Geographic Information System Analysis Research Articles

Site selection for managed aquifer recharge in the city of Kabul, Afghanistan, using a multi-criteria decision analysis and geographic information system

While the success and sustainability of managed aquifer recharge (MAR) strongly depends on many characteristics of the site, it is necessary to integrate the site characteristics and develop suitability maps to indicate the most suitable locations. The objective of this study is to integrate geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques to identify the most suitable areas for a MAR project in the Kabul city area, Afghanistan. Data for six effective criteria, including slope, drainage density, surface infiltration rate, unsaturated zone thickness, soil type and electrical conductivity, were collected and then a classification map was produced for each criterion in the GIS environment. By applying MCDA techniques, the weights of the effective criteria were obtained. A suitability map was generated from each technique separately based on a combination of all criteria weights and thematic layers. The result of the analytical network process (ANP) method was found to be more precise and reliable compared with that of the analytical hierarchy process (AHP) method. Based on the final suitability map produced from the ANP model, there is 3.7, 15.0, 37.4, 33.1 and 10.3% of the total area that is unsuitable, of low suitability, moderately suitable, suitable and very suitable for MAR application, respectively. As a final result of this work, seven sites have been prioritized based on land use. The integration of multi-criteria decision analysis and GIS is recognized as an effective method for the selection of managed aquifer recharge sites.

Sistem Informasi Geografis Pelanggaran AKB dan PSBB Berbasis Android Menggunakan Metode Extreme Programming

The importance of providing accurate and real-time information is indispensable in today's era of rapid development of information technology. Along with technological developments, the condition of the Coronnavirus Disease 19 (Covid-19) pandemic is now a task to assist the government in reducing the chance of the spread of Covid-19, where this information technology is used as a means of supporting minimizing the chance of the spread of Covid-19. This study aims to assist the government and those who are authorized in Indonesia in society who violate the New Normal (AKB) and Large-Scale Social Restrictions (PSBB) regulations by utilizing information systems. The information system in question is an information technology-based information system that records and facilitates data processing of community actions during the PSBB and AKB by the government. The data method used in this research is observation, interview, and documentation. The system design method used is the Extreme Programming system design method. The results of this study are in the form of analysis and design of an Android-based Geographical Information System of New Normal and Large-Scale Social Restrictions (PSBB) using the Extreme Programming method.

Urban-Rural Differences in Cardiac Arrest Outcomes: A Retrospective Population-Based Cohort Study

BackgroundApproximately 10% of people who suffer an out-of-hospital cardiac arrest (OHCA) treated by paramedics survive to hospital discharge. Survival differs by up to 19.2% between urban centres and rural areas. Our goal was to investigate the differences in OHCA survival between urban centres and rural areas. MethodsThis was a retrospective cohort study of OHCA patients treated by Nova Scotia Emergency Medical Services (EMS) in 2017. Cases of traumatic, expected, and noncardiac OHCA were excluded. Data were collected from the Emergency Health Service electronic patient care record system and the discharge abstract database. Geographic information system analysis classified cases as being in urban centres (population > 1000 people) or rural areas, using 2016 Canadian Census boundaries. The primary outcome was survival to hospital discharge. Multivariable logistic regression covariates were age, sex, bystander resuscitation, whether the arrest was witnessed, public location, and preceding symptoms. ResultsA total of 510 OHCAs treated by Nova Scotia Emergency Medical Services were included for analysis. A total of 12% (n = 62) survived to discharge. Patients with OHCAs in urban centres were 107% more likely to survive than those with OHCAs in rural areas (adjusted odds ratio = 2.1; 95% confidence interval = 1.1 to 3.8; P = 0.028). OHCAs in urban centres had a significantly shorter mean time to defibrillation of shockable rhythm (11.2 minutes ± 6.2) vs those in rural areas (17.5 minutes ± 17.3). ConclusionsNova Scotia has an urban vs rural disparity in OHCA care that is also seen in densely populated OHCA centres. Survival is improved in urban centres. Further improvements in overall survival, especially in rural areas, may arise from community engagement in OHCA recognition and optimized healthcare delivery.

