Suitability Map Research Articles

QGIS-based weighted linear combination plugin for landfill site selection: a case study in Tokat Province, Turkey.

Proper disposal of solid waste is crucial for the protection of natural resources and human health. However, increasing population and changes in consumption habits have led to a global increase in solid waste production. Therefore, a site selection process for solid waste management that takes into account environmental, economic, and social factors is needed. The number of open-source GIS (geographic information system) software programs used in site selection analysis is increasing day by day. QGIS software is an open-source GIS software developed by free software developers, with its popularity increasing with each new version and allowing for the development of plugins with the Python programming language. The shareability of plugins developed with QGIS software brings together open-source GIS users around the world for common goals. In this study, a plugin called "LANDFILL SITE SELECTION (LFSS)" was developed in the QGIS software environment for solid waste landfill site selection and a suitability map was created for solid waste landfill site selection in Tokat, Turkey, using this plugin. For this purpose, 14 evaluation criteria and 8 exclusion criteria were selected, the importance levels of criteria and sub-criteria were determined using the AHP method, and a solid waste landfill site selection suitability map was created using the developed plugin.

Geographic analysis of landfill suitability in Fez, Morocco: a multi-criteria approach

Solid waste management poses a significant challenge to sustainable development. Locating suitable landfill sites is a key difficulty. This study utilizes the Analytical Hierarchy Process (AHP) with a Geographic Information System (GIS) to identify potential landfill locations in Fez province, Morocco. Nine criteria were evaluated for the study area's suitability, including distance from surface water, distance from buildings, distance from roads, distance from protected areas, distance from forests, distance from farmland, elevation, slope, and slope direction. AHP determined criteria weights, and the Consistency Ratio (CR) ensured judgment reliability. Results highlight proximity to residential areas as the most critical factor, followed by distance from surface water and roads. The suitability map indicates the south and southeast of the province as more suitable for landfill placement than the urban areas, parks, and gardens in the north and northwest. These findings aid decision-makers in improving solid waste management practices in Fez province, Morocco.

The suitability mapping of an urban spatial structure for earthquake disaster response using a gradient rain optimization algorithm (GROA)

The urban spatial structure has a prominent role in the earthquake response process which should primarily be assessed in the areas that are most vulnerable to earthquake hazards. Search and rescue teams need to map and identify the appropriateness of urban infrastructures for disaster reaction after a quake to enable ease of movement and quick assistance to the casualties. The key objective of this study is to compute the appropriateness of a municipal spatial structure for crisis reaction after a destructive earthquake, with an emphasis on finding the most critical areas (those that are prone to emergency response disruption). The main contribution involves improving a geographic information system (GIS)-based earthquake-triggered hybrid framework for suitability analysis using a fuzzy analytical hierarchical process (FAHP) and gradient rain optimization algorithm (GROA). The modifying of a rain optimization algorithm (ROA) to a GROA based on gradient descent is carried out to avoid local optima, which results in optimizing the identification process of the key locations for emergency response. The planned approach has been executed in Tehran, the capital of Iran. The implementation consequences reveal the supreme crucial areas for emergency response in the study area with a demonstration of the efficiency of the GROA compared to the basic ROA. Both indicate that these sites are located in the west and southwest, while the junction degree and width of the roads are the most significant factors affecting a city's suitability for emergency response. In addition, the GROA is less sensitive to local optima and more economical than the ROA. Moreover, several rescue experts and urban planners expressed their high satisfaction (95 %) with the five-level suitability map for prioritizing the deployments of troops along with the critical area maps for preventing heavy casualties produced by the GROA.

Rice suitability mapping using the analytic hierarchy process approach in a river catchment

Rice suitability mapping using the analytic hierarchy process approach in a river catchment

Four-channel generative adversarial networks can predict the distribution of reef-associated fish in the South and East China Seas

