Potential Of Geographic Information Systems Research Articles

Risk Mapping of COVID-19 to Create a Common Operating Picture Using Data from Wastewater Monitoring

Monitoring wastewater quality at the inlet of a wastewater treatment plant provides an overview of the health of the community connected to the respective wastewater treatment plant. Wastewater monitoring has been increasingly recognized as a valid tool in pandemic risk management, especially during the coronavirus disease 2019 (COVID-19) crisis. However, the results of wastewater monitoring are not yet fully utilized in the decision-making process of public governance across most of the Asia-Pacific region. This study explored the potential of geographic information systems to map the results of wastewater monitoring and provide a common operating picture for swift and informed decision-making, especially in times of disasters. By creating an online dashboard tool, we found that an additional merit of mapping wastewater monitoring is that it allows overlaying various other information, such as evacuation shelters, onto the same map. As the service areas of wastewater treatment plants, or sewersheds, are not necessarily aligned with geopolitical boundaries, mapping provides opportunities for re-calculating wastewater monitoring results at the city or district levels. The potential for recalculation is also applicable to overlayed information, indicating that information from wastewater monitoring may be used to assess disaster preparedness or multi-hazard risks. The dashboard prototype was discussed with government officials and feedback was obtained. We aim to further develop the findings so that the information from wastewater monitoring can be shared on a platform, such as the shared information platform for disaster management, in the future for effective risk governance.

A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment.

Although previous studies have acknowledged the potential of geographic information systems (GIS) and social media data (SMD) in assessment of exposure to various environmental risks, none has presented a simple, effective and user-friendly tool. This study introduces a conceptual model that integrates individual mobility patterns extracted from social media, with the geographic footprints of infectious diseases and other environmental agents utilizing GIS. The efficacy of the model was independently evaluated for selected case studies involving lead in the ground; particulate matter in the air; and an infectious, viral disease (COVID- 19). A graphical user interface (GUI) was developed as the final output of this study. Overall, the evaluation of the model demonstrated feasibility in successfully extracting individual mobility patterns, identifying potential exposure sites and quantifying the frequency and magnitude of exposure. Importantly, the novelty of the developed model lies not merely in its efficiency in integrating GIS and SMD for exposure assessment, but also in considering the practical requirements of health practitioners. Although the conceptual model, developed together with its associated GUI, presents a promising and practical approach to assessment of the exposure to environmental risks discussed here, its applicability, versatility and efficacy extends beyond the case studies presented in this study.

Mapping and Estimating Forest Stand Volume using Machine Learning Methods and Multi-Spectral Sentinel 2 Data

Sustainable forest management necessitates the mapping and estimation of forest stand attributes such as density, volume, basal area, and aboveground biomass. This study was conducted to explore the potential of geographic information systems (GIS), remote sensing, machine learning, and field inventories to estimate the forest stand volume of natural and plantation forests within watersheds in the Abra River Basin. The common machine learning regression techniques, which are random forest (RF), k-nearest neighbors (KNN), and support vector machines (SVM), were used to model and predict forest stand volume. The validation of the three machine learning methods showed that the best model to estimate and map forest stand volume is the RF algorithm (R2 = 0.42, RMSE = 0.40 m3/plot, MAE = 0.31 m3/plot). Topographic variables such as the Digital Elevation Model (DEM) and the spectral band Near Infrared (NIR) were the most important variables in predicting forest stand volume. The estimated forest stand volume using the RF model ranged from 33 to 115 m3/ha, with a mean of 59 m3/ha. The results of this study revealed that forest volume can be measured using freely available satellite data and machine learning techniques.

Industrial housing clusters in nineteenth-century Lisbon: finding spatial patterns

Abstract This article aims to analyse housing solutions used in nineteenth-century Lisbon to deal with explosive demographic and urban development. It particularly focuses on two specific types of industrial housing ensembles created in Lisbon called pátios and vilas operárias. The goal of this article is to analyse the spatial distribution of pátios and vilas operárias in Lisbon. Through the potential of geographic information systems, we aim to understand in a spatial-quantitative way the spatial patterns of these kinds of industrial housing ensembles for the most deprived population. To do so, we used spatial modelling and spatial analysis procedures, including simple spatial distribution, mean centre, standard distance, directional distance and density estimation (hotspots). The new contribution of this article lies in the increase of scientific knowledge about these forms of working-class housing – the pátios and vilas operárias – and their spatial implementation in Lisbon in the second half of the nineteenth century.

