Geographic Information System Algorithms Research Articles

A global atlas of pumped hydro systems that repurpose existing mining sites

Large amounts of energy storage are required to support high levels of solar and wind power. Pumped hydro energy storage comprises the majority of global energy storage for the electricity industry. A previous study identified 616,000 potential “Greenfield” closed-loop (off-river) pumped hydro sites around the world with combined storage of 23,000 Terawatt-hours (TWh). In this study, we identify 904 sites in mining areas (“Brownfield”) with combined potential storage of 30 TWh. A high spatial resolution global atlas of Brownfield closed-loop pumped hydro energy storage systems is available online. It was developed through Geographic Information System (GIS) analysis of a digital terrain model. The GIS algorithm identified mining pits, pit lakes, and tailings ponds within mining sites and located nearby reservoirs that could form a suitable pair. All Brownfield pumped hydro sites were assigned a cost class of A to E to allow comparison between sites on the global atlas. There are far fewer Brownfield than Greenfield options, with 77 countries found to contain eligible locations. Despite the smaller number of eligible locations, Brownfield sites typically have other advantages including existing transmission infrastructure, water pumping infrastructure, road access, social licence and reduced environmental impact for development on disturbed land.

Production boreholes water quality evaluation using GIS based geostatistical algorithms in Windhoek

The acquaintance on the manifestation of production boreholes, its replenishment and chemical distinctive have distinct significance in semi-arid zone like Windhoek where production boreholes are partially source of water used for domestics. The goal of this research is to provide an overview for evaluation of production boreholes water quality in Windhoek by using GIS (Geographic Information System) and geostatistical algorithms. The production boreholes water quality parameters; pH, chloride, Iron, electrical conductivity and temperature were sampled and analyzed from production boreholes in Windhoek. Furthermore, maps of each parameter were produced by means of geostatistical (kriging) tactic. Moreover, semivariogram values were tested for different ordinary kriging models to ascertain the superlative fitted for the five water quality parameters and the superlative models were selected based on the average standard error, root mean square standardized error, root mean square error and mean square error. Five maps of the production boreholes water quality parameters were used to compute the production boreholes water quality map using the index technique. Therefore, pro-active measures must be taken into consideration to check the levels of pH, chloride, Iron and electrical conductivity and temperature to avert severe contamination and also to protect the production boreholes in Windhoek.

Research into the Optimal Regulation of the Groundwater Table and Quality in the Southern Plain of Beijing Using Geographic Information Systems Data and Machine Learning Algorithms

The purpose of this paper is to provide new ideas and methods for the sustainable use of groundwater in areas with serious groundwater overexploitation and serious groundwater pollution. Geographic information systems (GIS) were combined with machine learning algorithms, water resources optimization technology, and groundwater numerical simulation to optimize the regulation of the groundwater table and quality beneath the Daxing District in the southern plain of Beijing. By collecting local consumption and supply data and observations of the groundwater table and quality in the connected aquifer beneath Daxing for the years 2006–2020, the corresponding water demands and groundwater impact were extrapolated for the years 2021–2025 based on the basis of the existing development model. Through the combination of GIS and machine learning algorithms, the NO3-N concentration of local groundwater monitoring points in wet years, normal years, and dry years were predicted. With respect to NO3-N pollution, three new groundwater exploitation regimes were devised, which we numbered 1 to 3. The optimal allocation of water resources was then calculated for wet year, typical year, and dry year scenarios for the year 2025. By comparing the water shortage, groundwater utilization rate, and NO3-N pollution under the new groundwater exploitation regimes, the optimal groundwater exploitation mode for the three different types of hydrological year was determined. The results indicate that NO3-N pollution was greatly reduced after the adoption of the optimal regimes and that the groundwater table demonstrated rapid recovery. These results can be of great help in realizing the management, supervision, and regulation of groundwater by combining GIS with machine learning algorithms.

