Work

Investigating Multi-Objective Optimal Allocation of Coastal Cropland Driven by Industrial Clusters: A Case Study of Nantong, Jiangsu Province (China)

Year: 2026

Type: article

Abstract: The coastal zone exhibits complex resource constraints and environmental pressures, with marked industrial structure differentiation and considerable spatial stress on agriculture. This study enhances industrial cluster resilience by employing shift-share analysis to delineate industrial structure and constructing a multi-objective optimization model using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The model encompasses industrial cluster-driven development, economic benefits, social food security, ecological advantages, and land use efficiency, integrating coastal-specific constraints including soil salinity, tidal influence, and aquaculture competition. An empirical study in Nantong City, Jiangsu Province, China, demonstrates that optimized land allocation achieves a 3.13% reduction in cropland area while maintaining 42.56% coverage, increases forest land by 0.28% to 75.3847 km2, and enhances other land uses by 2.21% to 2169.6563 km2. The multi-objective optimization successfully balances five competing objectives with an overall improvement index of 0.847, validating both scientific robustness and practical feasibility. This research provides a scientific basis for agricultural space reconstruction and rural revitalization in coastal regions.

Source: Agriculture

DOI: 10.3390/agriculture16121326