Evaluasi Manajemen Tata Ruang Wisata Dan Ruang Terbuka untuk Meningkatkan Kunjungan Wisata Dan Pad Kota Palembang

Palembang city is one of the cities that has a very good tourism attraction. This city has tourist destinations, cultural heritage, and culinary tourism. As a leading tourism city, Palembang City should be able to manage tourism spatial planning and open space for optimizing Palembang City tourist visits. This is because the city of Palembang has great tourism potential because it is supported by the ownership of tourism objects, culinary tourism, and open spaces that can be used for various purposes.This study aims to evaluate the management of the utilization of Tourism Spatial Planning and Open Space by the Palembang City Government and to find out the factors that support and hinder the optimization of tourist visits that have an impact on the local revenue of Palembang City. The stages start from initial observation, data collection, data analysis, and conclusions. The rationale for this research is the case study method with the type of mix method. Data collection techniques using semi-structured interviews, selecting informants using expert analysis. Observations were made open. Test the validity of the data using triangulation and member checking. Data analysis techniques used in this research are Geographic Information System (GIS), Arc Map, Logic Model, and Thematic Analysis. The results of this study indicate that the spatial arrangement of tourism and open space has the potential to increase tourist visits and PAD in Palembang City. Supporting factors for tourist visits are human resources and budget. The inhibiting factor is the pandemic and the availability of spatial data. Keywords : Thematic analysis, logic model, tourism, GIS

GIS-based urban village regional fire risk assessment and mapping

Fires in residential areas are one of the threats out of 13 disasters in Indonesia. Fires are disasters based on their causes, classified as disasters caused by human negligence. This research aims to identify residential fire incidents, assess fire risk levels, and map the risk level. We used the geographic information system (GIS) analysis approach and direct observation of the study area. The research location was in the Tamansari sub-district in Bandung City. The subdistrict of Tamansari consists of 20 neighborhood units (rukun warga/ RW) with 22,995 people and 6,598 households. We conducted a field survey from December 2019 to March 2020. We used a spatial approach to analyze fire risk in this residential area by using GIS to map urban-village regional fire incidents and assess the risk level. There were four fire hazard variables: population density, building density, building quality, road class. On the other hand, vulnerability variables are based on the community's social parameters: population density, percentage of old age and children under five, people with disabilities, and the population's sex ratio. The hazard and vulnerability maps overlay showed three neighborhood units (rukun warga/ RW) with a high risk of fire, eight RWs with a moderate risk of residential fires, and nine RWs with a low risk of residential fires. The areas with low-risk categories must remain vigilant because the width of the roads in these areas is relatively narrow.

Combination of fuzzy-AHP and GIS techniques in land suitability assessment for wheat (Triticum aestivum) cultivation

Land suitability classification is a useful management practice to ensure planned and sustainable use of agricultural lands according to their potentials. The main purposes of this study were to analyze land suitability for bread wheat (Triticum aestivum) cultivation and generate a land suitability map for wheat by integrating the analytical hierarchy (AHP)-fuzzy algorithm with the Geographical Information System (GIS) in the Tozanlı sub-basin located in the upper part of Yeşilırmak Basin, Turkey. Topographic (elevation, slope, aspect) characteristics of the basin and some of physical and chemical properties of soils (texture, pH, electrical conductivity, lime, organic matter, and soil depth) were used as criteria in determining the suitability classes. Ninety-two disturbed soil samples were collected from 0 to 20 cm depth in October 2017 using random sampling method. Weighted overlay spatial analysis in GIS was used to combine different thematic layers to identify areas suitable for wheat production. The fuzzy-AHP suitability assessment model was adapted to determine the weights for topographic and soil properties. The highest specific weights were obtained for soil depth (0.232) and elevation (0.218), while the lowest weight was calculated for aspect (0.042). Highly, moderately, and marginally suitable lands for wheat cultivation cover 2.63, 9.85 and 32.59% of the study area, respectively. In addition, the results indicated that 54.92% of the total area is permanently unsuitable for wheat cultivation. The results revealed that integration of AHP-fuzzy algorithm and GIS techniques is a useful method for accurate evaluation of land suitability in planning for specific crop production and decreasing the negative environmental impacts of agricultural practices.

