Understanding the Rural Livelihood Stability System: The Eco-Migration in Huanjiang County, China

Immigrants are a special group whose livelihood stability is crucial to local sustainable development. To understand the positive effect of eco-migration policy on the immigrants, we innovatively selected the perspective of stability and quantified immigrants’ livelihood stability with relevant concepts, including livelihood capitals and strategies, response capacity, and land-use efficiency, which helped identify the problems and put forward suggestions to enhance livelihood sustainability, achieve better social integration, and promote the sustainable development of the rural resettlement areas. Huanjiang County was used as a study case as it is the largest and most representative eco-migrant resettlement county of the southwestern karst region, China. Aided by participatory rural appraisal (PRA), this paper explores the livelihood stability of immigrants and takes natives as the reference group. The results show that the livelihood stability values of immigrants were less than that of natives, but the gap was smaller than ten years ago; the natural, social, and other capitals owned by immigrants were almost the same as those of natives, demonstrating that the Chinese government’s poverty alleviation policies have benefitted immigrants. However, both immigrants and natives were found to have less natural and social capitals; high income dependency and an unbalanced proportion of income sources in addition to low land-use efficiency. Therefore, there are several suggestions put forward to achieve stable livelihood and rural sustainable development, and these items should be given increased consideration by both the government and households in resettlement areas.

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Monitoring global land-use efficiency in the context of the UN 2030 Agenda for Sustainable Development

Habitat International ◽

10.1016/j.habitatint.2021.102403 ◽

2021 ◽

Vol 115 ◽

pp. 102403

Author(s):

Ronald C. Estoque ◽

Makoto Ooba ◽

Takuya Togawa ◽

Yasuaki Hijioka ◽

Yuji Murayama

Keyword(s):

Land Use ◽

Sustainable Development ◽

Land Use Efficiency ◽

2030 Agenda ◽

Global Land ◽

Use Efficiency

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Urban Sprawl and Changes in Land-Use Efficiency in the Beijing–Tianjin–Hebei Region, China from 2000 to 2020: A Spatiotemporal Analysis Using Earth Observation Data

Remote Sensing ◽

10.3390/rs13152850 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2850

Author(s):

Meiling Zhou ◽

Linlin Lu ◽

Huadong Guo ◽

Qihao Weng ◽

Shisong Cao ◽

...

Keyword(s):

Land Use ◽

Sustainable Development ◽

Urban Areas ◽

Landsat Imagery ◽

Spatiotemporal Analysis ◽

Google Earth ◽

Observation Data ◽

Land Use Efficiency ◽

Use Efficiency ◽

Bth Region

Sustainable development in urban areas is at the core of the implementation of the UN 2030 Agenda and the Sustainable Development Goals (SDG). Analysis of SDG indicator 11.3.1—Land-use efficiency based on functional urban boundaries—provides a globally harmonized avenue for tracking changes in urban settlements in different areas. In this study, a methodology was developed to map built-up areas using time-series of Landsat imagery on the Google Earth Engine cloud platform. By fusing the mapping results with four available land-cover products—GlobeLand30, GHS-Built, GAIA and GLC_FCS-2020—a new built-up area product (BTH_BU) was generated for the Beijing–Tianjin–Hebei (BTH) region, China for the time period 2000–2020. Using the BTH_BU product, functional urban boundaries were created, and changes in the size of the urban areas and their form were analyzed for the 13 cities in the BTH region from 2000 to 2020. Finally, the spatiotemporal dynamics of SDG 11.3.1 indicators were analyzed for these cities. The results showed that the urban built-up area could be extracted effectively using the BTH_BU method, giving an overall accuracy and kappa coefficient of 0.93 and 0.85, respectively. The overall ratio of the land consumption rate to population growth rate (LCRPGR) in the BTH region fluctuated from 1.142 in 2000–2005 to 0.946 in 2005–2010, 2.232 in 2010–2015 and 1.538 in 2015–2020. Diverged changing trends of LCRPGR values in cities with different population sizes in the study area. Apart from the megacities of Beijing and Tianjin, after 2010, the LCRPGR values were greater than 2 in all the cities in the region. The cities classed as either small or very small had the highest LCRPGR values; however, some of these cities, such as Chengde and Hengshui, experienced population loss in 2005–2010. To mitigate the negative impacts of low-density sprawl on environment and resources, local decision makers should optimize the utilization of land resources and improve land-use efficiency in cities, especially in the small cities in the BTH region.

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

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8020096 ◽

2019 ◽

Vol 8 (2) ◽

pp. 96 ◽

Cited By ~ 17

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.

