Optimization of low-carbon land use in Chengdu based on multi-objective linear programming and the future land use simulation model

Wu, Ran; Lan, Haifeng; Cao, Yuxin; Li, Ping‐Yi

doi:10.3389/fenvs.2022.989747

Cited by 8 publications

(6 citation statements)

References 54 publications

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“…Based on the population and land statistics from 2010 to 2020 and the GM (1,1) algorithm, the total population of Ningxia is predicted to reach 8.19 million, and the average population densities of construction land and agricultural land (woodland, grassland, and cropland) will be 16. 38 (5)…”

Section: The Gmop-plus Modelmentioning

confidence: 99%

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Multi-Scenario Land Use Optimization Simulation and Ecosystem Service Value Estimation Based on Fine-Scale Land Survey Data

Shu,

Wang,

Guo

et al. 2024

Land

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Land optimization simulation and ecosystem service value (ESV) estimation can better serve land managers in decision-making. However, land survey data are seldom used in existing studies, and land optimization constraints fail to fully consider land planning control, and the optimization at the provincial scale is not fine enough, which leads to a disconnection between academic research and land management. We coupled ESV, gray multi-objective optimization (GMOP), and patch-generating land use simulation (PLUS) models based on authoritative data on land management to project land use and ESV change under natural development (ND), rapid economic development (RED), ecological land protection (ELP), and sustainable development (SD) scenarios in 2030. The results show that construction land expanded dramatically (by 97.96% from 2000 to 2020), which encroached on grassland and cropland. This trend will continue in the BAU scenario. Construction land, woodland, and cropland are the main types of land used for expansion, while grassland and unused land, which lack strict use control, are the main land outflow categories. From 2000 to 2030, the total amount of ESV increases steadily and slightly. The spatial distribution of ESV is significantly aggregated and the agglomeration is increasing. The policy direction and land planning are important reasons for land use changes. The land use scenarios we set up can play an important role in preventing the uncontrolled expansion of construction land, mitigating the phenomenon of ecological construction, i.e., “governance while destruction”, and promoting food security. This study provides a new approach for provincial large-scale land optimization and ESV estimation based on land survey data and provides technical support for achieving sustainable land development.

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Section: The Gmop-plus Modelmentioning

confidence: 99%

“…Combined with random seed generation and a threshold-decreasing mechanism, it can realize the dynamic simulation of land use change at the patch level. It has been widely proven to have higher accuracy in land use simulation [22,38].…”

Section: Introductionmentioning

confidence: 99%

Multi-Scenario Land Use Optimization Simulation and Ecosystem Service Value Estimation Based on Fine-Scale Land Survey Data

Shu,

Wang,

Guo

et al. 2024

Land

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“…However, this green space pattern may have an impact on people's dietary needs. We might also start with the following factors to create sustainable growth in Harbin: First of all, advanced farming techniques can be introduced and scientific planting methods can be used to increase the agricultural yield per unit area [89,90]. Secondly, explore the new development mode of forests, wetlands, grasslands, etc.…”

Section: Uncertainties and Implicationsmentioning

confidence: 99%

Multi-Scenario Simulation of Green Space Landscape Pattern in Harbin City Based on FLUS Model

Gao

2023

IJERPH

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In this study, the change in green space in different scenarios and the index characteristics of landscape patterns were analyzed and were conducive to providing the decision basis for future green space planning in Harbin, a city in Northeast China. The FLUS model was used to predict the layout of green space, and the prediction results were analyzed and evaluated using the landscape index method. Combined with the MOP model and LINGO12.0, the objective function of economic benefit and ecological benefit was established to maximize the comprehensive benefit. As revealed by the outcome, from 2010 to 2020, the fragmentation degree of cultivated land, forest, and grassland decreased, and the overall landscape level tended to be diversified and uniform. In the status quo scenario, the cultivated land and the forest land were increased, whereas the water area and the wetland changed little, and its overall benefit was the lowest. The forest was increased by 137.46 km² in the ecological protection scenario, the largest among the three scenarios, and the overall water quality improved. In the economic development scenario, the cultivated land tended to expand rapidly, the connectivity was increased, and the area of forest was decreased by 69.19 km², and its comprehensive benefit is lower than that under the scenario of ecological protection. The sustainable development scenario achieved the most significant economic and ecological benefits, with a total income of CNY 435,860.88 million. Therefore, the future green space pattern should limit the expansion of cultivated land, maintain the spatial pattern of woodland and wetland, and enhance the protection of water area. In this study, Harbin green space was studied from different scenario perspectives, combined with landscape pattern index and multi-objective planning, which is of great significance for Harbin green space planning decisions in the future and improving comprehensive benefits.

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“…Secondly, divided by the methodological purpose of the research in this field, scholars have already used the main tools such as the multi-objective programming model (MOP), gray linear programming (GM (1, 1)), system dynamics, etc. to optimize the land structure [29,30]. The ant colony algorithm [24], meta-cellular automata model [31], genetic algorithm [32], CLUE-S [33] (conversion of land use and its effects at small region extent) model, and other methods have been more frequently used in land spatial optimization studies [34].…”

Section: Introductionmentioning

confidence: 99%

Spatial Optimization of Land Use Allocation Based on the Trade-off of Carbon Mitigation and Economic Benefits: A Study in Tianshan North Slope Urban Agglomeration

Lee,

Yin,

Zhu

2024

Land

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The rational allocation of land use space is crucial to carbon emissions reductions and economic development. However, previous studies have either examined inter-objective trade-offs or intra-objective trade-offs within a single objective and lacked multilevel and comprehensive studies. Therefore, this paper integrates inter- and intra-objective carbon mitigation and economic efficiency trade-offs to comprehensively study the interaction between land pattern demand and space due to policies. The research methods were mainly multi-objective planning, a gray model, and patch-generating land use simulation model, and the study area was the less-developed urban agglomeration—the Tianshan north slope urban agglomeration. The results of the study show that the total change area of the study area from 2000 to 2020 was 5767.94 km2, the grassland area was transferred out the most, 3582.59 km2, accounting for 62.11%, and the cultivated land area was transferred in the most, 3741.01 km2. Compared with 2020, the simulated land use pattern obtained for 2030 has significantly changed. In addition, the total economic benefits and total carbon emissions under the economic and low-carbon objectives changed in the opposite direction. The four landscape patterns under the three scenarios of economic and low-carbon objectives changed in the same direction, and the degree of landscape fragmentation, agglomeration, and regularity under the low-carbon objective was better than that under the economic objective. The study results are essential references for future land resource management, carbon mitigation, and sustainable development of urban agglomerations.

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Optimization of low-carbon land use in Chengdu based on multi-objective linear programming and the future land use simulation model

Cited by 8 publications

References 54 publications

Multi-Scenario Land Use Optimization Simulation and Ecosystem Service Value Estimation Based on Fine-Scale Land Survey Data

Multi-Scenario Land Use Optimization Simulation and Ecosystem Service Value Estimation Based on Fine-Scale Land Survey Data

Multi-Scenario Simulation of Green Space Landscape Pattern in Harbin City Based on FLUS Model

Spatial Optimization of Land Use Allocation Based on the Trade-off of Carbon Mitigation and Economic Benefits: A Study in Tianshan North Slope Urban Agglomeration

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