Coastal cities in the Southern US floodplains: An evaluation of environmental equity of flood hazards and social vulnerabilities

Few empirical studies have examined environmental equity (EE) within the context of flooding in the United States (US). This paper explores whether lower-income, minority, and vulnerable communities in cities are disproportionately impacted by flooding, as evidenced by Federal Emergency Management Agency (FEMA) designated flood zones. Tampa and Houston, both coastal cities in the US, were investigated to understand flood risk and related equity issues using Geographical Information System (GIS) and statistical analyses. Both approaches allowed us to extract and integrate information from flood hazard maps with census block group-level sociodemographic data. Dasymetric mapping (i.e., binary mapping approach) was performed to calculate population density. Both correlations and logistic regression were used to examine the relationships between sociodemographic characteristics of population and flood risk associated with FEMA flood zones. Our research findings do not suggest any racial and ethnic disparities; however, a measurable inequity is observed in exposure to flood risk across age groups, education level, and income status. Since these vulnerable groups are often unrecognized in hazard-related policy discourses (i.e., preparedness, response, and recovery), the ramifications of these research findings may have significant impacts on EE research relating to flood hazards and related policy formulations.

Identification of critical watershed at risk of soil erosion using morphometric and geographic information system analysis

Morphometric analysis is a pertinent scientific approach in any hydrological analysis, and it is necessary in the progress and management of drainage basin. Identification of areas at risk of erosion, and the prioritization of 48 sub-watersheds of Inaouene basin, was done by using linear, relief and areal aspects of watershed. The research carried out the use of geographic information system spatial data. The linear aspects include stream number, stream sequence, stream length, and bifurcation ratio, mean length of stream order, stream length ratio, mean stream length ratio, and form factor. The areal aspect includes frequency of stream, drainage density, texture ratio, channel length constant, and overland flow maintenance length. Ultimately, the relief dimensions included relief proportion, relief and ruggedness number. The array of compound (Cp) values computed allow us to set the priority ranks and classify the sub-watershed into three priority ranks groups: low, moderate, and high priority. Such morphometric analyses can be used therefore as a watershed erosion status estimator to prioritize land and water conservation initiatives and natural resources management.

Potential areas of interest for the development of geothermal energy in La Réunion Island based on GIS analysis

La Réunion Island has been considered an attractive target for geothermal exploitation since the 1970s. However, to date, the island's geothermal resources are not being used. Here we use for the first time, a Geographic Information System (GIS) as a decision-making tool to target the most favorable zones for exploitation of moderate and high temperature geothermal resources. All data acquired since the 1970s (geology, geophysics, geochemistry) in addition to environmental constraints such as protection of the National Park that was recently classified as a UNESCO World Heritage Site, were analyzed using the weighted overlay method to delineate favorable areas for local geothermal exploration. Three thematic maps were constructed: geological and structural indicators, thermal indicators, and geophysical indicators. Cross-analysis of these maps highlights two zones that have high geothermal potential; six zones with unconfirmed geothermal potential; and two zones located within the National Park protected area and thus subject to stringent exploitation regulations. It appears that, while thermal anomalies exist in several areas, permeability of the geological formations is low or insufficient for traditional geothermal utilization. Future exploration phases should assess the feasibility of using enhanced geothermal system (EGS) technologies to obtain a satisfactory economic return.

Appraising groundwater potential zones using geospatial and multi-criteria decision analysis (MCDA) techniques in Andasa-Tul watershed, Upper Blue Nile basin, Ethiopia

An integrated approach of remote sensing, geographic information system and multicriteria decision analysis of analytical hierarchical process (AHP) were applied to delineate groundwater potential (GWP) zones in Andasa-Tul watershed, Upper Blue Nile Basin, Ethiopia with an area of 1872 km2. Nine GWP influencing thematic layers comprising lithology, lineament density, geomorphology, slope, soil, drainage density, land use/land cover, rainfall and depth to groundwater level prepared from conventional and satellite data were used. The thematic layers and classes within them were given scale values based on literature and experts’ decision by using Satty’s AHP. The thematic layers have been integrated via their weights/rates using weighted overlay spatial function tool of ArcGIS to provide GWP map. The result shows that GWP map comprises 250.8 km2 (13.4%) very good, 132.9 km2 (7.1%) good, 441.8 km2 (23.6%) moderate, 662.7 km2 (35.4%) poor and 383.8 km2 (20.5%) very poor zones. Validation of the GWP map with existing boreholes and springs yield shows 83.8% agreement indicating good accuracy of the method. The map removal sensitivity analysis result reveals that GWP is more sensitive to lithology (mean variation index, 1.92%) and less sensitive to geomorphology (mean variation index, 0.59%). Similarly, from the single layer sensitivity analysis, lithology and slope are found to be more effective parameters, whereas rainfall and depth to groundwater level are less effective variables. The generated GWP map in the study region can be used as important guideline for locating GWP areas for further exploration, planning and management of the groundwater resources.

