Comparison of Urbanization and Environmental Condition in Asian Cities using Satellite Remote Sensing Data
Makoto Kawamura, Sanath Jayamana, and Yuji Tsujiko
Dept. of Architecture and Civil Engineering
Toyohashi University of Technology
1-1 Hibarigaoka, Tempaku Cho, Toyohashi Shi, Aichi 441, Japan
Tel: (81)-532-47-0111 Fax(81)-532-44-6831
E-mail :r937654@res.tutcc.tut.ac.jp
Abstract
In this study urbanization and the environmental condition of several Asian cities have been compared using satellite remote sensing data. First the applicability of the proposed index UI and NDVI in different season and different region is examined. Then the UI-NDVI relation for 500 m grid is used to compare the urbanization condition within the cities and the UI-NDVI relation for the larger administrative units is used to compare the urbanization conditions of the cities at a regional level.
1. Introduction
Many urban areas in Asian countries fast due to rapid economic growth in these nations. This has given rise to many environmental problems that demand urgent attention. The increasing spatial concentration of people and productive activities also have environmental spillover effects outside the urban area itself, many leading to problem of a global nature. Therefore it has become necessary to develop a method to quantitatively evaluator urbanization and its relation with the natural environment condition quantitatively. The high cost and time required for traditional data collection methods have made as systematically developed urban database beyond the reach of many planning authorities in these countries. However satellite data can be applied to evaluate the changing conditions of the rapidly growing urban areas due to reported global coverage.
The objective of this study is to develop the method for the spatial evaluation of urbanization and its relation with the natural environment quantitatively using satellite remote sensing data so the urbanization and the balance between urban development and the environmental condition in the different urban areas cab be compared . this analysis will provide a basis for the discussion of sustainable development of cities. The urbanization index UI, proposed by the authors and estimated using Landsat TM data was used in this study to quantitatively evaluate urbanization. The Normalized Difference Vegetation Index 9NDVI) was used ot quantitatively evaluate the vegetation condition which represents the natural environment in ht urban area. The spatial characteristics of the indices UI and NDVI wer examined in this study by using data of this analysis it was seen that by using the UI-NDVI relation for the different cities the numbers of urbanized units and its balance with the vegetation area can be compared. The comparison was made for two classes of spatial units. One of for a 500m by 500m grid to compare the urbanization conditions at a regional level.
In this study satellite remote sensing data and conventional data of several Asian cities has been used. They are Colombo city in Sri Lanka ,Lumpur city in Malaysia, Morkpo and Ulsan Cities in South Korea , Nagoya city in Japan and several other cities in Aichi prefecture in Japan. These cities in Aichi prefecture in Japan. These cities in Aichi include Komaki, kasugai , Owariashai , Nagakute, Toyoake , Kariya , Tokai ,Obu, Seto and Obara cities. The area within the municipal council limits of Colombo city is 3370 hectares with a population of 650000. the federal Territory of Kuala Lumpur is approximately 24000 hectares with an estimated population of 1.4 million. Morpo city in South Korea has a land are of 2580 hectares with a population of 245000 and Ulasn city is 18190 hectares with a population of 708000. Nagoya city has a land area of 33000 hectares and consists of a population of 2.2 million. It is the largest city in the Aichi Prefecture.
Landsat TM data used of Colombo is of December 1987 and February 1993. a 1:50,000 land use map of 1981 of the Colombo District, and urban vegetation map of 1981 of the Colombo Urban Area and a 1:12672 building cover map of 1970 of the Colombo City was used. Statistical data used relate to the period 1991 to 1993.
Landsat TM data of Kuala Lumpur is of June 1989. a 1:50000 land use map of 1984 of Kuala Lumpur and Petaling Jaya, a 1:10000 land use and building cover map of 1988 of Kulala Lumpur and statistical data of 1983 was used.
Tm data used of Mokpo city in South Korea is of September 1992 and the Landsat TM data used in the case of ulsan city in South Korea is of January 1992.
TM data used of cities in Aichi prefecture in Japan is of July 1985 and July 1995 ( summer season ) and November 1985 and November 1991 ( winter season ). Land cover data of Nagoya city is of 1987, 1:10000 building cover maps of Nagoya and Toyohshi cities and statistical data relating to cities in Aichi Prefecture has been used.
2 The Urban Index Ui and its Effectiveness to Estimate Urbanization in Different Urnban Areas.
The Urban index shown by Eq. 1 below is computed by using Landsat TM bands 7 and 4 and has been proposed by the authors ( Kawamura et al, 1996) to estimate urbanization.
2.1 The Relation of UI with Urban Density (UD) for a 500m grid in different cities
The relation of UI with urban density (UD) measured by the building cover density has been investigated by the authors in a previous study for Colombo city in Sri Lanka ( Kawamura et al, 1996). The UD value or a 500m by 500m grid unit is the percentage of the area covered by buildings with in this unit. In this study the UI-DI relation was examined for a 500m grid for Nagoya City and Toyohashi city in Japan using TM data of both winter and summer seasons and also for Kuala Lumpur city in Malaysia. Building cover information of Nagoya and Toyohashi cities and Kuala Lumpur city has been obtained by scanning 1:10000 building cover maps. The TM data used for Nagoya and Toyohashi cities is of November 1991- winter season, and July 1995-smer season and for Kuala Lumpur city is of June 1989. the satellite data used in the space of Colombo city is of December 1987. UD and corresponding UI values were computed for the 500m gird units. Water areas have been omitted form the computation . the UI-UD relation for the four cities and different seasons is shown in Fig. 1. these figure showman approximate uniform relation for the different cities . this implies that UI can be used to compare the level of urbanization in the different urban areas .
Fig. 1 UI-UD Relation for cities
2.2 Relation of average UI value for each city with physical and social parameters of urban development
The relation between the average UI value for each city and the percentage of ht densely developed are comprising of commercial, industrial and residential area in each city is shown in fig.2.
Fig. 2 Relation between UI and the percentage built-up area.
In fig .3 the relation between the average UI value for each city and the population density in each city is shown. Form these figures it can be seen that the average UI value for each city represent its level of urbanization.
Fig. 3 Relation between UI and population Density
3. The Normalized Diference Vegetation Index (Ndvi) and it Apliccaiton to Estimate the Environmental Condition in Urban Areas.
The Normalized difference Vegetation Index (NDVI0 is a quantitative measure based upon digital values the at attempts to measure biomass or vegetative vigour. High NDVI values identify pixels covered by substantial portions of healthy vegetation . in recent times the importance of urban vegetation in preventing the deterioration of the urban environment has been well recognized. Therefore NDVI can be used as a measure of ht environmental in the urban area.
In this study NDVI is computed as shown by Eq. (2) using Landsat TM bands 3 and 4.
Fig.4 show how NDVI is related to the vegetation density in the Colombo Urban Area . the percentage vegetation in the planning units within the city of Colombo and the larger urban council units outside the city has been calculated by overlaying an urban vegetation map of the urban area with a map showing the boundaries of the spatial units. This figure shows that NDVI is strongly related to the vegetation density in the urban area and therefore is a measure of its environmental condition.
Fig. 4 Relation between NDVI and urban vegetation density
