Multi-objective Land Allocation Research Articles

Developing an integrated land allocation model based on linear programming and game theory.

Land use configuration in any given landscape is the result of a multi-objective optimization process, which takes into account different ecological, economic, and social factors. In this process, coordinating stakeholders is a key factor to successful spatial land use optimization. Stakeholders need to be modeled as players who have the ability to interact with each other towards their best solution, while considering multiple goals and constraints at the same time. Game theory provides a tool for land use planners to model and analyze such interactions. In order to apply the spatial allocation model and address stakeholder conflicts, an integrated model based on linear programming and game theory was designed in this study. For implementing such model, we conducted an optimal land use allocation process through multi-objective land allocation (MOLA) and linear programming methods. Then, two groups of environmental and land development players were considered to implement the optimization model. The game algorithm was used to select the appropriate constraint so that the result would be acceptable to all stakeholders. The results showed that during the third round of the game, the decision-making process and the optimization of land uses reached the desired Nash Equilibrium state and the conflict between stakeholders was resolved. Ultimately, in order to localize the results, a suitable solution was presented in a GIS environment.

Modelling Impact of Urban Expansion on Ecosystem Services: A Scenario-Based Approach in a Mixed Natural/Urbanised Landscape

The present study aims at predicting future land use/land cover (LULC) and quantifying and mapping the ecosystem services (ESs) of water yield, outdoor recreation opportunity and food production in current (here, 2017) and future landscapes in Northern Iran, using the InVEST, Recreation Opportunity Spectrum (ROS) and yield models. To that end, two LULC scenarios known as business as usual (BAU) and protection-based (PB) plan were applied for 2028, using the Markov Artificial Neural Network and Multi-objective land allocation (MOLA) models. The results show that rapid urbanisation, caused by the expansion of human settlements and industrial areas, has led to a decline in the ESs in the region. Compared to the ESs in 2017, the service of water yield increases as urban expansion increases, whereas food production and recreation services decrease as urban expansion increases, under the BAU scenario. On the other hand, in the PB scenario, relatively better conditions can be observed for all three ESs. Considering that the ecological structures of this region have been severely affected by rapid urban expansion, the results of this research will be useful for maintaining the existing ESs and can greatly affect planning and decision-making regarding future development towards urban sustainability.

Territorial spatial usage regulation based on resources endowment and sustainable development: A case of Wuhan, China

Urbanization with mismanagement has seriously threatened regional ecology and cultivated land security. At present, the territorial spatial usage regulations often isolate functions from a single aspect, which makes it difficult to meet demands of regional economic development, ecological protection, and sustainable development. This paper attempted to construct a zoning system of territorial spatial usages that comprehensively considers local development demands, resource endowment conditions, and sustainable development, and proposed a method to regulate sustainable development intensity. Wuhan City was selected as the study area. At first, the land resource function was zoned by the modified multi-objective land allocation (MOLA) model considering the resource endowment conditions and social development demands. The study area was divided into ecological, agricultural, and construction land resources. Also, the functions of land, water, and geological resources are integrated into the zonation framework of territorial spatial usages. Then, the construction and agricultural development intensity in different usage areas were quantitatively regulated by comprehensively considering the current basic demands, sustainable development, land use status, and relevant policies. The calculation results show that the development intensity of construction land in the construction space should be limited to 43%–53%, while the development intensity in the general farmland area should be limited to 10%. The agricultural development intensity should be greater than 65% in the general farmland, while it should be lower than 64% in the general ecological function area. Additionally, by comparing with the land-use status, the construction in the study area is within a reasonable scope (about 44%). The north and south of Huangpi District, the north of Xinzhou District, Hannan District, and the east of Caidian District still have great potential for development. Finally, based on territorial spatial usage and development intensity regulation, this paper proposed some effective suggestions for territorial spatial development. This paper can provide a reference for the territorial spatial planning and ecological environment protection of Wuhan City. At the same time, it provides a new idea for urban planning research considering the resource, environment, and economic development.

