Exploring the eco-efficiency of cultivated land utilization and its influencing factors in China's Yangtze River Economic Belt, 2001–2018

2021 ◽  
Vol 294 ◽  
pp. 112939
Author(s):  
Bin Yang ◽  
Zhanqi Wang ◽  
Lei Zou ◽  
Lilin Zou ◽  
Hongwei Zhang
Keyword(s):  
Influencing Factors ◽  
Yangtze River ◽  
Cultivated Land ◽  
Land Utilization

scholarly journals Temporal-Spatial Differentiation and Optimization Analysis of Cultivated Land Green Utilization Efficiency in China

Land ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 158 ◽  
Author(s):  
Qianru Chen ◽  
Hualin Xie
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Spatial Differentiation ◽  
Utilization Efficiency ◽  
Added Value ◽  
Scale Model ◽  
Eastern Region ◽  
Cultivated Land ◽  
Land Utilization ◽  
Extension System

Cultivated land is closely related to national food security, rural economic development and social stability. The cultivated land pollution and carbon emissions caused by chemical fertilizers, pesticides, film residues, etc., in the process of cultivated land utilization pose a serious threat to the cultivated land ecosystem in China. The comprehensive analysis on the cultivated land green utilization efficiency (GUECL), its influencing factors, and optimization direction provides a valuable basis for the green utilization of cultivated land. Based on a panel data of 30 provinces (cities or districts) in China from 2001 to 2016, the GUECL in China under the constraints of pollution and carbon emissions was measured by using a super-efficient SBM-VRS (slack based model-variable return to scale) model. The influencing factors and optimization directions of the GUECL were analyzed through the Tobit model and slack values, respectively. The results show that the GUECL in China rose with fluctuations from 2001 to 2016. Since 2014, the eastern region has surpassed the western region and has become the region with the highest mean GUECL value. The room for resource conservation and pollution reduction varies in different regions of China. Farmers’ dependence on cultivated land and agricultural added value are positively related to the GUECL in China. Farmers’ occupational differentiation, agricultural machinery density, and agricultural disaster rate have had negative effects on the GUECL in China. The loss of the GUECL in China is mainly due to the redundancies of land input, pollution emission, and mechanical input. By analyzing these influencing factors and optimization directions, it is concluded that improving rural land transfer market and agricultural infrastructure construction, establishing a new agricultural technology extension system, and vigorously cultivating new professional farmers are the targeted measures to improve the GUECL.

scholarly journals The evolution of cultivated land utilization efficiency and its influencing factors in Nanyang Basin

2021 ◽  
Vol 36 (3) ◽  
pp. 688
Author(s):  
Zheng-xin JI ◽  
Xiu-li WANG ◽  
Ling LI ◽  
Xiao-ke GUAN ◽  
Lin YU ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Utilization Efficiency ◽  
Cultivated Land ◽  
Land Utilization

scholarly journals The Spatio-Temporal Analysis of Urban-Rural Coordinated Development and Its Driving Forces in Yangtze River Delta

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 495
Author(s):  
Daizhong Tang ◽  
Mengyuan Mao ◽  
Jiangang Shi ◽  
Wenwen Hua
Keyword(s):  
Influencing Factors ◽  
Yangtze River ◽  
Driving Forces ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
System Level ◽  
Actual State ◽  
Coordinated Development ◽  
Urban Rural

This paper conducts an analytical study on the urban-rural coordinated development (URCD) in the Yangtze River Delta urban agglomeration (YRDUA), and uses data from 2000–2015 of 27 central cities to study the spatial and temporal evolution patterns of URCD and to discover the influencing factors and driving forces behind it through PCA, ESDA and spatial regression models. It reveals that URCD of the YRDUA shows an obvious club convergence phenomenon during the research duration. The regions with high-level URCD gather mainly in the central part of the urban agglomeration, while the remaining regions mostly have low-level URCD, reflecting the regional aggregation phenomenon of spatial divergence. At the same time, we split URCD into efficiency and equity: urban-rural efficient development (URED) also exhibits similar spatiotemporal evolution patterns, but the patterns of urban-rural balanced development (URBD) show some variability. Finally, by analyzing the driving forces in major years during 2000–2015, it can be concluded that: (i) In recent years, influencing factors such as government financial input and consumption no longer play the main driving role. (ii) Influencing factors such as industrialization degree, fixed asset investment and foreign investment even limit URCD in some years. The above results also show that the government should redesign at the system level to give full play to the contributing factors depending on the actual state of development in different regions and promote the coordinated development of urban and rural areas. The results of this study show that the idea of measuring URCD from two dimensions of efficiency and equity is practical and feasible, and the spatial econometric model can reveal the spatial distribution heterogeneity and time evolution characteristics of regional development, which can provide useful insights for urban-rural integration development of other countries and regions.

