Commercial Geographic Information Systems Research Articles

An open-source, QGIS-based solution for digital geological mapping: GEOL-QMAPS

Digital geological mapping has experienced significant growth over the past three decades due to the advent of commercial geographical information systems, advances in global positioning systems, and the availability of portable hand-held devices, such as mobile personal computers (PCs), smartphones, and tablets. Numerous software packages have been developed to collect, combine, organise, visualise, publish, and share field data with enhanced spatial accuracy and minimal post-field processing. However, many of these tools are not open-source or are not made available to the geoscientific community, remaining specific to given mapping projects or organisations.In this contribution we introduce GEOL-QMAPS, an open-source, QGIS-based solution promoting digital geological mapping in a harmonised, comprehensive and flexible way. It can be used in the field with a tablet PC or via the QGIS-based QField app on iOS or Android mobile devices, enabling synchronisation with desktop QGIS and the creation of field databases. Designed as a general solution, the GEOL-QMAPS solution consists of a QGIS field data entry template and a custom QGIS plugin, both available on free-access online repositories. The plugin allows for the adaptation of dictionaries (i.e., lists of attributes describing geological features), initially set to international nomenclatures, to the guidelines of different mapping projects. The solution also facilitates the loading and consultation of relevant legacy geodatasets (e.g., preexisting field data, geochemical, geophysical maps or punctual datasets). A fact map, created from field data collected across the Archean Sula-Kangari greenstone belt in Sierra Leone, demonstrates the solution's advantages in terms of post-field processing and raw field data sharing.

A Proposed Merging Methods of Digital Elevation Model Based on Artificial Neural Network and Interpolation Techniques for Improved Accuracy

ABSTRACT The digital elevation model (DEM) is one of the most critical sources of terrain elevations, which are essential in various geoscience applications. Most of these applications need precise elevations, which are available at a high cost. Thus, sources like the Shuttle Radar Topography Mission (SRTM) DEM are frequently accessible to all users but with low accuracy. Consequently, many studies have tried to improve the accuracy of DEMs acquired from these free sources. Importantly, using the SRTM DEM is not recommended for an area that partly contains high-accuracy data. Thus, there is a need for a merging technique to produce a merged DEM of the whole area with improved accuracy. In recent years, advancements in geographic information systems (GIS) have improved data analysis by providing tools for applying merging techniques (like the minimum, maximum, last, first, mean, and blend (conventional methods)) to improve DEMs. In this article, DEM merging methods based on artificial neural network (ANN) and interpolation techniques are proposed. The methods are compared with other existing methods in commercial GIS software. The kriging, inverse distance weighted (IDW), and spline interpolation methods were considered for this investigation. The essential step for achieving the merging stage is the correction surface generation, which is used for modifying the SRTM DEM. Moreover, two cases were taken into consideration, i.e., the zeros border and the H border. The findings show that the proposed DEM merging methods (PDMMs) improved the accuracy of the SRTM DEM more than the conventional methods (CDMMs). The findings further show that the PDMMs of the H border achieved higher accuracy than the PDMMs of the zeros border, while kriging outperformed the other interpolation methods in both cases. The ANN outperformed all methods with the highest accuracy. Its improvements in the zeros and H border respectively reached 22.38% and 75.73% in elevation, 34.67% and 54.83% in the slope, and 40.28% and 52.22% in the aspect. Therefore, this approach would be cost-effective, especially in critical engineering projects.

Exploring Historical Australian Expeditions with Time-Layered Cultural Maps

The Australian Time Layered Cultural Map platform was created to help digital humanities scholars investigate how online geospatial tools could provide exemplars to their humanities colleagues on how historical collections and cultural data could be extended and re-examined with geospatial tools. The project discussed here investigated how Recogito/TMT could effectively extract spatial and temporal data from pure text-based historical information and generate time-layered interactive maps of that spatio-temporal data using accessible and user-friendly software. The target audience was humanities scholars relatively new to geospatial technologies and relevant programming systems. The interactive maps were created with two free, open-source web applications and one commercial GIS (Geographic Information System) mapping application. The relative pros and cons of each application are discussed. This paper also investigates simple workflows for extracting spatiotemporal data into RDF (Resource Description Framework) format to be used as Linked Open Data.

