Rate Of Urban Expansion Research Articles

Exploring Forest Change Spatial Patterns in Papua New Guinea: A Pilot Study in the Bumbu River Basin

Papua New Guinea is a country in Oceania that hosts unique rain forests and forest ecosystems which are crucial for sequestering atmospheric carbon, conserving biodiversity, supporting the livelihood of indigenous people, and underpinning the timber market of the country. As a result of urban sprawl, agricultural expansion, and illegal logging, there has been a tremendous increase in land-use land cover (LULC) change happening in the country in the past few decades and this has triggered massive deforestation and forest degradation. However, only a few studies have ventured into quantifying the long-term trends and their associated spatial patterns—and have often presented contrasting responses. Herein, we intended to assess the extent of deforestation and the rate of urbanization that happened in the past 33 years (1987–2020) in the Bumbu river basin in Papua New Guinea using satellite imagery—for the years 1987, 2002, 2010, and 2020—and Geographic Information System (GIS) tools. On performing image classification, land use maps were developed and later compared with Google Earth’s high-resolution satellite images for accuracy assessment purposes. For probing into the spatial aspects of the land-use change issues, the study area was divided into four urban zones and four forest zones according to the four main cardinal directions centered in the urban and forest area centers of the 1987 image; subsequently, the rate of urban area expansion in each urban zone was separately calculated. From our preliminary analysis and literature survey, we observed several hurdles regarding the classification of regenerative forests and mixed pixels and gaps in LULC studies that have happened in Papua New Guinea to date. Through this communication paper, we aim to disseminate our preliminary results, which highlight a rapid increase in urban extent from 14.39 km2 in 1987 to 23.06 km2 in 2020 accompanied by a considerable decrease in forest extent from 76.29 km2 in 1987 to 59.43 km2 in 2020; this observation favors the presumption that urban and agricultural land expansion is happening at the cost of forest cover. Moreover, strategies for addressing technical issues and for integrating land-use change with various socioeconomic and environmental variables are presented soliciting feedback.

Exploring Annual Urban Expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal Features and Driving Factors in 1986–2017

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the largest bay areas in the world. However, the spatiotemporal characteristics and driving mechanisms of urban expansions in this region are poorly understood. Here we used the annual remote sensing images, Geographic Information System (GIS) techniques, and geographical detector method to characterize the spatiotemporal patterns of urban expansion in the GBA and investigate their driving factors during 1986–2017 on regional and city scales. The results showed that: the GBA experienced an unprecedented urban expansion over the past 32 years. The total urban area expanded from 652.74 km2 to 8137.09 km2 from 1986 to 2017 (approximately 13 times). The annual growth rate during 1986–2017 was 8.20% and the annual growth rate from 1986 to 1990 was the highest (16.89%). Guangzhou, Foshan, Dongguan, and Shenzhen experienced the highest urban expansion rate, with the annual increase of urban areas in 51.51, 45.54, 36.76, and 23.26 km2 y−1, respectively, during 1986–2017. Gross Domestic Product (GDP), income, road length, and population were the most important driving factors of the urban expansions in the GBA. We also found the driving factors of the urban expansions varied with spatial and temporal scales, suggesting the general understanding from the regional level may not reveal detailed urban dynamics. Detailed urban management and planning policies should be made considering the spatial and internal heterogeneity. These findings can enhance the comprehensive understanding of this bay area and help policymakers to promote sustainable development in the future.

