scholarly journals Spatiotemporal Evolution and Influencing Factors of Urban Land Ecological Security in Yunnan Province

2021 ◽  
Vol 13 (5) ◽  
pp. 2936
Author(s):  
Renyi Yang ◽  
Wanying Du ◽  
Zisheng Yang
Keyword(s):  
Influencing Factors ◽  
Yunnan Province ◽  
Urban Land ◽  
Least Square ◽  
Ecological Security ◽  
Entropy Weight ◽  
Index Method ◽  
Dynamic Panel Model ◽  
Comprehensive Index ◽  
Land Ecological Security

(1) Background: Urban land ecological security is the basis and premise to ensure the sustainable utilization of urban land resources and regional sustainable development. However, urban land ecological security and its influencing factors have not been studied thoroughly. (2) Methods: An index system of urban land ecological security in Yunnan Province from 2010 to 2019 was constructed, and a comprehensive index of urban land ecological security was calculated by using analytic hierarchy process, entropy weight method, and comprehensive index method, and the LSDVC (Biased-corrected Least Square Dummy Variables) dynamic panel model was constructed from the economic, social and geographical dimensions to systematically analyze the influencing factors of urban land ecological security in Yunnan Province. (3) Results: The comprehensive index of urban land ecological security was significantly affected by the previous period, showing obvious inertia; with the improvement of urbanization level, the comprehensive index of urban land ecological security showed an inverted “U” shape, which first increased and then decreased; the decrease in comprehensive energy consumption per unit of industry and the improvement of fixed-asset investment level, science and technology level, and GDP will significantly promote the ecological security of urban land.

Assessing the Land Use Change and Ecological Security Based on RS and GIS: A Case Study of Pingdingshan City, China

2014 ◽  
Vol 905 ◽  
pp. 329-333 ◽  
Author(s):  
Di Lu ◽  
Hai Long Yu ◽  
Guang Ming Yu
Keyword(s):  
Land Use ◽  
Common Good ◽  
Land Use Changes ◽  
Evaluation Index System ◽  
Ecological Security ◽  
Entropy Weight ◽  
Gradual Development ◽  
Entropy Weight Method ◽  
Land Ecological Security ◽  
Ecological Construction

The land use changes are analyzed based on the interpretation of remote sensing image in the year of 1983, 1995, and 2009, and then an evaluation index system is established on the basis of “Hazard-State-Immune” model in Pingdingshan City, China. The entropy-weight method is used to determine the weights of index; the comprehensive index is used to evaluate the land ecological security in the study area. The results of the study show that the land ecological security is trending to obvious improvement after the gradual development (Common - Common – Good) in the past 30 years. And they also reveal the temporal-spatial distribution of land ecological security in this study area, which provides a foundation of ecological construction and the improvement of land ecological security.

scholarly journals Spatial-temporal evolution characteristics and influencing factors of county rural hollowing in Henan

2019 ◽  
Vol 49 (4) ◽  
Author(s):  
Menghao Yang ◽  
Zhihong Yao ◽  
Lianhai Cao ◽  
Haipeng Zhang ◽  
Jie Huang
Keyword(s):  
Influencing Factors ◽  
Temporal Evolution ◽  
Henan Province ◽  
Middle Level ◽  
Net Income ◽  
Entropy Weight ◽  
Index Method ◽  
Evolution Characteristics ◽  
Variation Characteristics ◽  
Per Capita

ABSTRACT: Taking Henan province as an example, the index system of rural hollowing was constructed from three aspects of economy, population and land. Using the entropy weight method, hollowing index method, spatial autocorrelation analysis and Geo detector, spatial-temporal evolution characteristics and influencing factors of county rural hollowing from 2000 to 2013 in Henan province were analyzed. Results showed that the gap of rural hollowing between counties in Henan province expanded first and then decrease, and the whole province was at the middle level of rural hollowing, so the development of rural hollowing in Henan province was stable and positive. Spatial variation characteristics of different degrees rural hollowing during 2000-2013 were obvious, and the overall spatial pattern was higher in the northwest-southeast direction and lower in the northeast-southwest direction. There was a strong spatial positive correlation in rural hollowing, and spatial agglomeration was slightly weakened; the number of counties in H-H and L-L agglomeration areas was large and its agglomeration characteristics were obvious; the H-L agglomeration areas started from zero with a small number and scattered distribution. Influence of different factors on rural hollowing was quite different, and the per capita homestead area, the proportion of secondary and tertiary industries, the investment in fixed assets and the per capita net income of farmers were the dominant factors.

scholarly journals Evaluation and Influencing Factors of Industrial Pollution in Jilin Restricted Development Zone: A Spatial Econometric Analysis

2021 ◽  
Vol 13 (8) ◽  
pp. 4194
Author(s):  
Yanhua Guo ◽  
Lianjun Tong ◽  
Lin Mei
Keyword(s):  
Influencing Factors ◽  
Industrial Pollution ◽  
Production Capacity ◽  
Pollution Index ◽  
Green Technology ◽  
Econometric Analysis ◽  
Ecological Civilization ◽  
Entropy Weight ◽  
Spatial Econometric ◽  
Spatial Econometric Analysis

Winning the battle against pollution and strengthening ecological protection in all respects are vital for promoting green development and building a moderately prosperous ecological civilization in China. Using the entropy weight method, this paper establishes and evaluates a comprehensive industrial pollution index that contains and synthesizes six major industrial pollutants (wastewater, COD, waste gas, SO2, NOx, and solid waste) in the 2006–2015 period. Subsequently, this paper studies the spatiotemporal characteristics and influencing factors of industrial pollution via the Moran index and spatial econometric analysis. The empirical results indicate that (1) the temporal evolution of the industrial pollution index is characterized by an overall trend of first decreasing and then increasing. (2) The industrial pollution index of each county has certain geographical disparities and significant spatially polarized characteristics in 2006, 2009, 2012, and 2015. (3) The Moran test shows that there is a relatively significant spatial autocorrelation of the industrial pollution index among counties and that the geographical distribution of the industrial pollution index tends to show clustering. (4) Spatial regression models that incorporate spatial factors better explain the influencing factors of industrial pollution. The economic development level, technological progress, and industrialization are negatively correlated with industrial pollution, while population density and industrial production capacity are positively correlated. (5) Consequently, as relevant policy recommendations, this paper proposes that environmental cooperation linkage mechanisms, environmental protection credit systems, and green technology innovation systems should be established in different geographical locations to achieve the goals of green county construction and sustainable development.

Sign in / Sign up

Export Citation Format

Share Document