Title: Urban expansion in Asia: evaluation, spatial determinants, and future scenarios Submitted as a report to Asian Development Bank Project “Urbanization in Asia” Date: September 10, 2012 Authors: Peilei Fan ab*, Wenze Yue a,c, Joseph Messina a, Huiqing Huang a, Xue Lia, Peter Verburgd, and Jiaguo Qi a a : Center for Global Change and Earth Observation (CGCEO), Michigan State University b c : School of Planning, Design, and Construction, Michigan State University : Zhejiang University, China d : Institute for Environmental Studies, VU University Amsterdam *: Corresponding author, email: fanpeile@msu.edu Abstract: This paper studies urban expansion in Asia by selecting cities in different regions as our case cities, including coastal mega cities of Shanghai, Mumbai, and Hangzhou, an in-land mega city of Chongqing, and major cities in dryland East Asia, specifically Urumqi, Lanzhou, Yinchuan, Hohhot, Ulaanbaatar. We evaluate the expansion of urban built-up area by relying on data processed from satellite images and aerial photos, in combination with existing land use maps of different time periods. We also used four sets of urban growth indicators to measure various drivers of urban land uses, economics and population dynamics. Taking Shanghai as a case, we further identify major driving forces for urban land conversion by using spatial socio-economic data such as population and GDP, and other spatial data such as road networks, physical attributes, distances to various sites. Moreover, we simulate future urban land use change under different policy scenarios for Shanghai. The proposed study offers support for policy makers and urban planners in land management and decision-making. Key words: Urban expansion, urban growth indicators, Asia, simulation 1 Acknowledgement: We would like to acknowledge the funding support from the National Aeronautics and Space Administration (NASA)’s Land Cover and Land Use Program through the grant to Michigan State University (NNX09AI32G) and “Urbanization in Asia” Project at Asian Development Bank (ADB). We thank Prof. Anxin Mei at East China Normal University and Prof. Bin Zhao from Fudan University in Shanghai, Prof. Yaowen Xie and Yongchun Yang from Lanzhou University, Prof. Xi Cheng and his colleagues at Xinjiang Ecology and Geography Institute, China Academy of Science in Urumqi, and Prof. Yong Liu at Southwest University in Chongqing for their support of our research, data sharing, and insights on urban land development of their respective cities. We also appreciate the support of Nathan Moore and Jianjun Ge for our research of Urumqi and Shanghai. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of NASA or ADB. 2 1. Introduction Asian cities have experienced rapid urbanization in recent years. As of 2010, the Asia and Pacific region had 43% of the population living in urban areas. Notably over the last two decades, the Asia-Pacific urban proportion has risen by 29%, more than any other region in the world (UNPD, 2010 & 2009). A well-known example, China, dramatically increased its urbanization ratio, i.e., urban population as a percentage of total population, from 18% in 1978 to over 50% in 2011. The rapid urbanization process exerts tremendous pressures on social, economic and environmental sustainability (Pickett et al., 2001). Urban sprawl is becoming a common phenomenon across the Asian continent. Although most urban expansion tend to occur in coastal cities, such as Shanghai and Mumbai, where the economy experienced the fastest growth, in recent years, large-scale urban development also occurred in traditionally resource-limited and environmentally vulnerable regions, such as cities in inland China and within the dryland regions of East Asia including Chongqing, Urumqi, Ulaanbaatar. Despite the widely acknowledged urbanization and its severe impact, most previous studies on Asian urbanization focused on individual cities, and there is a lack of systematic analysis to present a comprehensive view of Asian urbanization, largely due to difficulty in collecting land use data over long time periods. This paper evaluates the urban land expansion of nine major cities in Asia by relying on data processed from satellite images, in combination with existing land use maps of different periods. Further, using Shanghai as a case, it identifies the driving forces for urban land change and simulates future urban land use change under different scenarios. This paper will significantly improve our understanding of urbanization in Asia and offer support for policy makers and urban planners in land management and decision-making. The rest of the paper is organized as follows: Section 2 describes the study area, data, and methodology. Section 3 presents findings on urban land expansion of the selected cities, driving forces for urban expansion and simulation of land use change of Shanghai. Section 4 further discusses (1) characteristics of urbanization in different types of Asian cities, such as coastal mega cities, inland mega cities, and major cities in the dryland region of East Asia, socio-economic driving force for urban expansion, and the implication of simulation. Section 5 concludes and offers policy implications. 2. Study Area, Data, and Methodology 2.1 Study Area We selected nine cities from three countries to assess the urban expansion of major cities in East and South Asia (Figure 1). These nine cities can be classified into three different types according to their geographic locations, including coastal mega cities, inland mega cities, and major cities in the dryland region of East Asia. Their socio-economic profiles illustrated in Figure 2 show that these cities share certain common characteristics. We 3 therefore consider it meaningful to classify the cities into three general types for studying urban expansion as patterns, dynamics, and driving factors, and constraints differ significantly across different types of cities. For instance, all the selected coastal cities, such as Shanghai, Mumbai, and Hangzhou, have quite high levels of economic development, as indicated by GDP per capita, large urbanized areas, and very large urban population. In contrast, all the cities of dryland East Asia are relatively small in population as well as in urbanized areas, and have diverse levels of economic performance. Chongqing, as the only inland mega city we chose, is unique. It has a larger urban population than other major cities in dryland East Asia and even coastal cities such as Hangzhou, but is not comparable to mega cities such as Shanghai and Mumbai. It is very low in economic development levels and also has a small urban builtup area. Figure 1. Geographic locations of selected cities 4 Profile of selected cities 25000 Lanzho u GDP per capita (US $) 20000 Yinchuan Shanghai 1255 Hohhot 15000 Hangzhou 308 92 Urumqi 10000 91 176 188 425 105 5000 Chongqing Mumbai 1554 UlaanBaatar 0 0 500 1000 1500 2000 2500 3000 3500 Urban built‐up area (square kilometer) Figure 2. Socio-economic profile of selected cities1 Coastal Megacities- Shanghai, Mumbai, and Hangzhou Coastal cities in China generally have experienced rapid economic growth and started their unprecedented urbanization as early as in the 1980s. Similar to Chinese coastal cities, coastal cities in India, such as Mumbai and Calcutta, are also loci of urbanization as the country started its economic reform in the 1990s. Here we selected Shanghai and Mumbai as our case cities as they are the largest and the most vibrant economic centers 1 Note: The bubbles and the figures inside the bubbles represent the sizes of the population (10,000 persons) of the selected cities. Sources: The urban built-up areas of all cities in 2010 are obtained from our own assessment based on the satellite imageries. For Chinese cities, i.e., Shanghai, Hangzhou, Chongqing, Urumqi, Lanzhou, Yinchuan, and Hohhot, the GDP per capita data is calculated based on 2010’s data from China Statistical Yearbook 2011 (total city) and the population data (city proper) is from the statistical yearbook of respective province or city in 2011 (Shanghai Statistical Yearbook, 2011; Zhejiang Statistical Yearbook, 2011; Chongqing Statistical Yearbook, 2011; Urumqi Statistical Yearbook, 2011; Gansu Statistical Yearbook, 2011; Ningxia Statistical Yearbook, 2011; Inner Mongolia Statistical Yearbook, 2011). For Urumqi, the city proper also deduct Dabancheng district due to its rural orientation. For Ulaanbaatar, population data of 2010 is from http://www.citypopulation.de/Mongolia.html; GDP per capita data is Mongolia Statistical Yearbook 2011. For Mumbai, the population data of 2010 is from the United Nations. (United Nations, Department of Economic and Social Affairs, Population Division. 