Reef-associated fish (RAF) are socioeconomically and ecologically important. Herein, we used a four-channel generative adversarial network (GAN) architecture with a retrospective cycle feature to model the distribution of RAF in the East China Sea (ECS) and South China Sea (SCS). Our approach entailed the use of RAF suitability maps and key environmental layers, including sea body temperature, chlorophyll-α concentration, and salinity, as input data. These environmental factors have been demonstrated to significantly influence the distribution of RAF. Our results show that four-channel GANs performed better than one-channel GANs in predicting the distribution of RAF. Furthermore, the proposed four-channel retrospective-cycle GAN (4CRCGAN) model outperformed the commonly used four-channel convolutional GAN (4CCGAN), emphasizing the importance of considering temporal dynamics and feedback loops in predicting the distribution of species. However, it is worth noting that the predictive performance for the distribution of RAF in summer and winter was relatively poor, implying that other environmental and biological factors also exert nonnegligible influences on fish movement and abundance; this underscores the necessity of comprehensively understanding the intricate and dynamic nature of species-environment interactions within marine ecosystems. Our study also revealed that the proposed 4CRCGAN model performed well over multiple steps, which is reflective of its potential to provide valuable insights for decision-makers and stakeholders in the fisheries management sector. Overall, our findings offer critical insights for the development of effective and sustainable management strategies that balance the conservation and sustainable use of these valuable marine resources.

A Geospatial Analysis Model for the Selection of Post-Mining Land Uses in Surface Lignite Mines: Application in the Ptolemais Mines, Greece

Among the procedures included in surface mines’ closure, the determination of post-mining land uses constitutes one of the early but primary steps. This research aims to develop an algorithm for the selection of the most suitable land use spatial distribution in the post-mining area of a surface lignite mine in northern Greece. Considering the already reclaimed areas and the local socioeconomic conditions, six distinct criteria that concern physical local characteristics were selected and, in turn, spatially combined with parameters affecting the mining area. Mining experts attributed weights to the criteria regarding their importance for the examined land uses. The six criteria concerned physical local characteristics (slope, elevation, and distance from villages, rivers, roads, and transmission lines), while the parameters affecting the mining area referred to the type of ground (undisturbed or graded areas), existing infrastructure, and mine closure planning, emphasizing the final landscape of the mining area. The investigated land uses encompassed agricultural, forest, industrial (including buildings, infrastructure, and photovoltaic parks), and recreational parks. Through the application of a fuzzification algorithm within a geographical information system (GIS) environment, four land use suitability maps were generated, which were subsequently overlaid to derive a comprehensive suitability map. The final suitability map was derived from the integration of the mining parameters as spatial information into the algorithm. The findings indicate that, even though the land use suitability analysis could be derived from a mathematical model, the integration of qualitative information related to the mining specifications is necessary to produce more reliable results. The proposed algorithm can be used as a useful tool by decision-makers in the mining industry to plan post-mining reclamation based on suitable criteria.

An integrated Geographic Information System and Analytical Hierarchy process based approach for site suitability analysis of on-grid hybrid concentrated solar-biomass powerplant

For sustainable and resilient energy future, cost-efficient renewable energy technologies are critical. In this regard, hybridization of concentrated solar power with biomass is one of the most promising options for two major reasons (1) dispatchability; (2) low carbon emissions. This study aims to propose a methodological framework to identify suitable areas for deployment of Hybrid Concentrated Solar Biomass (HCSB) powerplants by using a combined Geographic Information System (GIS) – Analytical Hierarchy Process (AHP) based approach. Moreover, Direct Normal Irradiance (DNI) and bioenergy resource potential in Pakistan are also evaluated and mapped. At first, different economical, technical, and meteorological factors were selected after in depth review of literature. High resolution criteria maps were developed for selected factors and unsuitable areas were excluded. Weights of selected factors were determined using AHP. Then a final suitability map, categorizing all non-excluded areas into five suitability classes was achieved. The results show that more than 80% area of Pakistan (i.e., 684,072.15 km2) receives DNI >1800 kWh/m2.year, whereas 19% of land (i.e., 153,978.142 km2) is found to have bioenergy potential greater than 45,000 kWh/m2year. Moreover, approximately 37% of land (i.e., 299,431.46 km2) is identified as suitable for installation of HCSB projects. The district of Jamshoro (located in Sindh Province) is found out to be the most suitable location, whereas 36 districts lie in the “Highly suitable” class. Although, the current study is focused on Pakistan, the approach applied informs decision makers, in realm of energy planning and development, on a regional level.

