scholarly journals An assessment of urbanization sustainability in China between 1990 and 2015 using land use efficiency indicators

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Huiping Jiang ◽  
Zhongchang Sun ◽  
Huadong Guo ◽  
Qihao Weng ◽  
Wenjie Du ◽  
...  
Keyword(s):  
Land Use ◽  
Census Data ◽  
Environmental Changes ◽  
Economic Transformation ◽  
Central China ◽  
Rapid Urbanization ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
Land Consumption ◽  
Efficiency Indicators

AbstractThe sustainability of China’s rapid urbanization is of significance in the implementation of the 2030 Agenda for Sustainable Development. Here we integrated Earth observation and census data to estimate the relationship between land, population and economic domains of urbanization in 433 cities over 25 years using land use efficiency indicators. We find that the rise in ratio of land consumption to population growth rates (LCRPGR) was paralleled by a decline in ratio of economic growth to land consumption rates (EGRLCR). LCRPGR and EGRLCR of cities in Northeast China showed an abnormal and intense dynamics compared to other regions, suggesting that the northeastern region is more vulnerable to socioeconomic and environmental changes. The spatial expansion of superlarge cities in Central China may be unrestrained and should be the focus of strengthened regulations now and in the near future. The resource-dependent cities faced severe challenges for more effective actions of both economic transformation and population migration. Nonetheless, the gap of land use efficiency indicators between different income groups of the cities has been narrowed between 1990 and 2015, indicating that the evolution of urbanization in China is heading toward a more sustainable and coordinated process.

scholarly journals Principles and Applications of the Global Human Settlement Layer as Baseline for the Land Use Efficiency Indicator—SDG 11.3.1

2019 ◽  
Vol 8 (2) ◽  
pp. 96 ◽  
Author(s):  
Michele Melchiorri ◽  
Martino Pesaresi ◽  
Aneta Florczyk ◽  
Christina Corbane ◽  
Thomas Kemper
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Spatial Distribution ◽  
Distribution Density ◽  
Census Data ◽  
Spatial Information ◽  
Human Settlement ◽  
Land Use Efficiency ◽  
Multi Temporal ◽  
Use Efficiency

The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics describing the human presence on the planet that is based mainly on two quantitative factors: (i) the spatial distribution (density) of built-up structures and (ii) the spatial distribution (density) of resident people. Both of the factors are observed in the long-term temporal domain and per unit area, in order to support the analysis of the trends and indicators for monitoring the implementation of the 2030 Development Agenda and the related thematic agreements. The GHSL uses various input data, including global, multi-temporal archives of high-resolution satellite imagery, census data, and volunteered geographic information. In this paper, we present a global estimate for the Land Use Efficiency (LUE) indicator—SDG 11.3.1, for circa 10,000 urban centers, calculating the ratio of land consumption rate to population growth rate between 1990 and 2015. In addition, we analyze the characteristics of the GHSL information to demonstrate how the original frameworks of data (gridded GHSL data) and tools (GHSL tools suite), developed from Earth Observation and integrated with census information, could support Sustainable Development Goals monitoring. In particular, we demonstrate the potential of gridded, open and free, local yet globally consistent, multi-temporal data in filling the data gap for Sustainable Development Goal 11. The results of our research demonstrate that there is potential to raise SDG 11.3.1 from a Tier II classification (manifesting unavailability of data) to a Tier I, as GHSL provides a global baseline for the essential variables called by the SDG 11.3.1 metadata.

scholarly journals Estimation of Urban Land-Use Efficiency for Sustainable Development by Integrating over 30-Year Landsat Imagery with Population Data: A Case Study of Ha Long, Vietnam

2021 ◽  
Vol 13 (16) ◽  
pp. 8848
Author(s):  
Shokhrukh-Mirzo Jalilov ◽  
Yun Chen ◽  
Nguyen Hong Quang ◽  
Minh Nguyen Nguyen ◽  
Ben Leighton ◽  
...  
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Population Growth Rate ◽  
Consumption Rate ◽  
Landsat Imagery ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
Land Consumption

