GISdevelopment.net ---> AARS ---> ACRS 1990 ---> Poster Session Q

Applications of aerophotos & satellite images in correlation analysis between urban thermal field and architectural volume rate
-----------taking Shanghai as an example--------


Wang zhisheng, Qian Bin, Guo Shulin
Department of Geography, shanghai Teachers,
university, 10 Gulin Road, Changhai 200234, China


Abstract
In this paper, by taking advantage of the interpretation data of color aerophotos with large scale and the thermal field data from the thermal IR images of meteorological Satellite and Landsat TM, an optimization correlation model between earth surface structure and thermal field in shanghai proper has been established, in which, the effect of heat carrying and energy storage of urban "canyon" is simulated by adopting the digitized factor of "urban architectural volume rate" (UAVR) which is the first to be designed. It has been proved by its calculated results that UAVR is the dominant factor fro causing thermal field temperature difference between the city & country, and within the city., the concrete contributions of other factors, such as waters and vegetation etc to thermal field are further described, as well as the characteristics of their variations with the seasonal change. It has been pointed out that the method for simulating the energy storage and heat carrying of urban underlying surface by using the digitized factor of UAVR has more significant feasibility and advantages that that for studying the "canyon" effect constituted between the building in the city by adopting the wind tunnel simulation and instrument measurement.

Foreword
The urban thermal field has been studied for 173 years, yet, the difference between urban and rural air temperature field the phenomenon of heat island has been more discussed, the mechanism of this phenomenon has been worked by many experts at home and abroad, and concluded by some experts. City, being the product of human activities, has been classified as the source of generating artificial heat during the climatologists discussing the thermal equilibrium of the mechanism of heat island. This is because of the thermal characteristics of surface structural radiation field which is closely related to the urban architectural scale different functional regions changed by mankind. In this paper using satellite thermal IR images and the interpretation data of 1/5000 color aerophotos an optimization model between Shanghai earth surface structure and its thermal field has been emphatically discussed, and the contributions of "urban architectural volume rate" (UAVR) to forming urban thermal field admits importance for forming "heat island" have been established.

Theoretical basis and information source
It is known from the radiation theory that energy can be emitted outward in the form of electromagnetic wave by the body with surface temperature greater than 0 k, and it can be expressed as :

Q = e sT4

Where Q is the radiation energy flux (w/m2), s the Stefan-Boltzmand constant (5.669 x 10-8 w/m2k4) e the emissivity and T the surface temperature of the body (k).

Based on this equation the radiation flux is not only related to the earth surface temperature, but also dependent on the emissivity and T the surface temperature of the body. Nevertheless, it is not very easy for one city to obtain a correct distribution of value Q (here, refer mainly to logn wave radiation Q emitted from earth surface. Fuggle & Oke pointed out in 970 that for this factor the different. Albedo and thermal capacity of urban surface structures should also be considered, that is why oke did the experiment on the effect of "metropolis canyon"[2].

Based on the theory mentioned above, the factor "urban architectural volume rate and other factors of urban underlying surface have been designed in this paper of participating the regression analysis of urban thermal radiation field, while the definition of the fuctor is

UAVR = ( Building covering area x building storey / Unit area ) x 100%

1 km is taken as unit are, while 320km, are taken in total in Shanghai proper. This factor is used for representing the average "canyon" effect model formed between every square kilometer of macroscopic field of 320km in shanghai proper.

Information source ; A. Interpretation database of 1/5000 Shanghai color aerophotos taken in May, 1988. B. Shanghai thermal field database from thermal IR images for materological satellite, three images in total, the time is about 10:00 May 18, 1987.

Optimization correlation models between thermal field distribution and factors, such as UVAR etc. in Shanghai proper
Let the dependent variable be Y { Y1, Y2, Y3, Y4 } and the independent variable be X { X1,X2,X3,X4,X5 }. Y1, Y2, Y3 represent the brightness temperature field of meteorological satellite images on Sept. 26, 1986, Feb. 2, 1987 and march 2, 1987 respectively (unit : C). Y4 represents the brightness temperature of thermal field of meterological satellite images on Sep 26, 1986. Feb. 2, 1987 and March2, 1987 respectively May 18, 1987 (Unit C) X1 is UAVR, the definitions of X2, X3, X4 and X5 are

X2 : Urban waters area rate = ( Waters area / Unit area ) x 100%

X3 : urban vegetation area rate = ( Vegetation area x Unit area ) x 100%

X4 : urban cement surface area rate = (Cement surface area / Unit area ) x 100%

X5 : urban roof tile surface area rate = (Roof tile surface area x Unit area ) x 100%
1 km is taken as the unit area for all of those mentioned above, and their optimization models are as follows :


In four optimization models above, the test values F of independents are shown in table 1.