Land mismatches, urban growth and spatial planning: A contribution to metropolitan sustainability

The unequal growth of population and buildings in metropolitan regions reflects dispersed urban expansion. This study illustrates an operational framework grounded on a diachronic analysis of urbanization processes in advanced economies that provides a comprehensive evaluation of the mismatch between resident population and building stock. Studying the urban cycle of a European city (Athens, Greece), a mismatch indicator was derived at the municipal level as the elasticity rate of resident population and total building stock changes over 7 time intervals between 1920 and 2010. Results indicate that divergences in population and building stock growth rates increased since the early 1980s. The population-buildings mismatch displays an increasingly asymmetric spatial distribution, evidencing more or less accelerated paths toward dispersed settlements that may outline unsustainable forms of land management. Municipalities with a compact morphology at the beginning of the study period showed a higher rate of self-contained urban expansion than municipalities with more dispersed settlements. A comparative analysis of the impact of town planning on enlarging population-settlement mismatches was finally proposed as a basic knowledge to sustainable land management in (rapidly expanding) metropolitan regions.

National urban land-use/cover change since the beginning of the 21st century and its policy implications in China

China has experienced rapid urban expansion since the beginning of the 21st century. Although many previous studies have explored the forces driving urbanization, how policies drive these changes at the national scale has not been fully examined. This research aims to delineate the regional differentiations of urban expansion and related impervious surface area (ISA) density and reveal the socioeconomic and macropolicy factors causing these changes. The result shows that national urban land expanded from 4.26 × 104 km² in 2000 to 6.90 × 104 km² in 2015 at an unprecedented rate, with an average increasing rate of 1760 km²/yr since 2000. The spatial metrics of ISA density diverted from a low-density sprawl mode during 2000–2010 to a dense expansion mode during 2010–2015, with the highest ISA density of 70.70% in 2015. Regionally, the rate of urban expansion and ISA growth reduced in the coastal zone in 2010–2015. In contrast, urban expansion accelerated in the western and central zones, due to the China Western Development Plan and the Rise of Central China Plan initiated in 1999 and 2006, respectively. Although the concept of “Sponge city” (an urban water management system) was proposed in 2013, the national ISA density still increased due to urban infilling. The overarching issue that must be seriously considered is the tradeoff between the magnitude of urban expansion and ISA density and building sustainable and livable cities in an era of urban transformation.

Rank-size Distribution of Cities and Municipalities in Bangladesh

This paper examines and updates the rank-size distribution of cities and municipalities in Bangladesh between 1990 and 2019 based on two criteria: (1) built-up urban areas; and (2) population. The distribution of built-up urban areas and population are compared to provide a robust theoretical underpinning of Zipf’s law for future urban developmental planning framework. The data on built-up urban areas is extracted from land cover classification using Google Earth Engine and the population data is obtained from the decennial censuses. The comparison of the conformity to Zipf’s law indicated contradictory results. While a greater proportion of the population has been increasingly concentrated in the smaller and midsized cities over the last three decades, built-up urban areas, on the other hand, have been mostly clustered in two largest cities— Dhaka and Chittagong—accounting for 50 to nearly 60 percent of the total built-up urban areas. These results shed light on the magnitude of continued spatial inequalities in urban development amongst cities and municipalities in Bangladesh despite there being an overall increase of evenness in the distribution of population over time. These results imply an unsustainable rate of urban expansion in Bangladesh and reinforce the need for the exploration of policies and regulations targeted at guiding the rate and direction of evenness in urban expansion.

Revisiting Spatiotemporal Changes in Global Urban Expansion during 1995 to 2015

This study used global land-use data interpreted from remote sensing images to quantitatively analyze the spatial and temporal changes in global urban expansion over the past 20 years, as well as the source, rate of expansion, and urban growth patterns of newly added urban land (NAUL) around the world. Some main conclusions included the following. (1) Globally, NAUL was mainly derived from agriculture, grassland, and forest. These three types of land use contributed 68.93%, 10.10%, and 9.76%, respectively, to the land sources for NAUL. (2) Eight countries/regions (CRs)—India, Pakistan, Nigeria, Bangladesh, Philippines, Ethiopia, Egypt, and Vietnam—had significant potential for future urban growth and were designated as the “Emerging Urban Growth G8.” Also, Africa will continue to lead global urbanization after Asia. (3) Global urban expansion was still in a typical stage of edge expansion. Urban expansion in Oceania was the most aggregated, whereas in Asia, it was the most diffuse. (4) Apart from African CRs, the urban expansion rate in most CRs was higher than the population urbanization rate, so urbanization does not pose a significant threat to global food security. In addition, for CR with NAUL>1,000 km2, the level of economic development had a positive effect compact urban development. This study mapped large-scale urban expansion using unified data, a unified definition of urban boundaries, and over a unified time span.

