What does this research mean for the field?

A balanced development scenario provides the most coordinated trade-off among economic development, ecological protection, food security, and landscape pattern stability for land use optimization in arid oasis regions. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To coordinate economic benefits, ecological protection, and food security by optimizing the quantitative structure and spatial distribution of land use in arid oasis regions.

August 24, 2026Land Degradation and DevelopmentOpen Access

Land Use Spatial Optimization Based on Multi‐Objective Ant Colony Algorithm and FLUS Model: A Case Study of Korla City and Tiemenguan City, China

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Authors

KZKaifa Zhang XYXiaojun Yin BLBenhao Li

Discussion

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Overview

Simulation study demonstrates multi-objective land allocation balances economic and ecological demands in arid regions, indicating a pathway for sustainable development.

Key Points

To coordinate economic benefits, ecological protection, and food security by optimizing the quantitative structure and spatial distribution of land use in arid oasis regions.
Optimized land use quantitative structure across economic, ecological, and food security objective functions using a multi-objective ant colony optimization (MOACO) algorithm.
Simulated spatial land allocation across four scenarios (economic priority, ecological priority, food production priority, and balanced development) using the future land use simulation (FLUS) model.
Evaluated landscape pattern characteristics and stability across all scenarios using Fragstats-4.2.
The spatial allocation model demonstrated high prediction reliability, achieving an overall simulation accuracy of 90.17%.
All four development scenarios led to increases in GDP, carbon sequestration, and grain production alongside marked reductions in soil erosion.
The balanced development scenario achieved the most coordinated trade-off among economic growth, ecological protection, food security, and landscape pattern stability.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a8c00c1bca056c88e6dfb13 https://doi.org/10.1002/ldr.70823

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August 24, 2026Land Degradation and DevelopmentOpen Access

Land Use Spatial Optimization Based on Multi‐Objective Ant Colony Algorithm and FLUS Model: A Case Study of Korla City and Tiemenguan City, China

View Full Paper

Ask AI

Bookmark

Authors

KZKaifa Zhang XYXiaojun Yin BLBenhao Li

Discussion

Member takes

Overview

Simulation study demonstrates multi-objective land allocation balances economic and ecological demands in arid regions, indicating a pathway for sustainable development.

Key Points

To coordinate economic benefits, ecological protection, and food security by optimizing the quantitative structure and spatial distribution of land use in arid oasis regions.
Optimized land use quantitative structure across economic, ecological, and food security objective functions using a multi-objective ant colony optimization (MOACO) algorithm.
Simulated spatial land allocation across four scenarios (economic priority, ecological priority, food production priority, and balanced development) using the future land use simulation (FLUS) model.
Evaluated landscape pattern characteristics and stability across all scenarios using Fragstats-4.2.
The spatial allocation model demonstrated high prediction reliability, achieving an overall simulation accuracy of 90.17%.
All four development scenarios led to increases in GDP, carbon sequestration, and grain production alongside marked reductions in soil erosion.
The balanced development scenario achieved the most coordinated trade-off among economic growth, ecological protection, food security, and landscape pattern stability.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a8c00c1bca056c88e6dfb13 https://doi.org/10.1002/ldr.70823

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