Insights into the dynamics of wolf occupancy in human-dominated landscapes

Among large carnivores, wolves show a remarkable capability to persist in human-dominated landscapes. However, the temporal dynamics of variation in spatial use of these landscapes remains poorly understood. Considering the relevance of spatio-temporal variations of territorial marking on wolf behaviour, either to defend territory boundaries and core areas or to expand into new areas, the location of wolf signs should reflect the dynamics of spatial use. Taking advantage of a long-term non-invasive wolf monitoring dataset spanning from 2005 to 2022 we fit a dynamic occupancy model to investigate the effects of environmental and anthropogenic factors on the dynamics of wolf spatial use in human-dominated landscapes. We focused on two dynamic parameters – colonization and extinction – and developed a wolf habitat suitability map for Iberia. Colonization probability increased with higher altitude, livestock density, and unpaved road density, and with the decrease of burned areas, national-regional, and local road densities. Extinction probability decreased with higher unpaved road density.In addition, we evaluated the wolf range dynamics in Iberia to understand if the ecological traits explained the expansion, stagnation or extinction sites observed since the beginning of the 2000s. Our results contribute to a sound understanding of wolf spatial use in human-dominated landscapes and its ability to adapt to these heterogeneous environments, allowing us to support adequate mitigation measures and conservation actions. The strong influence of livestock on the dynamics of wolf occupancy highlights the need to assess social factors, human dimensions, and direct wolf mortality causes for conflict management associated with livestock depredation.

Defining Optimal Location of Constructed Wetlands in Vojvodina, Serbia

With the continuous trend of urbanization, increase in industrial capacities, and expansion of agricultural areas, there is also a rise in the amount of wastewater. One of the effective and economical solutions for wastewater treatment has proven to be Constructed Wetlands (CWs). Defining the locations where CWs can be built is not an easy task and there are several criteria that need to be considered. The Geographical Information Systems (GIS) and Multi-Criteria Decision Analysis—Analytic Hierarchy Process (AHP) are combined to select CW locations. AHP is one of the most commonly used methods in many environmental decision making problems, involving various conflicting criteria. In this case, conflicts arise between the evaluation of criteria that influence the selection of CW locations. The evaluation of selected criteria and sub-criteria resulted in a suitability map indicating that the first class represents 44%, the second class 37%, and the third class 16% of the total area. The fourth and fifth classes represent 3% of the total area. The criteria with the highest significance are land use, floodplains and distance of the location from populated places. This study has important implications for sustainable wastewater management in Serbia and provides guidelines for selecting locations for CWs.

From the modeling of diadromous species’ marine distributions to the characterization of their current and future marine habitats

IntroductionMany diadromous fish species are currently facing the threat of generalized population extirpations across their range, and conservation efforts implemented primarily within the continental domain may not be sufficient to ensure their viability. In consequence, better understanding the use of the marine environment by these species turned out to be critical.Material and methodWe developed marine species distribution models for two species, Allis shad (Alosa alosa) and the European flounder (Platichthys flesus), and proposed a way to interpret the habitat suitability from a more functional perspective. Our approach defined marine habitats as highly suitable environments that remained with a high potential through the species life stage duration at sea. First, a species-specific probabilistic threshold was applied to select for highly suitable environments each year of the simulations. Then, annual maps of high suitability were combined into recurrence maps showing areas were the environmental conditions remained the most suitable across the life at sea of the given species, these areas being called ‘marine habitats’. We applied this approach to study the current and future marine habitats of Allis shad and European flounder under climate change scenarios.ResultsThe main current marine habitats of these species were coastal, primarily in the Bay of Biscay for Allis shad and in the English Channel-North Sea for European flounder. These habitats are expected to experience minimal changes by mid-century, and the species may even benefit from new habitats at higher latitudes. However, the European flounder is likely to face greater challenges in the central part of its range by the end of the century, as potential spawning grounds may be threatened.DiscussionThis study provided a way to rethink ‘traditional’ suitability maps by integrating basic knowledge on the diadromous species life at sea. Our findings were part of a larger effort to link continental and marine habitats in improving management of diadromous species.

Geospatial characterization of climate-smart agroforestry in two contrasting physiographic zones of Rwanda

