to reduce the adverse effect of industrial production activities on local geothermal environment.
Disclosure of Invention
The invention aims to provide a remote sensing definition method of an industrial heat island effect, which aims to solve the technical defect problem of the industrial heat island effect in the existing research and utilizes a thermal infrared remote sensing image to quantitatively measure and calculate the local geothermal environment effect of an urban industrial area.
The purpose of the invention is realized by the following technical steps:
step 1) framing the vector boundary of an industrial target area by utilizing Google Earth;
step 2) carrying out data preprocessing on the Landsat8 image of the target industrial area and inverting the earth surface temperature;
step 3) constructing 5 kilometer buffer areas on the periphery of an industrial area, and dividing 100 kilometer buffer areas equally to generate 100 layer-by-layer buffer areas of 50 meters;
step 4) calculating the average earth surface temperature of each layer of buffer area, drawing a scatter diagram of the average earth surface temperature along with the change of the distance, and performing interpolation by using a B-spline curve;
and 5) finding a first change critical point according to the surface temperature change curve, and further calculating a response range (km), a response temperature difference (DEG C) and response intensity (DEG C/km).
Drawings
FIG. 1 is an analytic graph based on the average surface temperature profile of a continuous buffer zone in an industrial zone;
FIG. 2 is a graph of inversion results of surface temperature of a sample steel plant;
FIG. 3 is a graph of the fitting results of the average surface temperature variation curves of the sample iron and steel plant;
Detailed Description
The invention 'a remote sensing definition method of industrial heat island effect' is further explained with the accompanying drawings.
(one) study region vector bounding box determination
Firstly, the basic position of the target area is determined by visual interpretation by using Google Earth, the vector boundary of the industrial target area is framed by using an 'adding polygon' tool and is stored in a kml or kmz format, and then vector data is converted into a shp format by using an 'rolling out from kml' tool of ArcGIS and is stored again.
(II) data preprocessing and surface temperature remote sensing inversion
Firstly, preprocessing of radiometric calibration and atmospheric correction is carried out on an original Landsat8 primary data product, and then the earth surface temperature is inverted by using Band10 data of Landsat8 based on a radiation transmission equation, wherein the radiation transmission equation is as follows:
in the above formula, TsRepresenting the surface temperature to be calculated; l issensorThe radiation brightness value after radiation calibration; b (T)s) Is at a temperature TsBlack body radiation value of time;
and
respectively refers to the uplink radiation and the downlink radiation of the atmosphere; τ is the atmospheric transmittance; the data preprocessing process can be realized by an ENVI radiation correction tool and an atmospheric correction tool, the calculation process of surface temperature inversion can be realized by an ENVI wave band operation tool, and the surface temperature inversion result of the sample area is shown in FIG. 2.
(III) layer-by-layer buffer construction
Constructing buffer areas of 5 kilometers at the periphery of an industrial area, and dividing 100 buffer areas equally to generate 100 buffer areas of 50 meters layer by layer; this step can be implemented in a batch process by the ArcGIS buffer tool.
(IV) mean surface temperature variation curve fitting
Calculating the average earth surface temperature of each layer of buffer area, drawing a scatter diagram of the average earth surface temperature changing along with the distance, and fitting by using a B-spline curve to obtain a smoothed earth surface temperature change curve (the abscissa is the distance from the boundary of the industrial area, and the ordinate is the earth surface temperature); the average surface temperature of the layer-by-layer buffer area can be obtained by using the attribute function of ArcGIS, and the generation of the surface temperature change curve is realized by using a nonlinear curve fitting tool after the ArcGIS is introduced into origin.