Evaluation of Drifting Snow Susceptibility Based on GIS and GA-BP Algorithms

Drifting snow, the flow of dispersed snow particles near ground level under the action of wind, is a major form of snow damage. When drifting snow occurs on railways, highways, and other transportation lines, it seriously affects their operational safety and results in drifting snow disasters. Drifting snow disasters frequently occur in the high latitudes of northwest China. At present, most scholars are committed to studying the prevention and control measures of drifting snow, but the prerequisite for prevention is to effectively evaluate the susceptibility of drifting snow along railways and highways to identify areas with a high risk of occurrence. Taking the Xinjiang Afukuzhun Railway as an example, this study uses a geographic information system (GIS) combined with on-site monitoring and surveys to establish a drifting snow susceptibility evaluation index system. The drifting snow susceptibility index (DSSI) is calculated through the weight of an evidence (WOE) model, and a genetic algorithm backpropagation (GA-BP) algorithm is used to obtain optimised evaluation index weights to improve the accuracy of model evaluation. The results show that the accuracies of the WOE model, WOE backpropagation (WOE-BP) model, and weight of evidence genetic algorithm backpropagation (WOE-GA-BP) model are 0.747, 0.748, and 0.785, respectively, indicating that the method can be effectively applied to evaluate drifting snow susceptibility.

Accuracy assessment and performance analysis of raster to vector conversions on LULC data – India

Purpose The purpose of this paper is to convert real-world raster data into vector format and evaluate loss of accuracy in the conversion process. Open-source Geographic Information System (GIS) is used in this process and system resource utilizations were measured for conversion and accuracy analysis methods. Shape complexity attributes were analyzed in co-relation to the observed conversion errors. Design/methodology/approach The paper empirically evaluated the challenges and overheads involved in the format conversion algorithms available in open-source GIS with real-world land use and land cover (LULC) map data of India. Across the different LULC categories, geometric errors of varying density were observed in Quantum GIS (QGIS) algorithm. Area extents of original raster data were compared to the vector forms and the shape attributes such as average number of vertices and shape irregularity were evaluated to explore the possible correlation. Findings The results indicate that Geographic Resources Analysis Support System provides near error-free conversion algorithm. At the same time, the overall time taken for the conversion and the system resource utilizations were optimum as compared to the QGIS algorithm. Higher vector file sizes were generalized and accuracy loss was tested. Research limitations/implications Complete shape complexity analysis could not be achieved, as the weight factor for the irregularity of the shapes is to be varied based on the demography as well as on the LULC category. Practical implications Because of the higher system resource requirements of topological checker tool, positional accuracy checks for the converted objects could not be completed. Originality/value This paper addresses the need of accuracy analysis of real-world spatial data conversions from raster to vector format along with experimental setups challenges and impact of shape complexity.

GIS and genetic algorithm based integrated optimization for rail transit system planning

Planning a rail transit system is a complex process involving the determination of station locations and a network of lines linking those stations. This requires the consideration of various local conditions, including travel demand patterns, land use patterns, land values, topography and soil conditions. This is in addition to the many interrelated requirements and constraints related to the rail transit system stakeholders necessitating the application of optimisation models in order to achieve reliable and cost-effective rail transit systems. This paper develops an integrated optimisation model to simultaneously optimise the locations of stations and the associated line network linking them, using a geographic information system (GIS) and a genetic algorithm (GA). In addition to measuring the feasibility of station sites prior to the optimisation process, the developed model considers various local conditions and multiple planning requirements that arise from passengers, operators and the community.The proposed model is tested for robustness through a real-world case study of the City of Leicester in the UK. The results show that it can generate station locations and line network alignment that satisfy the various stakeholder requirements and constraints. A comparative analysis is also conducted to reveal the importance of measuring the feasibility of station sites prior to the optimisation process so as to direct the search process towards optimal solutions, as well as to compare individual and simultaneous optimisation methods for planning a rail transit system. The developed model can be used to speed up the planning process and improve decision-making in respect to selecting a reliable and cost effective solution.

