Land-use Suitability Analysis Research Articles

Searching for the Profitability of Energy Crops: An Agroecological–Economic Land Use Suitability (AE-landUSE) Model

The current geopolitical and energy market instability calls for speeding up the EU clean energy transition to increase energy security in all the European regions and make Europe the first climate-neutral continent by 2050. Among renewable energies, modern bioenergy is a promising near-zero-emission fuel for increasing energy security in the heating, electricity and transport sectors while promoting growth and job creation, especially in rural areas. In such a context, energy crops will continue to play a key role. Since agricultural planning is a complex issue, especially when energy crops could compete with food ones, we propose an agroecological–economic land use suitability model (AE-landUSE model) to promote the sustainable use of land resources. The AE-landUSE model was developed by integrating cost–benefit analysis (CBA) and land use suitability analysis (LSA) within geographic information systems (GISs). Tested in the Basilicata region (Southern Italy), comparing two different energy crops (rapeseed and cardoon), the results show the model’s utility in identifying suitable areas for energy crops where the investments will be cost-effective. The proposed model will help decision-makers in energy-agricultural planning to increase energy security sustainably.

Land use suitability analysis using an approach combining GIS, regionalization, and PROMETHEE II

ABSTRACT Land-use Suitability Analysis, which aims to identify the suitability of a given area for a particular use by using a certain number of criteria, is a domain that has received a lot of attention from researchers during the last 20 years and most of the works that have been proposed rely on the use of multi-criteria methods which are based on a complete aggregation of alternatives such as Weighted Linear Combination (WLC). The outranking methods, which are multi-criteria methods that rely on a partial aggregation of alternatives, have rarely been used. In the context of Land-use Suitability Analysis, outranking methods quickly reach their computational limits because they require performing comparisons between each pair of pixels. To reduce the initial number of alternatives, we propose to proceed to the regionalization of the study area by grouping neighbouring pixels that have similar properties in homogeneous zones. We then use PROMETHEE II (Preference Ranking Organization Method for Enrichment of Evaluations), an outranking method whose objective is to rank a set of alternatives from the best to the worst. A study for the choice of a landfill site was carried out using our approach and the obtained results were compared with those of WLC.

Multi-criteria Assessment Using AHP Techniques for Agricultural Land Suitability Sharazoor and Sharbazher, Sulaimani as a Case study

Land suitableness evaluation should be essential before implementing any specific land use, particularly within the agricultural sector. The aim of this study was to determine suitable lands for agricultural use in the Sharazoor and Sharbazher districts. The Analytical Hierarchy Process method, commonly used in land-use suitability analysis, was used in this study. According to Analytical hierarchy process (AHP) techniques, to generate a land suitability graph various main criteria such as climate (rain, temperature, humidity), soil (texture, colour, PH ), land (elevation, slope, area, distance), and Agriculture services (Crop rotation, pesticide type, planting scheduling date, Seed variety, farm management, education level, number of personal work in the farm, equipment, production rate, planting rate, planting days, harvesting) factors were used. The questionary form is created. The form was distributed to academic people and ideal farmer for determine the importance of each criterion. In the result, the weight value is 0.465, 0.242, 0.209, and 0.084 for the Climate, Soil, Land, and Agriculture service respectively. Climate criteria are most important, and Agriculture has the least influence over decision-making procedures. According to AHP techniques, the ranking value ranges between 6.48-5.06 for producing wheat in the study area. The suitable land for producing wheat is in Kanispika village. Kelakawa Village's land is best suited for producing barely, when ranking values ranging from 6.08 to 5.15.

