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

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.

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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

Sustainability ◽

10.3390/su13168848 ◽

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.

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Big Data Supported the Identification of Urban Land Efficiency in Eurasia by Indicator SDG 11.3.1

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10020064 ◽

2021 ◽

Vol 10 (2) ◽

pp. 64

Author(s):

Chaopeng Li ◽

Guoyin Cai ◽

Mingyi Du

Keyword(s):

Land Use ◽

Sustainable Development ◽

Population Growth ◽

Urban Expansion ◽

Urban Land ◽

Urban Land Use ◽

Land Supply ◽

Large Cities ◽

Land Use Efficiency ◽

Use Efficiency

Indicator 11.3.1 of the UN Sustainable Development Goals (SDG 11.3.1) was designed to test land-use efficiency, which was defined as the ratio of the land consumption rate (LCR) to the population growth rate (PGR), namely, LCRPGR. This study calculates the PGRs, LCRs, and LCRPGRs for 333 cities from 1990–2000 and 391 cities from 2000–2015 in four geographical divisions in Eurasia according to the method given by UN metadata. The results indicate that Europe and Japan have the lowest PGR and LCR, indicating that this region’s level of urbanization is the highest. South and Central Asia have the lowest values of LCRPGR, indicating relatively lower urban land supply during the measurement periods. Compared with the mean LCRPGR in a region, the average values from SDG 11.3.1 by different types of cities in a region can have more guiding significance for urban sustainable development. While paying attention to the urban land-use efficiency of mega and extra-large cities, more attention should be paid to the coordination relationship between urban land supply and population growth in large, medium, and small cities. Additionally, the method from UN metadata works well for most urban expansion cities but is not suitable for cities with small changes in urban populations.

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Urban Expansion and Farmland Loss in Beijing during 1980–2015

Sustainability ◽

10.3390/su10113927 ◽

2018 ◽

Vol 10 (11) ◽

pp. 3927 ◽

Cited By ~ 9

Author(s):

Yingjie Hu ◽

Xiangbin Kong ◽

Ji Zheng ◽

Jin Sun ◽

Linlin Wang ◽

...

Keyword(s):

Land Use ◽

Urban Expansion ◽

Urban Land ◽

Urban Land Use ◽

Average Quality ◽

The Past ◽

Land Use Efficiency ◽

Farmland Loss ◽

Use Efficiency ◽

Urban Land Expansion

The analysis of urban land expansion and farmland loss is essential to adequately understand the land use change in a rapidly urbanizing China. We found that both urban expansion and farmland loss in Beijing experienced high- and low-speed stages and their spatial patterns were consistent during the past 35 years as most of the newly expanded urban land was converted from farmland. The area of farmland loss by urban expansion in Beijing is 12.6 km2/year, 39.86 km2/year, 23.38 km2/year, and 41.11 km2/year during the period of 1980–1990, 1990–2000, 2000–2010, and 2010–2015, respectively. The urban expansion in Beijing continuously preferred to consume “above average” quality farmland during 1980–2015. Meanwhile, although the urban expansion in Beijing was highly dependent on occupying farmland, the dependence of urban expansion on farmland consumption has declined over time. However, the contribution of urban expansion on farmland loss increased during 1980–2010 and decreased afterward. In order to protect the farmland from urban expansion, we call for more effort to improve the urban land use efficiency with rigid controls over areas of urban expansion.

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Identification of urban land use efficiency by indicator-SDG 11.3.1

PLoS ONE ◽

10.1371/journal.pone.0244318 ◽

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.

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Assessment and Spatial-Temporal Evolution Analysis of Urban Land Use Efficiency under Green Development Orientation: Case of the Yangtze River Delta Urban Agglomerations

Land ◽

10.3390/land10070715 ◽

2021 ◽

Vol 10 (7) ◽

pp. 715

Author(s):

Yingkai Tang ◽

Kun Wang ◽

Xuanming Ji ◽

He Xu ◽

Yangqing Xiao

Keyword(s):

Land Use ◽

Urban Development ◽

Evaluation System ◽

Yangtze River Delta ◽

Urban Land ◽

Urban Land Use ◽

Land Use Efficiency ◽

Green Development ◽

Use Efficiency ◽

Development Orientation

Rapid urbanization has provided a strong impetus for the economic growth of China, but it has also caused many problems such as inefficient urban land use and environmental pollution. With the popularization of the concept of green and sustainable development, the Environmental-Social-Governance (ESG) assessment concept is widely accepted. The government and residents are paying more and more attention to environmental issues in urban development, and environmental protection has formed an important part of urban development. In this context, this study takes 26 cities in the Yangtze River Delta as examples to build an evaluation system for urban land-use efficiency under green development orientation. The evaluation system takes into account the inputs of land, capital, labor, and energy factors in the process of urban development. Based on emphasizing economic output, the social benefits and undesired outputs brought about by urban development are taken into account. This paper measures urban land use efficiency by the super-efficiency SBM model, and on this basis, analyses the spatial-temporal evolution characteristics of urban land-use efficiency. Further, this paper measures urban land use efficiency without considering undesired outputs and compares the two evaluation methods. Again, the comparison illustrates the rationality of urban land use efficiency evaluation system under green development orientation.