ANALYSIS OF THE STATE OF PUBLIC TRANSPORT IN ALMATY

Public transport today is again gaining relevance as a means of transportation in connection with the personal cars that have flooded urban spaces. The city of Almaty is no exception and since the beginning of the last decade has taken a course to organize pilot projects to create a priority for the movement of public transport. The difficulty of implementing such innovations is the public, accustomed to crossing long distances by private vehicles, and in most cases city streets are loaded from nearby agglomerations. The emergence of such a trend is directly related to the expansion of the city in breadth, i.e. from east to west, because the natural uniqueness of the urban area in the south is limited by the mountain ranges of the Trans-Ili Alatau. This paper is presented taking into account the existing initial data for the study of public transport issues through the introduction of the GTFS scientific methodology, which can give a new angle of view on the current situation with the organization of bus and trolleybus routes. This paper focuses on studying the potential of public transport in Almaty for consistent growth, because with the help of the restructuring of route networks and the creation of a priority traffic network, there is a chance to achieve an increase in capacity and an increase in the number of users. The aim of this article is to provide information about the current state of the public transport network and to discuss the potential of geographic information systems (GIS) within the urban space, which are guided by spatial analysis approaches related to the processing of General Transit Feed Specification data (GTFS), since statistical data are based on providing a complete picture of the existing transport network, and afterwards can become the basis for subsequent optimization of public transport traffic. This paper creates new perspectives for future development of public transport and restructuring of the understanding how to create public network according to necessity in Almaty city.

Role of Traffic Network in Monitoring Crime and Violence Patterns in Karachi

Crime and geographical accessibility has very special relationship, if monitored on appropriate time it could resolve many complex issues of the crime dynamics. Karachi being the largest city of Pakistan is also very high in the intensity of street crimes that often has very close relationship with the network of the roads. This paper will assess the potential of Geographical Information Systems (GIS) for the analysis of crime pattern and its relationship with the road network in Karachi that would be beneficial for various crime agencies. Present research aims to provide a collective set of methods and techniques for geospatial analysis and 3D mapping of crime scenes. After identification of Hotspots assessment of relationships between robbery or snatching clusters and their spatial neighborhood is initiated by including the urban milieu. For obtaining the desired target copious geospatial data as well as a three-dimensional model is included for analysis. The combined and mutual effort of crime mapping methods with modern 3D modelling helps to facilitate on the spot clutch of multipart spatial phenomena in mapping of crime, and fruitful for both, the communal and responsible decision makers.

Hybrid segmentation approach to identify crash susceptible locations in large road networks

To perform crash analysis on large road networks, the network has to be segmented into smaller units. Existing approaches split road networks into road segments such that they result in (a)segments with constant length, (b) segments where attributes are homogeneous, (c) segments where crash-locations are interdependent. This study proposes a novel hybrid segmentation approach, especially to cater for network-level analysis. Road entities at network scale include intersections and mid-blocks which are dissimilar in their functionality as well as geometry. The effective zones of intersections and mid-blocks needs to be delineated, as there exists spatial correlation between crashes in them. The first level of the hierarchical hybrid segmentation uses crash locations to define intersections’ neighborhood. Subsequently, mid-blocks are segmented using attribute consistency. To illustrate its applicability on road networks in Low-and-Middle Income Countries (LMIC), we exemplify the methodology employing remote extraction of spatial attributes. The potential of Geographic Information System (GIS), Remote Sensing (RS), and Artificial Intelligence (AI) have been used for remote extraction of spatial features, including curvature, sight distance, land use, and network attributes. We compare the performance of hybrid segmentation with three other typical segmentation approaches. Crash susceptibility models using binary logistic regression, relating crashes and segment-specific attributes obtained with each of the four segmentation approaches were developed. The model developed with the proposed hybrid segmentation outperforms models with other segmentation approaches, in terms of goodness-of-fit and prediction accuracy. The proposed methodology can be readily used by practitioners for crash analysis.