Land use suitability assessment for economic development at the provincial level: The case study of Yazd Province, Iran

• The concept of land use suitability (LUS) is intended to help stakeholders make better land-use decisions on a regional scale. • GIS application with a hybrid Multi-Criteria Decision Analysis (MCDA)-Rule-Based System (RBS) in LUS is recommended. • This study suggests the real-time Spatial Decision Support System (SDSS) in LUS analysis. • SDSS should be used in places where suitable geodatabases are not available. Iran's Yazd Province has expanded its economy during the past 40 years due to requests from investors and decisions made by the Provincial Planning and Development Council. This article aims to aid the council's decision-making process by presenting an analytical method for determining whether a region is suitable, unsuitable, or conditionally suitable for generating various economic activities in the form of individual suitability maps. Using a hybrid Multi-Criteria Decision Analysis (MCDA)-Rule Based System (RBS), the method is made up of the Analytic Hierarchy Process (AHP) and semi/non-compensatory decision rules in combination with GIS spatial analysis. The findings show that the province has exceeded its environmental carrying capabilities since a significant portion of its overall land area is unsuitable for most industrial and agricultural activities. The Provincial Planning and Development Council seeks to have even fewer options than to concentrate on high-tech and service sector development along major and dense corridors while relocating other economic activity to the periphery to address issues with water scarcity, air pollution, uneven infrastructure distribution, and environmental limitations. The proposed model of this study can be utilized as a real-time Spatial Decision Support System (SDSS) for the Yazd Provincial Planning and Development Council. In sequential decision-making processes, the model can examine the effects of previous decisions and adjust its findings/conclusions as needed.

GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions

With recent increases in urban population and development, agricultural lands have been changed to residential areas and industrial settlements. Such urban population growth increases necessitate emerging relatively new strategies and forms in urban parks and landscape designs to meet today's economic, social, and ecological needs toward sustainable development. Urban agriculture is one of the strategies for achieving sustainable development and creating multi-purpose landscapes. Such an approach appears to partially solve the problem of agricultural land reduction and degradation. However, urban pollutants seem to hinder the development of such a sustainable concept in the cities. This research aimed to identify suitable locations for urban agriculture in urban green spaces according to various contamination criteria and the uniform distribution of the green spaces in Mashhad, Iran. In this research, using an Analytical Hierarchy Process (AHP) and a Geographic Information System (GIS) facilitated the decision-making process. It also determined the importance of the land use criteria for urban agricultural development. The results showed that the most suitable areas for urban agricultural development with the least impact of pollutants in Mashhad were the suburbs, especially in the northeast and southeast parts. These research results have practical implications for planning urban agricultural development at the city level across the world.

An Ontology-Based Information Extraction System for Residential Land-Use Suitability Analysis

We propose an Ontology-Based Information Extraction (OBIE) system to automate the extraction of the criteria and values applied in Land-Use Suitability Analysis (LUSA) from bylaw and regulation documents related to the geographic area of interest. The results obtained by our proposed LUSA OBIE system (land-use suitability criteria and their values) are presented as an ontology populated with instances of the extracted criteria and property values. This latter output ontology is incorporated into a Multi-Criteria Decision-Making (MCDM) model applied for constructing suitability maps for different kinds of land uses. The resulting maps may be the final desired product or can be incorporated into the cellular automata urban modeling and simulation for predicting future urban growth. A case study has been conducted where the output from LUSA OBIE is applied to help produce a suitability map for the City of Regina, Saskatchewan, to assist in the identification of suitable areas for residential development. A set of Saskatchewan bylaw and regulation documents were downloaded and input to the LUSA OBIE system. We accessed the extracted information using both the populated LUSA ontology and the set of annotated documents. In this regard, the LUSA OBIE system was effective in producing a final suitability map.

Assessing Land-use Suitability of Existing Inclusionary Zoning Projects in the Australian Capital Territory

Inclusionary Zoning (IZ) is a land-use planning initiative taken by governments that either mandates or provides voluntary incentives to achieve a proportion of affordable housing in a development project. This research aims to assess the land-use suitability of the current IZ projects in the Australian Capital Territory (ACT) by comparing them with IZ land-use suitability study findings. A multi-criteria IZ land-use suitability analysis is conducted first to understand the desirable IZ land features while considering sustainable development objectives. Four criteria are selected, including socioeconomic integration, access to jobs, access to public transport, access to green space, and compliance with zoning rules. Results indicate that relatively low suitability of current IZ. We conclude that the assessed low suitability across different IZ projects is driven by the current market-based affordable housing provision approach, which highly relies on private sectors. Nevertheless, the research recognises the need for improving IZ in the ACT through greater collaboration between state government, the federal government, and the property sector.