Sustainable Urban Land-Use Optimization Using GIS-Based Multicriteria Decision-Making (GIS-MCDM) Approach

Land-use optimization is an effective technique to produce optimal benefits in urban land-use planning. There are many approaches and methods to optimize land-use allocation. However, the focus on addressing urban sustainability in land-use optimization is very limited. In this study, we presented a GIS-based multicriteria decision-making (GIS-MCDM) approach to optimize the location of a new residential development considering sustainability dimensions (social, economic, and environmental benefits). Rajshahi City in Bangladesh was taken as a case study. Different types of data, including land use, land cover, ecosystem service value, land surface temperature, and carbon storage, were used to define sustainability criteria. Five physical criteria, three sustainability criteria, and two constraints were used to optimize residential land. Fuzzy membership functions were used to standardize the criteria. The ordered weighted averaging (OWA) was used to produce a residential suitability map. Finally, the multiobjective land allocation (MOLA) module of TerrSet v 19.0 was used to generate optimal locations under an alternative decision scenario. The findings suggest that about 9.00% more sustainability benefits can be achieved using our approach. Using our proposed approach, we also generated six alternative decision scenarios. Among the alternative decision strategies, “high risk–no trade-off” proved to be the most optimal decision strategy that generated the highest sustainability benefit in our case.

تلفیق نقشهسازی آلودگی هوا در برنامهریزی کاربری اراضی نمونة پژوهش: شهرستان مبارکه

تلفیق نقشهسازی آلودگی هوا در برنامهریزی کاربری اراضی نمونة پژوهش: شهرستان مبارکه

Simulation and optimization of land use pattern to embed ecological suitability in an oasis region: A case study of Ganzhou district, Gansu province, China

High-intensity land use has led to water resource imbalance and land degradation in oasis regions, which pose a great threat to ecological security. Optimization of land use patterns is crucial to ensuring the rational distribution of water and land resources and improving the stability of oasis ecosystems. The purpose of this study is to spatially allocate land use activities to more suitable regions. In this study, we first evaluated the land ecological suitability (LES) in Ganzhou District, a typical oasis region. Then, the LES evaluation results were embedded in an integrated CA–Markov model based on multiple criteria evaluation (MCE) and multi–objective land allocation (MOLA) to simulate and optimize land use patterns for the year 2025 under two scenarios, i.e., Business as Usual (BAU) and Land Ecological Optimization (LEO). The results revealed that the optimized land use pattern generated by LES was more reasonable. The growth rate of construction land was restricted, and a slightly increased area of construction land mainly occupied unused land. Farmland area had a decreasing trend, and was mainly converted to grassland. Moreover, the woodland and water areas had increasing trends. This study can serve as a scientific reference for planners and policy makers in formulating land use planning and land use resource management strategies in oasis regions.

GIS-Based Multi-Criteria and Multi-Objective Evaluation for Sustainable Land-Use Planning (Case Study: Qaleh Ganj County, Iran) \u201cLanduse Planning Using MCE and Mola\u201d

Land evaluation is a key factor in land-use spatial planning, affecting both success and sustainability. This study showcases the value of using the multi-criteria evaluation (MCE) and multi-objective land allocation (MOLA) GIS decision-making tools determine the most favorable spatial development of various land-use types, for Qaleh Ganj County in Iran. Weighted linear combination (WLC) and ordered weighted averaging (OWA) were used to assess the potential of seven land uses based on predefined criteria. MOLA was also used for land-use zoning based on suitability. The results derived from these techniques indicate that the rangeland zone with 30.80% and the ecotourism zone with 22.9% have the highest suitability potential, and aquaculture with 0.26% and tourism with 0.24% have the lowest potential in Qaleh Ganj. Considering the 7 land uses and a lot of defined criteria, MCE and MOLA provided an automatic and flexible way of dealing with qualitative multi-dimensional environmental effects, factors, constraints and objectives. The combination of WLC and OWA helped to manage selection factors differently, as their level of risk and trade-off is different. The result can be considered as optimal suitability maps with an environmental preservation goal which can help to protect the natural environment of this area, and will also allow for continued economic development. The approach described in this study can help developing countries and the sensitive area facing environmental challenges due to rapid development. This approach and its application procedures can be applied to similar territorial contexts, where several territorial factors should be considered and taken into account.