2012. World Urbanization Prospects, the 2011 Revision. http://esa.un.org/unpd/wup/GIS-Files/gis_1.htm), GDP per capita data of 2010 is from http://www.docin.com/p195719235.html. 5 of their respective countries, the scale and speed of their urbanization reflect the trend of first-tier cities in Asia’s emerging countries. Our selection of Hangzhou is based on consideration that the city represents second-tier cities in the coast area, the coast provincial capitals, which have experienced similar urbanization frenzy during the period but have their own features due to their special status in their respective provinces and competitions among second-tier cities in the coastal area in China and, to a larger extent, in the region. Shanghai (31°12’N 121°30’E) is located at the confluence of the Yangtze River and the East China Sea. Situated on an alluvial plain with an average elevation of 4 meters above sea level, the city proper has a total area of 6340.5 km2. Located in the subtropical monsoon climate zone, Shanghai has four distinct seasons with hot, humid summers and cool, wet winters. After China signed the Nanjing Treaty with the United Kingdom in 1842, Shanghai was forced to open as a port city for foreign trade and quickly grew from a small fishing village to an international metropolis as well as China’s largest economic center and has remained the position since then. Despite falling behind other coastal cities in terms of speed of economic development at the beginning of the economic reform initiated in 1978, Shanghai eventually caught up with other coastal cities and resumed its leading economic position in China after the central government established the Pudong New Area in the 1990s. Shanghai’s city core is divided into two parts by the Huangpu River, a tributary of Yangtze river: (1) the west of the river that has been the city center since the nineteenth century, and (2) the east of the river, the newly developed Pudong New Area since the 1990s. As the largest economic center in China, Shanghai had a population of 23 million in 2010, with 14 million officially registered and 9 million as a floating migrant population. Among the 14 million official residents, 12.6 million are urban population. Hangzhou (30°15’N 120°10’E) is located 180 km southwest of Shanghai in the Yangtze River Delta. Similar to Shanghai, Hangzhou has a humid subtropical climate with four distinctive seasons. It has a total administrative area of 16596 km2, with 3068 km2 in the city proper and a total population of 4.35 million, with 73% as urban population in 2010. Regarded as one of the most beautiful and historic cities in China, Hangzhou is built around the West Lake and has numerous tourist spots, such as the West Lake, Qiantang River, and the recently preserved Xixi Wetland. Benefiting from its proximity to Shanghai, Hangzhou accelerated its economic growth after the economic reform, particularly after 1992. Its GDP per capita is RMB 86,329 (equivalent to $12,751) in 2010, listed as the seventh of China’s 35 major cities2. Similarly to other large coastal cities in Asia, Hangzhou experienced rapid urban expansion and transformed itself from a medium city to a mega-city. However, to distinguish itself from other large cities in the Yangtze River Delta area, especially Shanghai, Hangzhou has promoted itself as a city with good life quality through various planning efforts. Part of the planning efforts involve Hangzhou, as a pilot city selected by the central government, to test various land policies such as land banking and using land trusts and land bonds to finance a land reserve system (Zhu, 2007). 2 The 35 major cities include all provincial capitals plus Dalian, Ningbo, Xiamen, Qingdao, and Shenzhen, but not include Lhasa due to the lack of data. 6 Mumbai (18°58’N 72°49’E), bounded by the Arabian Sea to the west, is located at the mouth of the Ulhas River on the western coast of India. With an average elevation of 14 meters above the sea level, it has a total area of 603.4 km2. Mumbai has a tropical wet and dry climate with the southwest monsoon season from June to September. With 12 million population in 2011 (India Census), Mumbai is the largest city and the most important economic center in India; it generated 6.16% of India’s GDP in 2008. In 2010, its GDP per capita is $2800 (Rs 125000), more than two times of the national average ($1211, Rs 54527). With textile production and seaport activities as initial economic engines, the city has diversified its economy into sectors such as information technology, engineering, and health care. Especially, the city experienced the boom of its economy since the economic liberalization reform in 1991. Inland Megacities-Chongqing Chongqing (29°33’N 106°34’E) is located at the southeast part of Sichuan Basin and the upper reach of Yangtze River. With a total area of 82,401 km2 including the city proper and the counties under its administration, it is the largest direct-controlled municipality, (the area of city proper is 2735 km2), 2.39 times of the total area of Beijing, Tianjin, and Shanghai, the other three directly-controlled municipalities. With the surrounding mountains to its north, east, and south, Chongqing is known as the “Mountain City.” Chongqing has a monsoon-influenced humid subtropical climate, with most of the year very humid. Along with Nanjing and Wuhai, Chongqing is known as one of the “Three Furnaces” of the Yangtze River” because of its very long, hot, and humid summer. It is also known as the “Fog City,” as on average, it has over 100 days of fog per year. Chongqing has been an important economic center and transportation hub of Southwest China. During the second Sino-Japanese War (1937-1945), many universities and factories relocated from the coastal area to Chongqing, the relative safe inland city and the wartime capital at the time, to continue the education and manufacturing production against the Japanese army. Due to the massive relocation, Chongqing quickly developed itself from an inland port to a heavily industrialized city despite the heavy bombing of the Japanese army during the period. The city was demoted to a sub-provincial city within Sichuan province in 1954, but in 1997 it was separated from Sichuan Province and made a direct-controlled municipality. Due to its inland and remote location, Chongqing traditionally has been an important industrial base for weapons research, development, and manufacturing. However, the city has diversified its industrial base, especially since 1997, into sectors such as food, autos, chemicals, textiles, machinery and electronics. Currently it is the third largest center for motor vehicle production and the largest for motorcycles. Although by 2010 the city had GDP of $117 billion, its GDP per capita was only $3544 far lower than the national average of $10464. With a total population of 6.12 million in its city proper, about 4.25 million are urban population. Major cities in the dryland region of East Asia Located in the arid region of Northwest China and Mongolia, Urumqi, Lanzhou, Yinchuan, Hohhot are provincial capitals of Xinjiang Uyghur Autonomous Region, 7 Gansu Province, Ningxia Hui Autonomous Region, and the Inner Mongolia Autonomous Region, respectively; Ulaanbaatar is the capital city of Mongolia. Most of the cities are developed along rivers and are surrounded by mountains, as typical river valley cities in arid regions. The cities feature semi-arid climates, with low annual temperature and precipitation and long cold winters; while Yinchuan and Hohhot have hot and humid summers, Urumqi has hot, dry summers and Ulaanbaatar has brief and warm summers. As the provincial or national capitals, they play important roles in economic development, and political and cultural activities of their respective regions/countries. Having a population range between one and three million (Figure 2), they all have experienced rapid urbanization and vast urban sprawl in the recent decades. Characteristic land use changes are the expansion of urban land at the cost of agricultural land and the conversion of other types of lands for agricultural usage. Urumqi (43°48’ N, 87°35’ E), literally “the beautiful pasture land” in the ancient Mongolian, is located at the north slope of Tianshan Mountain and the south edge of the Junggar Basin in the central north part of Xinjiang. Lying between mountains to the southwest and northeast, the city is composed of the Chaiwobao-Dabancheng Valley in the south and the alluvial plains of the Urumqi and Toutun rivers in the north. 