scholarly journals Study On the Evaluation Index System And Standard Of Arable Land Health

2016 ◽  
Author(s):  
Mei Shan ◽  
Xun Wang
Keyword(s):  
Index System ◽  
Arable Land ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Land Health

scholarly journals Spatio-Temporal Variation Characteristics and Driving Forces of Farmland Shrinkage in Four Metropolises in East Asia

2020 ◽  
Vol 12 (3) ◽  
pp. 754 ◽  
Author(s):  
Yaxin Shi ◽  
Yishao Shi
Keyword(s):  
East Asia ◽  
Metropolitan Area ◽  
Index System ◽  
Arable Land ◽  
Driving Factors ◽  
Evaluation Index System ◽  
Primary Factor ◽  
Evaluation Index ◽  
Cultivated Land ◽  
Tokyo Metropolitan Area

The shrinkage of cultivated land is a general trend in metropolitan areas. However, previous studies have mainly paid attention to the shrinkage of arable land in major grain-producing areas, mixed agro-pastoral areas, ecologically fragile areas and construction areas of major engineering projects (such as the Three Gorges project). This paper analyses the characteristics and driving factors of cultivated land change on the metropolitan area scale and longer time dimension. Exemplified by four metropolises in East Asia, Tokyo, Beijing, Shanghai and Guangzhou, based on official statistics for the cities involved, using correlation analysis, principal component analysis and regression analysis methods and Statistical Product and Service Solutions (SPSS) 25 software, the main driving factors and differences in cultivated land shrinkage in Beijing, Shanghai, Guangzhou and the Tokyo metropolitan area are quantitatively revealed. The results show the following: (1) there are some differences in the shrinkage in arable land and spatial distributions among different cities. Tokyo and Guangzhou still have some cultivated land in central urban areas, while there is no arable land in the central areas of Beijing and Shanghai. (2) There is a clear difference in the main driving factors of cultivated land shrinkage between the Tokyo metropolitan area and Beijing, Shanghai and Guangzhou. Residential area and population are the main driving factors for the former, while economic development and urbanisation are the main driving factors for the latter three areas. It shows that the shrinkage of cultivated land is closely related to the developmental stage of urbanisation. (3) There is a rather obvious difference in the main driving factors of cultivated land change among Beijing, Shanghai and Guangzhou. Gross Domestic Product (GDP) is the primary factor leading to the shrinkage of arable land in Beijing, built-up area is the primary factor in Shanghai, and the Engel’s coefficient for rural residents is the primary factor in Guangzhou. This reflects the difference in measures for the utilisation and protection of cultivated land among different cities. (4) The socioeconomic factors that affect the contraction of cultivated land are varied. In this study, industrial restructuring is included in the evaluation index system, mainly because industrial transformation and upgrading is essential for sustainable development of emerging global cities, and agricultural production conditions are not included in the evaluation index system, mainly because they are more the result of urbanisation than the cause.

scholarly journals Research on Utility Evaluation of Grid Investment considering Risk Preference of Decision-Makers

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Hongliang Wu ◽  
Daoxin Peng ◽  
Ling Wang
Keyword(s):  
Index System ◽  
Evaluation Model ◽  
Risk Preference ◽  
System Optimization ◽  
Decision Makers ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Risk Appetite ◽  
Utility Evaluation ◽  
The Index System

Effectiveness evaluations are one of the important ways to guide grid investment and to improve investment efficiency. Improving the effectiveness of grid investment evaluations is studied based on the optimization of the investment evaluation index system and the utility evaluation model. The index system is optimized by establishing an evaluation index system of grid investment effectiveness, considering the redundancy between the indices, and constructing an ISM-DEA model. The utility function model was introduced to fully consider the different risk appetites of decision-makers, and a utility evaluation model that takes risk appetite into account was established. An improved weight integration model based on multiobjective optimization was established by considering the minimum deviation and the trend-optimal objective function when setting the index weights. The calculation results show that the feasibility of the index system optimization model and utility evaluation model constructed in this study is verified under the premise of satisfying the assumptions. By adjusting the risk preference coefficient of decision-makers, the dynamic optimization of the grid investment utility evaluation results can be realized.

Research on Degree Evaluation of Rural Waste Recycling of Heilongjiang Province Based on the Integrated Evaluation Method

2011 ◽  
Vol 347-353 ◽  
pp. 1735-1739
Author(s):  
Jie Shang ◽  
Yuan Yao
Keyword(s):  
Index System ◽  
Agricultural Waste ◽  
Waste Recycling ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Heilongjiang Province ◽  
Entropy Weight ◽  
Development Direction ◽  
Entropy Weight Method ◽  
Weight Method

This paper has analyzed the degree of agricultural waste recycling utilization, and problems existing in current rural calculated degree of waste recycling in Heilongjiang province, using AHP and entropy weight method integrated and construct the rural waste recycling system, and points out that the evaluation index system of agricultural waste recycling after the development direction.,This paper has analyzed the degree of agricultural waste recycling utilization, and problems existing in current rural calculated degree of waste recycling in Heilongjiang province, using AHP and entropy weight method integrated and construct the rural waste recycling system, and points out that the evaluation index system of agricultural waste recycling after the development direction.

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