Serological Survey of Canine Vector-Borne Infections in North-Center Spain.

Various factors are currently causing an increase in vector-borne parasitic diseases at a global scale; among them, some stand out, such as climatic disturbances derived from global change, the increase in movements of reservoir animals, or changes in land made by human activity. In the European continent, there have been an increasing number of epidemiological studies focused on the detection of these diseases, especially in dogs. In Spain, there are few epidemiological studies focused on the evaluation of the biotic and abiotic factors that may influence the distribution, such as climatic zones, orography, or presence of water reservoirs. The aim of this study was to analyze the prevalence and distribution of several canine vector-borne diseases caused by Dirofilaria immitis, Leishmania infantum, Anaplasma platys, and Ehrlichia canis in the autonomous community of Castilla y León, the largest region of the Iberian Peninsula, providing a geospatial approach based on a geographic information system (GIS) analysis. Blood from a total of 1,475 domestic dogs from the nine provinces of Castilla y León were analyzed. Also, a GIS analysis of the sample locations was carried out, taking into account the most important predictor variables. The prevalence in dogs infected by D. immitis was 7.19%, and the seroprevalence by L. infantum was 4.61 and 1.56% for A. platys and E. canis. Most of the infected animals were located in areas with stagnant water, irrigated agriculture, or riverbanks, always close to forest and woodland vegetation. These results indicate that dogs living in Castilla y León should take prophylactic measures to avoid infections.

Factors controlling the spatial distribution of coseismic landslides triggered by the Mw 6.1 Ludian earthquake in China

Understanding the spatial distribution regularity of coseismic landslides is important for mitigation in future earthquakes. Unveiling the controlling factors of the distribution of coseismic landslides is a long-standing unsolved problem. On 3 August 2014, a Mw 6.1 earthquake occurred in Ludian County, Yunnan Province, China, and resulted in a great number of landslides and substantial losses. The coseismic landslide distribution in this earthquake, which was triggered by an unmapped fault, shows a different pattern. This paper conducted a spatial analysis to reveal the controlling factors in the Ludian earthquake. A spatial database of landslides has been built by interpreting the ZY-3 pre-earthquake, unmanned aerial vehicle (UAV), GeoEye-1 and GF-1 post-earthquake. A total of 1414 landslides were identified after a combination of image interpretation and field investigation in an area of 704.7 km2. The geological setting of the study area, including the tectonics and lithology, has been mapped in detail. The digital elevation model (DEM) of the study area with a resolution of 30 m × 30 m was presented to address the topographic characteristics. A geographic information system (GIS) was used to analyse the spatial characterization of the landslides. Correlations between the occurrences of landslides and factors, i.e., slope gradient, elevation, slope aspect, intensity, distance to coseismic fault, distance to the epicentre, lithology, distance to non-coseismic faults, distance to rivers and distance to road, were characterized with a spatial analysis in GIS. It can be concluded that the slope gradient and the distance to the coseismic fault are the two most important factors for determining the spatial distribution of coseismic disasters. Some other factors play a role by influencing the slope gradient to a certain extent, and the movement of the coseismic fault is the prone direction of coseismic landslides. Slope cutting fractures the rock mass, increases the slope gradient, and significantly increases the occurrence of coseismic landslides. A statistics analysis indicates that the landslide concentration (LC) generally has an obvious exponential decrease with an increasing distance to the coseismic fault, while it has a good Weibull cumulative distribution with the slope gradient.