Determining agricultural suitable land in peri-urban geography using GIS and Multi Criteria Decision Analysis (MCDA) techniques

Land-use suitability analysis is of significance for the planning and management of cities. The main objective of this study was to develop a spatial model for land suitability assessment for peri-urban agricultural development with the use of geographic information systems (GIS) integrated with Multi Criteria Decision Analysis (MCDA) techniques. Physical attributes, land use, natural resources, accessibility, geology and soil properties were recognised as the key factors influencing land suitability for peri-urban agriculture in the study area. The study follows an integrated approach for the suitability assessment of agricultural development in Pendik District of Istanbul (Turkey) through integrating fuzzy logic model, Analytical Hierarchy Process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) methods. Suitability classification of land was done in GIS by using the specified fuzzy membership functions. The weights of the main criteria and their sub-criteria were determined through the AHP method. Eight different zones were ranked according to agricultural development priority by the TOPSIS method. The area classified as suitable amounts to 27% of the total area with 0.07% classified as unsuitable. The highly suitable areas are mainly located in the north where there are villages specialised in agricultural production. The prioritisation of the suitable agricultural areas would assist in land use planning and urban management.

Scenario farmland protection zoning based on production potential: A case study in China

Establishing farmland protection areas is an important measure for developing countries to protect limited farmland resources and guarantee food security. The general approaches lack the ability to simulate the farmlands’ production potential under different scenarios. This paper proposes a modified farmland protection zoning framework to demarcate farmland protection by coupling the Agro-Ecological Zone (AEZ) model with a state-of-the-art farmland protection zoning framework. The modified zoning framework was applied to China, a typical fast developing country. The results indicated that the average potential production of the entire country would increase by 2.96 % in the coming decade if the irrigation efficiency criteria of 55 % established by the National Program for Agricultural Water Conservation (2012–2020) can be fulfilled. Furthermore, the farmland protection area could also be reduced by 2.91 % (2.96 million ha) while the total production potential of the protected areas would remain unchanged. This study contributes two main aspects: (1) The AEZ model was used as a replacement for the general land-use suitability analysis (LUSA) or multi-criteria evaluation (MCE) based farmland assessment models in a farmland zoning framework, which can accurately assess the production potential of the farmland protection demarcation. (2) This farmland protection zoning approach can analyze and simulate a wide range of scenarios on the effect of environmental factors (climate, soil, terrain, etc.) and human production factors (irrigation condition, cropping system, etc.).

Use of the McHargian LUSA in agricultural research and decision-making in the age of non-stationarity and big earth observation data

In the past 50 years, there have been two major changes that are of methodological and consequential importance to the McHargian land-use suitability analysis (LUSA): increasing evidence of non-stationarity of global and regional ecological conditions and increasing availability of high-resolution spatial–temporal earth observation data. For 50 years, the McHargian LUSA has been an important analysis tool for designers and planners for both regional conservation planning and development. McHarg’s LUSA is a decision support tool that reduces the dimensions of spatial–temporal data. This makes the technique relevant beyond decision support to spatial identification and prediction of areas of socio-ecological opportunity, risk, and priority. In this article, I use a set of recent studies relating to agricultural LUSA to reveal relationships between the traditional McHargian LUSA and related spatial–temporal research methods that are adapting to more data and non-stationary ecological conditions. Using a classification based on descriptive, predictive, and prescriptive research activities, I organize these related methods and illustrate how linkages between research activities can be used to assimilate more kinds of spatial “big data,” address non-stationarity in socio-ecological systems, and suggest ways to enhance decision-making and collaboration between planners and other sciences.