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.

A blueprint for a methodology to balance land-use in semi-natural areas

I investigated the effectiveness of a multi-criteria decision analysis process in integrating the study of community composition, aimed to allow sustainable use of semi-natural habitats. Weighted linear combination identified the suitability for recreational use and conservation potential of different sectors of the study area, obtained respectively from questionnaires and the examination of plant biodiversity. After assessing human impacts, I created a compromise scenario using a multi-objective land allocation method. I found a positive relationship between the most frequented areas and the presence of anthropogenic vegetation, but a negative relationship with biodiversity. My method effectively detected human presence hotspots and highlighted the most vulnerable areas. Therefore, multi-criteria decision analysis, used alongside plant ecology expertise, can successfully promote balanced land-use planning, especially in highly frequented regions with significant natural features.

Evaluación multicriterio y multiobjetivo para optimizar la selección de áreas para establecer plantaciones forestales

La selección del sitio adecuado para establecer plantaciones forestales es crucial si se desea maximizar su probabilidad de éxito. Los análisis de aptitud de tierras sirven para ese propósito al empatar los requerimientos ecológicos de las especies a plantar con el potencial productivo del suelo y con las condiciones climáticas existentes para el crecimiento óptimo de las especies elegidas. Este estudio describe un modelo, desarrollado en el marco del proceso analítico jerárquico y la asignación de tierras multiobjetivo e integrado en un sistema de información geográfica, para seleccionar el sitio óptimo para el establecimiento de plantaciones forestales comerciales en los municipios Durango, Nombre de Dios y Súchil, del estado de Durango, México, considerando seis especies de pino (Pinus engelmannii, P. leiophylla, P. arizonica, P. cembroides, P.chihuahuana y P. durangensis). El modelo es jerárquico, considera criterios y subcriterios climáticos, edafológicos y topográficos que afectan la localización de áreas adecuadas para establecer plantaciones forestales comerciales. Los valores de los subcriterios fueron estandarizados, ponderados y ordenados mediante matrices de comparaciones pareadas, considerando su importancia para el desarrollo de plantaciones. El modelo inicialmente cuantificó la aptitud de la tierra para establecer plantaciones forestales. Posteriormente, los resultados de aptitud se optimizaron mediante un procedimiento multiobjetivo para identificar la mejor especie a plantar en la zona bajo cuatro escenarios de decisión: turno de producción, calidad de la madera, supervivencia y susceptibilidad a plagas y enfermedades. Los resultados indican que el municipio de Durango presenta la mayor cantidad de áreas óptimas para establecer plantaciones forestales con las especies analizadas.

Multi-objective land allocation for zoning of ecosystem services in mountain forests

Abstract The paper proposes a system for zoning of mountain areas based on the level of provisioning of ecosystem services. Techniques of multi-objective land allocation were applied to allocate complementary and conflicting objectives. The zoning system consists of four phases: i) Identification of criteria for the evaluation of ecosystem services; ii) Quantification of criteria for three different forestland states; iii) Evaluation of potential and effect of the forest on providing the ecosystem services and iv) Zoning of ecosystem services with their prioritization and spatial allocation of support measures. The study was conducted in the Tatra Mountains (Slovakia). Erosion control, avalanche control, wood production and cultural services were evaluated. The greatest differences between potential and effect of the evaluated ecosystem services were identified for the avalanche control. A comparison of our results with the existing (control) map of ecosystem services has proved that the proposed system is a potent means for multi-objective forest planning.

Spatiotemporal analysis of the housing bubble's contribution to the proliferation of illegal landfills – The case of Gran Canaria

