An improved knowledge-informed NSGA-II for multi-objective land allocation (MOLA)

Multi-objective land allocation(MOLA)can be regarded as a spatial optimization problem that allocates appropriate use to certain land units subjecting to multiple objectives and constraints.This article develops an improved knowledge-informed non-dominated sorting genetic algorithm II(NSGA-II)for solving the MOLA problem by integrating the patch-based,edge growing/decreasing,neighborhood,and constraint steering rules.By applying both the classical and the knowledge-informed NSGA-II to a simulated planning area of 30×30 grid,we find that:when compared to the classical NSGA-II,the knowledge-informed NSGA-II consistently produces solutions much closer to the true Pareto front within shorter computation time without sacrificing the solution diversity;the knowledge-informed NSGA-II is more effective and more efficient in encouraging compact land allocation;the solutions produced by the knowledge-informed have less scattered/isolated land units and provide a good compromise between construction sprawl and conservation land protection.The better performance proves that knowledge-informed NSGA-II is a more reasonable and desirable approach in the planning context.

Scenario-based estimation of catchment carbon storage: linking multi-objective land allocation with InVEST model in a mixed agriculture-forest landscape

This study performed a scenario-based land allocation in a mixed agriculture-forest landscape in northern Iran to investigate how different land use policies contribute to changes in carbon storage.In pursuit of this goal,a temporal profile of the trade-off between the region’s land use land cover(LULC)classes was produced using Landsat image of the year 2016.The weighted linear combination procedure was also used to map the suitability of land for agriculture,forest,urban,and rangeland based on ecological and socio-economic criteria.The suitability maps were analyzed through the Multi-Objective Land Allocation procedure under five scenarios with differing areas devoted to each LULC to generate different patterns of LULC distribution in the region.In addition,the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model was used to estimate the potential of LULC classes in carbon storage.The amount of carbon storage differed significantly between the scenarios,ranging from 1.29 tons/ha/year when the majority of the land was devoted to agriculture(76%of the area)to 5.40 tons/ha/year when the landscape was dominated by forest(77%of the area).The extreme conditions presented in this research may not be as likely to occur,but opens a dialog between different stakeholders and informs of a probable trend of ecosystem service loss due to agricultural land expansion.

Land Allocation between Food and Energy

Many countries are promoting biofuels as a substitute for scarce oil. This paper develops a dynamic model of land allocation between food and energy and shows how the model can be calibrated using standard optimization techniques. Some possible implications of the trade-offs between food and energy are discussed. Specifically, we show that the effect of mandates is mainly felt through increased land conversion, which increases indirect carbon emissions Crude oil prices do not decrease significantly because of leakages.

Integrated use of GIS, remote sensing and multi-criteria decision analysis to assess ecological land suitability in multi-functional forestry

The Zagros forests are a treasure of valuable oak forests, but they have been severely degraded from long-term misuse. Geographic information systems （GIS） and multi-criteria decision analysis （MCDA） have been increasingly used to improve the management of vulnerable ecosystems to prevent further degradation and increase the sustainability of land use. This study presents a methodology to assess land suitability using remote sensing （RS） to obtain wall-to-wall data for the calculations, GIS to analyze the data, and MCDA to rank alternative land uses. The criteria and subcriteria affecting the suitability of land for different uses were identified and weighted using an analytic hierarchy process. Variables used as subcriteria were assessed using satellite data and other sources of information such as existing maps and field surveys. Numerical values for the subcriteria were classified, and each class was given a priority rating according to expert judgments. Based on the ratings and weights of the subcriteria, a priority map was created for each land use using the weighted linear combination method. The priority maps for different land uses were overlaid to obtain a preliminary land use map, which often indicated several simultaneous land uses for the same location. The preliminary map was further edited by removing unrealistic, mutually exclusive land-use combinations. The study tested and demonstrated the potential of integrating RS, G1S and MCDA techniques for solving complicated land allocation problems in forested regions using a scientifically sound and practical approach for efficient and sustainable allocation of forestland for different uses.

Fiscal Pressure, Inter-Industrial Allocation of Land and Agglomerations Effects

Land is a production factor that supports industrial development and also an important resource for increasing local government revenue.The scientific allocation of land has a positive effect on applying a new development philosophy.Based on the data of China's micro land transaction,this paper constructs the industrial dispersion indicator of land transfer to discuss about how short-term fiscal pressure affects allocation of land resources among industries and then analyzes its impacts on agglomeration effects.The results show that the greater the short-term fiscal pressure,the higher the dispersion of land transfer among industries,which holds true after going through a series of robustness tests.Further analyses show that the dispersion of land transfer among industries deteriorates the policy orientation of giving priority to key industries.Finally,the practice of dispersion of land transfer among industries weakens agglomeration economies.The research results of this paper show that local governments'strategy of land transfer among induestries for coping with short-term fiscal pressure has the characteristics of"increasing fiscal revenues and weakening the role of industrial guidance."This means that in the new stage of development,local governments urgently need to enhance their understanding of the multiple functions of land and avoid impairing industrial development for addressing the shortterm fiscal pressure.

Modelling urban expansion using a multi agentbased model in the city of Changsha

Although traditional urban expansion simulation models can simulate dynamic features, these models fail to address complex changes produced by different agents＇ behaviors. The paper has built up a set of spatial-temporal land resource allocation rules and developed a dynamic urban expansion model based on a multi-agent system, which can simulate the interaction among different agents, such as residents, peasants, and governments. This model is applied to simulate urban expansion process taking Changsha City, in China as a study area. The results show that this model can not only reflect basic characteristics of urban expansion, but also help explain the reasons for urban expansion process and understand the effect of agents＇ behavior on the expansion process, and provide insights into the causing factors behind the expansion. In addition, in contrast to simulation results with land use classification map from remote sensing images, the precision of the simulation reached over 68% with higher precision than cellular automata model according to the cell-by-cell comparison. The results suggest that the model can help to provide land use decision making support to government and urban planners.

Government L and Regulations and Housing Supply Elasticity in Urban China

This paper studies the effects of government land regulations(GLR)on housing supply elasticity in urban China.We first extend the theoretical framework of Saiz(2010),then use land transaction microdata,satellite-generated data,and the construction of instrumental variables to analyze the marginal effect of GLR,and finally calculate the housing supply elasticity caused by GLR.Our analysis finds that GLR is an important reason for the overall inelasticity of housing supply in 272 Chinese cities,which reduces housing supply elasticity from 1.457(elastic)to 0.872(inelastic).Housing supply elasticity caused by GLR has declined the most in first-tier cities and the eastern regions.The marginal effect of land use regulation is greater than that of land allocation and supp!y regulations.The initial development level and natural geographic constraint of each city also matter in China's housing supply market.