Table 1: Checking the significance of each independent in equation
Independent X1 X2 X3 X5 X5
Value F
No.of equation
2-1 95.39 5.303 - 5.758 -
2-2 47.02 20.39 - - -
2-3 29.05 23.41 - - -
2-4 232.5 44.46 - 14.90 14.42

Analysis of results
  1. It can be known by analyzing the results of optimization models that the distribution of urban thermal field is mainly dependent on the factor of UAVR which is one of major source for the energy base of urban "heat island". The greater the difference of every square kilometer for this factory is, the greater the canopy density of urban macroscopic space is and the stronger the "urban canyon effect" is: the smaller the difference is, the smaller the canopy density is. The thermal flux of earth surface can be easily diffused and naturally sparse. Obviously its physical implication is clear, it is one of the main reasons for producing macroscopic landscape difference between urban and rural thermal field and causing the microscopic difference of thermal field within the city.

  2. The conclusion of the test value F in the optimization models has been further demonstrated by the equation (2-5), namely, UAVR is the dominant factor, then the other factors is in this order : waters, cement and roof tile, while vegetation factor is cancelled in each optimization model, that means the contribution of vegetative is not great. Due to Shanghai bordering on the East china sea and having a network of waterways, such as the Huangpu River and the Suzhou Creek mingled I urban centre, the area of its waters are much greater than vegetative areas, so the contributions of its waters rank the its second. It should be indicated that the contributions of waters and vegetation factors to thermal field are generally negative in our regression analysis. Yet, in equation (2-1), the coefficients of water area rate and cement surface area rate take the opposite symbols to other optimization models, which is mainly related to seasonal change of thermal radiation field, the equation (2-1) was taken just at the end of summer or the beginning of autumn. After the net solar radiation energy was absorbed by water the net solar radiation energy in summer the heat stored in water body reaches the maximum, so the water temperature is the highest one (in general, solar radiation energy absorbed by water surface will be 10 - 20% more than that by land surface). During the process of seasonal change in solar radian which takes a sudden turn and then drops rapidly, the temperature of water body keeps high at daytime, as well as at night. The thermal capacity of the cement surface is greatly reduced, while the releasing heat rate of the cement is much greater than those of water surface and other factors, which forms the peculiarity of changing brightness temperature field of each earth surface structural factor at this period.

    The improvement and regulation of local radiation temperature field by vegetation can be discovered from the interpretation result of aerial thermal IR scanning image in shanghai. The area of high temperature with low vegetation rate (<9%) amounts to 48-79%* total area of three large industrial regions of Shanghai city, while vegetation rate in low-temperature radiation regions is the highest (>34%) in the whole city.

  3. It is shown in optimization models that the statistical effect of the contributions of UAVR to thermal field is clear. Owing to lack of the information of artificial energy consumption (mainly referring to fired coal, oil and gas), which therefore, cannot be added into the regression analysis. It can be known from the result of comparing the grade diagram of TM thermal field distribution in 1987 with that of energy consumption status in Shanghai investigated artificially in 1985 that the identity of TM thermal field with map of energy consumption is almost up to 100% (see fig 1 and fig2) at the same time good match between distribution ideal on the whole (see fig.3) by which it had been shown that UAVR considered as generalized artificial heat really reflects its ability of energy storage and heat carrying.


    Fig.1 Energy consumption distribution in Shanghai in 1995


    Fig.2 Thermal field distribution of TM image in May 18, 1987.


    Fig.3 Grade diagram of UAVR in Shanghai proper


  4. The contribution of UAVR to thermal field varied with season. It has been discovered after analyzing metrological satellite images that the contribution of this factor is the grates in autumn, while ranks the second in winter. In addition, the authors have found out that the effect of waters factor n urban thermal field in greater in winter and spring, while smaller in fall.

  5. Through this paper, we realize that the calculating accuracy of simulating the urban "canyon" model in terms of digitized factor of UAVR is related t resolution of thermal IR scanning image we use and to the size of the smallest statistical unit in color aerophoto interpretation. As soon as the database is established, the accuracy can be completely determined according to the requirements. It is much superior to wind tunnel simulation and instrument measurement.
Conclusion
By adopting the result of regression analysis of the interpretation data of large scale color aerophotos i.e. urban underlying surface structural types matched with thermal IR image data fro metrological satellite and Landsat TM, it is first time to be recognized that UAVR is the fundamental factor forming the thermal field temperature in urban district which is higher than suburban. It is also the dominant reason for the difference of thermal field within city. The feasibility and advantages of urbancanyon" model digitally simulated by UAVR are demonstrated, A new theory and methods have been provided for further studying energy equilibrium mechanism of urban "heat island and the atmospheric diffusion near earth surface in the city.

References
  • Zhou shuzhen et al: Trends of urban climatic study in foreign countries. Urban Climate and Regional Climate, East China Normal Publishing House, 1989, P285-288.
  • Helmut E. Landsburg: Metropolis Climatology, translated by Zheng Shizhong, published by Taibei Mr. Xu's Foundation in 1988, P-53-143.