Evaluation and dynamic prediction of ecological security from the perspective of sustainable development: a case study of Shaanxi Province, China

被引:17
作者
Chen, Shuai [1 ]
Yao, Shunbo [1 ]
机构
[1] Northwest A&F Univ, Coll Econ & Management, 3 Taicheng Rd, Xianyang 712100, Peoples R China
基金
中国国家自然科学基金;
关键词
Ecological security; DPSR model; Time and space differences; Early warning; Sustainable development; CONFIRMATORY FACTOR-ANALYSIS; ENTROPY-WEIGHT; AREA; GREENSPACE; FOOTPRINT; MODEL; ARIMA;
D O I
10.1007/s11356-022-19812-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
How to measure the overall level of regional social economy, resources, and environment and how to grasp the coordinated development between them has become a hot issue. In this paper, the driving force-pressure-state-response (DPSR) model is used to build an ecological security index (ESI) system to measure the overall ecological security level of social economy, resources, and environment. In addition, dynamic nonlinear auto regressive (NAR) neural network is used to predict the ESI level to achieve the purpose of early warning. First, the results show that the weight of the employment rate, the proportion of students in colleges, and the per capita consumption level are relatively high, which play an important role for the ecological security level of Shaanxi Province. Second, Xi'an City has been the best level in ecological security level, the ecological security of Southwest Shaanxi is relatively good, which is related to its economic development and comparative advantage geographical conditions, while the ecological security level of Weinan and Shangluo are poor. Third, the ESI of most cities in Shaanxi Province is maintained at grade III. The ESI in Shaanxi has an upward trend from 2000 to 2006; however, the trend of this increase has not been maintained, and nearly half of the cities in Shaanxi have slightly decreased the ecological security level. Four, the ESI of Xi'an and Hanzhong will remain at a high level in the future, while the ecological security situation of Shangluo, Weinan, and Yulin probably become very poor in the next years.
引用
收藏
页码:42331 / 42346
页数:16
相关论文
共 69 条
[1]   Optimal Design Based on Fabricated SiC/B4C/Porcelain Filled Aluminium Alloy Matrix Composite Using Hybrid AHP/CRITIC-COPRAS Approach [J].
Aherwar, Amit ;
Pruncu, Catalin I. ;
Mia, Mozammel .
SILICON, 2022, 14 (02) :603-615
[2]   Climate extremes and housing rights: A political ecology of impacts, early warning and adaptation constraints in Lagos slum communities [J].
Ajibade, Idowu ;
McBean, Gordon .
GEOFORUM, 2014, 55 :76-86
[3]   Hydrometeorological Drought Forecasting in Hyper-Arid Climates Using Nonlinear Autoregressive Neural Networks [J].
Alsumaiei, Abdullah A. ;
Alrashidi, Mosaed S. .
WATER, 2020, 12 (09)
[4]   Forecasting hourly global solar radiation using hybrid k-means and nonlinear autoregressive neural network models [J].
Benmouiza, Khalil ;
Cheknane, Ali .
ENERGY CONVERSION AND MANAGEMENT, 2013, 75 :561-569
[5]  
Bonetto R, 2016, INT CONF SMART GRID
[6]   Early Warnings of Regime Shifts: A Whole-Ecosystem Experiment [J].
Carpenter, S. R. ;
Cole, J. J. ;
Pace, M. L. ;
Batt, R. ;
Brock, W. A. ;
Cline, T. ;
Coloso, J. ;
Hodgson, J. R. ;
Kitchell, J. F. ;
Seekell, D. A. ;
Smith, L. ;
Weidel, B. .
SCIENCE, 2011, 332 (6033) :1079-1082
[7]   Ecological security early-warning in central Yunnan Province, China, based on the gray model [J].
Chen, Yun ;
Wang, Jinliang .
ECOLOGICAL INDICATORS, 2020, 111 (111)
[8]  
Cheng C., 2017, ADV HIGH ENERGY PHYS, V2017, P1
[9]   Ecological Environment Evaluation of Liaohe Delta Wetland Based on PSR Model [J].
Cheng Qian ;
Zhou Linfei ;
Zhang Yulong .
ADVANCES IN ENVIRONMENTAL SCIENCE AND ENGINEERING, PTS 1-6, 2012, 518-523 :1133-1136
[10]   Day-ahead electricity price forecasting using the wavelet transform and ARIMA models [J].
Conejo, AJ ;
Plazas, MA ;
Espínola, R ;
Molina, AB .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (02) :1035-1042