Humans are moving into urban areas at an accelerated pace. An increasing urban population fuels urban expansion and reduces nearby agricultural lands and natural environments such as forests, swamps, other water-pervious areas. Unsustainable development creates a disproportion between the growth of urban areas and the growth in urban population. The UN SDG indicator 11.3.1 specifically addresses the issue of the measurement of land-use efficiency. While the metric and methodology to estimate the indicator are straightforward, it faces problems of data unavailability and inconsistency. Vietnam has a record of tremendous economic growth that has translated into more urban settlements of size. Consequently, rural population movement into urban areas has led to many urban sustainable planning and development challenges. In the absence of previous work on estimating land-use efficiency in Vietnamese cities, this study makes the first attempt to examine land-use efficiency in Ha Long, one of the country’s fast-growing cities in recent decades. We mapped land use from high-resolution Landsat imagery (30 m) spanning multi-decadal observations from 1986 to 2020. An advanced machine learning approach, the Support Vector Machine algorithm, was applied to estimate the built-up area, which, by integration with census data, is essential for calculating SDG indicator 11.3.1. This study shows that the land-use efficiency metric was positive but small at the beginning of the considered period but increased in 2000–2020. These results suggest that before 2000, the urban land consumption rate in Ha Long was lower than the population growth rate, implying denser urban land use. The situation changed to the opposite when the urban land consumption rate exceeded the population growth rate in the past two decades. The study’s approach is applicable to regional and district levels to provide comparative analyses between cities or parts of a region or districts of the city. These analyses are valuable tools for assessing the impact of local urban and municipal planning policies on urban development.

scholarly journals Spatio-Econometric Analysis of Urban Land Use Efficiency in China from the Perspective of Natural Resources Input and Undesirable Outputs: A Case Study of 287 Cities in China

2020 ◽  
Vol 17 (19) ◽  
pp. 7297
Author(s):  
Xiao Han ◽  
Anlu Zhang ◽  
Yinying Cai
Keyword(s):  
Economic Growth ◽  
Land Use ◽  
Natural Resources ◽  
Clean Energy ◽  
Urban Land ◽  
Urban Land Use ◽  
Sustainable Urban Development ◽  
Rapid Urbanization ◽  
Land Use Efficiency ◽  
Use Efficiency

The rapid urbanization in China has had a huge impact on land use and the scarcity of land resources has become a constraint for sustainable urban development. As urban land is an indispensable material basis in economic development, measuring its use efficiency and adopting effective policies to improve urban land use efficiency (ULUE) are important links in maintaining sustainable economic growth. By establishing a comprehensive ULUE evaluation index system that emphasizes on incorporating the natural resources input and the undesirable output, ULUE from 2010 to 2016 was calculated based on super efficiency SBM model, and its potential influencing factors were explored using a spatial econometric model. The results show that: (1) temporally, the overall ULUE in China is upward growing, and the gap among regions is becoming gradually convergent. (2) Spatially, the ULUE of Chinese cities are positively correlated. (3) Economic agglomeration and industrial structure significantly improve ULUE in China, but the intensity of energy consumption has a negative impact on ULUE. We suggest that: (1) differentiated industrial development strategies should be formulated; (2) the economic growth pattern should be changed from energy-consuming to energy-saving; (3) priority should be given to innovation on science and education, so as to increase in clean energy input and cleaner production.

scholarly journals Identification of urban land use efficiency by indicator-SDG 11.3.1

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244318
Author(s):  
Guoyin Cai ◽  
Jinxi Zhang ◽  
Mingyi Du ◽  
Chaopeng Li ◽  
Shu Peng
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Positive Impact ◽  
Urban Land ◽  
Urban Land Use ◽  
Rapid Urbanization ◽  
Error Matrix ◽  
Land Use Efficiency ◽  
Multiple Data ◽  
Use Efficiency