High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015

High-resolution global maps of annual urban land coverage provide fundamental information of global environmental change and contribute to applications related to climate mitigation and urban planning for sustainable development. Here we map global annual urban dynamics from 1985 to 2015 at a 30 m resolution using numerous surface reflectance data from Landsat satellites. We find that global urban extent has expanded by 9,687 km2 per year. This rate is four times greater than previous reputable estimates from worldwide individual cities, suggesting an unprecedented rate of global urbanization. The rate of urban expansion is notably faster than that of population growth, indicating that the urban land area already exceeds what is needed to sustain population growth. Looking ahead, using these maps in conjunction with integrated assessment models can facilitate greater understanding of the complex environmental impacts of urbanization and help urban planners avoid natural hazards; for example, by limiting new development in flood risk zones. The world keeps urbanizing. This study finds that since 1985 global urban lands have expanded four times faster than previously recognized and faster than population is growing.

Urban expansion analysis through Remote Sensing and GIS in Semarang-Indonesia

Urban areas and their expansion are important roles for the analysis of the urban ecological status, indicators for global ecological health, and sustainable development. Although urban expansion can improve the living conditions of the residents, it will also lead to various urban environmental and ecological issues. Semarang City is the center of a functioning metropolitan city of Kedungsepur (Kendal, Demak, Ungaran, Semarang Regency, Salatiga City, Semarang City and Purwodadi, Grobogan Regency) so that the development of various sectors in the Semarang City region shows a positive increase. This study aims to measure urban expansion and analyze its spatial patterns from 2005 to 2015 using remote sensing and GIS. The analysis method to measure urban expansion and developing patterns uses the urban expansion intensity index and local Moran’s I, and quantification the typology of urban expansion. The results showed that the annual growth rate of urban expansion in Semarang city increased in the last decade, which was 2.7 km2/year (2005-2011) to 5.8 km2/year (2011-2015). The intensity of urban expansion is more dominated by low intensity followed by very rapid, moderate and rapid intensity. The results of Local Moran’s I analysis also show the formation of urban growth clusters out of the city center that leads to the south. Between 2005 and 2015 the type of urban expansion was dominated by the type of edge expansion.

Trends in urban land expansion, density, and land transitions from 1970 to 2010: a global synthesis

The physical expansion of urban areas lead to lasting impacts on landscapes and livelihoods. Here, we conduct a global synthesis of trends in urban land expansion, in urban population densities, and lands converted into urban from 1970 to 2010. We find that small-medium urban areas lead their larger counterparts in both rates of urban land expansion and decreases in urban population densities. Urban population densities have consistently declined only in India, China, North America, and Europe with significant exceptions across city sizes. Over 60% of the reported urban expansion was formerly agricultural land with China, Southeast Asia, and Europe in the lead. Counterfactual analysis suggests that, due to the decrease in urban population densities, an estimated 125 000 km2 land was converted to urban land uses that could have otherwise remained in cultivation or as natural vegetation. In particular, in India and Nigeria, with much of their populations dependent on agriculture, 85% and 30% more land, respectively, was converted to urban land due to decreasing urban population densities. With increasing urbanization, proactive management of urban land expansion, especially in small and medium cities, will be critical for saving agricultural lands in peri-urban regions while creating equitable and affordable urban landscapes.