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The Natural and Socioeconomic Influences on Land-Use Intensity: Evidence from China

Land ◽

10.3390/land10111254 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1254

Author(s):

Longgao Chen ◽

Xiaoyan Yang ◽

Long Li ◽

Longqian Chen ◽

Yu Zhang

Keyword(s):

Land Use ◽

Socioeconomic Factors ◽

Socioeconomic Development ◽

Positive Impact ◽

Land Use Intensity ◽

Appraisal System ◽

Land Use Efficiency ◽

Use Efficiency ◽

The Government ◽

Intensive Land Use

Intensive land use can support sustainable socioeconomic development, especially in the context of limited land resources and high population. It is measured by land-use intensity that reflects the degree of land-use efficiency. In order to support decision-making for efficient land use, we investigated the mechanism whereby natural and socioeconomic factors influence land-use intensity from the perspectives of overall, region-, and city-based analysis, respectively. This investigation was conducted in Chinese cities using the multiple linear stepwise regression method and geographic information system techniques. The results indicate that: (1) socioeconomic factors have more positive impact on land-use intensity than natural factors as nine of the top 10 indicators with the highest SRC values are in the socioeconomic category according to the overall assessment; (2) education input variously contributes to land-use intensity because of the mobility of a well-educated workforce between different cities; (3) the increase in transportation land may not promote intensive land use in remarkably expanding cities due to the defective appraisal system for governmental achievements; and that (4) in developed cities, economic structure contributes more to land-use intensity than the total economic volume, whereas the opposite is the case in less-developed cities. This study can serve as a guide for the government to prepare strategies for efficient land use, hence promoting sustainable socioeconomic 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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The efficiency of use of land as a factor of development of the agrarian sector of the European North of Russia

Scientific bulletin of the Southern Institute of Management ◽

10.31775/2305-3100-2018-4-33-44 ◽

2018 ◽

pp. 33-44

Author(s):

N. A. Frieva

Keyword(s):

Land Use ◽

Sustainable Development ◽

Agricultural Production ◽

Agricultural Land ◽

Necessary Condition ◽

Land Resources ◽

The Sustainable Development ◽

Land Use Efficiency ◽

European North ◽

Use Efficiency

Currently, the rational use of land resources, identification of problems of their implementation, development of key areas and implementation of measures to improve the efficiency of economic use of the land fund plays an important role in strengthening the economy of the region, and is also important for increasing the volume of agricultural products. The aim of the study was to analyze the efficiency of land use in the regions of the European North of Russia (ESR). The article summarizes the theoretical aspects of the study, which emphasized the importance of land, which is the main means of agricultural production, considered the concept of economic efficiency of land use in agriculture, the existing system of indicators of land use efficiency according to various scientists, the author’s system of relative and natural indicators of land use efficiency; the analysis of the effectiveness of land use in the ESR. The characteristic feature of these territories, such as the gradual reduction of agricultural land due to soil degradation and misuse of land resources, is noted. It is emphasized that the necessary condition for ensuring the growth of agricultural production and sustainable development of the region is a stable provision of state support at a sufficient level. In conclusion, the article proposes a set of tools aimed at the implementation of the existing land potential of the regions of the European North of Russia. Among them-agrotechnical, meliorative and organizational and economic measures, the implementation of which will contribute to the sustainable development of agriculture and the economy of the region as a whole.

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Can Carbon Finance Optimize Land Use Efficiency? The Example of China’s Carbon Emissions Trading Policy

Land ◽

10.3390/land10090953 ◽

2021 ◽

Vol 10 (9) ◽

pp. 953

Author(s):

Bin Duan ◽

Xuanming Ji

Keyword(s):

Land Use ◽

Sustainable Development ◽

Policy Implementation ◽

Environmental Effects ◽

Emissions Trading ◽

Economic Effects ◽

Carbon Emissions Trading ◽

Land Use Efficiency ◽

Use Efficiency ◽

Carbon Finance

Land resources have become one of the major factors limiting urban development in China. In the context of sustainable development, how to improve land use efficiency (LUE) has become a major challenge on the road to sustainable development in China. Carbon finance provides a new idea for sustainable development. With the help of carbon emissions trading policy (CETP), this paper aims to investigate whether carbon finance can optimize LUE in terms of economic effects and environmental effects. Based on the data of 158 prefectural-level cities in China from 2010 to 2017, this paper uses a combination of qualitative and quantitative analysis to investigate these issues. Specifically, this paper measures the land use efficiency from economic effects (LUE_Eco) and environmental effects (LUE_Env) using the entropy method, and visualizes the data to obtain information on their spatio-temporal evolution patterns. Furthermore, this paper verifies the causal relationship between policy implementation and LUE_Eco and LUE_Env by using the difference in differences (DID) method. The conclusions show that: (1) the levels of LUE_Eco and LUE_Env in the pilot regions generally increase after the implementation of the CETP, but only the increase of LUE_Env is due to the policy implementation; (2) the CETP not only effectively reduces CO2 emissions, but also promotes the reduction of industrial ‘three wastes’ emissions. Accordingly, this paper has gained insights on how to improve LUE in China.

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

Land ◽

10.3390/land10080850 ◽

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.

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

10.20944/preprints201810.0085.v1 ◽

2018 ◽

Cited By ~ 1

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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