2,500 km (1,400 miles) from the nearest coastline, Urumqi is also the most remote city from any sea in the world. Urumqi has a semi-arid climate, with precipitation of 286 millimeters (11.4 in) and 2523 sunshine hours in an average year. The hot summer (average temperature around 30°C in July) is in direct contrast with its cold winter (average temperature -7.4°C in January), with summer slightly wetter than winter. With a population of 2.29 million in its city proper in 2010, Urumqi has 49 ethnic groups, and the non-Han ethnicity population is 25% of the total population. Multiethnic groups live in compact, mixed communities consisting of primarily Uyghur, Han, Hui, Kazak, Mongolian, Kirgiz, and Xibe ethnicities. The city was once an important town on the northern route of the Silk Road, essential to Sino-foreign economic and cultural exchanges. Lanzhou (36°02’N 103°48’ E) is located in the upper course of the Yellow River and bounded by mountains on the south and north sides. Due to its unique geography, Lanzhou has developed in a “Dumb-bell” shape. The distance between the west and the east of the city is about 35 km whereas the distances from the north to the south vary dramatically from 2 km to 8 km. In 2010, the city proper’s total population reached 1.3 million and 0.9 million of them are urban. Belonging to the middle temperate zone and with the average altitude 1520 m, Lanzhou has a moderate climate with annual average temperature of 11.2°C, notably without freezing winters or hot summers. Like other cities in Northwest of China, Lanzhou is dry with an annual precipitation of 327 mm, primarily occurring from June to September. Although daily temperature varies widely, it has plenty of sunshine with sunlight hours of 2446 and more than 180 frost-free days per year. As one of the oldest industrial bases of China, Lanzhou is the largest industrial city in the upper stream of the Yellow River and an important base of the raw materials industry in China’s West. At the intersection of inland China, Northwest of China, and Tibet Plateau, Lanzhou is the transportation center of northwestern China with four of China’s main railway lines and six national highways converging here. 8 Yinchuan (38°28’ N 106°16’ E) is located in the middle of the Yinchuan Plain with the Helan Mountain to its west and the Yellow River running through the city from southwest to northeast. With a desert climate and an annual average temperature of 9.0°C, Yinchuan’s winters are cold, windy, and dry whereas summers are hot and humid. Yinchuan has a long history of development, especially agricultural and commercial activities. Irrigation systems in Yinchuan were developed during the Han Dynasty to improve wheat and rice production (Chen and Gao, 2007). Yinchuan’s urbanization accelerated post 1949 when the P.R. China was established: the total population of the city proper grew from 200,000 in 1949 to nearly 1.99 million by 2010, with a nonagriculture population increasing from about 30,000 to 1.29 million. The city is also a center for the Muslim (Hui) minority people that account for 25% to 30% of Yinchuan’s population. Hohhot (40°49’ N 111° 39’ E), the “green city” in Mongolian, is located on the Tumuochuan Plain, the south central part of Inner Mongolia Autonomous Region, surrounded by Daqing Mountain to its north and the Yellow River and Hetao Plateau to its south. Hohhot has a population of 1.21 million (0.92 million urban population) in its city proper in 2010. It has a cold semi-arid climate with a low annual average temperature of 6.7°C and the annual precipitation of 400mm. The city has long, cold and very dry winters and hot, somewhat humid summers, with strong winds especially in spring. Although most residents are Han (87.2%), Hohhot has a significant presence of ethnic minorities, especially Mongolian (8.6%) and Hui (1.6%). Founded by Mongol ruler Altan Khan in the late 16th century, the city has a rich cultural background. Serving as the region's administrative, economic, and cultural centre, it is also called the "Dairy Capital of China" due to two giant dairy producers headquartered in the city – Mengniu and Yili. Ulaanbaatar (47°55’ N 106°55’ E), meaning "Red Hero" in Mongolian, is located in the north central part of Mongolia in a valley on the Tuul River at the foot of the mountain Bogd Khan Uul. Ulaanbaatar is the coldest national capital in the world, due to its high elevation, relatively high latitude location hundreds of kilometers from any coast, and the effects of the Siberian anticyclone. It has a monsoon-influenced, cold semi-arid climate featuring long, cold and dry winters and brief, warm summers. As the capital of the country, Ulaanbaatar is the largest city in Mongolia. Hosting one third of the total population of Mongolia (Bolormaa, 2010), its population reaches 1.15 million in 2010. Apart from the political importance of the Ulaanbaatar, the city contributes 48% of industrial output, 52% of construction, 41% of trade, 75% of hotel and restaurant services as well as 56% of transportation and communications in Mongolia (Herro et al, 2003). Ulaanbaatar’s urban development is concentrated along the Tuul River valley with an east-west built-up area of approximately 24 km long. 2.2 Data & Methodology Urban growth indicators 9 In this paper, we adopt four sets of indicators to measure various aspects of the urban land use and population dynamics based on previous work conducted by other researchers (e.g., Huang et al, 2007; Kasanko et al, 2006; Schneider and Woodcock, 2008; Schwartz, 2010; Tsai, 2005) (Table 1). The first and second sets of indicators measure size and growth of urban built-up areas, the most fundamental aspect of urban land use, and their relation to non built-up areas. The third and fourth sets of indicators link population with land use, measuring population density in urban built-up area and total area, as well as how population occupies the available built-up space by examining the ratio of population growth to the growth of built-up areas in different periods. Table 1. Urban land use indicators used for the selected cities Category Indicator 1. Built-up area 1.1 Built-up area Unit Description Km2 1.2 Growth in built-up area 1.3 Percentage change, annual percentage change 2. Density of built-up area Km2 built-up area in 1990, 2000, 2010 new urban built-up area during the periods 1990-2000, 2000-2010 rate of built-up area expansion for the periods of 1990-2000, 2000-2010 2.1 Urban land density 2.2 Percentage change in urban land density 3. Population density % 3.1 Urban population density in urban land 3.2 total population density in total land 4. Urban density 4.1 Population growth in contrast with urban growth % urban land as a percentage of all land in 1990, 2000, 2010 change of urban land density for the periods of 1990-2000, 2000-2010 % person/Km2 urban population density in built-up area in 1990, 2000, 2010, = urban population/builtup area total population density in 1990, 2000, 2010, = total population/total land person/Km2 population growth in contrast with urban growth for the periods of 1990-2000, 20002010, = change in population /change in built-up land person/Km2 Satellite image data and processing In this study, we mainly use urban built-up land and associated characteristics to assess urban expansion. The urban built-up land of our selected cities was derived from multisource satellite imagery including Landsat 7 Enhanced Thematic Mapper plus (ETM+), Landsat 5 Thematic Mapper (TM), and SPOT5. Detailed information on all satellite images used is listed in Table 2. All level 1G Landsat images, downloaded from the USGS website, have been geometric corrected to the UTM coordinate system. After radiometric enhancement, one year SPOT 5 images of Shanghai, purchased from SPOT Image Corporation, were registered to the Shanghai ETM+ images, and resampled (RMSE <0.5 pixels) using the nearest neighbor algorithm to a nominal pixel size of 5m×5m. The administrative boundary datasets of China, India, and Mongolia were downloaded from the geographical information center of China and the GADM organization (Available at http://gadm.org), respectively. The Asia map is obtained from ShareGeo Open (Available at http://www.sharegeo.ac.uk/handle/10672/22). 