Efficient use of rich natural resources notably land, is one of the most important indicators of economic progress. The unmatched population growth with production has triggered increased demand for food. Nations have prioritized sustainable agriculture as a coping strategy. Climate-smart agroforestry (CSAF) can be one of the options to increase productivity, income, and food security, and stabilize the environment. CSAF denotes a practiced farming system of combining trees with crops or animals (AF) evolved in practices to enhance productivity and feed the food-insecure people while coping with the adverse effects of climate change. This study investigates the land suitability for CSAF in the Bugesera and Rulindo regions of Rwanda. Nine variables were considered for investigation in the study viz. elevation, slope, soil type, rainfall, temperature, LU/LC, distance from roads and trade centers, and landslide risks. The analysis used two commonly known techniques (AHP and GIS) integrated to classify and sort out the suitable land for CSAF practices and development. Results identified three CSAF suitability zones, ranging from 1,662.82 ha (1.60 %) as highly suitable and 90,123.78 ha (86.62 %) as moderately suitable to 12,262.50 ha (11.78 %) less suitable zones in Bugesera. In Rulindo, suitability zones range from 709.92 ha (9.69 %) as highly suitable and 6,514.56 ha (88.92 %) as moderately suitable to 102.24 ha (1.39 %) less suitable land for CSAF. Results further showed that the available means suitable land for CSAF are 34,683.03 ha in Bugesera (34,683.03 ± 48,304.71) and 2,442.24 ha in Rulindo (2,442.24 ± 3,539.79). Land suitability scores for CSAF largely varied across sites (F = 1.33, p = 0.31). Cross-validation using ground-truthing information (field visit and collection of GPS-based ground coordinates of random locations of actual CSAF) mostly supported the generated CSAF suitability maps (nearly 91 % of ground-based locations supported the model output). This study integrates GIS with AHP to plan CSAF farming and scaling up. In sites such as Bugesera and Rulindo where investigations on CSAF are scanty, these results reveal the extent of CSAF farming in the targeted areas. They can provide direction for future land use modifications, better land stewardship, and cost-effective solutions in study areas, and other agroclimatic zones. Moreover, this study will pave the way for further studies on the potential CSAF and possibly required interventions for the assessed areas.

Rainwater harvesting for agriculture development using multi-influence factor and fuzzy overlay techniques

Rainwater harvesting (RWH) is an essential technique for enhancing agricultural development, particularly in regions facing water scarcity or unreliable rainfall patterns. Water shortage, however, is one of the key causes of low crop production especially in mountainous regions like the Khyber Pakhtunkhwa province where most rainwater is lost by runoff. Therefore, rainwater harvesting could be a suitable to make better use of runoff and increase crop production. The study focuses on selecting suitable rainwater harvesting sites in District Karak to enhance agriculture by utilizing multi-influence factor (MIF) and fuzzy overlay techniques. We considered seven factors, i.e., land use land cover (LULC), slope, geology, soil, rainfall, lineament, drainage density, to create a ranking system to understand its application in site selection analysis. The results were combined into one overlay process to produce a rainwater harvesting suitability map. The weighted overlay analysis of the MIF model results reveals that 167.96 km2 area has a very high potential for rainwater harvesting, 874.17 km2 has a high potential, 1182.92 km2 has a moderate and 354.50 km2 has a poor potential for rainwater harvesting. The fuzzy overlay analysis revealed that 257.53 km2 has a very high potential for rainwater harvesting, 896.56 km2 area is classified as high, 1018.30 km2 moderate, and 407.7 km2 has poor potential for rainwater harvesting. The findings of this research work will help the policymakers and decision-makers construct various rainwater harvesting structures in the study area to overcome the water shortage problems.

GIS-Based Analysis of Wildlife Habitat Suitability and Conservation Strategies in Maasai Mara Reserve

The significance of conducting an animal habitats suitability analysis is to enhance sustainable management in the face of land use modification, population growth, and changing settlement patterns, thereby safeguarding Kenya's natural resources, tourism, biodiversity, resource utilization, and community livelihoods. This paper establishes a habitat suitability analysis of specific animal habitats based on GIS technology. Firstly, key indicators were identified and subjected to the single factor analysis. Secondly, the AHP model was employed to calculate the weights of the indicators. A comprehensive evaluation was then carried out to visualize the animal habitat suitability map. Finally, the results of the animal habitat suitability analysis were overlaid with the spatial data of the road network. Overall, the results show that the suitable habitat for wildlife habitat is concentrated in the eastern and western corners of the Masai Mara Reserve, evenly distributed in the south-eastern corner, with a small amount in the north. The impact of lost opportunities for people living near the reserve will be significantly reduced. A kernel density estimation model was introduced to make predictions based on the first law of geography. The visualized predictions show that the habitable range of animals is relatively close to the results of model 1, which proves that animal populations and the quality of human life are secure.

