scholarly journals Driving Factors of Land Change in China’s Loess Plateau: Quantification Using Geographically Weighted Regression and Management Implications

2020 ◽  
Vol 12 (3) ◽  
pp. 453 ◽  
Author(s):  
Yanjiao Ren ◽  
Yihe Lü ◽  
Bojie Fu ◽  
Alexis Comber ◽  
Ting Li ◽  
...  

Land change is a key topic in research on global environmental change, and the restoration of degraded land is the core component of the global Land Degradation Neutrality target under the UN 2030 Agenda for Sustainable Development. In this study, remote-sensing-derived land-use data were used to characterize the land-change processes in China’s Loess Plateau, which is experiencing large-scale ecological restoration. Geographically Weighted Regression was applied to capture the spatiotemporal variations in land change and driving-force relationships. First, we explored land-use change in the Loess Plateau for the period 1990–2015. Grassland, cropland and forestland were dominant land cover in the region, with a total percentage area of 88%. The region experienced dramatic land-use transitions during the study period: degraded grassland and wetland, expansion of cropland and built-up land and weak restoration of forestland during 1990–2000; and increases in grassland, built-up land, forestland and wetland, concurrent with shrinking cropland during 2000–2015. A Geographically Weighted Regression (GWR) analysis revealed altitude to be the common dominant factor associated with the four major land-use types (forestland, grassland, cropland and built-up land). Altitude and slope were found to be positively associated with forestland, while being negatively associated with cropland in the high, steep central region. For both forestland and grassland, temperature and precipitation behaved in a similar manner, with a positive hotspot in the northwest. Altitude, slope and distance to road were all negatively associated with built-up land across the region. The GWR captured the spatial non-stationarity on different socioeconomic driving forces. Spatial heterogeneity and temporal variation of the impact of socioeconomic drivers indicate that the ecological restoration projects positively affected the region’s greening trend with hotspots in the center and west, and also improved farmer well-being. Notably, urban population showed undesired effects, expressed in accelerating grassland degradation in central and western regions for 1990–2000, hindering forestland and grassland restoration in the south during 2000–2015, and highlighting the long-term sustainability of the vegetation restoration progress. Such local results have the potential to provide a methodological contribution (e.g., nesting local-level approaches, i.e., GWR, within land system research) and spatially explicit evidence for context-related and proactive land management (e.g., balancing urbanization and ecological restoration processes and advancing agricultural development and rural welfare improvement).

2020 ◽  
Vol 12 (3) ◽  
pp. 353 ◽  
Author(s):  
Xiaozheng Du ◽  
Xiang Zhao ◽  
Shunlin Liang ◽  
Jiacheng Zhao ◽  
Peipei Xu ◽  
...  

The global land surface cover is undergoing extensive changes in the context of global change, especially in the Loess Plateau, where ecological restoration policies have been vigorously implemented since 2000. Evaluating the impact of these policies on land cover is of great significance for regional sustainable development. Nonetheless, there are few quantitative assessment studies of the impact of ecological restoration policies on land use and land cover change (LULCC). In this study, a relative contribution conceptual model (RCCM) was used to explore the contribution of the policies to LULCC under the influence of natural background change, which was based on the Markov chain and the future land use simulation (FLUS) model. The results show that LULCC is influenced by ecological restoration policies and the natural environment, of which the policies contribute about 72.37% and natural change contribute about 27.63%. Ecological restoration policies have a profound impact on LULCC, changing the original direction of LULCC greatly. Additionally, these policies regulate the pattern of LULCC by controlling the amount of cropland as a rebalanced leverage. These findings provide useful information for facilitating sustainable ecological development in the Loess Plateau and theoretically supporting environmental decision-making.


2020 ◽  
Vol 9 (6) ◽  
pp. 345
Author(s):  
Tao Li ◽  
Xiaoshu Cao ◽  
Menglong Qiu ◽  
Yu Li