Application of Geospatial Techniques and Logistic Regression Model for Urban Growth Analysis in Limbe, Cameroon

Little is known about the nature of ecosystem loss, rampant changes in land use and land cover (LULC) and urban growth taking place in Limbe. The aim of this study is to analyze urban growth in Limbe, Cameroon from 1986-2019 using geospatial techniques and Logistic Regression Model (LRM). Landsat Thematic Mapper (1986), Enhanced Thematic Mapper+ (2002) and Operational Land Imagery/Thermal Infrared Sensor (2019) were utilized in this study. The images were classified into land cover classes using supervised image classification algorithm in ENVI software. The classification output was subjected to LRM application to evaluate urban growth. Image difference of urban growth between 1986 and 2019 was calculated as dependent variable and the independent variables were produced by calculating the Euclidean distance and Buffer of built-up, waterbody, road and farmland as driving factor for urban growth. Future urban growth was determined for 2035 using the Land Change Modeler in IDRISI Selva. Classification overall accuracy for the three date were not less than 99%. LRM results show a good fit with relative operation characteristic of 0.8344 and Pseudo R2 of 0.21. Analysis of LULC shows that built-up increased from 3.5% (1986) to 17.6% (2019). An urban land expansion rate of about 23% was observed for 2035. Transition probability matrix revealed high probability (0.6345) of build-up to remaining build-up by 2035, while the probability for it changing to waterbody, bare land, farm land and vegetation are 0.1099, 0.0459, 0.1939 and 0.1221, respectively. This study successfully demonstrates the application of geo-spatial techniques and LRM for land use/land cover change detection and in understanding the urban growth dynamics. It also identifies the potential areas of future urban growth, which can help land use policy planners for making optimum decisions of land use planning and investment.

Indices based assessment of built-up density and urban expansion of fast growing Surat city using multi-temporal Landsat data sets

The population growth in urban areas leads to the expansion of built-up area which leads to a number of serious problems like environmental pollution, destruction of urban ecology, climatic modification etc. In this study, we have tried to assess the linkages and association between population growth and built-up expansion in Surat city. Landsat satellite data (TM, ETM+ and OLI/TIRS) has been used for 1991, 2001, 2011 and 2019 to extract the built-up area while the demographic data of the city was obtained from the Census of India and SMC. The built-up area has been extracted using index based built-up index (IBI) method. The association between urban expansion rate (RUE) and population growth rate (PGR), distribution of population and built-up area and the population and built-up density was analyzed using linear regression technique. The result shows that both the population and built-up area of Surat has increased rapidly but the rate of increase of built-up area is higher than the population. The statistical analysis shows that the density of population and built-up area have very strong-positive relationship while their distribution have moderate-positive relationship. On the other hand the PGR and RUE shows positive but weak relationship. The main finding of the study is that the growth rate of population and urban area are not identical to each other but their distribution and density have strong relationships with each other. The association between PGR and RUE is not always significant because of the variation in their rate.