Better irrigation management using the satellite-based adjusted single crop coefficient (aKc) for over sixty crop types in California, USA

Several Surface Energy Balance (SEB) models are currently used to unleash the boundless potential of Geographic Information System (GIS) and Remote Sensing (RS) techniques. Their main output, namely the actual evapotranspiration (ETa), is required for the assessment of water budget at basin, regional and national levels. Still, the lack of the required expertise coupled with sometimes missing input data limits their usage by researchers, policy makers, water managers and farmers. In this study, a novel comprehensive monthly adjusted crop coefficients (aKc) list was produced, in which these coefficients are usually used to retrieve the much-needed ETa using the climate-sensitive reference crop evapotranspiration (ET0). More particularly, the ETa is calculated for more than sixty different crop types present in the Mediterranean-climate California, United States. It is based on the two consecutive years of 2018 and 2019, which were wet and dry, respectively. The Google Earth Engine (GEE) version of the Surface Energy Balance Algorithm for Land-Improved (SEBALI), surnamed SEBALIGEE, with an Absolute Mean Error (AME) of 9.56 mm/month in the study area was used along the annual crop map from the United States Department of Agriculture (USDA). The main results showed that the average monthly aKc values ranged between 0.45 and 1.53. More specifically, October and November presented the lowest aKc values averaged among all crop types with aKc values around 0.76. On the other hand, March, April and June had the largest average aKc values at nearly 1.17. The monthly aKc values of the 60 crops studied in the plain of California, would potentially assist authorities and hydrologists to better calculate the actual monthly plant water consumption, in a simpler way over the upcoming years.

Vernacular Farm Buildings and Rural Landscape: A Geospatial Approach for Their Integrated Management

Over the centuries, farm buildings, which accompany the development of agriculture, have played an important role in defining spatial and environmental planning. In some European countries in particular, these rural structures have been built based on traditional agricultural needs and typical land characteristics. Considering the land abandonment that has occurred over the last five decades, with farmers moving to more comfortable residences in neighboring urban settlements, historical farm buildings have often been abandoned, thus causing a leakage of the historical-cultural heritage of the rural landscape. Nowadays, open data and geographic technologies together with advanced technological tools allow us to gather multidisciplinary information about the specific characteristics of each farm building, thus improving our knowledge. This information can greatly support the protection of those buildings and landscapes that have high cultural and naturalistic value. In this paper, the potential of Geographic Information Systems to catalogue the farm buildings of the Basilicata region (Southern Italy) is explored. The analysis of these buildings, traditionally known as masserie, integrates some typical aspects of landscape studies, paving the way for sustainable management of the important cultural heritage represented by vernacular farm buildings and the rural landscape.

Parametric Modeling And Visualization In Decoding Of Collective Values: From Absolute To Relative Values

The work herein provides a general discussion on the issues involved in urban and landscape planning, with an emphasis on the visualization. The paper reviews some of the challenges involved in the planning using visualization tools and Geographic Information Systems. The purpose is to present a motivation to think about choices users make while applying methods of geoprocessing analysis for, somehow, most of users just apply tools but do not question their meaning. A proper conceptual base is a way to avoid following new tools without really contributing to new methodologies and not using the real potential of Geographic Information Systems. We have been living a new paradigm on urban planning, changing from authorial design to the decoding of collective values, using parametric modeling to understand, define and control values and expectations in urban land use. The responsibility of making urban proposals clear has as purpose not only making citizens understand plans, but also to instruct them on an urban common landscape, which is the role of the visualization. It discusses concepts on visualization and presents a methodological proposal to transform representation from absolute into relative in order to support the decision-making in urban landscapes. The paper herein presents techniques to construct a diagnosis of potentials and limitations, to propose maximum constructive envelopes for plots’ occupation, and to promote the visualization in order to share the decision with the community, mostly on the Parametric Modeling of Urban and Natural Landscape approach.

