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

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1398
Author(s):  
Md. Mostafizur Rahman ◽  
György Szabó
Keyword(s):  
Land Use ◽  
Population Distribution ◽  
Optimization Problems ◽  
Social Benefit ◽  
Urban Land ◽  
Urban Land Use ◽  
Social Benefits ◽  
Land Use Allocation ◽  
Land Use Optimization ◽  
Conflicting Objectives

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.

scholarly journals MULTI-AGENT BASED SIMULATION OF OPTIMAL URBAN LAND USE ALLOCATION IN THE MIDDLE REACHES OF THE YANGTZE RIVER, CHINA

2016 ◽  
Vol XLI-B8 ◽  
pp. 1089-1092 ◽  
Author(s):  
Y. Zeng ◽  
W. Huang ◽  
W. Jin ◽  
S. Li
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Resource ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Land Use Allocation ◽  
Land Use Optimization ◽  
Multi Agent ◽  
Optimization Allocation

The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.

scholarly journals MULTI-AGENT BASED SIMULATION OF OPTIMAL URBAN LAND USE ALLOCATION IN THE MIDDLE REACHES OF THE YANGTZE RIVER, CHINA

2016 ◽  
Vol XLI-B8 ◽  
pp. 1089-1092
Author(s):  
Y. Zeng ◽  
W. Huang ◽  
W. Jin ◽  
S. Li
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Resource ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Land Use Allocation ◽  
Land Use Optimization ◽  
Multi Agent ◽  
Optimization Allocation

The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.

A hybrid mathematical model for urban land-use planning in association with environmental–ecological consideration under uncertainty

2016 ◽  
Vol 44 (1) ◽  
pp. 54-79 ◽  
Author(s):  
Shukui Tan ◽  
Lu Zhang ◽  
Min Zhou ◽  
Yanan Li ◽  
Siliang Wang ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Urban Land ◽  
Urban Land Use ◽  
Constraint Violation ◽  
Allocation Model ◽  
Land Use Allocation ◽  
Trade Offs ◽  
Land Use System ◽  
System Benefit

Various uncertainties exist in most urban land-use allocation systems; however, they have not been considered in most traditional urban land-use allocation methods. In this study, an interval-probabilistic urban land-use allocation model is developed based on a hybrid interval-probabilistic programming method. The developed interval-probabilistic urban land-use allocation model can deal with uncertainties expressed as intervals and probability distributions; moreover, it can also help examine the reliability of satisfying (or risk of violating) system constraints under uncertainty; the interval-probabilistic urban land-use allocation model not only considers economic factors, but also involves environmental and ecological constraints, which can effectively reflect various interrelations among different aspects in the urban land-use system. The developed model is applied to a case of long-term land-use allocation planning in the city of Wuhan, China. Interval solutions associated with different risk levels of constraint violation are obtained. The desired system benefit from the land-use system will be between $ [1781.921, 2290.970] × 109 under the minimum violating probabilities, and in this condition, the optimized areas of industrial land, commercial land and landfill will be [35,739, 42,402] ha, [58,572, 62,450] ha, and [903, 1087] ha. Results provide the decision makers of Wuhan with desired land-use allocation patterns and environmental policies, which are related to a variety of trade-offs between system benefit and constraint-violation risk. Willingness to accept low benefit from land-use system will guarantee meeting the environmental protection objective. A strong desire to acquire high system benefit will run into the risk of violating environmental constraint.

scholarly journals Detailed Mapping of Urban Land Use Based on Multi-Source Data: A Case Study of Lanzhou

2020 ◽  
Vol 12 (12) ◽  
pp. 1987 ◽  
Author(s):  
Leli Zong ◽  
Sijia He ◽  
Jiting Lian ◽  
Qiang Bie ◽  
Xiaoyun Wang ◽  
...  
Keyword(s):  
Land Use ◽  
Road Network ◽  
Population Distribution ◽  
Land Development ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Classification ◽  
Point Of Interest ◽  
Source Data ◽  
Population Information

Detailed urban land use information is the prerequisite and foundation for implementing urban land policies and urban land development, and is of great importance for solving urban problems, assisting scientific and rational urban planning. The existing results of urban land use mapping have shortcomings in terms of accuracy or recognition scale, and it is difficult to meet the needs of fine urban management and smart city construction. This study aims to explore approaches that mapping urban land use based on multi-source data, to meet the needs of obtaining detailed land use information and, taking Lanzhou as an example, based on the previous study, we proposed a process of urban land use classification based on multi-source data. A combination road network dataset of Gaode and OpenStreetMap (OSM) was synthetically applied to divide urban parcels, while multi-source features using Sentinel-2A images, Sentinel-1A polarization data, night light data, point of interest (POI) data and other data. Simultaneously, a set of comparative experiments were designed to evaluate the contribution and impact of different features. The results showed that: (1) the combination utilization of Gaode and OSM road network could improve the classification results effectively. Specifically, the overall accuracy and kappa coefficient are 83.75% and 0.77 separately for level I and the accuracy of each type reaches more than 70% for level II; (2) the synthetic application of multi-source features is conducive to the improvement of urban land use classification; (3) Internet data, such as point of interest (POI) information and multi-time population information, contribute the most to urban land use mapping. Compared with single-moment population information, the multi-time population distribution makes more contributions to urban land use. The framework developed herein and the results derived therefrom may assist other cities in the detailed mapping and refined management of urban land use.

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