Development of an Asset Management System Integrated with GIS and K-Means Algorithm for Large Industrial Area

The large industrial area has more than a thousand assets that make asset management activities to become more challenging. However, the current asset management in several industrial companies still records the asset information in paper-based documents. Therefore, the technical problems found in current practices in the field are the difficulties in determining the actual position of assets and which group of asset belongs accurately. To overcome those problems and to improve the asset management activities, an asset management system using GIS (Geographic Information System) and K-Means Algorithm is proposed. GIS to visualize the asset coordinate and condition on a geographical map, manage and store the assets detail information and K-Means Clustering Algorithm to cluster the assets based on their coordinate and simplifies the scattered asset. The system is developed using the Waterfall model. The system is native applications built using electron framework and can be accessed within industrial area network only, to keep the user convenience and security of asset data. The Leaflet used as interactive map software frameworks to visualize the industrial map, manage the geospatial data and mapped the industrial asset, including machinery, equipment, land, and building. For the initial operation, the system contains more than 700 assets data with 6 categories and 4 clusters. This system improves the assets accuracy, reduces the time of asset management practices, and the asset clusters can be used as decision support for industrial asset management activities.

Mapping Bahrain’s subsurface municipal solid waste

The objective of this paper is to map possible subsurface dumpsites of solid waste in the Kingdom of Bahrain. Due to limited land availability, random garbage dumping for waste disposal and reclamation has occurred in the past and continues to occur in the Kingdom. Consequently, the process causes economic stress, creates environmental hazards, and contributes to the failure of many dwellings. The input data used to achieve research objective includes data from 300 boreholes, aerial photos, LandSat images, digital elevation model, and 1969–2015 land use maps. Data on the amounts and types of municipal solid waste (MSW) were collected from 1997 to 2017, as were the locations of 3665 deteriorated houses. All types of data are screened, georeferenced, and converted into geographic information system (GIS) formats. At first, a map of possible dumping areas is produced based on citizen testimonies, government engineer interviews, LandSat, aerial photos, and 1969 topo map, followed by data analysis of the aforementioned input data performed such as image classification, buffering, and others. In the next step, multi-criteria GIS algorithm was developed to identify, locate, and map possible sites. The criteria used are distances from dwelling outskirt and the shoreline, land use, relative elevation, and soil type based on borehole data. Lastly, ground truth validation assesses the accuracy of the obtained result. Overall, the study identified 101 confirmed dumping sites and 590 probable dumping sites. Site size is ranging from 18,000 m2 to 3.6 km2 distributed over 100 city blocks which are spread throughout the Kingdom. The Capital Governorate is the most affected by dumping, and the Southern Governorate is the least impacted. A comparison of results and ground observations yielded 87.5% accuracy. The proposed integrated method was effective, and the obtained identification and location accuracy were acceptable. The method can be used to identify, locate, and map random dumping sites in a similar situation.

Template-based GIS computation: a geometric algebra approach

ABSTRACTThe tight coupling between geospatial data and spatial analysis results in high costs in terms of efficiency when developing algorithms to accommodate different types of data, even when the analysis tasks are the same. Universal GIS (Geographic information system) algorithms, as alternatives to tightly coupled approaches, can reduce development costs. However, a unified representation of spatial data is necessary to support the development of universal GIS algorithms. To this end, this research proposes and implements a template-based approach using geometric algebra to create a unified representation of multidimensional data. The template is composed of parameters and operators for GIS representation and computation. The template approach can support general GIS analyses with parameter unfolding and operator integration methods. A case study of intersection analysis shows that developing programming scripts based on computation templates is much simpler than traditional methods. The results suggest that the template-based method is more efficient than traditional methods and more convenient for high-dimensional applications.

Delineation of alluvial fans from Digital Elevation Models with a GIS algorithm for the geomorphological mapping of the Earth and Mars

Alluvial fans are prominent depositional geomorphic features present in nearly all global climates on Earth, and also found on Mars. In this study, we present a Geographic Information System (GIS) algorithm designed for the semi-automated detection of alluvial fans that are connected to their contributing upstream drainage network, from the analysis of Digital Elevation Models (DEMs). Through a combination of spatial analysis procedures, the GIS algorithm generates maps of alluvial fans and their upstream source drainage and watersheds. Tests of the algorithm in areas with well-known alluvial fans indicate that this new GIS procedure is capable of high-accuracy mapping of the fan apexes and correct delineation of fan deposits, in both arid and humid climates. Possible future applications of the GIS algorithm presented in this study include the systematic survey of alluvial fans at the local, regional and planetary scales, important for geologic hazard assessment, studies on the evolution of climate, analysis of continental sedimentary environments, understanding of the interplay between the endogenous dynamics and exogenous processes, and the evaluation of natural resources.