Multicriteria Evaluation of Transport Plan for High-Speed Rail: An Application to Beijing-Xiongan

Beijing has an enormous transportation challenge: to relieve the extreme congestion that has arisen, largely due to overpopulation. To meet this challenge, the city administration has decided to extend its territory; a new city will be planned and built. This new city, Xiongan, will reduce the burden on the capital. A new high-speed railway (HSR) line is designed to transport millions of people every day within less than an hour. This study applies the potential of Geographical Information Systems (GIS) and multicriteria methods, Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II), to determine the best alternative of transportation for the new high-speed railway line between Beijing and Xiongan, comparing different ones. The methodology consists of two stages. In the first stage remote sensing datasets such as ASTER DEM and LANDSAT images and GIS software such as ERDAS IMAGINE and ArcGIS have been used to determine settlement distribution, station location, elevation model, slope percentage, vegetation percentage, and route alignment for a new high-speed railway line for better understanding of its spatial distribution pattern over the study area. The second phase of the study focusing on assessing the various alternatives of transportation has been determined, and three approaches to choosing the best alternative have been introduced. In the paper we examine criteria associated with travel and economic criteria: travel time, the number of train stops, public satisfaction with transport, the number of seats per day, connectivity, operating costs, profit, and the payback period. Six alternatives of transportation have been studied. The stops in Guan and stations in the metro’s rings have been investigated. In the second stage, the Analytic Hierarchy Process (AHP) and PROMETHEE II methods have been used to select the best alternative. The first approach uses only criteria related to the trip, as the criterion to choose the best alternative is the maximum of the net outranking flows by PROMETHEE II method; the second approach applies two independent criteria: the ratio of normalized operating costs and the normalized net outranking flows, and the ratio of the normalized payback period and the normalized net outranking flows; the third approach includes all defined criteria, and the criterion of choosing the best alternative is the maximum of net outranking flows as calculated by the PROMETHEE II method. The approaches have been analyzed with the purpose of comparing the results. The result indicates that it is expedient to have a station in Guan, which will increase the connection and connectivity among the cities while providing fast mobility options for a large number of inhabitants of Guan city. Furthermore, the result from Remote Sensing and GIS analysis demonstrates that the proposed high-speed railway line will be environmentally sustainable and is economically/socially feasible and that it will certainly attract current and future passengers because of their needs.

Gender Mainstreaming in Urban Planning: The Potential of Geographic Information Systems and Open Data Sources

ABSTRACTWhile gender mainstreaming has become a key principle for fostering equality across all fields of policy, actual implementation in the field of urban planning is still underdeveloped. We posit that Geographic Information Systems (GIS) and open data sources can and should be useful tools that effectively contribute to devising more effective ways of implementing a gender-sensitive agenda in urban planning. We take the case of Madrid to illustrate how these tools can contribute to gender mainstreaming in planning by building a methodology based on the concepts of infrastructures for everyday life and the perception of safety.

Combating substance abuse with the potential of geographic information system combining multivariate analysis

Substance abuse problems have been a growing concern for people from all over the world. The objective of this study is to demonstrate the usefulness of a combination between a geographic information system and a multivariate analysis in substance abuse research. However, due to the limited studies on a combination of both these methods in the substance abuse field, we review some other studies in various fields indicating the potential of this method in future substance abuse studies. As the expertise of GIS lies in spatial analysis and the multivariate analysis lies in analyzing huge data thus being capable of interpreting the results very well, we hope this method will attract researchers to applying it in their studies and can consequently and indirectly help in combating substance abuse problems. Keywords: substance abuse; geographic information system; multivariate analysis; spatial analysis; combat

Designing Web-based GIS Application by CSF Method: A Case Study in Boven Digoel Papua

Since Boven Digoel Regency was established in 2003, to this day its infrastructures are very limited, the region is still not developed, Human Resources (SDM) and Information and Communication Technology are still manual. The development of Geographic Information System was expected to contribute to ICT development in Papua, particularly Boven Digoel Regency, in displaying data of existing local potentials, e.g. tourism, plantation and forestry. Critical Success Factor Method was the right method in considering factors determining the success of the implementation of a strategy, in good information management and in providing data of local potentials of geographic information system for people in Boven Digoel Regency and the people of Indonesia in general to introduce Boven Digoel Regency, Papua. Framework Laravel with PHP programming language was expected to support Geographic Information System well to determine the distribution of local potentials in Boven Digoel Regency‥