GIS and RS-Based Analysis of Water Pollution Potential Caused by Acid Mine Drainage in Samarinda, Indonesia

Large-scale mining activity is the major environmental issue, including water pollution caused by Acid Mine Drainage (AMD). Samarinda, which is located in the province of East Kalimantan, Indonesia, has open pits and acid contributing land as a source of AMD pollutants. The potential AMD pollution can be assessed by utilizing Geographic Information System (GIS) and Remote Sensing (RS), which are considered reliable tools for measuring, mapping, monitoring, and model making for an area. The variables used in this research are void distribution, land cover, soil type, rainfall, topography, water body, and groundwater. The integration of these variables is used to analyze the potential of AMD pollution to water bodies by acid contributing land. Meanwhile, the void distribution and groundwater integration data are used to analyze the potential of AMD pollution to groundwater by voids. The overlay method is employed to analyze the potential spatial patterns of AMD pollution in the study area. The results show the high potential of AMD pollution to water bodies, specifically in the districts of Samarinda Utara, Palaran, and Sungai Kunjang. The high potential of AMD pollution to groundwater is found in the south delineation area, namely Palaran, Loa Janan Hilir, and Samarinda Seberang districts, with low and medium groundwater depth categories (20 - 70 and 50 - 150 MBGL). The spatial pattern of AMD pollution was random with the geometric arrangement of AMD pollution in the form of clusters.

Retraction Note: Landscape design of hill ecology and rural human settlement environment based on the analysis of geographic information system

Retraction Note: Landscape design of hill ecology and rural human settlement environment based on the analysis of geographic information system

LANDSLIDE SUSCEPTIBILITY ZONATION, KABILA BONE SUB-DISTRICT, BONE BOLANGO DISTRICT, GORONTALO PROVINCE

The research area is administratively located in the Kabila Bone Sub-district, Bone Bolango District, Gorontalo Province which has an area of 143,51 km 2 . The purpose of the research is determine landslide susceptibility zonation of Kabila Bone Sub-district , Bone Bolango District, Gorontalo Province. The method used in this research is geological survey method and analysis of geographic information system. The parameters used refers to Peraturan Menteri Pekerjaan Umum No. 22/PRT/M/2007, which includes of slope, soil condition, lithology, rainfall, slope water system, seismicity, and vegetation. The result of research show that Kabila Bone Sub-district consists of a zone with a low level of susceptibility which has an area of 1258,76 ha, a zone with a medium level of susceptibility which has an area of 4026,90 ha, and a zone with a high level of susceptibility which has an area of 502,03 ha. Zones that have a high level of susceptibility are distributed in several villages, namely Botubarani Village with an area of 117,92 ha, Huangobotu Village with an area of 89,35 ha, Bintalahe Village with an area of 64,22 ha, Oluhuta Village with an area of 119,98 ha, and Olele Village with an are of 104,01 ha.

Rural electrification planning based on graph theory and geospatial data: A realistic topology oriented approach

By the year 2019, the number of people without access to electricity was 770 million, most of which lived in rural areas. The currently models for rural electrification are often limited in their electrical analysis, or focus on a idealistic optimal solution whilst ignoring the real hierarchical topology of power systems. This work proposes a rural electrification strategy that makes use of Geographic Information System (GIS), graph theory and terrain analysis to create the best electric network topology. It uses the GIS for Electrification (GISEle) tool while improving the former topological-focused analysis, to one that considers other aspects of electric network planning such as cable sizing based on current-carrying capacity constraints and the sharing of substations connections. By considering these factors, a better and more realistic topology is achieved. Furthermore, an electrical analysis was performed to endorse the topology found, by executing load flow analysis in critical parts of the grid, in order to investigate steady-state voltages, as well as substation and line loading. The strategy proposed was applied to a real case study of grid expansion in the municipality of Cavalcante, in a rural area in Brazil. The goal is to find the most cost-efficient network topology reaching up to 100% of the local population through an expansion of the MV distribution network. The results show that by using the new approach proposed, a reduction of up to 47% (compared to a standard minimum spanning tree procedure) of the total investment cost in line deployment was achieved. This reduction is possible through a proper sizing, based on the power supplied, of the MV cables used in the electrification planning.