Adaptive Choropleth Mapper: An Open-Source Web-Based Tool for Synchronous Exploration of Multiple Variables at Multiple Spatial Extents

Choropleth mapping is an essential visualization technique for exploratory spatial data analysis. Visualizing multiple choropleth maps is a technique that spatial analysts use to reveal spatiotemporal patterns of one variable or to compare the geographical distributions of multiple variables. Critical features for effective exploration of multiple choropleth maps are (1) automated computation of the same class intervals for shading different choropleth maps, (2) dynamic visualization of local variation in a variable, and (3) linking for synchronous exploration of multiple choropleth maps. Since the 1990s, these features have been developed and are now included in many commercial geographic information system (GIS) software packages. However, many choropleth mapping tools include only one or two of the three features described above. On the other hand, freely available mapping tools that support side-by-side multiple choropleth map visualizations are usually desktop software only. As a result, most existing tools supporting multiple choropleth-map visualizations cannot be easily integrated with Web-based and open-source data visualization libraries, which have become mainstream in visual analytics and geovisualization. To fill this gap, we introduce an open-source Web-based choropleth mapping tool called the Adaptive Choropleth Mapper (ACM), which combines the three critical features for flexible choropleth mapping.

Relative space-based GIS data model to analyze the group dynamics of moving objects

The relative motion of moving objects is an essential research topic in geographical information science (GIScience), which supports the innovation of geodatabases, spatial indexing, and geospatial services. This analysis is very popular in the domains of urban governance, transportation engineering, logistics and geospatial information services for individuals or industrials. Importantly, data models of moving objects are one of the most crucial approaches to support the analysis for dynamic relative motion between moving objects, even in the age of big data and cloud computing. Traditional geographic information systems (GIS) usually organize moving objects as point objects in absolute coordinated space. The derivation of relative motions among moving objects is not efficient because of the additional geo-computation of transformation between absolute space and relative space. Therefore, current GISs require an innovative approach to directly store, analyze and interpret the relative relationships of moving objects to support their efficient analysis. This paper proposes a relative space-based GIS data model of moving objects (RSMO) to construct, operate and analyze moving objects’ relationships and introduces two algorithms (relationship querying and relative relationship dynamic pattern matching) to derive and analyze the dynamic relationships of moving objects. Three scenarios (epidemic spreading, tracker finding, and motion-trend derivation of nearby crowds) are implemented to demonstrate the feasibility of the proposed model. The experimental results indicates the execution times of the proposed model are approximately 5–50% those of the absolute GIS method for the same function of these three scenarios. It’s better computational performance of the proposed model when analyzing the relative relationships of moving objects than the absolute methods in a famous commercial GIS software based on this experimental results. The proposed approach fills the gap of traditional GIS and shows promise for relative space-based geo-computation, analysis and service.

Deciding on maintenance of small municipal roads based on GIS simplified procedures

This paper describes a survey of a Portuguese municipality road network and the development of a simplified procedure to support road network maintenance. This procedure considers inspection and quality evaluation of pavements. In addition, it allows programming of maintenance actions based on deterministic and probabilistic models to predict the evolution of pavement condition. The potential of this procedure is demonstrated through its use to establish scenarios, which enable the development of maintenance programs for the municipality’s road network.The data was represented in a commercial geographic information system (GIS) and processed through Python scripts. The GIS capabilities can analyse, query and modify the road network database as well as the production of maps and useful graphical information.The methodology was applied to 55.7 km of routes from a small municipality in Portugal, aiming at demonstrating the practical feasibility of the procedure, even when specialized means are not available. This means that after defining the rules for the collection and recording of information, it is not essential to maintain a specialized technical structure to proceed with the process of network analysis and decision-making.Two different techniques provided the prediction of pavement condition. For segments in which traffic of heavy vehicles was significant, the deterministic AASHTO model was applied. For the remaining cases, Markov chains (a probabilistic model) were used.The study made it possible to carry out some analysis on future scenarios of maintenance on the network, providing better decisions for the overall municipality and/or for specific areas of its territory. The obtained scenarios resulted in a prediction of pavement condition over the planning period, as well as a cost estimate for the studied scenarios.