Data Preparation for GIS based Land Suitability Modelling: A Stepped Approach

The land suitability analysis of any facility has become a complex affair. Each aspect of the landscape has inherent properties that are, to some extent, appropriate or inappropriate for planned activities. Compliance with government guidelines, installation guidelines and customer needs has made this task more complex. Land-use suitability analysis is identifying the most suitable spatial pattern for future land uses according to specific requirements, preferences, or predictors of some activity. Land-use suitability can mean different things to different experts depending on the purpose. Geographic Information System (GIS) has proven to be a key tool in addressing these land compatibility issues. GIS is a science of analysing position information that can count several numbers of these parameters at the same time, and it can be used to identify and analyse earth compatibility for all types of physical planning. A spatial aptitude model generally corresponds to the scientific question “Where is the best location for a particular facility or business? Therefore, this paper aims to provide an intensified approach to prepare datasets and layers for such land suitability problems using GIS. This paper will be valuable to land managers in land-use planning for any facility.

Spatial multicriteria decision support for robust land-use suitability: The case of landfill site selection in Northeastern Greece

Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of geographical information systems (GIS) and multiple criteria decision aid (MCDA) methods for incorporating conflicting objectives and decision makers’ preferences into spatial decision models. In this paper, we present spatial UTASTAR (S-UTASTAR), a raster-based MC-SDSS for land-use suitability analysis. The multicriteria component of the system is based on the UTA-type disaggregation-aggregation approach. S-UTASTAR is applied in a raster-based case study concerning land-use suitability analysis to identify appropriate municipal solid waste landfill (MSW) sites in Northeast Greece. Moreover, robustness analysis tools are implemented to guarantee robust decision support results. More specifically, during the aggregation phase, the Stochastic Multiobjective Acceptability Analysis (SMAA) is used to indicate the frequency at which a site achieves the best ranking positions within a large set of alternative landfill sites.

English

Selection of suitable areas for urban development is a complex process and needs many diverse indications on the basis of which decision may be assumed. The aim of this study is to examine the GIS-based land-use suitability analysis and its application in urban planning decision making, using Bendigo, a regional city in Victoria as a case study. The objective of this study is to provide evidence-based solutions to urban growth management issues in regional Victoria. Bendigo is a major regional municipality of Victoria, including Bendigo city and surrounding rural hinterland, with six smaller townships scattered across the region. Greater Bendigo boasts of large areas of national parks, reserves and bushland, as well as agriculture land, which is the major land use of the area. This region has been earmarked by the Victorian Government’s Initiative Urban Development Plan for future development as one of Victoria’s regional centres for increased development and new homes. Geophysical, socio-economic and cultural data are used to assess future urban growth suitability in Bendigo based on key goals such as Connected and Compact City (transport and connectivity), City of Equality (education, health services), Ecological City (environmental conservation), and Safe City (risk of disasters). The resultant suitability map indicates primary suitable lands for future urban growth are located adjacent to the established urban areas. Reflecting the current urban development in Bendigo, the paper concludes with several recommendations aimed at improving the long-term urban development plans for the Greater Bendigo area. Key words: Land use, suitability analysis, Victoria, Bendigo

Land-use suitability analysis for urban development in Beijing

Land-use suitability analyses are of considerable use in the planning of mega-cities. An Urban Development Land-use Suitability Mapping (UDLSM) approach has been constructed, based on opportunity and constraint criteria. Two Multi-criteria Evaluation (MCE) methods, the Ideal Point Method (IPM) and Ordered Weighted Averaging (OWA), were used to generate the opportunity map. The protection map was obtained by means of constraint criteria, utilizing the Boolean union operator. A suitability map was then generated by overlaying the opportunity and protection maps. By applying the UDLSM approach to Beijing, its urban development land-use suitability was mapped, and a sensitivity analysis undertaken to examine the robustness of the proposed approach. Indirect validation was achieved by mutual comparisons of suitability maps resulting from the two MCE methods, where the overall agreement of 91% and kappa coefficient of 0.78 indicated that both methods provide very similar spatial land-use suitability distributions. The suitability level decreases from central Beijing to its periphery, and the area classed as suitable amounts to 28% of the total area. Leading attributes of each opportunity factor for suitability were revealed, with 2256 km2, i.e. 70%, of existing development land being overlaid by suitable areas in Beijing. Conflicting parcels of land were identified by overlaying the resultant map with two previous development blueprints for Beijing. The paper includes several recommendations aimed at improving the long-term urban development plans for Beijing.