Inefficiency in urban land use is one of the problems caused by rapid urbanization. The UN Sustainable Development Goals (SDGs) indicator 11.3.1 is designed to test urban land use efficiency. This study employed geospatial and statistical data to compute land use efficiencies from 1990 to 2015 with five 5-year and ten 15-year intervals in Wukang, center of Deqing County, China. A flowchart was designed to extract the built-up lands from multiple data sources. The produced built-up lands were demonstrated to provide good accuracy by constructing an error matrix between the extracted and manually interpreted built-up lands as classified and reference images, respectively. By using the model provided by UN metadata to calculate SDG 11.3.1, the land use efficiencies from 1990 to 2015 were identified in Wukang. Our results indicate that the land use efficiency in Deqing County center is lower than the average of cities around the world, primarily because our in-situ study focused on a county center with larger rural regions than urban areas. Over the long term, urban land use becomes denser as the population grows, which will have a positive impact on the sustainability of urban development. This work is helpful for the local government to balance urban land consumption and population growth.

scholarly journals Optimization of Population Distribution Pattern in China Based on Land Use Efficiency

2018 ◽  
Author(s):  
Minmin Li ◽  
Biao He ◽  
Renzhong Guo ◽  
You Li ◽  
Yu Chen ◽  
...  
Keyword(s):  
Land Use ◽  
Distribution Pattern ◽  
Urban Areas ◽  
Population Distribution ◽  
National Level ◽  
Rapid Urbanization ◽  
Land Use Efficiency ◽  
Economic Production ◽  
Use Efficiency ◽  
Economic Concentration

With the accelerating urbanization process, the population increasingly concentrates in urban areas. In view of the special situation in China and a series of problems in the process of rapid urbanization, there were no reasonable measures for optimizing the population pattern. This study explored the distribution pattern of the Chinese population and proposed an optimization plan for the population distribution using GIS analysis. The main findings were as follows. (1) From 2010 to 2015, the distribution of population density in China presented a pattern of high in the southeast and low in the northwest based on the county-level administrative regions. The population still showed a tendency to migrate to the southeast of the country based on the “Hu Huanyong Line”. (2) There was a great difference in the land use efficiency in terms of population and economic production in China. The economic concentration in China was higher than the population concentration. In the areas where population and economic production were aggregated, GDP per capita and land use efficiency were higher. (3) Based on the land use efficiency in terms of population and economic production, the optimized urbanization plan of “1+4+11” for China’s urbanization was put forward, namely, one national-level aggregated area of population and economic production, 4 regional-level aggregated areas of population and economic production, and 11 local regionally aggregated areas of population and economic production. This optimization plan for urbanization represents an attempt to explore the direction of China’s urbanization, and it can be used to optimize the spatial development pattern and provide scientific guidance for the new urbanization plan.

scholarly journals Urban Land-Use Efficiency Analysis by Integrating LCRPGR and Additional Indicators

2021 ◽  
Vol 13 (24) ◽  
pp. 13518
Author(s):  
Chaopeng Li ◽  
Guoyin Cai ◽  
Zhongchang Sun
Keyword(s):  
Land Use ◽  
Population Growth ◽  
Urban Areas ◽  
Urban Expansion ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
Land Consumption ◽  
The Relationship

Sustainable Development Goal (SDG) target 11.3 is to enhance inclusive and sustainable urbanisation and capacity for participatory, integrated, and sustainable human settlement planning and management in all countries by 2030. Within that goal, the indicator SDG 11.3.1 is defined as the ratio of land consumption rate to population growth rate (LCRPGR). This ratio is primarily used to measure urban land-use efficiency and reveal the relationship between urban land consumption and population growth. The LCRPGR indicator is aimed at representing overall urban land-use efficiency. This study added compactness, urban expansion speed, and urban expansion intensity to better reflect the impact of built-up area changes on the overall urban land-use efficiency. In addition, this study combined LCRPGR and the land consumption per capita rate (LCPC) to comprehensively analyse the relationship between land consumption and population growth in existing built urban areas, expanded built urban areas, and total built areas. This study employed three years of urban built-up and population data for 2010, 2015, and 2020 for 338 cities along the Belt and Road region to analyse land-use efficiency. The results show that the average LCRPGR for the period 2010–2015 was 1.01, which is close to the recommended ideal LCRPGR value of 1.0 in the United Nations Human Settlements Programme. For 2015–2020, the LCRPGR was 0.71, indicating that the overall urban land consumption in the study area decreased. This is also supported by the fact that the urban expansion intensity in 2020 was weaker than that in 2015. In addition, according to research on the tendency of changes in the entire urban built-up area, the smaller the urban population, the slower the urban expansion speed, the smaller the compactness, and the increasingly complex the urban borders. In cities where the overall LCRPGR is far from the ideal value of 1, the entire built-up area is divided into existing and expanded urban regions. It was found that the average LCPC value in expanded built-up areas was higher than that of existing built-up areas, showing that as cities developed, the LCPC of the newly developed urban areas was greater than that of existing built-up areas. Meanwhile, the LCPC in the expanded built-up areas showed a decreasing trend over time from 2010 to 2015 to 2020, indicating that land use in the expanded built-up regions tended to be efficient. These findings provide helpful information in decision making for balancing urban land consumption with population growth.