10 To extract urban built-up land of our selected cities, we used an integrated approach combining supervised classification, unsupervised classification, and visual interpretation. The classification and post-classification enhancements were completed using Erdas Imagine 9.3. Except for the urban built-up land data of Shanghai in 2010, derived from SPOT5, all other data were extracted from Landsat. For the coastal cities with low average elevation, such as Shanghai, Hangzhou and Mumbai, we followed the steps below. First, a supervised classification with maximum likelihood algorithm was performed to derive the primary urban built-up land data. Second aided by comparing with Google Earth and other high-resolution images, a visual interpretation classification was conducted to enhance the above classification result. Third a serial of post-classification processes were employed to refine the classification. We followed this general process for the other aforementioned cities. For the major cities in dryland East Asia, the terrain complexity made the task of automatically extracting the urban information difficult except for Yinchuan. Therefore, visual interpretation, in addition to supervised and unsupervised classification, was particularly important for identifying urbanized areas, including large townships or villages in suburban areas and the concrete surfaces in the cities. This additional step was completed for Urumqi, Lanzhou, Hohhot and Ulaanbaatar. We found that a machine-classified result resulted in lower accuracies. We conducted an accuracy assessment for the 2010 urban land maps, based on independent literature and Google Earth high-resolution images. We consider our classification sufficiently accurate with kappa coefficients ranging from 0.80 to 0.93 and producer and user accuracies of all cities over 0.9 except for Hangzhou’s producer accuracy (0.83) and Chongqing’s user accuracy (0.87) (Table 3). Yinchuan, as expected, has slight lower values of kappa coefficient and producer and user accuracies than most of the other cities. Table 2. Description of satellite images of selected cities Sensor Shanghai Hangzhou Mumbai Chongqing Urumqi Lanzhou Yinchuan Hohhot Ulaanbaatar 1990 Path Row TM 118 38 TM 118 39 TM 148 47 TM 128 39、 40 142 30 TM 131 35 TM 129 33 TM 126 32 TM 131 27 TM Date 08/11 /1989 07/23 /1991 11/09 /1992 09/15 /1988 10/09 /1990 02/03 /1989 08/04 /1989 08/22 /1990 09/10 Sensor ETM+ 2000 Path Row 11838119 39 ETM+ 118 39 TM 148 47 ETM+ 128 39、 40 142 30 TM 131 35 TM 129 33 TM 126 32 TM 131 27 ETM+ 11 Date 06/14 /2000 10/11 /2000 11/13 /1999 05/22 /2001 04/19 /2000 08/12 /2000 04/16 /2000 05/24 /1998 08/31 Sensor 2010 Path Row SPOT * ETM+ 118 39 TM 148 47 ETM+ 128 TM 143 39、 40 2930 TM 131 35 TM 129 33 TM 126 32 TM 131 27 Date * 09/21/ 2010 11/14/ 2010 09/20/ 2010 04/14/ 2010 07/18/ 2011 07/01/ 2010 07/12/ 2010 07/31/ /1990 /2001 2010 Note: *Shanghai 2010’s data is derived from the following SPOT images: SCENE 5 295-286 09/04/22 02:29:29 2 J SCENE 5 295-287 09/04/22 02:29:38 2 J SCENE 5 295-288 09/06/03 02:23:09 2 J SCENE 5 296-287 10/03/16 02:27:58 2 J SCENE 5 297-288 10/03/16 02:28:07 2 J The numbers after SCENE5 indicate the SPOT Scene ID in the format of the SPOT grid reference system (GRS) Table 3. Accuracy assessment for urban built-up area of 2010 Producer Accuracy Shanghai Hangzhou Mumbai Chongqing Urumqi Lanzhou Yinchuan Hohhot Ulaanbaatar 0.98 0.83 0.97 0.95 0.97 0.98 0.90 0.96 0.96 User Accuracy Kappa 0.95 0.89 0.92 0.80 0.95 0.93 0.87 0.80 0.91 0.88 0.95 0.93 0.90 0.87 0.92 0.88 0.94 0.90 Other data, particularly economic statistics, and population are from data sources such as the China Statistical Yearbook, Statistical Yearbook of the provinces and the cities, and planning and government policy documents (NBS, 1991, 2001, & 2011; Shanghai Bureau of Statistics, 1991, 2001, & 2011; Hangzhou Bureau of Statistics, 1991, 2001, & 2011; Chongqing Bureau of Statistics, 1991, 2001, & 2011; Urumqi Bureau of Statistics, 1991, 2001, & 2011; Gansu Bureau of Statistics, 1991, 2001 & 2011; Ninxia Bureau of Statistics, 1991, 2001, & 2011; Inner Mongolia Bureau of Statistics, 1991, 2001, & 2011; Mongolia Bureau of Statistics, 2011). CLUE-s Model & Logistic Regression CLUE-s Model We used the CLUE-s model for our urban land simulations. The Conversion of Land Use and its Effect (CLUE) was designed for the dynamic land use change simulations at the national and continental scale using the empirical analysis between the land use and its driving factors (Veldkamp and Fresco, 1996; Verburg et al.; 1999). Because of its inability to work with high-resolution data, the Conversion of Land Use and its Effect at Small regional extent model (CLUE-S) was developed, which incorporates the competition of spatial and temporal land use dynamic at multi scales, from 20 to 1000 m in case studies (Verburg et al.; 2002; Verburg and Veldkamp, 2004; Overmars et al.; 2007). The CLUE-S model has been widely and successfully applied in many regional researches, such as Europe (Erdogan et al.; 2011) and Asia (Liao et al.; 2010; Luo et al.; 2010; Zhang et al.; 2003; Verburg et al.; 2002). The CLUE-s model includes two 12 fundamental segments of simulations, namely the non-spatial model and the spatial model. The non-spatial model refers to the investigation of relations between land use and the driving factors through empirical methods. The spatial model determines the allocation of each land use grid by calculating the suitability map. In this research, we use the CLUE-s model and use Shanghai as a case. In order to use the CLUE-s model to simulate Shanghai’s urban land till 2020, we first obtained historic urban land maps and identified spatial determinants for urban land use changes. We derived urban land maps of Shanghai of 2000, 2005 and 2010 from satellite images (including TM, ETM+ and SPOT images) by the process described earlier. These maps allowed us to characterize the spatial pattern of Shanghai’s urbanization from 2000-2010. To be able to simulate the future land use change, we needed to identify the underlying driving forces, determined by both the human and the nature systems (Liu et al., 2007); we achieved this through logistic regression. Logistic regression As urban landscapes are affected by both human and nature systems (Liu et al.; 2007), it is of great importance to examine the relationships between land use and the driving factors. Logistic regression is used in the CLUE-s model to calculate the suitability of any location for certain land use types. The probability for converting location i into land type k can be calculated through a binomial logit model. The logistic regression model is denoted as follows: Log (Pi/(1−Pi)) =β0 +β1 X1i +β2 X2i + … … +βnXni (1) Where Pi is the probability of location i for the occurrence of the considered land use type k. Log (Pi/(1−Pi)), the log transformation of the ratio of the probability that conversion occurred (Pi) to the probability that conversion does not occur (1-Pi), can be expressed as a linear combination function of the explanatory variables Xni, the location factors. Using the actual land use patterns as dependent variable, the coefficients (βn) are estimated through the logistic regression. The value of Relative Operating Characteristics (ROC) is used to validate the model performance (Pontius and Schneider, 2001). We used 12 variables (Table 4), including several socioeconomic variables, geographical attributes and land use variables, to identify the most influential variables in the urbanization process. These variables were chosen based on literatures (Zhang et al.; 2011; Han 2009; Deng et al.; 2009). With the 2000 land use map as an initial map, we used these variables in the Clue-s model to calculate the suitability of each grid for urban land conversion thus simulating the urbanization of Shanghai until 2020. Table 4. Details of variables used in the logistic regression Meaning Notation Unit Generation Method 13 Source Distance to Main Roads DMR Km Calculated the Euclidean distance to main roads for each cell in ArcGIS 10. Own calculation Distance to CBD DCBD Km Calculated the Euclidean distance to CBD for each cell in ArcGIS 10. Own calculation Own calculation Time Cost to CBD TCOST Hour Calculated the time cost distance for each cell based on 2000's road network data in ArcGIS 10. Industrial Land Density IDEN % Percentage of industrial land in 1km * 1km grid Own calculation Percentage of Potential Industrial Land PPI % Percentage of agricultural land in 1km * 1km grid Own calculation Gong, 2007 Land Planning of 1999-2020 LP n.a. Dummy variable for whether or not the cell falls in the 2000's industrial land plan Gross Domestic Product per Capita GDP RMB 10,000 per person Survey SBS,2001 Foreign Direct Investment per Capita FDI US$ 10,000 per person Survey SBS,2001 Income INC RMB Survey SBS,2001 Population Density PDEN 10,000 persons/km2 Survey SBS,2001 SBS,2001 SBS,2001 Higher Education Percentage HEDUR % Calculated based on census data. The percentage of people with college or higher education Immigrant Rate IMGR % Survey Second, to examine future land use pattern in Shanghai from 2000-2020, we designed three different scenarios for our CLUE simulation, considering different urban growth rates and whether or not green land protection policy (Shanghai Bureau of Urban Planning, Land, and Resources, 2001 and 2002) is implemented (Table 5). These three scenarios are: (1) a base scenario that continues the historic trend of urban land