Land use database generalization aided by supporting data structure and semantic evaluation model

2004 ◽  
Author(s):  
Yaolin Liu
Keyword(s):  
Land Use ◽  
Data Structure ◽  
Evaluation Model ◽  
Database Generalization

scholarly journals Recessive Transition Mechanism of Arable Land Use Based on the Perspective of Coupling Coordination of Input–Output: A Case Study of 31 Provinces in China

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 41
Author(s):  
Yi Lou ◽  
Guanyi Yin ◽  
Yue Xin ◽  
Shuai Xie ◽  
Guanghao Li ◽  
...  
Keyword(s):  
Land Use ◽  
Evaluation Model ◽  
Arable Land ◽  
Temporal Trends ◽  
Mainland China ◽  
Input Output ◽  
Transition Mechanism ◽  
Input And Output ◽  
Spatio Temporal ◽  
Arable Land Use

In the rapid process of urbanization in China, arable land resources are faced with dual challenges in terms of quantity and quality. Starting with the change in the coupling coordination relationship between the input and output on arable land, this study applies an evaluation model of the degree of coupling coordination between the input and output (D_CCIO) on arable land and deeply analyzes the recessive transition mechanism and internal differences in arable land use modes in 31 provinces on mainland China. The results show that the total amount and the amount per unit area of the input and output on arable land in China have presented different spatio-temporal trends, along with the mismatched movement of the spatial barycenter. Although the D_CCIO on arable land increases slowly as a whole, 31 provinces show different recessive transition mechanisms of arable land use, which is hidden in the internal changes in the input–output structure. The results of this study highlight the different recessive transition patterns of arable land use in different provinces of China, which points to the outlook for higher technical input, optimized planting structure, and the coordination of human-land relationships.

scholarly journals An Exploration of a Synthetic Construction Land Use Quality Evaluation Based on Economic-Social-Ecological Coupling Perspective: A Case Study in Major Chinese Cities

2020 ◽  
Vol 17 (10) ◽  
pp. 3663
Author(s):  
Xufeng Cui ◽  
Sheng Yang ◽  
Guanghong Zhang ◽  
Bin Liang ◽  
Fei Li
Keyword(s):  
Land Use ◽  
Negative Impact ◽  
Evaluation Model ◽  
Evaluation Framework ◽  
Ecological Quality ◽  
Coordinated Development ◽  
Construction Land ◽  
The Social ◽  
Synthetic Construction

Recently, with the rapid increase of urban population and industrial agglomeration, the price of construction land has increased, and construction land has become increasingly scarce. Therefore, how to improve the construction land use quality (CLUQ) becomes more and more important. The purpose of the study is to evaluate CLUQ in China’s major cities and to analyze the dominant obstacle factors for quality improvement in order to provide policy advice for construction land management. This study adapts the data from 2014 to 2016 and constructs the evaluation framework of CLUQ involving economic quality, social quality, and ecological quality of construction land to evaluate and analyze CLUQ with the synthetic evaluation model, coupling evaluation model, and obstacle diagnosis model (ECO model). This study shows that the synthetic CLUQ of 23 cities out of 36 major cities in China shows a general increasing state. The economic quality of 26 cities out of 36 major cities in China has increased, while the social and ecological quality of 20 out of 36 major cities in China has decreased. In terms of spatial characteristics, the synthetic quality in the east and southwest of China is relatively high; in terms of spatial trend, the synthetic quality in longitude increases from west to east, and it shows an inverted U-shaped state in latitude. Moreover, economic development is the main obstacle factor for the improvement of CLUQ in Hohhot, Lanzhou, Urumqi, and Changchun. Social development results in the CLUQ lagging in Beijing, Guiyang, Shanghai, Xining, and Chongqing. Ecological development has a negative impact in that of Harbin, Qingdao, and Wuhan. Furthermore. The improvement of CLUQ lies in the coupling and coordinated development of economic, social, and ecological quality. For those with a low coupling degree, the targeted suggestions are given for different types based on city’s quadrant distribution.

A benefit evaluation model for build-up land use in megacity suburban districts

2020 ◽  
Vol 99 ◽  
pp. 104861 ◽  
Author(s):  
Lie You ◽  
Yurui Li ◽  
Rui Wang ◽  
Haozhi Pan
Keyword(s):  
Land Use ◽  
Evaluation Model ◽  
Benefit Evaluation

Study on the Evaluation of Urban Industrial Land Intensive Use

2012 ◽  
Vol 226-228 ◽  
pp. 2442-2449 ◽  
Author(s):  
Zhen Hua Lu ◽  
Jun Lian Zhang ◽  
Xian Wen Li ◽  
Xiu Lian Wang ◽  
Xiao Fei Bai ◽  
...  
Keyword(s):  
Land Use ◽  
Policy Making ◽  
Evaluation Model ◽  
Control Policy ◽  
Indicator System ◽  
Scale Structure ◽  
Industrial Land ◽  
Industrial Land Use ◽  
Intensive Use ◽  
The Status

With the Comprehensive database of industrial land, the paper taken Hefei district as study area and taking Administrative regions as evaluation Unit, evaluated and analyzed the status of urban industrial land intensive use, the main steps of the research are: construct evaluating indicator system based on the scale, structure, intensity and layout; constitute criteria according to contents of the indicator system; construct evaluation model; put data of Hefei and criteria into the evaluation model and obtain the evaluating result about the intensive utilization of industrial land in Hefei; analyze the result to find problems and based on the problems in the industrial land use in Hefei, improving region industrial land intensive use suggestions were put forward in this paper to provide reference for region industrial land intensive use control Policy-making.

scholarly journals Optimization of random forest model for assessing and predicting geological hazards susceptibility in Lingyun County

2021 ◽  
Author(s):  
Chunfang Kong ◽  
Junzuo Wang ◽  
Xiaogang Ma ◽  
Yiping Tian ◽  
Zhiting Zhang ◽  
...  
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Vegetation Index ◽  
Evaluation Model ◽  
Field Investigation ◽  
Slope Aspect ◽  
Geological Hazards ◽  
Operating Characteristics ◽  
Model Based ◽  
Prediction And Prevention

Abstract The frequent occurrence of geological hazards will not only cause peoples' property loss and deterioration of living environments, but will also endanger peoples' lives. Therefore, rapid and accurate evaluation of geological hazards susceptibility can provide an important scientific basis for emergency rescue and disaster reduction and prevention. In this paper, ten effective variables including slope, aspect, curvature, normalized differential vegetation index, annual precipitation, strata lithology, tectonic complexity, residential density, road network density, and land use/land cover were selected as evaluation indexes. Meanwhile, random forest (RF) model is improved by the optimization of unbalanced geological hazards dataset, differentiation of continuous geological hazards evaluation factors, sample similarity calculation, and iterative method for finding optimal random characteristics by calculating out-of-bagger errors. The geological hazards susceptibility evaluation model based on optimized RF (OPRF) was established and used to assess the susceptibility level of geological hazards for Lingyun County. Then, receiver operating characteristics (ROC) curves and field investigation were performed to verify the efficiency for five models. Analysis and comparison of the results denoted that the model based on OPRF has the highest prediction accuracy of 93.4%, which is far better than the other four models. Furthermore, the evaluation results can provide reference for geological hazards prediction and prevention, and can also provide decision support for land use development and rational utilization of resources and environment in Lingyun County. Based on these results, the OPRF model could be extended to other regions with similar geological environment backgrounds for geological hazards susceptibility assessment and prediction.

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