Cancer in an Historic Washington DC African American Population and Its Geospatial Distribution.

Background: Cancer continues to be a major cause of morbidity and mortality in the African American community but insights into the types and incidence of cancer 85 years ago have been virtually non-existent and little is known of its geospatial distribution. Historical information on cancer can shed light on current health disparities, particularly among African Americans.Objective: The aims of this study were to: (1) assess the frequencies of the cancer types present among Cobb Collection individuals; (2) compare these data with current research on cancer in African Americans; and (3) evaluate the pattern of cancer expression, including its geospatial distributions, as a cause of death between 1931 and 1969 in an historic African American subgroup and compare this pattern with the historic and contemporary patterns of cancer etiology and incidence.Methods: Systematic assessments of the existing clinical, demographic, and anatomical records in the Cobb Research Laboratory were made of individuals identified as dying from specific cancers from 1931 to 1969. These were compared with the national profiles of cancer during the historic time an individual died as well as the contemporary patterns of cancer deaths. Analysis of their residential addresses just prior to death were assessed using a commercial geographic information system. Each location was assigned a geospatial location and proximity between each site and clusters of sites were investigated.Results: Seventeen different cancer types were found within 28 individuals of the Cobb Collection between 1931 and 1969. The cancer types with the highest frequencies were carcinoma of stomach, lung, esophagus, larynx and bronchogenic carcinoma. Eighty-four percent of all cancer incidents occurred in males and 76% were among individuals identified as African American. Seventy-one percent of the highest incidence cancers were among African American males. Geospatial clustering was observed most noticeably in the redistribution of carcinoma of the esophagus.Conclusion: Our results provide historical depth to our knowledge of the common cancer causes of morbidity among African Americans of Washington DC from 1931 to 1969. We contrast these findings with national historical data on cancer etiology and ethnic disparities in incidence. Our study suggests that historic data can provide longitudinal depth to our understanding of the persistence of cancer susceptibilities in a vulnerable subgroup.

Development and performance evaluation of new AirGIS – A GIS based air pollution and human exposure modelling system

AirGIS, a Geographic Information Systems (GIS) based air pollution and human exposure modelling system, is routinely used in conjunction with the Operational Street Pollution Model (OSPM®), across the globe, to assess local- or street-scale air pollution. We developed a substantially revised version of AirGIS (hereafter, new AirGIS) as a new modelling system in open-source GIS i.e. PostgreSQL software with its spatial extension PostGIS to (1) optimize the model performance enabling model calculations for a large number of sites over a large geographical area, with limited computing resources (2) replace the outdated programming language Avenue (3) become independent of commercial GIS software. This paper, therefore, aims to describe the overall structure of new AirGIS modelling system together with its strengths and limitations. Furthermore, the new AirGIS has been evaluated against various measured datasets of ambient air pollution (NOx, NO2, PM10 and PM2.5). In terms of reproducing temporal variation (single location, time series of concentrations e.g. annual, daily etc.) of air pollution, the new model achieved correlations (R) in the range 0.45–0.96. While, in terms of reproducing the spatial variation (several locations, single time interval), the new AirGIS achieved correlations in the range 0.32–0.92. The new model, therefore, can be used for both short- and long-term air pollution exposure assessments to facilitate health related studies. However, the present evaluation of the new modelling system also revealed that the new AirGIS significantly overestimated the observed concentrations for two out of four datasets. The possible reasons for these errors and future directions to reducing the bias in the new model output have been discussed.

MASHUP SCHEME DESIGN OF MAP TILES USING LIGHTWEIGHT OPEN SOURCE WEBGIS PLATFORM

Abstract. To address the difficulty involved when using existing commercial Geographic Information System platforms to integrate multi-source image data fusion, this research proposes the loading of multi-source local tile data based on CesiumJS and examines the tile data organization mechanisms and spatial reference differences of the CesiumJS platform, as well as various tile data sources, such as Google maps, Map World, and Bing maps. Two types of tile data loading schemes have been designed for the mashup of tiles, the single data source loading scheme and the multi-data source loading scheme. The multi-sources of digital map tiles used in this paper cover two different but mainstream spatial references, the WGS84 coordinate system and the Web Mercator coordinate system. According to the experimental results, the single data source loading scheme and the multi-data source loading scheme with the same spatial coordinate system showed favorable visualization effects; however, the multi-data source loading scheme was prone to lead to tile image deformation when loading multi-source tile data with different spatial references. The resulting method provides a low cost and highly flexible solution for small and medium-scale GIS programs and has a certain potential for practical application values. The problem of deformation during the transition of different spatial references is an important topic for further research.

