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Updated: Jun 9, 2026
11:53
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Coordinating production-living-ecological space efficiency in suburban rural areas using a DEA-triangular model
Tianyi Zhao1, Wei Xu1, Yuning Cheng2
1School of Design, Art and Media, Nanjing University of Science and Technology, Nanjing, China.
Iscience
|June 8, 2026
Summary
Rural China
Area of Science:
- Rural Geography
- Spatial Planning
- Sustainable Development
Background:
- Rapid urbanization in China's suburban rural areas leads to low efficiency in production-living-ecological spaces (PLES).
- Existing research often overlooks trade-offs in spatial efficiencies and lacks integrated analytical frameworks for PLES.
- Addressing these inefficiencies is crucial for sustainable rural development.
Purpose of the Study:
- To enhance the utilization efficiency of production-living-ecological spaces (PLES) in multi-input/output systems.
- To analyze the spatiotemporal disparities and interrelationships within PLES in rural China.
- To provide a framework for improved rural governance and spatial management.
Main Methods:
- Data Envelopment Analysis (DEA) to measure spatial utilization efficiency.
- Geographic Information System (GIS) analysis to identify distribution patterns.
- Gini coefficient decomposition and a triangular model to analyze disparities and interrelationships.
Main Results:
- Average PLES utilization efficiency in Nanjing townships increased by 48.14% from 2011 to 2021.
- 17 townships shifted from imbalance to coordination, with 49% achieving primary coordination and 9% reaching high-quality coordination.
- Significant improvements in spatial utilization efficiency and coordination were observed.
Conclusions:
- The study developed an effective multi-criteria evaluation framework for PLES.
- The framework enhances the precision and coordination of rural governance and spatial management.
- Findings support sustainable rural development by optimizing PLES utilization.
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