The spatial pattern of rural poverty and its influencing factors are unique in regions located in the “double zone”, overlaying the Loess Plateau landform and interprovincial border socioeconomic zone. Using Huining County, located in the interprovincial border area of the Loess Plateau, as a case study, this paper examines the spatial heterogeneity of rural poverty patterns and poverty-causing factors by using geographically weighted regression (GWR) modeling. The potential accessibility indicator is employed to identify the formative mechanism of rural poverty. The results show that rural poverty is significantly correlated with county-level accessibility, water resource accessibility, and town-level accessibility. County-level accessibility and town-level accessibility have significant border effects on rural poverty. The arid characteristics in certain areas of the Loess Plateau mean that the impact of water resource accessibility on the incidence of rural poverty is second only to that of county-level accessibility. Forestland resources have a positive correlation with the incidence of rural poverty in the region dominated by farming. Finally, targeted poverty reduction policies are proposed based on the results of the analysis of poverty-causing factors. The findings derived from this paper can help other developing countries in designing their own poverty reduction policies.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Chuqiao Chen ◽  
Simon Hu ◽  
Washington Y. Ochieng ◽  
Na Xie ◽  
Xiqun (Michael) Chen

The emerging ride-sourcing service has become an important element of urban mobility. A challenging question underlying the provision of such service is how and to what extent the built environment affects origin-destination (OD) travel flows. This paper employs the geographically weighted regression (GWR) model to analyze the OD-based ride-sourcing travel flow. It makes a comparison with the existing ordinary least square (OLS) model and spatial autocorrelation model (SAM). We have collected ride-sourcing order data in Hangzhou, China, to provide an accurate source for acquiring ride-sourcing travel flow. We investigate the effects of the residential area, points of interest (POIs), and transit stations on ride-sourcing travel flow among traffic analysis zones (TAZs). The results show the following: (a) GWR has better goodness-of-fit than SAM and OLS. (b) Residential area, enterprise, and bus stations have positive correlations with ride-sourcing OD flows, but education and subway stations have negative correlations. We have further investigated the issue and found that it is not a causal relationship between the bus station and OD flow, due to collinearity between the two variables. The bus station builds on locations with high demand, but its capacity is not large enough to reduce the ride-sourcing flow to a low level, which results in a positive coefficient. (c) Based on the estimated coefficients, the prediction of ride-sourcing flows is feasible, supporting the impact analysis for urban land use and transportation planning. This paper contributes to understanding OD-based ride-sourcing travel flow distributions and provides a framework of long-term OD flow prediction for urban land use and transportation planning.


Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 673
Author(s):  
Chen Yang ◽  
Meichen Fu ◽  
Dingrao Feng ◽  
Yiyu Sun ◽  
Guohui Zhai

Vegetation plays a key role in ecosystem regulation and influences our capacity for sustainable development. Global vegetation cover has changed dramatically over the past decades in response to both natural and anthropogenic factors; therefore, it is necessary to analyze the spatiotemporal changes in vegetation cover and its influencing factors. Moreover, ecological engineering projects, such as the “Grain for Green” project implemented in 1999, have been introduced to improve the ecological environment by enhancing forest coverage. In our study, we analyzed the changes in vegetation cover across the Loess Plateau of China and the impacts of influencing factors. First, we analyzed the latitudinal and longitudinal changes in vegetation coverage. Second, we displayed the spatiotemporal changes in vegetation cover based on Theil-Sen slope analysis and the Mann-Kendall test. Third, the Hurst exponent was used to predict future changes in vegetation coverage. Fourth, we assessed the relationship between vegetation cover and the influence of individual factors. Finally, ordinary least squares regression and the geographically weighted regression model were used to investigate the influence of various factors on vegetation cover. We found that the Loess Plateau showed large-scale greening from 2000 to 2015, though some regions showed decreasing vegetation cover. Latitudinal and longitudinal changes in vegetation coverage presented a net increase. Moreover, some areas of the Loess Plateau are at risk of degradation in the future, but most areas showed a sustainable increase in vegetation cover. Temperature, precipitation, gross domestic product (GDP), slope, cropland percentage, forest percentage, and built-up land percentage displayed different relationships with vegetation cover. Geographically weighted regression model revealed that GDP, temperature, precipitation, forest percentage, cropland percentage, built-up land percentage, and slope significantly influenced (p < 0.05) vegetation cover in 2000. In comparison, precipitation, forest percentage, cropland percentage, and built-up land percentage significantly affected (p < 0.05) vegetation cover in 2015. Our results enhance our understanding of the ecological and environmental changes in the Loess Plateau.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ferdinando Ofria ◽  
Massimo Mucciardi