scholarly journals Urban Land Use Efficiency under Resource-Based Economic Transformation—A Case Study of Shanxi Province

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 850
Author(s):  
Xin Janet Ge ◽  
Xiaoxia Liu
Keyword(s):  
Land Use ◽  
Economic Transformation ◽  
Urban Land Use ◽  
State Council ◽  
Land Productivity ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
Main Determinants ◽  
The Government ◽  
The Impact

Shanxi, one of China’s provinces, has been approved by the State Council as the only state-level comprehensive reform zone for resource-based economic transformation in 2010. Consequently, the implementation of National Resource-based Cities Sustainable Development Planning (2013–2020) and The State Council on Central and Western Regions Undertaking of Industrial Transformation Guide were also introduced. As a result, many agricultural lands were urbanized. The question is whether the transformed land was used efficiently. Existing research is limited regarding the impact of the government-backed transformation of the resource-based economy, industrial restructuring, and urbanization on land use efficiency. This research investigates urban land use efficiency under the government-backed resource-based economy transformation using the Bootstrap-DEA and Bootstrap-Malmquist methods. The land use efficiency and land productivity indexes were produced. Based on the empirical study of 11 prefectural cities, the results suggest that the level of economic development and industrial upgrading are the main determinants of land use efficiency. The total land productivity index declined after the economic reform was initiated. The findings imply that the government must enhance monitoring and auditing during policy implementation and evaluate the policy effects after for further improvement. With the scarcity of land resources and urban expansion in many cities worldwide, this research also provides an approach to determining the main determinants of land use efficiency that could guide our understanding of the impact of the future built environment.

scholarly journals Principles and Applications of the Global Human Settlement Layer as Baseline for the Land Use Efficiency Indicator –SDG 11.3.1

2018 ◽  
Author(s):  
Michele Melchiorri ◽  
Martino Pesaresi ◽  
Aneta J. Florczyk ◽  
Christina Corbane ◽  
Thomas Kemper
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Spatial Distribution ◽  
Distribution Density ◽  
Census Data ◽  
Spatial Information ◽  
Human Settlement ◽  
Land Use Efficiency ◽  
Multi Temporal ◽  
Use Efficiency

The Global Human Settlement Layer (GHSL) produces new global spatial information, evidence-based analytics and knowledge describing the human presence on the planet based mainly on two quantitative factors: i) the spatial distribution (density) of built-up structures and ii) the spatial distribution (density) of resident people. Both factors are observed in the long-term temporal domain and per uniform surface units in order to support trends and indicators for monitoring the implementation of international framework agreements. The GHSL uses various input data including global, multi-temporal archives of fine-scale satellite imagery, census data, and volunteered geographic information. In this paper, we present the characteristics of GHSL information to demonstrate how original frameworks of data and tools rooted on Earth Observation could support Sustainable Development Goals monitoring. In particular, we demonstrate the reach of gridded, open and free, local yet globally consistent, multi-temporal data in filling the data gap for the Sustainable Development Goal 11. Our experiments produce a global estimate for the Land Use Efficiency indicator (SDG 11.3.1) for 10,000 urban centers, calculating the ratio of land consumption to population growth rate that took place between 1990 and 2015. The results of our research demonstrate that there is a potential to lift SDG 11.3.1 from a tier 2 as GHSL provides a global baseline for the essential variables called by the SDG 11.3.1 metadata.

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