Optimal Urban Waste Dumping Site Selection in Kalutara DS Division of Sri Lanka using GIS-based Multi-Criteria Decision Analysis

Improper waste dumping is an emerging issue in Sri Lanka because of the unsystematic urbanisation process. The main problem of the study is determining sites that are ideal for waste dumping. The use of improper waste disposal methods adversely affects the environment and human lifestyle. This study focuses on integrating a structured approach under multi-criteria decision analysis for waste dumping. The present study has been carried out in Kalutara DS Division, integrating Analytical Hierarchy Process (AHP)-based Multi-Criteria Decision Analysis (MCDA) and geospatial techniques to find suitable waste dumping sites. Ten different types of criteria were selected for the study in vector and raster format, namely, land use, population density, schools, religious places, government offices, coastal areas, hospitals, roads, railways, and environmentally sensitive areas. After finalising the criteria, the GIS-based AHP-MCDA methodology was used for weighting, standardisation, and normalisation by obtaining the opinions of experts and conducting literature surveys. The results of the study are sorted into not-suitable, less-suitable, and suitable dumping sites. Classified suitability maps revealed that 36.94% are not suitable, 53.06% are less suitable, and completely 9.9% are suitable for urban waste dumping sites. The spatial variance of suitable and not suitable waste disposal sites was found in the north, north-eastern, and western and central parts of the study area. Hence, based on the results indicated using such methods, it will be an effective manual for engineers, regional planners, and decision-makers to implement sustainable waste management in the study area in the future.

Suitability Analysis Using GIS-Based Analytic Hierarchy Process (AHP) for Solar Power Exploration

Sibuyan Island is experiencing a significant increase in electricity demand due to population growth, urbanization, and industrial development. The island plans to use solar energy, recognizing its abundance and renewable nature; thus, this study was conducted to visualize the spatial distribution of solar exploration suitability using a geographic information system (GIS). Various criteria, including climatology, location, geography, meteorology, and disaster susceptibility, were considered in the assessment. Parameters affected by government policies, such as protected areas, proximity to rivers, roads and faults, ancestral domains, and proclaimed watersheds, were also considered. Parameters were weighted, and suitability levels were highlighted using AHP. The study revealed that about 5.88% (2674.06 km2) of the island was categorized as highly suitable for a solar farm, 34.99% (15,908.21 km2) as suitable, 2.49% (1129.95 km2) as moderately suitable, and the majority, 56.64% (25,754.47 km2), was considered not suitable for solar projects. A solar power suitability map was developed as a reference for local governments and residents in establishing solar PV systems in their respective sites, thus maximizing the full potential of their land. The study also directs future solar power exploration studies in Sibuyan Island, supporting ongoing efforts to maximize solar energy utilization.

Enhancing wind turbine site selection through a novel wake penalty criterion

In this study, a novel approach that incorporates the wake effect as a penalty criterion within the Analytical Hierarchy Process (AHP) method is proposed. The research introduces the wake penalty criterion for the first time, considering both existing and newly located turbines. The results demonstrate the impact of the wake effect and identify areas with varying wake penalties. A comprehensive suitability analysis is conducted using AHP and Geographic Information System (GIS) techniques, resulting in a suitability map for wind turbine site selection. The analysis considers seven criteria, including the novel wake penalty criterion. The suitability map reveals a distribution of suitability ranges, with 73.8% of the total area excluded due to various constraints. Additionally, a comparative analysis is performed by excluding the wake penalty criterion, highlighting the contrasting effects of wake on turbine placement. Case studies in the Karaburun and Çeşme regions of İzmir further illustrate the influence of wake on turbine clusters and their alignment with prevailing wind directions. The findings indicate that the inclusion of wake effects provides a more precise and realistic depiction of viable wind turbine site selection. This is evident in the reduction of 55.5% and 18.6% in the most suitable region (80–100% suitability) and highly suitable region (60–80% suitability), respectively.

MODELLING SUITABLE SITES FOR SOLAR HARVESTING IN RURAL AREAS OF KENYA: A CASE STUDY OF KIBWEZI EAST AND WEST SUB COUNTIES