Geographical information system parallelization for spatial big data processing: a review

With the increasing interest in large-scale, high-resolution and real-time geographic information system (GIS) applications and spatial big data processing, traditional GIS is not efficient enough to handle the required loads due to limited computational capabilities.Various attempts have been made to adopt high performance computation techniques from different applications, such as designs of advanced architectures, strategies of data partition and direct parallelization method of spatial analysis algorithm, to address such challenges. This paper surveys the current state of parallel GIS with respect to parallel GIS architectures, parallel processing strategies, and relevant topics. We present the general evolution of the GIS architecture which includes main two parallel GIS architectures based on high performance computing cluster and Hadoop cluster. Then we summarize the current spatial data partition strategies, key methods to realize parallel GIS in the view of data decomposition and progress of the special parallel GIS algorithms. We use the parallel processing of GRASS as a case study. We also identify key problems and future potential research directions of parallel GIS.

Optimal Design of Transmission Line Route Based on GIS

Transmission line route reflects the geospatial constraints on the grid. Environmental factors affecting the power transmission line route design are diverse and complex. This paper studies the method based on GIS (Geographic Information System) and Dijkstra algorithm. Establish environmental factors hierarchical model of transmission line route design using IAHP and gridded map and obtain each grid’s weight. Take into account weight of each grid’s environmental factors and number of the corner in order to build the branch weights of Dijkstra algorithm. After that the optimal route can be obtained using Dijkstra algorithm.

COMPARING A LARGE‐SCALE DEM‐BASED FLOODPLAIN DELINEATION ALGORITHM WITH STANDARD FLOOD MAPS: THE TIBER RIVER BASIN CASE STUDY

ABSTRACTA large‐scale floodplain delineation algorithm is applied to identify potentially inundated areas at the basin scale. The model, which mainly uses a digital elevation model (DEM) and design flood peak discharge at the outlet as input data, is implemented within a geographic information system (GIS). It implements a preliminary GIS‐based terrain analysis framework for estimating the stream network, surface flow direction and drainage grids, while the core algorithm implements an automated fluvial cross‐section extraction for discharge and flow height estimation. The delineation is then implemented by filtering the floodplain cells as those cells whose elevation is lower than the corresponding channel flow height. The proposed ‘hydrogeomorphic floodplain’, obtained on the Tiber River basin (approx. 17 000 km2) using the global NASA Shuttle Radar Topography Mission (SRTM) DEM at 90 m resolution, is compared to the official flood maps of the Tiber River Basin Authority to evaluate the model behaviour with respect to standard flood mapping results. The presented case study shows the potential of using an automated GIS algorithm and largely available remotely sensed data for the preliminary identification of the floodplain footprint at the global scale. Copyright © 2013 John Wiley & Sons, Ltd.

Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study

The combination of increasing challenges in administering household travel surveys and advances in global positioning systems (GPS)/geographic information systems (GIS) technologies motivated this project. It tests the feasibility of using a passive travel data collection methodology in a complex urban environment, by developing GIS algorithms to automatically detect travel modes and trip purposes. The study was conducted in New York City where the multi-dimensional challenges include urban canyon effects, an extreme dense and diverse set of land use patterns, and a complex transit network. Our study uses a multi-modal transportation network, a set of rules to achieve both complexity and flexibility for travel mode detection, and develops procedures and models for trip end clustering and trip purpose prediction. The study results are promising, reporting success rates ranging from 60% to 95%, suggesting that in the future, conventional self-reported travel surveys may be supplemented, or even replaced, by passive data collection methods.

Integrated Decision Support for Roadway Safety Analysis

This paper presents an integrated decision-support framework that helps public agencies identify high-crash locations and develop cost-effective safety improvement projects. State-of-the-art safety concepts, such as safety performance functions, empirical Bayesian method, and potential for safety improvements, are incorporated to identify hazardous highway locations. Cost-effective safety projects are prioritized based on life-cycle safety benefit evaluation and optimal resource allocation models. An efficient solution algorithm to the optimization model is also proposed. The models are implemented in an internet-based, geographic information system (GIS) software tool that builds on state-of-the-art information technologies, graphical interfaces, and customized GIS algorithms such as spatial analysis with buffering operations.