Mapping of Groundwater potential zones in Lingasugur Taluk in North-eastern part of Karnataka, India using Remote Sensing, GIS and multi-criteria data analysis

Groundwater research has evolved tremendously as presently it is the need of society. Remote Sensing (RS) and Geographical Information System (GIS) are the main methods in finding the potential zones for the groundwater. They help in assessing, exploring, monitoring and conserving groundwater resources. A case study was conducted to find the groundwater potential zones in Lingasugur taluk, Raichur District, Karnataka State, India. Ten thematic maps were prepared for the study area such as geology, hydrogeomorphology, land use/ land cover, soil type, NDVI, NDWI, slope map, lineament density, rainfall and drainage density. A weighted overlay superimposed method was used after converting all the thematic maps in raster format. Thus from analysis, the classes in groundwater potential were made as very good, moderate, poor and very poor zones covering an area of 10.1 sq.km., 169.25 sq.km., 1732.31 sq.km. and 53.66 sq.km. respectively. By taking the present study into consideration, the future plans for urbanization, recharge structures and groundwater exploration sites can be decided.

Racial and Socioeconomic Disparities in Out-Of-Hospital Cardiac Arrest Outcomes: Artificial Intelligence-Augmented Propensity Score and Geospatial Cohort Analysis of 3,952 Patients

Introduction Social disparities in out-of-hospital cardiac arrest (OHCA) outcomes are preventable, costly, and unjust. We sought to perform the first large artificial intelligence- (AI-) guided statistical and geographic information system (GIS) analysis of a multiyear and multisite cohort for OHCA outcomes (incidence and poor neurological disposition). Method We conducted a retrospective cohort analysis of a prospectively collected multicenter dataset of adult patients who sequentially presented to Houston metro area hospitals from 01/01/07-01/01/16. Then AI-based machine learning (backward propagation neural network) augmented multivariable regression and GIS heat mapping were performed. Results Of 3,952 OHCA patients across 38 hospitals, African Americans were the most likely to suffer OHCA despite representing a significantly lower percentage of the population (42.6 versus 22.8%; p < 0.001). Compared to Caucasians, they were significantly more likely to have poor neurological disposition (OR 2.21, 95%CI 1.25–3.92; p=0.006) and be discharged to a facility instead of home (OR 1.39, 95%CI 1.05–1.85; p=0.023). Compared to the safety net hospital system primarily serving poorer African Americans, the university hospital serving primarily higher income commercially and Medicare insured patients had the lowest odds of death (OR 0.45, p < 0.001). Each additional $10,000 above median household income was associated with a decrease in the total number of cardiac arrests per zip code by 2.86 (95%CI -4.26- -1.46; p < 0.001); zip codes with a median income above $54,600 versus the federal poverty level had 14.62 fewer arrests (p < 0.001). GIS maps showed convergence of the greater density of poor neurologic outcome cases and greater density of poorer African American residences. Conclusion This large, longitudinal AI-guided analysis statistically and geographically identifies racial and socioeconomic disparities in OHCA outcomes in a way that may allow targeted medical and public health coordinated efforts to improve clinical, cost, and social equity outcomes.

Retraction Note: Landscape simulation of small towns along Huaihe River based on geographic information system and big data analysis

Retraction Note: Landscape simulation of small towns along Huaihe River based on geographic information system and big data analysis

Spatially explicit vulnerability analysis of contaminant sources in a karstic watershed in southeastern Mexico

A water vulnerability assessment was performed on the Río Grande-Lagos de Montebello watershed, in southeastern region of Chiapas, Mexico. This is a karstic environment highlighted by well-preserved lakes, close to Guatemala border. We used multicriteria analysis to identify areas vulnerable to water contamination at subbasin scale using geographic information system and spatial analysis. Potential contamination sources were georeferenced and overlapped with precipitation and slope layers to identify areas prone to contaminant transport and infiltration. The results showed that both irrigation and rainfed agriculture were the main contamination sources, followed by wastewater discharge. Supported by land use and forest change analysis, agricultural activities were the most important drivers of change. A water vulnerability map at subbasin scale is presented as an outcome, which enables the ranking of water contamination potential in presence of different contamination sources using the weighted sum and linear normalization methods. Two subbasins were identified within the most vulnerable categories, Comitán and El Triunfo. No previous water vulnerability analyses have been performed for this region. We propose this vulnerability map as a decision-making tool for sustainable water management at watershed scale in areas with scarce information and increasing water quality degradation processes.