粤港澳大湾区生态系统格局变化与模拟

PDF HTML阅读 XML下载 导出引用 引用提醒 粤港澳大湾区生态系统格局变化与模拟 DOI: 10.5846/stxb201906101228 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学青年科学基金项目（71804180） Evolution and simulation of ecosystem patterns in Guangdong-Hong Kong-Macau Bay Area Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:快速城市化是导致粤港澳大湾区生态系统时空格局变化的主要驱动力之一，模拟生态系统变化趋势对于优化区域土地利用格局、防控城市化的生态风险具有重要意义。以2000、2005、2010、2015、2018年5期土地利用数据，分析该区域生态系统格局演变，并运用CA-Markov模型模拟2025年的生态系统格局。研究结果表明：（1）2018年大湾区的森林、农田和城镇为主要生态系统类型，分别占区域总面积的53.99%、22.67%和14.51%。（2）2000-2018年农田、森林、湿地面积分别下降了1983、740、278 km2，城镇和草地面积分别上升了2896、103 km2，城镇面积增长的主要途径是对周围农田、林地和湿地的侵占，草地面积增长是因为管理经营不善导致部分林地退化为草地。（3）大湾区的景观多样性和均匀度下降，景观正在向小斑块趋势发展，空间连通性下降，破碎度增加。（4）模拟2025年的生态系统格局发现，与2018年相比，城镇面积增长了609 km2，农田和森林分别减少了309 km2和316 km2。基于大湾区生态系统格局变化与模拟发现，快速城市化区域中，落实耕地保护红线和生态保护红线制度、保护重要生态空间完整性，对于降低城市化的生态风险具有重要作用。 Abstract:Rapid urbanization has been one of the primary drivers of ecosystems change in the Guangdong-Hong Kong-Macau Bay Area (the Great Bay Area). To understand these spatio-temporal dynamics, it is important to simulate ecosystem trend and patterns during regional land use optimization, preventing and controlling the ecological risks of urbanization. Based on land use-land cover (LULC) data for the years 2000, 2005, 2010, 2015 and 2018, this paper analyzed the evolution of ecosystem types and landscape patterns in this region. A CA-Markov model was used to simulate ecosystem pattern in 2025. The results showed that: (1) the forests, farmland and urban land were the main ecosystem types in the Greater Bay Area in 2018, accounting for 53.99%, 22.67% and 14.51% of the total area, respectively. (2) From 2000 to 2018, the area of farmland, forest, and wetland decreased by 1983 km2, 740 km2 and 278 km2 respectively, and the area of urban and grassland increased by 2896 km2 and 103 km2, respectively. The growth in urban areas came from the conversion of surrounding farmland, woodland and wetland. Due to poor management, portions of woodland degraded to grassland, leading to the growth of the latter. The change rate of ecosystem types in the Greater Bay Area had obvious periodical characteristics. The fastest period of urban expansion was from 2000 to 2005, leading to a rapid decline in farmland. The rate of urban expansion and farmland reduction slowed after 2005.The speed of forest reduction accelerated in 2000-2015 and slowed down in 2015-2018. The grassland area increased from 2000 to 2015, with a slow growth rate from 2000 to 2010 and a rapid growth rate from 2010 to 2015, then decreased from 2015 to 2018. From 2000 to 2018, the wetland area continued declining with the same speed. (3) Under the effects of demographic urbanization and LULC urbanization, the landscape pattern changed significantly. Fragmentation and separation increased, and the diversity and evenness of the landscape decreased. The Contagion index (CONTAG) increased and the Division index (DIVISION) increased, indicating that the fragmentation and heterogeneity of the landscape increased. The largest patches of farmland and forestland were destroyed, and the Number of Patches index (NP) increased. Urban patches showed a spreading growth, while the urban landscape's degree of fragmentation and separation fell. (4) The ecosystem pattern in 2025 was simulated based on a CA-Markov model, and the accuracy test was carried out by comparison with the actual data in 2015; the Kappa coefficient was 0.94. Compared with 2018, the urban area is projected to increase by 609 km2, extending outward along the larger urban patches, mainly in Guangzhou, Dongguan and Foshan prefectures. The area of farmland and forest ecosystem is projected to decrease by 309 km2 and 316 km2, respectively. The areas of grassland ecosystem and wetland ecosystem are projected to remain unchanged. Based on the change and simulation of ecosystem patterns in the Greater Bay Area, it was found that the farmland protection red line, ecological protection red line and the protection of important ecological space integrity (all national policies) played important roles in reducing the ecological risk of urbanization in a rapidly urbanizing region. 参考文献 相似文献 引证文献

Governance and policy limitations for sustainable urban land planning. The case of Mexico

In the last 25 years, unplanned and dispersed urban development has become the norm rather than the exception mostly in medium and small cities of the global south, a region with high poverty rates and weak institutions in charge of land use changes. This paper is based on environmental discourses and governance policy integration to address the limitations in preventing the conversion of open land, which provides ecosystem services, into settlement land. It analyzes the case of the Metropolitan Zone of Queretaro in central Mexico, which has experienced particularly high rates of urban expansion in recent years. This paper focuses on the private sector's significant contribution to urban sprawl, a situation linked to the following deficits: policy domain integration deficit, which is related to competing goals among multi-level, multi-scale and multi-sector actors; the interdisciplinary deficit, which requires various procedures and instruments to promote stakeholder collaboration; and the democracy deficit, which involves micro-level actions rather than substantive policy design to encourage citizens to become agents of change and develop awareness of the value of nature in cities.