Rail-Route Planning Using a Geographical Information System (GIS)

The aim of this study is to analyse the potential of geographical information system (GIS) in decision making in rail route planning process. The various parameters affecting the alignment of rail route are considered in this study and a feasibility map is prepared considering the cumulative effect of these factors. The factors considered in this study are road network, slope, topographical characteristics and drainage characteristics of study area. Each parameter is given weights according to analytic hierarchy process (AHP) in GIS environment. The layers of parameters affecting the feasibility of route are overlaid in GIS environment to find a feasibility map. Feasibility map is divided into five categories i.e. very low, low, moderate, high and extremely feasible on the basis of feasibility index.

GIS Analysis of Flood Vulnerable Areas In Benin- Owena River Basin, Nigeria

The frequency and intensity of flood disasters have become serious issues in the national development process of Nigeria as flood disasters have caused serious environmental damages, loss of human lives and other heavy economic losses; putting the issue of disaster reduction and risk management higher on the policy agenda of affected governments, multilateral agencies and NGOs. The starting point of concrete flood disaster mitigation efforts is to identify the areas with higher risk levels and fashion out appropriate preventive and response mechanisms. This research paper explored the potentials of Geographic Information System (GIS) in data capture, processing and analysis in identifying flood-prone areas for the purpose of planning for disaster mitigation and preparedness, using Benin-Owena river basin of Nigeria as a unit of analysis. The data used in this study were obtained from FORMECU and were entered and use to develop a flood risk information system. Analysis and capability of the developed system was illustrated and shown graphically. The research showed that over one thousand settlements harbouring over ten million people located in the study area are at grave risk of flooding. Key words: Flood, Risk, Vulnerability, Geographical Information System (GIS), River -Basin

Potential of Geographic Information Systems for Refugee Crisis: Syrian Refugee Relocation in Urban Habitats

Spatial decision support systems have become ubiquitous tools in planning and understanding regional dynamics. With the present challenges faced throughout the world, Canada is becoming an increasingly important benchmark for migrants of different nations to start safe and productive lives. With the latest group currently entering the country are refugees being brought in primarily from Syria, in larger numbers than Canada has seen in decades. Because of this, the government has had to rapidly implement plans to allocate this influx to available places around the country. Because of the particular status of these immigrant's particular attention must be given to address complex social and economic interactions that guarantee opportunity and growth for refugees as well as functional socio-economic habitats within metropolitan regions. This paper adopts a spatially-explicit approach using a key set of socio-economic variables to understand micro-spatial location optima for refugees to begin their lives in Toronto. By intertwining key variables such as accessibility to employment, English language classes, people of similar cultures or situations, proximity to food/clothing/healthcare, a combinatory metric is designed to assess the most adequate liveability within the Toronto Census Metropolitan Area. The micro-spatial models propose an integrative vision of weighted measures to assess the spatial perspective brought by Geographic Information Systems. It is concluded that suburban regions around major cities hold a significant potential for refugee habitats, suggesting the integration of regional intelligence paradigms in the spatial planning and regional decision support systems of governmental and policy interaction.

Flood risk and vulnerability mapping of settlements within upper and lower Niger river basin, Nigeria

The frequency and intensity of flood disasters have become serious issues in the national development process of Nigeria as flood disasters have caused serious environmental damages, loss of human lives and other heavy economic losses. The starting point of concrete flood disaster mitigation efforts is to identify the areas with higher risk levels and fashion out appropriate preventive and response mechanisms. This research paper explored the potentials of Geographic Information System (GIS) in data capture, processing and analysis in identifying flood-prone areas for the purpose of planning for disaster mitigation and preparedness, using both upper and lower Niger River basin as units of analysis. This work uses a number of physical, demographic and landuse data which were obtained from Forestry Management Evaluation and Coordination Unit and were entered and use to develop a flood risk information system. Results were illustrated graphically and showed that generally, areas with height less than 180m are categorized high risk areas; areas with height between 180.1 and 500m were categorized as medium or moderate risk areas while areas above 500m are designated as low risk areas. At the end of the study, maps of flood vulnerable areas in the river basin was generated with a view to assisting decision makers on the menace posed by the disaster.Key Words: Flood, Risk, Vulnerability, Geographical Information System (GIS), River Basin