Development of GIS Integrated Big Data Research Toolbox (BigGIS-RTX) for Mobile CDR Data Processing in Disasters Management

This article reports the development of a geographical information system (GIS) embedded text-based geospatial Big Data research toolbox (BigGIS-RTX) designed especially for mobile CDR (Call Details Record) data processing in urban transport planning and disaster management. BigGIS-RTX is a standalone computer program that aims to provide a bridge between geospatial Big Data and end users (i.e. students and researchers) by reducing difficulties in handling geospatial Big Data processing and analysis tasks. This research toolbox makes it possible to handle text-based geospatial Big Data cleaning, formatting, subsetting, and extraction by keywords or structured query language (SQL), CDR data aggregation by base transceiver stations (BTSs), generation of origin–destination (OD) trips, OD matrices, and OD routes, and computation of OD links. Moreover, this research toolbox can be integrated with current commercial GIS software to perform further geospatial analysis functions to improve spatial decision making in urban and transport planning and disaster management. In this report, we discuss two current research outputs using BigGIS-RTX: first, multitemporal grid square population estimation and second, human mobility studies in transportation planning. These research outputs are essential for disaster management and emergency preparedness in terms of providing knowledge and information about population distribution changes over space and time, human mobility flow by a user defined time frame, and travel volume or link count information for individual road segments. This research is part of the core project “Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar” in a research collaboration between Yangon Technological University, Myanmar, and The University of Tokyo, Japan, sponsored by the Japan Science and Technology Agency (JST) and the Japan International Cooperation Agency (JICA).

Power Management for Hybrid Energy Storage System of Electric Vehicles Considering Inaccurate Terrain Information

Terrain information can significantly impact load power demand, and in turn, on battery life and system efficiency of a hybrid energy storage system (ESS) with battery and supercapacitor. Taking terrain information ahead into consideration for proactive power management is one of the most important ways to improve battery life and overall system efficiency. However, since terrain information is typically available from commercial geographic information systems database, it is by nature inaccurate with uncertainties with respect to the requirements of power management. This is often worsening when combining with commercially low-quality global positioning systems. This paper proposes a novel power management strategy to cope with the inaccuracy and uncertainties of the terrain information with the aim to improve battery life, while maintaining overall system performance. First, the impact of terrain inaccuracy on battery life and system efficiency is analyzed based on two different hybrid ESSs with semiactive topologies. Then, a power management control strategy is developed that actively distributes the power between battery and supercapacitor with adaptation to terrain inaccuracy and uncertainties. The objective of the proposed power management control strategy is to minimize the total cost of the system, including the cost for battery life and energy. Finally, simulation is conducted that has verified the effectiveness of the proposed control strategy.

A Generic Framework for Using Multi-Dimensional Earth Observation Data in GIS

Earth Observation (EO) data are critical for many Geographic Information System (GIS)-based decision support systems to provide factual information. However, it is challenging for GIS to understand traditional EO data formats (e.g., Hierarchical Data Format (HDF)) given the different contents and formats in the two domains. To address this gap between EO data and GIS, the barriers and strategies of integrating various types of EO data with GIS are explored, especially with the popular Geospatial Data Abstraction Library (GDAL) that is used by many GISs to access EO data. The research investigates four key technical aspects: (i) designing a generic plug-in framework for consuming different types of EO data; (ii) implementing the framework to fix the errors in GIS when using GDAL to understand EO data; and (iii) developing extension for commercial and open source GIS (i.e., ArcGIS and QGIS) to demonstrate the usability of the proposed framework and its implementation in GDAL. A series of EO data products collected from NASA’s Atmospheric Scientific Data Center (ASDC) are used in the tests and the results prove the proposed framework is efficient to solve different problems in interpreting EO data without compromising their original content.