Illegal landfills are the source of many impacts that can alter the environment and represent a public health risk. This study investigates their spatiotemporal distribution in two representative areas of Gran Canaria: northwest (Zone A) and east (Zone B). Illegal landfill occurrence was simulated between 2000 and 2018, to estimate and spatially locate the surface growth of illegal landfills based on cellular automata, cellular automata-Markov and multiobjective land allocation models. The proliferation of illegal landfills in 2018 was simulated following the calibration and validation of the proposed models. Models' accuracy was assessed using Kappa index and landscape metrics. The cellular automata-Markov model had the best performance. The model simulations predicted an increase of 52.3 ha and 81.5 ha affected by illegal landfills in Zone A and Zone B for 2018, respectively. The interannual growth rate of surfaces affected by illegal landfills for the period between 2000 and 2006 was 4.5% and 9.5% and between 2006 and 2012 it was 6.6% and 6.7%, for Zone A and Zone B respectively. The growth of illegal landfills between 2000 and 2006 was higher in urban areas, construction sites, and industrial zones, and may be closely related to the process of urban expansion linked to the real estate boom. The latter would have a deep impact on the landscape due to the proliferation of illegal construction and demolition waste. The growth rate of illegal landfills in urban environments fell during the later period of urban expansion. Overall, simulation outputs showed the model's ability to correctly reproduce the distribution patterns for illegal landfill proliferation. Even though the simulated spatial location of illegal landfills was not highly accurate, the models built in this study provide an informative tool to policy makers to aid the process creating policies for environmental protection as well as territorial planning.

Hybrid spatiotemporal simulation of future changes in open wetlands: A study of the Abitibi-Témiscamingue region, Québec, Canada

Among the most productive ecosystems around the world, wetlands support a wide range of biodiversity such as waterfowl, fish, amphibians, plants and many other species. They also provide ecosystem services that play important roles in relation to nutrient cycling, climate mitigation and adaptation, as well as food security. In this research, we examined and projected the spatiotemporal trends of change in open wetlands by coupling logistic regression, Markov chain methods and a multi-objective land allocation model into a hybrid geosimulation model. To study the changes in open wetlands we used multi-temporal land cover information interpreted from LANDSAT images (1985, 1995, and 2005). We predicted future spatial distributions of open wetlands in the administrative region of Abitibi-Témiscamingue, Quebec, Canada for 2015, 2025, 2035, 2045 and 2055. A comparison and assessment of the model’s outcomes were performed using map-comparison techniques as well as landscape metrics. Change analysis between 1985 and 2005 showed an increase of about 63% in open wetlands, while simulation results indicated that this tendency would persist into 2055 with a continuous augmentation of open wetlands in the region. The spatial distribution of predicted trends in open wetlands could provide support to local biodiversity assessments, management and conservation planning of the open wetlands in Quebec, Canada.

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

ABSTRACTMulti-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.

MOLA Model for Optimization of Nickel Mining Management in North Morowali District

Geology of North Morowali Regency is dominated by ultrabasic rock compounds, most of which have weathered to form rich nickel. The Local Government has issued 52 letters of Nickel Mining Business Licence with a total area of 177,249.20 Ha. Issues for local government are: there are indications of overlapping of land Licences, areas for other limited uses, and many abandoned mine land. Local governments should have clear rules in the provision of Mining Business Licence in order not to cause spatial conflicts. Decisions must be supported by a system that can help local governments to minimize the occurrence of problems. The purpose of this research is to select mine land allocation by using MOLA (Multi Objective Land Allocation) Model. The method used is multicriteria analysis by weighting and scoring in Geographic Information System. The model results show scenario 2 with the proposed 80,000 ha mine area is the best choice, and recommended to the local government. The allocation of mining area is 69, 72%, so there is still 30, 28% for other used. In this scenario, mining area with Exploration Mining Business Licence status decreased 49.60%, while with Production Operation Mining Business Licence status decreased 24.41%.

Carbon stock projection in North Sumatera using multi objective land allocation approach

Nowadays, GHG emission is a critical issue for environmental management due to the large scale of land cover change, especially forest cover. This study provides a protection development strategy for North Sumatera as one way to manage the area. By using Multi Objective Land Allocation (MOLA), we evaluated two GHG emission scenarios, including a Business As Usual (BAU) scenario and Protection scenario. The result shows that the province will lose the carbon stock up to 24 million tons in the year of 2035 by using a BAU scenario. On the other hand, by implementing the Protection scenario, total carbon stock that is lost in the same period is about 5 millions tons solely. It proves that protection scenario is a good scenario and effective to reduce the carbon loss. Furthermore, this scenario can be an alternative for North Sumatera spatial plan.