THE POTENTIAL OF GIS AS A MANAGEMENT TOOL FOR AVENUE TREES POPULATION IN SMALL COMMUNITIES; A CASE STUDY OF IDI-SHIN COMMUNITY, IBADAN, NIGERIA

This study demonstrates the potentials of Geographic Information System (GIS) as a management tool for avenue trees (Street trees) populations in small communities (using Idi-Ishin community, Ibadan, Nigeria as a case study). GIS is a decision support system which integrate data or set of data from different sources, bringing them under the same referencing system in a computer system. An Ikonos Imagery (1m Spatial Resolution) of the study area was digitized to produce a digital map using ArcGIS 10.1 version. The avenue trees species ≥ 5cm diameter at breast height (DBH) was selected for enumeration. These trees were then measured and tagged. The Height, Girth and Geographic location (X &Y coordinate) of the trees were measured with Haga altimeter, Girthing tape and Hand held Global Positioning System (GPS) respectively. The species and families of the trees enumerated were also identified. Data were analysed for basal area (BA) and volume (V). A total number of 43 avenue trees were assessed in Idi-Ishin Community. <i>Roystonea regia</i> accounted for the majority of the avenue trees (25.58%), followed by <i>Polyanthia longiflora</i> (23.26%), <i>Gliricida seprium</i> (20.93%), <i>Eucalyptus toreliana</i> (13.95%), <i>Delunix regea</i> (6.98%). However <i>Terminalia catapa</i>, <i>Terminalia radii</i>, <i>Azadrachita indica</i> and <i>Newbodia levis</i> had the same abundance of 2.33%. It was also observed that the benefits derived from these avenue trees includes; Carbon sequestration, Beautification, Wind break and shade. A spatial relational database was created for the assessed avenue trees using ArcCatalog of ArcGIS 10.1 version. Based on the findings from the study (which serves as baseline information for the management of the avenue trees in the study area), it was therefore recommended that subsequent assessment should be carried out at 3-5 year interval in other to ensure proper and continuous monitoring and updating of the data.

THE POTENTIAL OF GIS AS A MANAGEMENT TOOL FOR AVENUE TREES POPULATION IN SMALL COMMUNITIES; A CASE STUDY OF IDI-SHIN COMMUNITY, IBADAN, NIGERIA

Abstract. This study demonstrates the potentials of Geographic Information System (GIS) as a management tool for avenue trees (Street trees) populations in small communities (using Idi-Ishin community, Ibadan, Nigeria as a case study). GIS is a decision support system which integrate data or set of data from different sources, bringing them under the same referencing system in a computer system. An Ikonos Imagery (1m Spatial Resolution) of the study area was digitized to produce a digital map using ArcGIS 10.1 version. The avenue trees species ≥ 5cm diameter at breast height (DBH) was selected for enumeration. These trees were then measured and tagged. The Height, Girth and Geographic location (X &Y coordinate) of the trees were measured with Haga altimeter, Girthing tape and Hand held Global Positioning System (GPS) respectively. The species and families of the trees enumerated were also identified. Data were analysed for basal area (BA) and volume (V). A total number of 43 avenue trees were assessed in Idi-Ishin Community. Roystonea regia accounted for the majority of the avenue trees (25.58%), followed by Polyanthia longiflora (23.26%), Gliricida seprium (20.93%), Eucalyptus toreliana (13.95%), Delunix regea (6.98%). However Terminalia catapa, Terminalia radii, Azadrachita indica and Newbodia levis had the same abundance of 2.33%. It was also observed that the benefits derived from these avenue trees includes; Carbon sequestration, Beautification, Wind break and shade. A spatial relational database was created for the assessed avenue trees using ArcCatalog of ArcGIS 10.1 version. Based on the findings from the study (which serves as baseline information for the management of the avenue trees in the study area), it was therefore recommended that subsequent assessment should be carried out at 3-5 year interval in other to ensure proper and continuous monitoring and updating of the data.