PurposeThe purpose is to analyze the spatially varying impacts of corruption and public debt as % of GDP (proxies of government failures) on non-performing loans (NPLs) in European countries; comparing two periods: one prior to the crisis of 2007 and another one after that. The authors first modeled the NPLs with an ordinary lest square (OLS) regression and found clear evidence of spatial instability in the distribution of the residuals. As a second step, the authors utilized the geographically weighted regression (GWR) to explore regional variations in the relationship between NPLs and the proxies of “Government failures”.Design/methodology/approachThe authors first modeled the NPL with an OLS regression and found clear evidence of spatial instability in the distribution of the residuals. As a second step, the author utilized the Geographically Weighted Regression (GWR) (Fotheringham et al., 2002) to explore regional variations in the relationship between NPLs and proxies of “Government failures” (corruption and public debt as % of GDP).FindingsThe results confirm that corruption and public debt as % of GDP, after the crisis of 2007, have affected significantly on NPLs of the EU countries and the following countries neighboring the EU: Switzerland, Iceland, Norway, Montenegro, and Turkey.Originality/valueIn a spatial prospective, unprecedented in the literature, this research focused on the impact of corruption and public debt as % of GDP on NPLs in European countries. The positive correlation, as expected, between public debt and NPLs highlights that fiscal problems in Eurozone countries have led to an important rise of problem loans. The impact of institutional corruption on NPLs reports that the higher the corruption, the higher is the level of NPLs.


Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3147
Author(s):  
Mengxue Zhang ◽  
Radosław Stodolak ◽  
Jianxin Xia

Climate, land use and human activity have an impact on the Qingshui River in Chongli County. The Soil and Water Assessment Tool (SWAT) was used to separately analyze the contributions of climate, land use and direct human activity on the discharge variations. The results indicated that human activity had been the dominant factor for the discharge decrease, while climate and land use change had a positive influence on the discharge increase. The contributions of these three factors were −56.24%, 38.59% and 5.17%, respectively. Moreover, on the seasonal scale, the impact of those factors was consistent with their impact on the annual scale. Human activity was the main factor for discharge decrease in the summer, the contribution accounting for −77.13%. Due to the over-extraction of groundwater for irrigation and use in the mining industry, the discharge showed a decreasing tendency, which has the potential to place stress on sustainable water use in the future. The result of the study may contribute to the optimization of water resource allocation and management.


2007 ◽  
Vol 20 (2) ◽  
Author(s):  
Yasmin Handaja ◽  
Hans De Witte

Quantitative and qualitative job insecurity: associations with job satisfaction and well-being Quantitative and qualitative job insecurity: associations with job satisfaction and well-being Y. Handaja & H. De Witte, Gedrag & Organisatie, volume 20, June 2007, nr. 2, pp. 137-159 This study analyses the associations between both quantitative and qualitative job insecurity and job satisfaction and psychological ill-being. We also analyse whether the relationship between job insecurity and psychological ill-being is mediated by job satisfaction. A more subtle and differentiated measurement of qualitative job insecurity is used, in which insecurity is measured regarding four aspects: the job content, working circumstances, working conditions and social relations. Data gathered among Belgian bank employees are used to test the hypotheses. The results show that both quantitative and qualitative job insecurity are negatively associated with job satisfaction and positively associated with psychological ill-being. The relationship between job insecurity and psychological ill-being is only partially mediated by job satisfaction. This signifies that the impact of job insecurity exceeds the boundaries of work, since it exerts an autonomous impact on the psychological well-being of individual workers. Limitations of the research and recommendations for further research are discussed.  


Land ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 147
Author(s):  
Hiebert ◽  
Allen

As global consumption and development rates continue to grow, there will be persistent stress placed on public goods, namely environmental amenities. Urban sprawl and development places pressure on forested areas, as they are often displaced or degraded in the name of economic development. This is problematic because environmental amenities are valued by the public, but traditional market analysis typically obscures the value of these goods and services that are not explicitly traded in a market setting. This research examines the non-market value of environmental amenities in Greenville County, SC, by utilizing a hedonic price model of home sale data in 2011. We overlaid home sale data with 2011 National Land Cover Data to estimate the value of a forest view, proximity to a forest, and proximity to agriculture on the value of homes. We then ran two regression models, an ordinary least squares (OLS) and a geographically weighted regression to compare the impact of space on the hedonic model variables. Results show that citizens in Greenville County are willing to pay for environmental amenities, particularly views of a forest and proximity to forested and agricultural areas. However, the impact and directionality of these variables differ greatly across space. These findings suggest the need for an integration of spatial dynamics into environmental valuation estimates to inform conservation policy and intentional city planning.


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