Solving land-use suitability analysis and planning problem by a hybrid meta-heuristic algorithm

The aim of Land-use Suitability Analysis and Planning Problem (LSAPP) is to identify the most suitable parcels of land for future land-uses considering several conflicting criteria. LSAPP can be modeled using a variant of a well-known combinatorial optimization problem called Quadratic Assignment Problem (QAP). In this paper, a multi-objective mathematical model is developed for LSAPP based on QAP modeling. The large-size instances of the proposed multi-objective mathematical model are difficult to solve in a reasonable CPU time using exact algorithms. So, an efficient three-phase hybrid solution procedure is proposed. In the first phase, the compensatory objectives are integrated using Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory. Then, based on the aforementioned suitability objective function and other spatial objectives and constraints, a multi-objective LSAPP is constructed. Finally, a hybrid multiple objective meta-heuristic algorithm is proposed to solve the LSAPP. The core of the proposed algorithm is based on Scatter Search while Tabu Search and Variable Neighborhood Search are also utilized. The proposed algorithm is equipped with the concepts of Pareto optimality and Veto Threshold, which improve its efficacy. The proposed algorithm is applied on a real LSAPP case study, in ‘Persian Gulf Knowledge Village’, wherein its performance is compared with a well-known evolutionary computation algorithm called Vector Evaluated Genetic Algorithm (VEGA) using comprehensive statistical analysis. A survey on time complexity of the proposed algorithm is also accomplished. The results show that MOSVNS is significantly superior to VEGA both in single and in multi-objective modes. Furthermore, analysis of time complexity of the proposed algorithm shows that it is of polynomial time and can be applied to significantly larger problems with multiple compensatory and non-compensatory objectives.

GIS-Based Framework for Supporting Land Use Planning in Urban Renewal: Case Study in Hong Kong

Land use planning plays an important role in achieving sustainable urban development. One of the problems planners frequently encounter is the absence of an integrated quantitative approach to assessing land-use suitability and supporting land use planning (site level), particularly in urban renewal. This paper develops a geographic information system (GIS)-based framework to solve this problem. The framework consists of three main modules: land information database, planning/policy control mechanism, and model of land-use suitability analysis (LUSA). In the process of developing this framework, three tasks are completed. First, key factors affecting land-use decision making in urban renewal planning are identified and 20 of them are quantitatively examined from five perspectives of land attributes: inherent/physical, locational, social, economic, and environmental. Second, two submodels, namely, the criterion-value generation model and suitability assessment model are designed and built for LUSA in land redevelopment/urban renewal. Third, five types of land use, i.e., residential, commercial, industrial, government/institutional/community (G/IC), and open space in Hong Kong are defined and considered for land-use suitability grading. Several new planning approaches such as scenario planning, public participation, and collaborative interaction are included in this framework to improve planning processes by enhancing their adoption and application in urban (land use) planning. This proposed framework is found to be a useful tool for both practitioners and researchers involved in sustainable land use planning in urban renewal.