Analyzing Effects of Spring Highway Load Restrictions on North Dakota's Agricultural Freight Flows

This paper describes a statewide agricultural freight transportation model that is used to estimate the benefits of improving North Dakota's state highway system by removing spring load restrictions. The transportation model measures changes in freight flows caused by truck weight regulations during the spring thaw cycle. The primary focus is on grain transportation. A geographic information system (GIS) network of federal, state, and county roads is developed to represent flows from fields to elevators and final destinations. The state is divided into 182 production zones on the basis of agricultural land use patterns. The data for the trip generation component of the model are derived from satellite imagery of crop layers in the state, with the use of GIS spatial analysis and algorithms developed for this purpose. The annual demand at elevators is estimated from grain movement reports filed with the State of North Dakota. Agricultural freight movement is modeled separately as two flows: internal-to-internal (i.e., from fields to elevators) and internal-to-external (i.e., from elevators to final destinations). CUBE transportation planning software is used to model the flows. In addition, the onion model concept used in Iowa is applied as a demand planning tool to capture the effects of spring load restrictions, which are dynamic and move from the southern to the northern part of the state during the spring thaw cycle. The costs of spring load limits are quantified as the increased distance and travel time caused by circuitous truck movements or as the reduced payload per trip.

GIS and genetic algorithms for HAZMAT route planning with security considerations

Singapore is the third largest oil-refining centre in the world, with a large petrochemical hub located at Jurong Island. In view of the increasing concern for transportation security, there is an urgent need to improve the way trucks carrying hazardous materials (HAZMATs) are being routed on urban and suburban road networks. Routing of such vehicles should not only ensure the safety of travelers in the network but also consider the risk of the HAZMAT being used as weapon of mass destruction. This paper explores a novel approach to evaluating the risk of HAZMAT transportation by integrating Geographic Information Systems (GISs) and Genetic Algorithms (GAs). A set of evaluation criteria that are used to route the HAZMAT vehicles was identified and assessed. The criteria considered are related to safety, costs and, more importantly, security. A GIS was employed to quantify the factors on each link in the network that contribute to the evaluation criteria for a possible route, while a GA was applied to efficiently determine the weights of the different factors in the hierarchical form, allowing for the computation of the relative total costs of the alternate routes. Therefore, each route can be quantified by a generalized cost function from which the suitability of the routes for HAZMAT transportation can be compared. The proposed route evaluation method was demonstrated on a typical portion of the road network in Singapore.

Visual Evaluation of GIS Algorithms Using a Reference Grid

Geographic Information Systems (GIS) algorithms are used to simplify, edge match, and overlay large data sets. Some of these GIS processes can cause considerable positional changes to spatial data which are sometimes difficult to assess. This study presents a visualization technique for the evaluation of GIS algorithms and their positional effects on spatial data. The technique is applicable to vector representations and can be used with any GIS operation that changes vector geometry. The technique employs a uniform reference grid to exploit the visual skills of human operators in the evaluation of positional changes in spatial databases after applying GIS transformations. Changes in grid cell length, area, and shape, along with a set of displacement vectors, can be analyzed to evaluate positional changes in spatial data and to compare the behaviors of different algorithms. The technique can assist GIS users in the documentation of positional changes and in the comparison and selection of algorithms for v...

Geographic Information Systems in the Classroom: Methods and Philosophies

Geographic Information Systems (GIS) is a spatial analysis tool that has received increasing interest for natural resource applications. This tool is being employed in the classroom setting to teach students about natural resource management, planning, and design. The tool is still relatively new and educators are interested in learning about how to use this tool in the classroom. Based on GIS classroom experiences from 1972 through 1993, we present our philosophy concerning methods and approaches when teaching spatial applications for environmental management. We suggest that the student maintain real experiences and contact with the landscape through classroom exercises; emphasize contextual issues related to GIS before and after computer modeling; integrate GIS with verbal, written, and graphical skills; and allow flexibility in the modeling topics to be studied. In addition, we discourage the endless memorization of GIS routines and algorithms, rather we stress the experiential act of modeling.