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Does the Construction and Operation of High-Speed Rail Improve Urban Land Use Efficiency? Evidence from China

Land ◽

10.3390/land10030303 ◽

2021 ◽

Vol 10 (3) ◽

pp. 303

Author(s):

Xinhai Lu ◽

Yifeng Tang ◽

Shangan Ke

Keyword(s):

Economic Growth ◽

Land Use ◽

High Speed ◽

Urban Land ◽

Urban Land Use ◽

Western China ◽

High Speed Rail ◽

Land Use Efficiency ◽

Use Efficiency ◽

The Impact

The construction and operation of high-speed rail (HSR) has become an important policy for China to achieve efficiency and fairness and promote high-quality economic growth. HSR promotes the flow of production factors such as labor and capital and affects economic growth, and may further affect urban land use efficiency (ULUE). To explore the impact of HSR on ULUE, this paper uses panel data of 284 cities in China from 2005 to 2018, and constructs Propensity Score Matching-Differences in Differences model to evaluate the effect of HSR on ULUE. The result of entire China demonstrates that the HSR could significantly improves the ULUE. Meanwhile, this paper also considers the heterogeneity of results caused by geographic location, urban levels and scales. It demonstrates that the HSR has a significantly positive effect on ULUE of Eastern, Central China, and large-sized cities. However, in Western China, in medium-sized, and small-sized cities, the impact of HSR on ULUE is not significant. This paper concludes that construction and operation of HSR should be linked to urban development planning and land use planning. Meanwhile, the cities with different geographical locations and scales should take advantage of HSR to improve ULUE and promote urban coordinated development.

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Is high-tech zone a policy trap or a growth drive? Insights from the perspective of urban land use efficiency

Land Use Policy ◽

10.1016/j.landusepol.2020.104583 ◽

2020 ◽

Vol 95 ◽

pp. 104583 ◽

Cited By ~ 3

Author(s):

Xinhai Lu ◽

Danling Chen ◽

Bing Kuang ◽

Chaozheng Zhang ◽

Chen Cheng

Keyword(s):

Land Use ◽

Urban Land ◽

Urban Land Use ◽

High Tech ◽

Land Use Efficiency ◽

Use Efficiency

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Study on Temporal and Spatial Variation Characteristics and Influencing Factors of Land Use Efficiency in Xi’an, China

Sustainability ◽

10.3390/su11236649 ◽

2019 ◽

Vol 11 (23) ◽

pp. 6649

Author(s):

Jing Huang ◽

Dongqian Xue

Keyword(s):

Land Use ◽

Urban Area ◽

Influencing Factors ◽

Urban Land ◽

Urban Land Use ◽

Western China ◽

Land Use Efficiency ◽

Use Efficiency ◽

Underdeveloped Areas ◽

The City

China’s urban land use has shifted from incremental expansion to inventory eradication. The traditional extensive management mode is difficult to maintain, and the fundamental solution is to improve land use efficiency. Xi’an, the largest central city in Western China, was selected as the research area. The super-efficiency data envelopment analysis (DEA) model and Malmquist index method were used to measure the land use efficiency of each district and county in the city from the micro perspective, and the spatial-temporal change characteristics and main influencing factors of land use efficiency were analyzed, which not only made up for the research content of urban land use efficiency in China’s underdeveloped areas, but also pointed out the emphasis and direction for the improvement of urban land use efficiency. The results showed that: (1) The land use efficiency of Xi’an reflected the land use intensive level of the underdeveloped areas in Western China, that is, the overall intensive level was not high, the gap between the urban internal land use efficiency was large, the land use efficiency of the old urban area and the mature built-up area was relatively high, and the land use efficiency of the emerging expansion area and the edge area was relatively low. (2) Like the eastern economically developed areas, the land use efficiency of western economically underdeveloped areas was generally on the rise, while Xi’an showed the U-shaped upward evolution characteristics, and there were four types of changes in the city, that is, highly intensive, medium intensive, high–medium–low-intensive, and intensive–extensive. (3) Various cities should configure resources and optimize mechanism to improve their land use efficiency based on economic and social development. During the study period, Xi’an showed the law of evolution from the south edge area and the emerging expansion area to the main urban area. (4) The improvement of technological progress was the main contribution factor of the land use efficiency in underdeveloped areas of China, and the low-scale efficiency was the main influence factor that caused low land use efficiency. In future urban land use, efforts should be made to optimize and upgrade technology and strictly control the extensive use of land.

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