conversion without any green land protection policy; (2) a decelerating scenario where 14 urbanization follows a decelerating trend without any green land protection policy; and (3) a restriction scenarios where urbanization follows a decelerating trend but with a green land protection policy. The 2000 land use map is used to initialize the simulation while the land use maps of 2005 and 2010 are used to assess the results of simulations. Table 5. Three scenarios for CLUE-s simulation Scenario Name Description Base Deceleration Restricted Urbanization occurs at a linear rate following the historic trend without any green land protection policy (the scenario is designed for comparison purpose) Urbanization occurs at a decelerating rate (urban land conversion follows a nonlinear trend) and without any green land protection policy Urbanization occurs at a decelerating rate (urban land conversion follows a nonlinear trend) and with green land protection policy 3. Findings 3a. Urban growth indicator and urban expansion Our urban growth indicators illustrate that these nine cities have experienced extensive urbanization since the 1990s. Overall, costal cities, including Shanghai, Hangzhou and Mumbai have much larger urban built-up areas than other cities. It is also worth noting that while Chinese coastal cities slowed down their expansion rates, all other cities increased their expansion rates from 2000-2010, enhancing their urbanization processes. At the individual city level, the annual growth ratios of urban built-up area varied from 2% (Ulaanbaatar, 1990-2000) to 27% (Yinchuan, 2000-2010). 15 Figure 3. Expansion of urban built-up area of selected cities, 1990-2010 16 Urban built‐up area (km2) UlaanBaatar Hohhot Yinchuan Lanzhou Urumuqi Chongqing Mumbai Hangzhou Shanghai 0 500 2010 1000 2000 1500 1990 2010 2000 2000 2500 3000 1990 Figure 4. Urban built-up area of selected cities, 1990, 2000, and 2010 Urban land density UlaanBaatar Hohhot Yinchuan Lanzhou Urumuqi Chongqing Mumbai Hangzhou Shanghai 0% 10% 20% 2010 2000 30% 40% 50% 1990 Figure 5. Urban land density (the percentage urban built-up area to the total area), 1990, 2000, and 2010 17 Urban population density (person/km2) UlaanBaatar Hohhot Yinchuan Lanzhou Urumuqi Chongqing Mumbai Hangzhou Shanghai 0 5000 10000 15000 20000 25000 30000 35000 40000 2010 2000 1990 Figure 6a. Urban population density, 1990, 2000, and 2010 Total population density (person/km2) UlaanBaatar Hohhot Yinchuan Lanzhou Urumuqi Chongqing Mumbai Hangzhou Shanghai 0 1000 2000 2010 2000 3000 4000 5000 1990 Figure 6b. Total population density, 1990, 2000, and 2010 18 Urban density change UlaanBaatar Hohhot Yinchuan Lanzhou Urumuqi 2000‐2010 Chongqing 1990‐2000 Mumbai Hangzhou Shanghai 0% 50% 100% 150% 200% 250% 300% Figure 7. Urban density change, 1990, 2000, and 2010 Urban land density further confirmed the urbanizing trend of the Chinese coastal cities. While Shanghai and Hangzhou have 44% and 27% urban land density respectively, all other cities have less than 20% urban land density. Among them, Ulaanbaatar and Chongqing have the lowest urban land density, 3% and 5%, respectively. Urban population density indicated that Mumbai, Chongqing, and Lanzhou have much higher urban population density than the other cities, over 11,000 person/Km2, significantly more than Shanghai or Lanzhou. For total population density, Mumbai had the greatest density with 4460 person/Km2 and Shanghai held a close second with 2227 person/Km2. Excepting Ulaanbaator in 1990-2000, urban density change, the ratio of urban population change in contrast of urban built-up land change, are below 100%, indicating that urban population did not increase as fast as urban built-up land, i.e., urbanization in our selected cities happened physically, reflected by land use change, whereas the urban population has followed the physical urbanization. It is interesting to note that some cities, such as Shanghai, Hangzhou, Chongqing, and Urumqi, have increased their urban density change in the 2000-2010 than that of 1990-2000, whereas others have the reverse trend, which indicates an accelerating sprawl pattern of urban expansion. Coastal Mega cities Among all cities, Shanghai has the largest urban built-up area and increased its urban built-up area more than five times from 1990 to 2010, reaching a total urban built-up area of 2815 Km2, far above the other selected cities. For each of 1990-2000 and 2000-2010, the city added over 1000 Km2 to its urban built-up land. While before 1990 the city 19 mainly expanded along the axis of northeast- southwest, Shanghai has expanded development towards east and west since 1990. From 2000-2010, most of the urbanization took place around the existing urban areas, such as the city center and the district centers, and along the northwest to southeast axis, changing the original city’s development pattern along the northeast-southwest axis. It is worth noting that Shanghai’s urbanization rate has slowed down since 2005. While urbanized area has been increased by 45.2% to 2461 km2 from 2000 to 2005, it only increased 18.3% from 2005 to 2010 (Figure 8). Figure 8. Expansion of urban built-up area, Shanghai, 2000-2010 Our investigation indicates that Hangzhou expanded urban built-up area in its city proper over 7 times in 20 years, from 118 km2 in 1991 to 841 km2 in 2010, with a much faster rate in the second decade. Although the newly added urban built-up area is mainly located in the north of Qiantang River around the main city area, the area of south of Qiantang River also experienced fast growth. Hangzhou’s urban expansion reveals a close relationship between newly developed lands with the locations of original towns, such as Xiaoshan in the south of Qiantang River, and Linping in the northeast of main city. The urban expansion in Mumbai has accelerated over the past two decades, as its urban built-up area expanded 2.5 times, mainly surround the Bombay Bay, from 263 km2 in 1992 to 666 km2 in 2011. During these two decades, the relative expansion rate was evidently higher in the east of Bombay Bay (New Mumbai and Nawa Sheva) than the west side (Greater Mumbai), which has revealed that most new urban construction land in Mumbai was promoted by the development of the satellite city (New Mumbai), independent of the old urban district. As an island city surrounded by water, Mumbai suffers serious space restrictions, therefore continuous urban expansion in Mumbai is suppressed, in contrast, leapfrogging urban development dominated during these two decades, at significantly higher rates. In-land Mega City – Chongqing 20 The built-up area in the main city of Chongqing has experienced rapid growth since 1988, expanding urban built-up area 4.3 times, from 67 km2 in 1988 to 296 km2 in 2010, mainly towards north and south. At earlier periods, the core urban area was built at the intersection of the internal valleys of the Yangtze and Jialing Rivers and near the edges of nearby mountains. However, Chongqing’s urban spatial pattern has undergone rapid transformation from concentration to diffusion during the period from 2001 to 2010 and has been dominated by polycentric development and outer area urban growth. Dryland East Asia Urumqi has experienced fast urban land expansion from 1990, its urban built-up area expanded from 212 Km2 to 289 Km2 in 2000, but sharply increased to 412 Km2 in 2010. A slightly rotated (towards west) T shape features the current urban built-up of Urumqi, with wide area in the north and narrow stripe in the southern part, respectively. Urumqi’s urban expansion has been affected by natural factors, administrative boundaries, and transportation factors. As a river valley city, the initial population of the city settled along the old river bed (Hetan, in Chinese) that runs southeast to northwest but later development expanded the city to the northwest and southeast along the valley. Some of the oasis ecosystems, which were cultivated during and shortly after the civil war that ended in 1949 (officially), were converted into impervious urban lands. In addition to the natural factors, the administrative boundary of Urumqi city also constrained urban expansion as Miquan, and Changji are closely bordered Urumqi. Finally, the urban expansion in the late 1990s along the major transportation routes was believed to be a result of the rapid development of public transportation and increased use of private vehicles. The urbanized area of Lanzhou grew over two times from 1990 to 2010, mostly occurring between the existing urban built-up areas and at the northern bank of the Yellow River. The city experienced fast expansion in the last decade. Similar to Urumqi, Lanzhou’s expansion is constrained by its geography. It is worth mentioning that in the recent