MODELLING URBAN GROWTH FOR BANGKOK AND ASSESSING LINKAGES WITH ROAD DENSITY AND SOCIO-ECONOMIC INDICATORS

Abstract. The fastest urbanization is occurring in the Global South which includes many developing nations in Asia. However, a rapid and unplanned urban growth could threaten the sustainability of the process. A key step towards a sustainable urban development is to better understand interdependencies amongst urban growth patterns, infrastructure and socio-economic indicators. Here we chose Bangkok, Thailand as a megacity case study to assess the spatio-temporal urban growth dynamics and specifically its dependency with road density at intra-city scales. The SLEUTH urban growth model is further applied for predicting future expansion over the next decade and to assess the future intra-city expansion. Urban expansion patterns for Bangkok were generated for 1987 and 2017 using Landsat derived urban land-cover maps. Open Street Map (OSM) is used to generate a 2017 road density map. The urban expansion (1987–2017) was observed to follow a radially outward expanding pattern inland, with the logarithmic urban expansion rate having an inverted concave trend with road density. The rising/falling limbs then indicated an increase/decrease of urban expansion for which a road density “turning point” is readily identified and further used to develop a road density-based zoning map that highlights the different intra-city urban expansion rates. The SLEUTH predicted urban growth till year 2027 which also showed expansion outward from existing urban areas. The future expansion trend is also consistent with the turning point trend. This study showed that such spatial-temporal analysis of urban expansion coupled with SLEUTH can be useful for investigating likely outcomes of city development plans.

THE STUDY OF HEAT ISLAND AND ITS RELATION WITH URBANIZATION IN GURUGRAM, DELHI NCR FOR THE PERIOD OF 1990 TO 2018

Abstract. Rapid growth in population and land cover makes urban areas more vulnerable to Urban Heat Island. Due to which, cities experience higher mean temperature than its proximate surrounding rural or non-urban area. The relationship between UHI and urbanization is proven in previous studies. Delhi the capital city of India is well known for its extreme heat condition in summer and air pollution. In this study, an attempt has been made to understand UHI behavior in a satellite town of Delhi. Satellite town or cities are the small independent towns built in the vicinity of a large city or metropolitan city. In this paper 4 major satellite towns of Delhi, i.e. Gurugram (name changed from Gurgaon in April 2016), Noida, Faridabad and Ghaziabad has been studied to understand the changing trends in urbanization and temperature. The parameters used are rate of urban expansion, population density, GDP growth and increasing temperature over the last two decades. Gurugram showed the maximum urbanization and identified as study area. Gurugram has undergone a major growth journey from being a small town to ‘The Millennium city’ of the country in a short span. The Landsat images of past three decades ranging from different time period i.e. 1990, 1996, 2002, 2009, 2014 and 2018 were investigated by applying integrated approach of GIS and Remote sensing. The images represent the condition of UHI and urbanization in different period. The temporal change in LULC was used to study the rate of urban growth in last three decades. The results showed the increase in built-up area out of the total area of Gurugram from 10% (i.e.50.6 sq. km) in 1990 to 17.25% (80.5 sq. km) in 2002 which further increased to 45.1% (210.4 sq. km) in 2018. Thermal Infrared band of Landsat series were used to retrieve land surface temperature (LST) intensity of the study period. The results show a positive correlation (r = 0.46) between impervious surfaces and LST. The results of the study could be helpful in identifying the causative factors and level of impacts in different zones and also enable us to develop a mitigation strategy based on spatial decision support system.