Comparative Analysis Study of Open Source GIS in Malaysia

Open source origin might appear like a major prospective change which is qualified to deliver in various industries and also competing means in developing countries. The leading purpose of this research study is to basically discover the degree of adopting Open Source Software (OSS) that is connected with Geographic Information System (GIS) application within Malaysia. It was derived based on inadequate awareness with regards to the origin ideas or even on account of techie deficiencies in the open origin instruments. This particular research has been carried out based on two significant stages; the first stage involved a survey questionnaire: to evaluate the awareness and acceptance level based on the comparison feedback regarding OSS and commercial GIS. This particular survey was conducted among three groups of candidates: government servant, university students and lecturers, as well as individual. The approaches of measuring awareness in this research were based on a comprehending signal plus a notion signal for each survey questions. These kinds of signs had been designed throughout the analysis in order to supply a measurable and also a descriptive signal to produce the final result. The second stage involved an interview session with a major organization that carries out available origin internet GIS; the Federal Department of Town and Country Planning Peninsular Malaysia (JPBD). The impact of this preliminary study was to understand the particular viewpoint of different groups of people on the available origin, and also their insufficient awareness with regards to origin ideas as well as likelihood may be significant root of adopting level connected with available origin options.

Quantitative morphometric analysis of lakes using GIS: rectangularity R, ellipticity E, orientation O, and the rectangularity vs. ellipticity index, REi

Quantitative measures of polygon shapes and orientation are important elements of geospatial analysis. These kinds of measures are particularly valuable in the case of lakes, where shape and orientation patterns can help identifying the geomorphological agents behind lake formation and evolution. However, the lack of built-in tools in commercial geographic information system (GIS) software packages designed for this kind of analysis has meant that many researchers often must rely on tools and workarounds that are not always accurate. Here, an easy-to-use method to measure rectangularity R, ellipticity E, and orientation O is developed. In addition, a new rectangularity vs. ellipticity index, REi, is defined. Following a step-by-step process, it is shown how these measures and index can be easily calculated using a combination of GIS built-in functions. The identification of shapes and estimation of orientations performed by this method is applied to the case study of the geometric and oriented lakes of the Llanos de Moxos, in the Bolivian Amazon, where shape and orientation have been the two most important elements studied to infer possible formation mechanisms. It is shown that, thanks to these new indexes, shape and orientation patterns are unveiled, which would have been hard to identify otherwise.

Applying GIS and high performance agent-based simulation for managing an Old World Screwworm fly invasion of Australia

Agent-based modelling has proven to be a promising approach for developing rich simulations for complex phenomena that provide decision support functions across a broad range of areas including biological, social and agricultural sciences. This paper demonstrates how high performance computing technologies, namely General-Purpose Computing on Graphics Processing Units (GPGPU), and commercial Geographic Information Systems (GIS) can be applied to develop a national scale, agent-based simulation of an incursion of Old World Screwworm fly (OWS fly) into the Australian mainland. The development of this simulation model leverages the combination of massively data-parallel processing capabilities supported by NVidia's Compute Unified Device Architecture (CUDA) and the advanced spatial visualisation capabilities of GIS. These technologies have enabled the implementation of an individual-based, stochastic lifecycle and dispersal algorithm for the OWS fly invasion. The simulation model draws upon a wide range of biological data as input to stochastically determine the reproduction and survival of the OWS fly through the different stages of its lifecycle and dispersal of gravid females. Through this model, a highly efficient computational platform has been developed for studying the effectiveness of control and mitigation strategies and their associated economic impact on livestock industries can be materialised.