decade, the city has leapfrogged its surrounding mountains and established new industrial zones as well as residential communities outside the original core. Among the five cities of dryland East Asia, Yinchuan experienced the most dramatic expansion. The urban area only occupied 47 km2 in 1990, but grew to 65 km2 in 2000, then skyrocketed to 240 km2 in 2010. Two of its major urban districts, Xixia and Xinqing, separated by farmland in 1990, have become connected over time. Hohhot increased its urbanized area from 89 Km2 in 1990 to 117 km2 in 2000, then to 229 km2 in 2010. The rate of urban expansion in Hohhot increased after 2000 with an annual area increase of close to 10 km2 /year. While development occurred mostly along the eastern urban fringe area from 1990 to 2000, urban built-up lands were added to the rest of the urban periphery area from 2000 to 2010. Although Ulaanbaatar fell behind the other major cities in China’s Northwest in overall urbanized rates and the speed of urban expansion, it nevertheless expanded noticeably from 82 Km2 in 1990 to 142 Km2 in 2010, especially after 2000. Examining highresolution imagery from the Google Earth, we found that the settlement areas in the 21 northern hilly areas accounted for most of Ulaanbaatar’s urban expansion. This echoes Amarsaikhan (2011) that the newly added urban built up areas were concentrated in the original agricultural lands along the Tuul River and the mountainous areas in the north and within the traditional Ger areas. Further, satellite towns emerged in response to the high land prices in the city center (Amarsaikhan, 2011). 3b. Spatial determinants and simulation of Shanghai Through logistic regression, we identified four variables as influential variables (significance at the 0.05 level) (Figure 9). They are: the distance to main roads (DMR), industrial land density (IDEN), population density (PDEN), and land use planning (LP), which are also identified by others as significant factors for urban land changes in Shanghai (Deng et al. 2005; Han 2009; Zhang et al. 2011;). The four significant driving factors have different impacts on the presence of urban lands. For the distance to main roads, every 1 km further decreases the possibility of urban land presence by 7.01%. The other 3 variables make positive contributions to the urban lands’ presence. Every 1% of increase in the industrial land density and every 1000 persons per km2 increase in population density increased the presence of urban lands by 6.77% and 11.67%, respectively. The influence of land planning is the most significant among the four factors. The possibilities of urban lands’ presence are 55% more in the places with urban land plans. With 2000’s land use map as an initial map, we then used these four variables in the Clue-s model to calculate the suitability of each grid for urban land conversion thus simulating the urbanization of Shanghai until 2020. Figure 9. Four significant variables identified as spatial determinants for Shanghai’s urban land conversion Our Clue-s model simulation indicates a lasting trend of urbanization in Shanghai from 2000 to 2020 (Figure 10). Generally, the urbanization happens around the city core and existing urban areas in suburbs. Moreover, most of the urbanization takes place along the axis from northwest to southeast, modifying the original city’s shape that developed along an axis from northeast to southwest. Our simulation illustrates distinct spatial 22 patterns with different scenarios. For instance, more urbanization is observed from 2010 to 2020 in the base scenario while more urbanization appears before 2010 in the decelerating scenario. Further, the decelerating scenario causes the depletion of nonurban lands in the city center before the peripheral urbanization happens whereas the restricted scenario maintains the non-urban areas for protecting the green land, but forces the urbanization towards the suburban area, especially in Fengxian district. Figure 10. Clue-s simulation of three scenarios 4. Discussion 4.1 Characteristics of urbanization in Asia Coastal mega cities Our findings first confirm that coastal mega cities have led urbanization over other types of cities of this study, measured by indicators related to urban built-up land and urban population. Coastal cities, including Shanghai, Hangzhou and Mumbai, have much larger urban built-up areas than other cities, but they have decreased their expansion rates in comparison with the other cities. Further, the large urban density of Chinese coastal cities indicates a limited potential for further urbanization in comparison to the other cities. All coastal cities measured have very large base urban populations. Conversely, current urban population density is not as high, especially as compared with Chongqing or Lanzhou where the urban built-up potential area geographiclly limited leading to extremely high urban population density. It is also interesting that Chinese coastal cities have significantly higher urban density change in the 2000-2010 period than 1990-2000 period, indicating that the increase of urban population is catching up to the past production of converted urban built-up area. Another distinct characteristic of urbanization of coastal mega cities is the polycentric urban development pattern. Past research on Hangzhou (Yue et al, 2010) and others (Wu, 1998; Han, 2005) have indicated that urban land conversion mainly occurred near the city core or sub-centers, leading to a polycentric pattern of development, rather than 23 chaotic sprawl. For instance, Mumbai’s most recent urban construction has concentrated in New Mumbai, its satellite city in the east of Bombay Bay. In recent years, Hangzhou has expanded in different directions at various speeds, shifting to a polycentric urban pattern through radial expansion. Along the main transportation corridors, the values of the mean patch sizes of urban patches displayed multiple peaks, and the landscape-shape index maintained a horizontal trend in urban fringes, reflecting the formation of polycentricity (Yue et al, 2010). Further, as edge growth and spontaneous growth accounted for 40%- 50% and 30 - 40% of urban growth, respectively, and infill growth was responsible for only a small proportion of urban growth, indicating that dispersed urban patches have been increasingly agglomerated into big ones, especially along road corridors. Inland mega cities (case of Chongqing) Chongqing’s urban development is severely constrained by its geographic location as a peninsular city formed by two rivers and surrounded by mountains. For a long time, Chongqing had a small and concentrated urban built-up area built on limited hilly areas of the intersected valleys of the Yangtze and Jialing Rivers. Therefore, to counter its quite large urban population base, Chongqing’s urban population density was extremely high, especially in the 1990, comparable to Mumbai’s level. Nevertheless, the recent decade witnessed Chongqing’s development beyond the surrounding mountains, with bridges and tunnels making land beyond the Yuzhong Peninsular available for urbanization. The relatively low urban land density also indicates that unlike Shanghai, Chongqing can still convert a large amount of non-urban land to urban built-up land, thus facilitating urbanization far beyond its existing urban core. Chongqing’s urbanization has been closely associated with its strategy of transportoriented urban development. In recent years, Chongqing has undergone remarkable construction of its infrastructure, as its hilly topography requires higher unit investment. An impressive project initiated in 2003, named the eight-hour-Chongqing traffic project, has set up a transport network that allows one commuting from the urban core to the rural counties by expressways within eight hours. Since 2008, a new traffic project has been under construction, targeting at connecting multiple urban clusters with commuting time less than half an hour, using inner and outer ring expressways, light rails and subways, bridges over the rivers, and tunnels across the mountains. Major cities in dryland East Asia Through literature review on major cities in dryland East Asia, we identified three common trends of urbanization and land conversion: (1) the increase of urban land at the cost of other land, (2) a typical land conversion pattern of “grass land => agricultural land => urban land,” and (3) the reverse trend to increase forest land mainly through government intervention. 