The impact of rapid urban expansion on coastal mangroves: a case study in Guangdong Province, China

Mangroves serve many important ecological functions and consequently represent a dominant coastal ecosystem. However, coastal regions are very susceptible to ecological damage due to their high population density, urban expansion being one of the most important influencing factors. Accordingly, it is vital to ascertain how urban expansion endangers mangrove ecosystems. This study used the decision-tree classification method based on classification and regression tree (CART) algorithm to extract areas of mangrove and built-up land from Landsat images. A correlation analysis was performed between the change in the area of mangroves and the change in the area of built-up land at the cell scale. This study aimed to reveal the magnitude of the influence of urban expansion on mangrove forests in different periods and in different regions, and to identify the places that are seriously affected by urban expansion. The results demonstrate that this approach can be used to quantitatively analyze the impact of urban expansion on mangrove forests, and show that larger areas of mangrove were affected by urban expansion in the past 30 years. The effects of urban expansion were stronger over time, with approximately 12% of cells containing mangroves showing a negative correlation between the increase in the area of built-up land and the change in the area of mangrove forests to different degrees from 2005 to 2015. The same quantitative analysis was also carried out in three subregions of Guangdong Province, namely western Guangdong Province, the Pearl River Delta, and eastern Guangdong Province. It was found that the situations in these three regions were very different due to discrepancies in the distribution of mangroves, the rate of urban expansion, and the awareness of the local government regarding environmental protection. These results can assist in the management of coastal cities and the protection of mangrove ecosystems.

Urban Expansion and the Loss of Prairie and Agricultural Lands: A Satellite Remote-Sensing-Based Analysis at a Sub-Watershed Scale

Prairies or grasslands together with areas designated as agricultural lands are one of the largest types of land cover and land use that exist today. While prairies provide habitat to a wide variety of animals and organisms, and agricultural lands support human populations, these lands, especially those in the immediate vicinities of large urban areas, are giving way to urbanization at alarming rates. In particular, prairies are often viewed as wastelands because their benefit to the effective functioning of the urban ecosystem is often not fully understood. On the other hand, many agricultural lands are being converted for several urban uses because of the high economic returns from their sale. In this study, we classified SPOT (Satellite Pour l’Observation de la Terre) satellite data of the study area using the supervised maximum likelihood classification approach in order to investigate the loss of prairies and agricultural lands due to urban expansion in six sub-watersheds in the Kansas City metropolitan area of the States of Kansas and Missouri in the U.S. Based on the classified maps, we computed the magnitude and rate of urban expansion, and the proportion of loss in prairies and agricultural lands that was a result of urban expansion. Results from the 22-year study revealed that in all six sub-watersheds, agricultural lands and grassland were depleted at alarming rates with no sustainable effort to conserve them. These results provide baseline information that can support a data-driven and sustainable path for urban expansion in the examined sub-watersheds.

Investigating the urbanization process and its impact on vegetation change and urban heat island in Wuhan, China.

Rapid urbanization significantly changes vegetation coverage and heat distribution, which threatens the sustainable development and the quality of life. As the largest developing city in Central China, Wuhan was chosen as the experimental region. This study investigated the urbanization process of Wuhan from 1989 to 2917 based on Landsat data. Combined with MODIS EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) data, vegetation disturbance and surface urban heat island (SUHI) caused by urbanization were discussed for 2001-2017. Furthermore, correlation between ∆EVI (urban EVI minus rural EVI) and ∆LST (urban LST minus rural LST) was also conducted. The results were as follows: (1) Wuhan experienced a strong urbanization over the past 29years, with an increasing urban expansion rate and the altered dominant urban expansion pattern (edge expansion and infilling). After the enhanced vegetation functions and urban increased structures, the urbanization finally caused the fragmented patches and irregular urban shapes. (2) Urbanization had a positive effect on LST but a negative effect on EVI. From 2001 to 2017, the highest increasing rate of ∆LST for the old urban area (OUA) and urbanized area (UA) was both observed in summer daytime (OUA, 0.106°C/a; UA, 0.207°C/a). The decreasing rate of ∆EVI reached the highest value in summer (OUA, 0.00697/a; UA, 0.00298/a). (3) There was a strong negative correlation (except spring and winter for OUA) between ∆EVI and ∆LST in daytime, which proved that the activity of vegetation in daytime could relieve LST to a certain extent. This study clarifies the dynamic urbanization process of Wuhan and discusses its impacts on vegetation change and SUHI. Efficiently investigating urbanization process and quantifying its impacts on urban environment are critical for regional ecological conservation.