Exploring multi-criteria decision strategies in GIS with linguistic quantifiers: an extension of the analytical network process using ordered weighted averaging operators

Many real-world spatial planning and management problems give rise to a geographical information system (GIS)-based multi-criteria decision-making. Analytical network process (ANP) provides a comprehensive methodology for representing complex multi-criteria decision-making problems as a network of criteria and alternatives, where feedback and interdependence relationships may exist within and between all the criteria and alternatives. Experts’ experiences are used to estimate relative magnitudes of tangible and intangible factors through paired comparisons in order to make rational and consistent decisions. However, the GIS-based ANP, an adoption of weighted linear aggregation rule, typically employed a high trade-off decision strategy and neglected other decision strategies. This paper develops a novel GIS-based multi-criteria evaluation (MCE) procedure by extending the ANP using fuzzy quantifiers-guided ordered weighted averaging (OWA) operators. This extension, which generalizes the aggregation process used in the ANP, would provide a generic powerful decision-making tool that allows decision-makers to define a decision strategy on a continuum between pessimistic (risk-averse) and optimistic (risk-taking) strategies. By changing the linguistic quantifiers, the GIS-based ANP–OWA can generate a wide range of decision strategies taking into accounts the level of risk the decision-makers wish to assume in their MCE. A land-use suitability analysis in a region of Saudi Arabia is presented to demonstrate the application of the proposed procedure.

Application of geographic information system technique and analytical hierarchy process model for land-use suitability analysis on coastal area

Land-use suitability is the ability of a given type of land to support a defined use. GIS is known as a powerful tool for handling spatial data in land-use analysis. Application of this tool alone cannot overcome the lack of consistency in opinions given by experts when trying to assign relative importance to each of the several criteria considered in a suitability analysis. The combination of GIS and Multi-Criteria Decision Analysis (MCDA) is a powerful approach used to assess land suitability. To address this issue, the Analytical Hierarchy Process method is used in combination with the GIS tool. The aim of this study is to demonstrate how GIS tools and AHP model can be used for integrated coastal resource planning and management. Based on the information from final map/suitability map, we can define the best area. The findings indicate that the area 1 (2111 m) from class 3 is the most appropriate one because it has good facilities and wide open areas. This study indicates how the integrated tool is handled effectively in a land use suitability analysis for building hotels in the coastal areas of Terengganu in Malaysia. This research develops a framework for integrating GIS and AHP to incorporate the decision maker’s preferences on a range of factors in finding land areas suitable for coastal development.

Application of geographic information systems in land-use suitability evaluation for beekeeping: A case study of Vahregan watershed (Iran)

Decisions on land use have become progressively more difficult in the last decade. The main reasons for this development lie in the increasing population combined with an increasing demand for new land and resources and in the growing consciousness for sustainable land and resource use. The objective of this paper is to incorporate the concept of multiple land use into geographic information systems (GIS)-based land suitability analysis using the Food and Agricultural Organization (FAO) approach. The effective environmental factors and vegetation parameters on apiculture were described as map layers within GIS so that each map layer represented one alternative. Three alternative land suitability patterns for beekeeping are presented. The study indicated that decreasing nectar or pollen species and shortening of the flowering period were the most limiting factors in land suitability for beekeeping. In contrast suitable distribution of water resources, the good climate condition and dominant unpalatable species by over grazing with extended flowering period increased the land suitability for beekeeping. Generally, 54% of the area had an acceptable score of excellent suitability for beekeeping. Therefore, apiculture may have an important role in increasing and promoting better land use. Key words: geographic information systems (GIS), Food and Agricultural Organization (FAO), land-use suitability analysis, landscape pattern, apiculture.

Multicriteria methods and logic aggregation in suitability maps

In this paper, we identify and describe fundamental logic properties of multicriteria methods for land-use suitability analysis and the design of suitability maps. The existing multicriteria methods can be evaluated from the standpoint of their ability to support the necessary logic properties that affect the expressive power of evaluation methods. The paper investigates and compares simple additive scoring, multiattribute value technique, multiattribute utility technique, analytic hierarchy process, ordered weighted average, outranking methods, and logic scoring of preference (LSP). We introduce canonical forms of logic aggregation in suitability maps and show how to use canonical aggregation structures to design LSP suitability maps that evaluate distributions of points of interests (POIs) in urban areas. © 2011 Wiley Periodicals, Inc. © 2011 Wiley Periodicals, Inc.