24 First, our findings confirm other studies on the rapid urban land expansion from the 1980s to the 2010s of our selected cities, at the expense of other types of non-urban land. Second, while urban land expanded mostly through the loss of agricultural land, agricultural production drives conversion from other types of land, especially grass land or forest land, as shown by situations in Urumqi (Chen et al, 2010), Lanzhou (Dong et al, 2005; Huang and Zhang, 2009; Zhang et al, 2005; Zhen et al, 2007), Yinchuan (Chen and Gao, 2007; Du, 2007; Zhu and Zhang, 2010), Hohhot (Du, 2003; Li et al, 2008; Sheng, 2004; Zhang et al, 2008), and Ulaanbaatar (Amarsaikhan et al, 2011). Chen and Gao (2007)’s study on urban land conversion from 1996 to 2003 in Yinchuan illustrates that urban built up land increased fastest and took large areas of existing agricultural land while agricultural lands maintained their area by taking other types of land such as pasture and forest lands. Further, Chen et al (2010)’s research on Urumqi from 19902005 indicates that agricultural land increased dramatically in Xinjiang, including Urumqi Metro area with forest land and pastures as main contributors. Third, government policies on converting agricultural lands back to forests have had a significant impact on the increase of forest land for Lanzhou (Huang& Zhang, 2009), Yinchuan (Chen and Gao, 2007; Du, 2007), Hohhot (Sun et al, 2010; Zhang et al, 2008), and Ulaanbaatar (Amarsaikhan et al, 2011). From 1990 to 2006, forest lands gained the greatest total area in Lanzhou, mainly due to the conversion from pasture and agricultural lands. This conversion occurred under proactive land management and investment from the Lanzhou municipal government. It is important to consider that the geographic locations of our selected cities have contributed to certain characteristics of urban expansion and environment challenges. The arid region cities exemplify four urban island phenomena: heat island, rain island, dry island, and dark island (Ren et al, 2006; Li and Tan, 2009). Due to the constraints of surrounding mountains and other geographic factors such as location of rivers, elevation, and soil types, most development options are spatially restricted. Further, most of the cities experience severe ambient air pollution, especially during the winter months when coal-generated pollutants are trapped in the city’s air by surrounding mountains and atmospheric inversions. Another distinguishing environmental challenge shared by the cities is the aggravation of scarce water resources. The case cities have temperate continental climate with little rainfall and high evaporation rates, exacerbating the scarcity of water resources, as exemplified by Urumqi. Such a fast rate of urban expansion is of major concern for long-term sustainability of the cities in dryland East Asia. This concern is even more warranted in light of recent changes in the region’s climate (Lioubimtseva et al, 2005; Schmidhuber and Tubiello, 2007). Despite the water scarcity due to the arid climate of the region, industrial and agricultural activities place high demands on the water. For instance, in Urumqi, available water per capital is only 489 m3, a quarter of the national average and one tenth of Xinjiang’s average. Since the economic reform, the water usage of Urumqi has increased almost five times from 1978 to 2000, but the overexploitation of underground water has lowered the underground water table significantly (Chen, 2008). 4.2 Socio-economic driving factors 25 We would like to highlight several socio-economic factors that have been extremely relevant for recent urban expansion of our selected cities: (1) economic development, especially industrialization; (2) institutional factors such as urban land market controls and national development policies; and (3) social characteristics such as history, ethnicity, and cultural factors. First, urbanization of Asian cities has closely corresponded to their economic development, especially industrialization. The Chinese coastal cities Shanghai and Hangzhou have led urbanization over the other cities, mainly due to their existing developed urban economy and because of the further opening of their economies in the 1990s. The private sector, and especially foreign investment, has facilitated the urban transformation in Hangzhou (Liu et al, 2011). In contrast, in-land cities and major cities in dryland East Asia have facilitated their urbanization only after 2000, when their economic growth rates accelerated. Urbanization and economic development in coastal mega cities have been well-studied (Wu, 1998; Wei and Li 2002; Han et al, 2009; Luo and Wei 2009; Fan and Qi, 2010; Yue et al, 2010; Liu et al, 2011), here we focus on linking the economic development, especially industrialization with urbanization in Chongqing and other major cities in dryland East Asia. Chongqing’s industrialization contributed to its urbanization. Chongqing, the largest city and the prefectural city in the western China, is of historical significance as a national wartime capital and was designated a traditional industrial base in the era of “third-line” defense. At that time, Chongqing was developed into one of the largest industrial bases in China through the relocation of manufacturing units from coastal areas and via newly built military enterprises. Industrialization not only boosted the urban economy, but also facilitated the increase of urban population and conversion of urban land use. Today most of military enterprises have been converted to civilian ones, such as Chang’an Automobile Group, Jialing Moto Group and Construction Engineering Group. In recent decades, Chongqing’s industrialization has been enhanced through its linkages with the global economy as large international firms, such as the Ford Motor Company, HewlettPackard (HP) from the United States, and Foxconn from Taiwan, which have all opened subsidiaries in Chongqing. Similarly, economic growth, especially industrialization, is the most distinguishing factor behind the rapid urban expansion of our selected cities and is highly associated with the pollution loads of the cities. In our field visit to Urumqi, we witnessed the large-scale conversion of agricultural or grazing land to urban land along the urban fringe, mostly for industrial uses. Other cities followed the same trajectory (Liang et al, 2010; Li et al, 2008). The intensification of three major air pollutants, i.e., particulate matter, sulfur dioxide, and nitrogen dioxide, in our selected cities indicated the linkage between industrialization, urbanization and urban environment degradation. As the wealth of city residents increased, life style changes and social infrastructure upgrading has become another major cause of urban land conversion (to urban residential land), air pollution (due to automobile usage), and water shortages (due to increased per capita usage as well as increase of urban population). 26 Second, institutional factors, such as the development of urban land/property market and the national development policies, have substantially affected the urban development of our selected cities. In the post-reform era, China set up a new type of urban land tenure system whereby the government retains the ownership of land but sells land use rights (LUR) through a market mechanism (Chan, 1999; Li et al, 2000; Liu, 1997). Nevertheless, a dual-track land use system exists in which both administrative land allocation and market LUR transfers are utilized simultaneously. Furthermore, China started to transition into a market-based urban housing system in 1993 (Chen et al, 1996; Lim and Lee, 1993; Tong and Hays, 1996). The changing land/property market became an important driver for urban sprawl in China, expanding urban boundaries at an accelerating rate. Large-scale private or quasi-private investments were particularly favored by local authorities, due to the potential revenues that such land transactions bring to local governments (Zhang and Fang, 2004). All major cities in China have experienced rapid urban expansion and the astonishing rise of real estate prices, including provincial capitals, in China’s coastal, inland, and arid regions. For instance, the market has played an increasingly important role in shaping Hangzhou’s urban landscape, particularly by driving the relocation of state owned enterprises (SOEs), forming additional housing demand from migrants, and the involvement of foreign direct investment (Liu et al, 2011). The national development policy in China and planning and development in Mongolia after the market reforms have had considerable impact on urban development. It is well known that Shanghai’s urban development was greatly facilitated after Shanghai Pudong Area was designated by the State Council as a Special Development Zone. For Hangzhou, administrative annexation and the set up of development zones serve as the primary forces for making more land available for urban development and forming subcenters. Further, the rapid urban