Comparison on Multi-Scale Urban Expansion Derived from Nightlight Imagery between China and India

“The Dragon and the Elephant” between China and India is an important manifestation of global multipolarization in the 21st century. As engines of global economic growth, the two rising powers have followed similar courses of development but possess important differences in modes of development and urban development, which have attracted the widespread attention of scholars. From a geospatial perspective, and based on continuous annual night light data (Defense Meteorological Satellite Program-Operational Linescan System, DMSP-OLS) from 1992 to 2012, this paper conducts a multi-scale comparative analysis of urban development differences between China and India by employing various approaches such as the Gini coefficient, Getis–Ord Gi* index, and the Urban Expansion Intensity Index (UEII). The results show that: (1) The urban land space of the two countries expand rapidly, with the average annual expansion rate of China and India being 5.24% and 3.85%, respectively. The urban land expansion rate in China is 1.36 times faster than that in India. Resource-typed towns in arid northwest China and the resource-typed towns in central India have developed rapidly in recent years. (2) The unbalanced development in India is more prominent than in China; and the regional and provincial development imbalances in China are shrinking, while India’s imbalances are improving slowly and its regional differences are gradually widening. (3) The spatial pattern of land use in both countries shows significant coastal and inland differences. The difference between the east, the central regions, and the west is the main spatial pattern of China’s regional development, while the difference between the north and the south is the spatial pattern of India’s regional development. (4) There are obvious differences in the expansion intensity of core cities between the two countries. From 1997 to 2007, the expansion intensity of core cities in China was relatively higher than that in India, while that in India was relatively higher than that in China from 2007 to 2012.

Spatial differences and pattern evolution of Multi-scale Urban Land between China and India

Abstract. “The dragon and the elephant” between China and India is an important manifestation of global multipolarization in the 21st century. As an engine of global economic growth, China and India have similar development processes, different development models as well as differences in urban development, which have attracted widespread attention from scholars. Based on the 1992–2012 consecutive annual nighttime lighting data (DMSP-OLS), this paper uses the Gini coefficient, the Getis-Ord Gi* index and the Compounded Night Light Index (CNLI) to conduct a multi-scale comparative analysis of the differences in urban development between China and India from the perspective of geospatial. The results show that: (1) The space of urban land in the two countries expanded rapidly, with an average annual expansion rate of 5.24% and 3.85% respectively. China's urban land expansion rate is 1.36 times that of India. Among them, the arid resource towns in northwest China and the resource towns in central India have recently developed rapidly. (2) India’s imbalance in development is more prominent than China’s. China's regional and provincial imbalances are narrowing, while the regional differences in India are gradually widening. (3) The spatial pattern of land use in both countries shows a certain degree of coastal and inland differences. The main spatial pattern of China's regional development is the difference between East-Central-West, while the spatial pattern of regional development in India is North-South difference. (4) The strength of the expansion of the core cities of the two countries is quite different. From 1997 to 2007, China's core urban expansion intensity remained at a relatively high level while India was at a relatively low level. But from 2007 to 2012, India's core cities expanded at a relatively high level while China was at a relatively low level.