Project implementors in the PV solar farm space have long relied on very little analysis as regards site selection of solar farms is concerned. This in part has been attributed to the fact that small scale solar farm projects requiring relatively low investment costs have been the investment vehicle of choice in the past. With the ongoing need to develop, utility-scale PV solar farms are fast becoming a viable investment vehicle to deliver this valuable resource to even the most rural of communities. Site selection has a direct impact on the power performance of the solar farm, economic and social aspects, as well as existing and future infrastructure. Selecting the best site therefore requires a multi-faceted approach. In this study, an attempt is made to model suitable sites for solar PV farms using restriction factors categorized as climatic factors, topographic factors, and location factors. Taking Kibwezi West and Kibwezi East sub counties as study area, several parameters are evaluated using the analytical hierarchy process. The parameters used are broken down into three (3). These are: Climatic Factors comprising of Solar Radiation and Temperature, Topographic factors comprising of Aspect, Location factors comprising of Land Use/ Land Cover, Slope, and road access. Weighting of parameters is carried out through a process that involves collecting parameter comparison data from respondents in the form of a questionnaire and using the collected data in a pairwise comparison to come up with weights. Reclassification of data and overlay analysis is then carried out in GIS environment. The resultant suitability map has shown areas that are considered on a scale from most suitable to not suitable. The generated map exposes an area of 3,172.8km2 area as highly suitable, 904.8km2 area as moderately suitable, 169.0km2 area as marginally suitable and 3.4km2 area as not suitable.

A decision framework for potential dam site selection using GIS, MIF and TOPSIS in Ulhas river basin, India

The Ulhas River Basin, India has been severely impacted by climate change, frequent rainfall, and an ineffective drainage system in recent years, resulting in flooding. To alleviate flood and water scarcity issues, constructing dams in suitable locations is a crucial water management strategy. In this study, potentiality of sites for dam construction have been evaluated by integrating spatial analytical Multi Influencing Factor (MIF), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Twelve climatic, geophysical, and accessibility factors were considered to delineate the dam site suitability. The dam site selection suitability map produced using the weighted overlay to delineate the suitability zones as 5 distinct classes “very high (15.36%),” “high (27.90%),” “moderate (25.74%),” “low (22.05%)” and “very low (8.95%). Total five suitable locations for dams have been recommended based on MIF and TOPSIS evaluation. Based on their maximum storage capacity, width, height, and cost, Dam E was given the highest ranking followed by Dam - C, A, B, and D, respectively. The majority of the chosen locations for dam construction were situated in the elevated and gently sloping eastern portion of the Ulhas River Basin. The ROC curve's AUC value was computed to be 0.806, indicating that the model's performance was "good" and suitability map exhibited a strong correlation with the available dam data. This study provides decision-makers with an inexpensive and useful tool to eliminate less suitable sites and concentrate on those with fewer limitations for constructing dams, resulting in valuable insights.

Assessment of landfill site suitability using GIS, remote sensing, and the multi-criteria decision-making (AHP) approach, Ethiopia

ABSTRACT Solid waste management (SWM) in Ethiopian cities is a significant public health, economic, and environmental issue, with access to suitable disposal locations becoming challenging due to social, environmental, economic, and technical factors. This study aims to propose suitable landfill sites for Debrebirhan Town's solid waste disposal using an integrated survey mechanism, including geographical information system, remote sensing, and analytical hierarchy process (AHP), to address limiting factors. Economic, social, and environmental data were used for the suitable site selection. Satellite images were processed by ERDAS IMAGINE Software, and ArcGIS software was used to identify and map the potential landfill sites. The suitability map was produced by the combined effect of the weights of the criteria and the suitability of the factor maps. The result is summarized with four suitability levels labeled as highly suitable (23%), moderately suitable (51.75%), less suitable (0.25%), and unsuitable (25%). The most suitable landfill sites were found in three locations in the west, north-west, and north directions of Debrebirhan Town that fulfill the economic feasibility, environmental safety, and social acceptability requirements for solid waste disposal. The findings are relevant for governmental decision-making and policy framework implementation.

Locating new docked bike sharing stations considering demand suitability and spatial accessibility

In recent years, a growing number of cities worldwide have implemented docked bike sharing (DBS) systems. One of the most important features to the success of a DBS scheme is the deployment of the stations. However, prior studies on locating DBS stations have focused on travel demand while accessibility factors received limited attention. To tackle the above issue, this study proposes a three-stage framework to determine the appropriate locations for new DBS stations. Concretely, first, important factors influencing DBS usage are explored to yield a demand-based suitability map. Second, the ease of access to DBS services aggregated at demand points is assessed to generate a DBS accessibility map. Finally, combined with suitability and accessibility maps, a location-allocation model is leveraged to identify locations for building new stations to serve the most potential demand. A case study is conducted in Nanjing, China. The identification results show that ten new stations can further expand the DBS service area outward to some extent (from 80.71% to 83.87%) while meeting the high suitability and low accessibility conditions. These findings provide a useful tool for transportation planners and policymakers to take appropriate measures to achieve an equitable and profitable DBS system.