Investigation of likely effects of land use planning on reduction of soil erosion rate in river basins: Case study of the Gharesoo River Basin

We investigated the effects of land use planning on reduction of soil erosion rate in the Gharesoo River Basin, Golestan Province, Iran. For this, the Revised Universal Soil Loss Equation (RUSLE) was used in conjunction with Geographic Information System (GIS) to model potential soil erosion. The average potential soil erosion in the river basin was 18.65 t ha−1 yr−1, with a standard deviation of 33.88 t ha−1 yr−1. The severe and very severe erosion classes comprised 8% and 4% of the river basin, respectively. We found that all areas with severe and very severe erosion were located in agricultural land. Assessing the impacts of land use and slope confirmed importance of interaction between these factors in increasing soil erosion, especially in agricultural areas with steep slopes. We applied a land use planning to control and reduce soil erosion rate, with a specific focus on agricultural areas. For this purpose, the Multi-Criteria Evaluation (MCE) and Multi-Objective Land Allocation (MOLA) were implemented for agriculture, urban and industrial development, and afforestation. We used the output land use map from MOLA in the RUSLE model. The results showed a significant reduction of average potential soil erosion equal to 25.6% (from 18.65 t ha−1 yr−1 to 13.86 t ha−1 yr−1) when the MOLA land use plan was followed. Also, the area impacted by severe and very severe erosion classes were reduced by 25.50% and 42.59%, respectively. The results of this research emphasized that implementation of land use planning in the Gharesoo River Basin is helpful in controlling soil erosion. The method presented in this study can be a basis for sustainable and comprehensive management of river basins.

Climatic zoning for eucalyptus cultivation through strategic decision analysis

The rapid expansion of eucalyptus cultivation necessitates studies that can identify areas amenable to the planting and development of its different varieties. This study therefore aimed to verify the suitability of two varieties of eucalyptus in the state of Espírito Santo, using Geographic Information Systems supported by strategic decision analysis. Mean precipitation, mean temperature, hydric deficit and land slope data were used as decision factors. These factors were submitted to fuzzy standardization, aggregated and compensated by the Weighted Linear Combination (WLC) process, resulting in the final aptitude mapping. For the reconciliation of conflict areas between the varieties, the Multi-objective Land Allocation (MOLA) module was used to maximize the suitability of the land for the objective. The WLC analysis allowed us to identify the suitability of the areas and with the use of the MOLA module it was possible to resolve the conflict of suitability between the two eucalyptus varieties. Most of the state of Espírito Santo is highly suitable for the the development of varieties. The northwestern region and part of the northern region presented less suitability for both analyzed eucalyptus varieties. Considering the 10,000 km2 most adaptable area for eucalyptus cultivation in the state of Espírito Santo, it was verified that the most suitable areas for planting the two eucalyptus varieties are located in the mountainous regions, part of the southern region and near the northeastern coast.

Land use Optimization using Combination of Goal Programming and Multi Objective Land Allocation Methods

Land use Optimization using Combination of Goal Programming and Multi Objective Land Allocation Methods

A comparison of three heuristic optimization algorithms for solving the multi-objective land allocation (MOLA) problem

ABSTRACTMulti-objective land allocation (MOLA) can be regarded as a spatial optimization problem that allocates appropriate use to specific land units concerning some objectives and constraints. Simulating annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO) have been popularly applied to solve MOLA problems, but their performance has not been well evaluated. This paper applies the three algorithms to a common MOLA problem that aims to maximize land suitability and spatial compactness and minimize land conversion cost subject to the number of units allocated for each use. Their performance has been evaluated based on the solution quality and the computational cost. The results demonstrate that: (1) GA consistently achieves quality solutions that satisfy both the objectives and the constraints and the computational cost is lower. (2) The popular penalty function method does not work well for SA in handling the constraints. (3) The solution quality of PSO needs to be improved. Techniques that better adapt PSO for discrete variables in MOLA problems need to be developed. (4) All three algorithms take high computational costs to achieve quality solutions in handling the objective of maximizing spatial compactness. How to encourage compact allocation is a common problem for them.