Optimizing Land Use in Lumajang Regency

Land use in Lumajang Regency is dominated by agricultural land. However, over time there was a conversion of agricultural land into residential land as a result of an increase in population. The purpose of this study was to determine the pattern and area of optimal land-use allocation increase economic value in Lumajang Regency. The method used in this study was linear programming with the simplex method. The maximum farming income obtained from optimizing land use is Rp710,306,800,000.00. The optimal land-use area for paddy fields is 42,686.71 ha, the protected forest is 12,652 ha, and residential land is 18,284 ha. The optimal proportion of land use is 58% rice fields, 17% protected forests, and 25% settlements. The optimal paddy field area has decreased by 6,003.26 ha from the land area in 2018 because there are paddy fields that do not match their characteristics. The largest area of rice field reduction in Candipuro District is 2,138.51 ha. Meanwhile, the direction for the allocation of residential land has increased settlement land from 2018 with an area of 1,114.1 ha. The development of residential land is allocated to land that has been planned for settlement in the Spatial Planning (RTRW), potential land that has a slope value of 0 - 25%, and areas with low population density. The largest additional area of residential land in Pronojiwo District is 300 ha.

Sustainable Land-Use Allocation Model at a Watershed Level under Uncertainty

Land-use allocation models can effectively support sustainable land use. A large number of studies solve the problems of land-use planning by constructing models, such as mathematical models and spatial analysis models. However, these models fail to fully and comprehensively consider three uncertain factors of land-use systems: randomness, interval and fuzziness. 33Therefore, through the study of the watershed land-use system, this paper develops a land-use allocation model considering the regional land–society–economy–environment system under uncertain conditions. On the basis of this model, an interval fuzzy two-stage random land-use allocation model (IFTSP-LUAM) combining social, economic and ecological factors is proposed to provide sustainable development strategies at the basin level. In addition, the proposed IFTSP-LUAM takes into account the above three uncertainties and multistage, multiobjective, dynamic, systematic and complex characteristics of typical land-use planning systems. The results showed that the model considers more socioeconomic and ecological factors and can effectively reflect the quantitative relationship between the increase in economic benefits and the decrease in environmental costs of a land-use system. The model was applied to land-use planning of Nansihu River Basin in Shandong Province. The results provided a series of suitable land-use patterns and environmental emission scenarios under uncertain conditions, which can help the watershed environmental protection bureau and watershed land-use decision-makers to formulate appropriate land-use policies, so as to balance social and economic development and ecological protection. The simulation results can provide support for an in-depth analysis of land-use patterns and the trade-off between economic development and ecological environment protection.

A Geospatial Approach to Measure Social Benefits in Urban Land Use Optimization Problem

Different conflicting objectives are used in urban land use optimization problems. The maximization of social benefit is one of the important objectives in urban land use optimization problems. Many researchers have used different methods to measure social benefits in land use optimization. Studies show that there is no established method to measure social benefit in the urban land use allocation game. Against this background, this study aims to (a) identify the appropriate indicators as a measure of social benefit, and (b) propose a composite index to measure social benefit in urban land use optimization problems. Based on the literature review and expert opinion, this study identifies four indicators as a measure of social benefit. These are spatial compactness, land use compatibility, land use mix, and evenness of population distribution. Using the weighted sum approach, this study proposes a composite social benefit index (SBI) to measure social benefit in urban land use allocation/optimization problems and planning. The study suggests that spatial compactness is the most influential indicator to the SBI, but the most critical indicator is compatibility, whose 11.60% value reduction from 0.5 alters the decision of choice. Finally, the proposed method was applied in Rajshahi city in Bangladesh. The result suggests the potential of using SBI in the land use allocation problem. It is expected that the proposed social benefit index (SBI) will help the land use optimization and planning and will be helpful for decision makers.

Multi-Objective Land Use Allocation Optimization in View of Overlapped Influences of Rail Transit Stations

Taking into consideration the overlapped influences of multiple rail transit stations upon land use characteristics, this study newly develops a multi-objective land use allocation optimization model to decide the land use type and intensity of every undeveloped land block of an urban area. The new model is solved by successively utilizing the non-dominated sorting genetic algorithm and the technique for order performance by similarity to ideal solution to obtain the least biased Pareto-optimal land development scheme. The study area is an urban region around two metro stations in Beijing of China. The influencing scopes of these two stations are overlapped in part, and many of the land blocks in the study area are not yet developed. It is shown that the newly developed land use allocation optimization model is able to rationally achieve multi-objectives in coordination to the most extents for the sustainable urban development in view of the integrated effect of multiple rail transit stations.

Multi-Objective Optimization of the Spatial Structure and Layout of the Protected Area Based on Ecosystem Services: A Case Study of the Yellow River’s Headwaters Region in the Three-River-Source National Park

The optimization of the spatial structure and layout is to determine an optimal and cost-effective land-use allocation plan for protected areas. The key goal is to maximizing the value of ecosystem services. This paper establishes a framework for optimizing the spatial structure and layout of the protected area based on ecosystem services. With the objective of maximizing the value of ecosystem services, it uses the CoMOLA (Constrained Multi-objective Optimization of Land-use Allocation) model for multi-objective optimization under the constraints of area and conversion rules. Taking the Yellow River’s headwaters region in the Three-River-Source (Sanjiangyuan) National Park as the study area, this paper uses the data of the year 2015 as a benchmark, and obtains the optimization results of the study area by 2035. The results show that the total value of ecosystem services of the Yellow River’s headwaters region after optimization will reach RMB [Formula: see text], with a total increase of RMB [Formula: see text] (8.47%). The land covers that contribute most to the value of ecosystem services are rivers, lakes and wetlands (51.55%), and grasslands (40.71%). Among the various types of ecosystem services, the value of provisioning services will increase by RMB [Formula: see text], regulating services by RMB [Formula: see text], supporting services by RMB [Formula: see text], and cultural services by RMB [Formula: see text]. The research results can provide a scientific basis for the spatial optimization of protected areas and the management of national parks.

Hybrid Economic-Environment-Ecology Land Planning Model under Uncertainty—A Case Study in Mekong Delta

The research on land natural resources as the leading factor in the Mekong Delta (MD) is insufficient. Facing the fragile and sensitive ecological environment of MD, how to allocate limited land resources to different land use types to obtain more economic benefits is a challenge that local land managers need to face. Three uncertainties in land use system, interval uncertainty, fuzzy uncertainty, and random uncertainty, are fully considered and an interval probabilistic fuzzy land use allocation (IPF-LUA) model is proposed and applied to multiple planning periods for MD. IPF-LUA considers not only the crucial socio-economic factors (food security, output of wood products, etc.) but also the ecological/environmental constraints in agricultural production (COD discharge, BOD5 discharge, antibiotic consumption, etc.). Therefore, it can effectively reflect the interaction among different aspects of MD land use system. The degree of environmental subordination is between 0.51 and 0.73, the net benefit of land system is between USD 23.31 × 109 and USD 24.24 × 109 in period 1, and USD 25.44 × 109 to 25.68 × 109 in period 2. The results show that the IPF-LUA model can help the decision-makers weigh the economic and ecological benefits under different objectives and work out an optimized land use allocation scheme.