(V) quantitative index calculation
According to the surface temperature change curve (figure 1), a first turning critical point is found, and then a response range (km), a response temperature difference (DEG C) and response intensity (DEG C/km) are calculated. The turning critical point refers to the first point position with non-negative curve slope, and the abscissa of the point position is the response range (km); the ordinate of the turning critical point represents the surface temperature of the turning point, and the difference between the boundary surface temperature of the industrial area and the surface temperature of the turning point is calculated, so that the response temperature difference (DEG C) can be calculated; the response intensity (DEG C/km) is the ratio of the response temperature difference to the response range. The results of the sample zone mean surface temperature curve fit are shown in fig. 3.
Claims (6)
1. A remote sensing definition method of industrial heat island effect comprises the following steps:
step 1) framing the vector boundary of an industrial target area by utilizing Google Earth;
step 2) carrying out data preprocessing on the Landsat8 image of the target industrial area and inverting the earth surface temperature;
step 3) constructing 5 kilometer buffer areas on the periphery of an industrial area, and dividing 100 kilometer buffer areas equally to generate 100 layer-by-layer buffer areas of 50 meters;
step 4) calculating the average earth surface temperature of each layer of buffer area, drawing a scatter diagram of the average earth surface temperature along with the change of the distance, and performing interpolation by using a B-spline curve;
and 5) finding a first change critical point according to the surface temperature change curve, and further calculating a response range (km), a response temperature difference (DEG C) and response intensity (DEG C/km).
2. The method of claim 1, wherein step 1): the basic position of the target area is determined by visual interpretation by using Google Earth, the vector boundary of the industrial target area is framed by using an 'adding polygon' tool and is stored in a kml or kmz format, and then vector data is converted into a shp format by using an 'rolling out from kml' tool of ArcGIS.
3. The method of claim 1, wherein step 2): firstly, preprocessing radiation correction and atmospheric correction is carried out on an original Landsat8 primary data product, and then the earth surface temperature is inverted by using Band10 data of Landsat8 based on a radiation transmission equation, wherein the radiation transmission equation is as follows:
in the above formula, TsRepresenting the surface temperature to be calculated; l issensorThe radiation brightness value after radiation calibration; b (T)s) Is at a temperature TsBlack body radiation value of time;
and
respectively refers to the uplink radiation and the downlink radiation of the atmosphere; τ is the atmospheric transmittance; the data preprocessing process can be realized by an ENVI radiation calibration tool and an atmospheric correction tool, and the earth surface temperature inversion calculation process can be realized by an ENVI wave band operation tool.
4. The method of claim 1, wherein step 3): constructing buffer areas of 5 kilometers at the periphery of an industrial area, and dividing 100 buffer areas equally to generate 100 buffer areas of 50 meters layer by layer; this step can be implemented by the buffer tool of ArcGIS.
5. The method of claim 1, wherein step 4): calculating the average earth surface temperature of each layer of buffer area, drawing a scatter diagram of the average earth surface temperature changing along with the distance, and fitting by using a B-spline curve to obtain a smoothed earth surface temperature change curve (the abscissa is the distance from the boundary of the industrial area, and the ordinate is the earth surface temperature); the average surface temperature of the layer-by-layer buffer area can be obtained by using the 'attribute' function of ArcGIS, and the generation of the surface temperature change curve is realized by using a nonlinear curve fitting tool after the ArcGIS is introduced into origin.
6. The method of claim 1, wherein step 5): and finding a first turning critical point according to the surface temperature change curve, and further calculating a response range (km), a response temperature difference (DEG C) and response intensity (DEG C/km). The turning critical point refers to the first point position with non-negative curve slope, and the abscissa of the point position is the response range (km); the ordinate of the turning critical point represents the surface temperature of the turning point, and the difference between the boundary surface temperature of the industrial area and the surface temperature of the turning point is calculated, so that the response temperature difference (DEG C) can be calculated; the response intensity (DEG C/km) is the ratio of the response temperature difference to the response range.
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| CN115630535A (en) * | 2022-12-19 | 2023-01-20 | 中国农业科学院农业资源与农业区划研究所 | Dynamic quantification method and device for urban surface heat island strength and electronic equipment |
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