scholarly journals Spatial Distribution and Land Use of Traditional Villages in Southwest China

2021 ◽  
Vol 13 (11) ◽  
pp. 6326
Author(s):  
Xiye Zheng ◽  
Jiahui Wu ◽  
Hongbing Deng
Keyword(s):  
Cultural Heritage ◽  
Influencing Factors ◽  
Landscape Pattern ◽  
Southwest China ◽  
Spatial Clustering ◽  
Interaction Mechanism ◽  
Cultivated Land ◽  
River Population ◽  
Local Conditions ◽  
Countermeasures And Suggestions

Traditional villages are the historical and cultural heritage of people around the world. With the increases in urbanization and industrialization, the continuation of traditional villages and the inheritance of historical and cultural heritage are facing risk. Therefore, to grasp the spatial characteristics of them and the human–nature interaction mechanism in Southwest China, we analyzed the distribution pattern of traditional villages using the ArcGIS software. Then, we further analyzed the spatial clustering characteristics, influencing factors and landscape pattern, and put forward relevant protection countermeasures and suggestions. The results revealed that traditional villages in Southwest China were clustered, being mainly distributed in areas with relatively low elevation, gentle slopes, low relative positions, nearby water sources, and convenient transportation. They can be divided into four categories due to obvious differences in influencing factors such as elevation, slope, relative position, distance to the nearest river, population density, etc. The landscape pattern of traditional villages differed among the different clusters, being mainly composed of forests, shrubs, and cultivated land. With the increase in the buffer radius, the landscape pattern of them changed significantly. The results of this study reflect that traditional villages and the natural environment are interdependent, so the protection of traditional villages should carry out measures according to local conditions.

scholarly journals Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data

2021 ◽  
Vol 13 (6) ◽  
pp. 1150
Author(s):  
Yang Zhong ◽  
Aiwen Lin ◽  
Chiwei Xiao ◽  
Zhigao Zhou
Keyword(s):  
Influencing Factors ◽  
Yangtze River ◽  
Electrical Power ◽  
Random Forest Algorithm ◽  
Temporal Dynamic ◽  
Urban Agglomerations ◽  
Evolution Characteristics ◽  
Spatio Temporal ◽  
Electrical Power Consumption ◽  
Gwr Model

In this paper, based on electrical power consumption (EPC) data extracted from DMSP/OLS night light data, we select three national-level urban agglomerations in China’s Yangtze River Economic Belt(YREB), includes Yangtze River Delta urban agglomerations(YRDUA), urban agglomeration in the middle reaches of the Yangtze River(UAMRYR), and Chengdu-Chongqing urban agglomeration(CCUA) as the research objects. In addition, the coefficient of variation (CV), kernel density analysis, cold hot spot analysis, trend analysis, standard deviation ellipse and Moran’s I Index were used to analyze the Spatio-temporal Dynamic Evolution Characteristics of EPC in the three urban agglomerations of the YREB. In addition, we also use geographically weighted regression (GWR) model and random forest algorithm to analyze the influencing factors of EPC in the three major urban agglomerations in YREB. The results of this study show that from 1992 to 2013, the CV of the EPC in the three urban agglomerations of YREB has been declining at the overall level. At the same time, the highest EPC value is in YRDUA, followed by UAMRYR and CCUA. In addition, with the increase of time, the high-value areas of EPC hot spots are basically distributed in YRDUA. The standard deviation ellipses of the EPC of the three urban agglomerations of YREB clearly show the characteristics of “east-west” spatial distribution. With the increase of time, the correlations and the agglomeration of the EPC in the three urban agglomerations of the YREB were both become more and more obvious. In terms of influencing factor analysis, by using GWR model, we found that the five influencing factors we selected basically have a positive impact on the EPC of the YREB. By using the Random forest algorithm, we found that the three main influencing factors of EPC in the three major urban agglomerations in the YREB are the proportion of secondary industry in GDP, Per capita disposable income of urban residents, and Urbanization rate.

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