Statistics collection in oracle spatial and graph

Oracle Spatial and Graph is a geographic information system (GIS) which provides users the ability to store spatial data alongside conventional data in Oracle. As a result of the coexistence of spatial and other data, we observe a trend towards users performing increasingly complex queries which involve spatial as well as non-spatial predicates. Accurate selectivity values, especially for queries with multiple predicates requiring joins among numerous tables, are essential for the database optimizer to determine a good execution plan. For queries involving spatial predicates, this requires that reasonably accurate statistics collection has been performed on the spatial data. For extensible data cartridges such as Oracle Spatial and Graph, the optimizer expects to receive accurate predicate selectivity and cost values from functions implemented within the data cartridge. Although statistics collection for spatial data has been researched in academia for a few years; to the best of our knowledge, this is the first work to present spatial statistics collection implementation details for a commercial GIS database. In this paper, we describe our experiences with implementation of statistics collection methods for complex geometry objects within Oracle Spatial and Graph. Firstly, we exemplify issues with previous partitioning-based algorithms in presence of complex geometry objects and suggest enhancements which resolve the issues. Secondly, we propose a main memory implementation which not only speeds up the disk-based partitioning algorithms but also utilizes existing R-tree indexes to provide surprisingly accurate selectivity estimates. Last but not the least, we provide extensive experimental results and an example study which displays the efficacy of our approach on Oracle query performance.

An algorithm for generating geometric buffers for vector feature layers

The paper presents an algorithm for constructing geometric buffers for vector feature layers and dissolving those buffers using a sweep-line approach and vector algebra. The algorithm works by first constructing a geometric buffer for a vector feature layer, then dissolving each single geometric buffer for that feature layer, and finally dissolving the overlapping buffers of the entire layer. The algorithm has been implemented successfully in a commercial Geographical Information System software package.

(OBIFS) isotropic image analysis for improving a predicting agent based systems

In this interdisciplinary study a novel hybrid forecasting system is presented, in which an isotropic buffer operator is applied for case-based creation within the structure of the organization-based multi-agent system. Commonly used as an image analysis technique by commercial Geographic Information Systems (GIS), the buffer operator in this particular system calculates the area of a forest fire for prediction and visualization tasks. The use of the buffer operator improves the quality of the data used by the system and in consequence the quality of the results obtained. The system has been successfully tested using real historical data on forest fires evolution, by generating accurate predictions.

Suitability analysis for siting MSW landfills and its multicriteria spatial decision support system: Method, implementation and case study

Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of geographical information systems (GIS) and multiple criteria decision analysis (MCDA) methods for incorporating conflicting objectives and decision makers’ (DMs’) preferences into spatial decision models. This article presents a raster-based MC-SDSS that combines the analytic hierarchy process (AHP) and compromise programming methods, such as TOPSIS (technique for order preference by similarity to the ideal solution) and Ideal Point Methods. To the best of our knowledge it is the first time that a synergy of AHP and compromise programming methods is implemented in raster-driven GIS-based landfill suitability analysis. This procedure is supported by a spatial decision support system (SDSS) that was developed within a widely used commercial GIS software package. A real case study in the Thrace region in northeast Greece serves as a guide on how to conduct a suitability analysis for a MSW landfill site with the proposed MC-SDSS. Moreover, the procedure for identifying MSW disposal sites is accomplished by performing four computational models for synthesizing the DMs per criterion preferential system. Based on the case study results, a comparison analysis is performed according to suitability index estimations. According to them Euclidean distance metric and TOPSIS present strong similarities. When compared with Euclidean distance metric, TOPSIS seems to generate results closer to that derived by Manhattan distance metric. The comparison of Chebychev distance metric with all the other approaches revealed the greatest deviations.

Investigating variations in the provision of digital services in public libraries using network-based GIS models

Public libraries have been seen to have an important role in providing digital services to potentially excluded groups in order to help meet government targets regarding the delivery of digital services. Geographical information systems (GIS) have been used to investigate library service areas, to aid initial location decisions, and to model the implications of the opening and closure of library services. Recent studies have promoted the use of GIS-based techniques to investigate spatial variations in accessibility to public and private services in relation to socio-economic characteristics of population groups. One such technique, based on floating catchment area (FCA) approaches, has been primarily used to investigate potential inequalities in health services, access to employment and leisure opportunities, as well as planning public transport. In this study, FCA techniques are used to research variations in accessibility to public library facilities using bespoke application tools developed within a commercial GIS package. Drawing on a preliminary analysis of variations in accessibility to library services in a local authority area in south Wales, UK, a case study is presented whereby GIS-based models can be used to investigate spatial variations in digital services provision. As a result, provision gaps of such services can be identified. This study's findings help guide national government delivery programs to promote digital inclusion.