sprawl of Chongqing and major cities in China’s Northwest has to be considered in the context of China’s national development policy. The West China Development Program (WCDP) set forth by the central government in 2000 had a great influence on the development of our selected cities and their respective regions at large. One of the central goals of the WCDP was to decrease the inequality of regional development, as the first two decades of China’s economic reform mainly benefited east coast areas, and the western region fell far behind the national average in GDP per capita. Before the WCDP, from 1996 to 1999, Urumqi’s GDP per capita grew at a slow 2.6%. However, after the WCDP, the city’s economy exploded, and its GDP per capita grew at a rate of 14.5% from 2000 to 2006, higher than the national average. In particular, Chongqing’s urban development has benefited from many preferential policies and investments from the central government, especially after Chongqing was designated by the central government as the fourth prefectural city in China, and the only one in China’s west, in 1997. Preferential policies, such as “West Development Program” policies, and reforms for coordinated and balanced urban-rural development, have allowed Chongqing to test out new approaches of urbanization. Particularly, the Chongqing Liangjiang New Area was established with the approval of the State Council in 2010 to model the development of Shanghai Pudong New Area and Tianjin Binhai 27 New Area. Covering a total area of 1,205 km2 and 550 km2 for construction, Liangjiang New Area will play an important role in industrialization and urban development in Chongqing. Similarly, Ulaanbaatar’s urban development and environment conditions have been significantly shaped by institutional factors, especially the market economy. The political change in 1990 promoted the market economy and completely changed the urban development process in Mongolia. While before 1990, urban development in Ulaanbaatar as well as other Mongolian cities was entirely planned, owned, and controlled by the government, after 1990, many urban developments occurred without any control and the private sector became significantly involved, leading to the increased commercialization of the city’s center and inner city region, urban expansion in formal and informal Ger areas, the formation of satellite towns around Ulaanbaatar and increasing suburbanization featuring single family houses (Amarsaikhan et al, 2011). In particular, the expansion of Ger areas, appearing after 1990, have become a major consequence of Ulaanbaatar’s urbanization, housing 58% of its urban residents and occupying 70% of the geographic area of Ulaanbaatar (Amarsaikhan et al, 2011; Amarbayasgalan, 2008). Most Ger areas are built with insufficient or without necessary infrastructure including heating, potable water, sewage, solid waste collection, and public transit. Ger areas have become a major source of urban environment pollution and the de facto slums (Herro et al, 2003; ADB, 2008; Guttikunda, 2008). Finally, urban development of our selected cities should be examined through a social lens, because of their unique historic, ethnic, and cultural characteristics. Urumqi, Yinchuan, and Hohhot are provincial capitals of China’s ethnic autonomous region with high concentrations of ethnic minorities such as Uyghur, Huis, and Mongol. The recent tragic ethnic clash in 2009 between the Han majority and Uyghur minority attracted national and international attention. The Chinese government’s ability to effectively build harmonious ethnic relationships in Xinjiang and other regions of Northwest, either through economic development, migration strategy, policy incentives, or a combination of all three measures, will be critical to the sustainability of these cities. 4.3 Future prospect (implications of simulation) Based on spatial determinants associated with biophysical and socio-economic characteristics, we simulated the patterns of land use change of Shanghai from 2000 to 2020. From 2000 to 2020, the city will expand along the axis from northwest to southeast, thus a more spatially even distribution of urbanization is likely to take place than before 2000. As we expected, the growth rates have a profound impact on the city’s landscape. The faster the city expands, the more non-urban lands will be converted to urban lands, causing more loss in landscape diversity and agricultural lands. The long and discontinuous edges of the urban land patches create enormous interactive zones between urban and rural areas; these zones warrant attention from policy makers as they are the most dynamic areas for physical and social transformation. Urban planning policies have proven to be important based on the results of our simulation as clearly the policy of 28 green land protection leads to a more complex landscape. Despite government involvement in such green land protection policies, the continuing urbanization are encroaching more agricultural land in suburb areas. This, together with the expanding city’s urban land, may cause severe environmental problems, such as urban heat island, air pollutions, etc. 5. Conclusion In this paper, we evaluated urban land expansion of nine cities in different regions of Asia by mainly relying on data processed from satellite images and using five sets of urban growth indicators to measure various aspects of the urban land use and population dynamics. We found that all nine cities have experienced extensive urbanization from 1990 to 2010 and non-urban land has been converted to urban land at a much higher rate than population, but cities in different regions have shown distinct variations and internal dynamics. Further, except for Urumqi, all cities seem to have a more fragmented urban built-up landscape. For instance, overall coastal cities have much larger urban built-up areas than the other cities but the urban expansion rates of Chinese cities have slowed during the period of 2000-2010 compared to the earlier period of1990-2000. All other cites increased their expansion rates during the same period. Using Shanghai as a case, we also identified the driving forces for urban land change as the distance to main roads, industrial land density, population density, and land use planning to simulate future urban land use changes under different scenarios. We found that the decelerating scenario (urbanization at a decelerating rate and without green land protection) causes the depletion of non-urban lands in the city center before the peripheral urbanization happens. In contrast, the restricted scenario (urbanizes at a decelerating rate but with green land protection) maintains the non-urban areas for the public service purpose, but accelerates the rate of urbanization into suburban areas. We discussed the characteristics of urbanization in Asia by regions: costal mega cities led urbanization over other types of cities and are also moving towards a polycentric urban development pattern. Chongqing’s urban development, as an in-land mega city, is severely constrained by its geographic position but closely associated with its transportoriented urban development strategy in recent years. For major cities in dryland East Asia, they typically increase urban lands at the cost of other types of land, but have also a land conversion pattern “grass land => agricultural land => urban land.” In these dryland cities, government intervention, in recent years, has been somewhat effective in reversing the urbanization trend by increasing regional forest lands. We highlighted relevant socio-economic factors for recent urban expansion including, economic development (industrialization) and institutional factors. First, urbanization of Asian cities has closely corresponded to their economic development, especially industrialization. Second, institutional factors, such as the development of urban land/property markets and the national development policies, have substantially affected the urban development trends. Third, the unique historic, ethnic, and cultural characteristics of cities have also affected urbanization process, and clearly indicate that 29 we should pay more attention to these issues in order to promote the sustainability of these cities. There are obvious limitations of our current studies. We only selected nine cities from three countries, across three types of regions. The representativeness of the nine selected cities for the whole Asia is limited. However, our research did reveal common characteristics of urban expansion through our urban growth indicators across these nine cities and does provide a starting point for future research based on land use data derived from satellite images. 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