Displaying publications 1 - 20 of 116 in total

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  1. Arshad S, Lihan T, Rahman ZA, Idris WMR
    Environ Sci Pollut Res Int, 2023 Sep;30(41):93760-93778.
    PMID: 37516702 DOI: 10.1007/s11356-023-28764-7
    Globally, around 1.3 billion tonnes of waste are generated annually, and solid waste management has thus become a major concern worldwide. There are projections of a 70% increase in waste generation from 2016 to 2050 owing to urbanization and the rapid growth of the global population. Estimates indicate that around 38,200 tonnes of waste are generated per day in Malaysia, and this volume of waste is significantly shortening the planned life spans of operating sanitary landfills in the country. Batu Pahat is a district in the state of Johor, Malaysia, with a relatively large population of 495,000 and with no record of an operational sanitary landfill. This study was conducted to identify and classify the most suitable sites for sanitary landfill developments in southern Peninsular Malaysia by means of the Analytical Hierarchy Process (AHP), which is recognized as a competent technique for multicriteria decision-making. The resulting landfill site suitability index map established 33.88 km2 of area coverage as very highly suitable for landfill development, while 353.86 km2 of area coverage was classified as unsuitable. Sites 1-6 were identified as the most suitable for landfill activities. Sites 1-5 are situated in agricultural land areas, while site 6 is in a forested land area; this implies public participation and the adoption of compensatory measures in the event of landfill development in these areas, given their socioeconomic importance. The six suitable sites are all at least 2000 m from rivers: 2000-3000 m for sites 1, 3, and 5 and > 3000 m for sites 2, 4, and 6. The six sites are all > 3000 m from fault zones and > 1000 m from flood-prone areas, meaning that occurrences such as fault movements and flooding will have minimal impact on the operational activities of landfills at these sites. The selection of sites 1-6 as very suitable for landfill development was associated with an overall accuracy rating of 93.33% and kappa coefficient score of 0.92 based on accuracy assessment analysis of all sites. This study will guide the actions of policymakers, city planners, and local authorities toward sustainable and environment-friendly landfill development and operation in Batu Pahat and other districts in the state of Johor.
    Matched MeSH terms: Geographic Information Systems
  2. Moharir KN, Pande CB, Gautam VK, Singh SK, Rane NL
    Environ Res, 2023 Jul 01;228:115832.
    PMID: 37054834 DOI: 10.1016/j.envres.2023.115832
    The Damoh district, which is located in the central India and characterized by limestone, shales, and sandstone compact rock. The district has been facing groundwater development challenges and problems for several decades. To facilitate groundwater management, it is crucial to monitoring and planning based on geology, slope, relief, land use, geomorphology, and the types of the basaltic aquifer in the drought-groundwater deficit area. Moreover, the majority of farmers in the area are heavily dependent on groundwater for their crops. Therefore, delineation of groundwater potential zones (GPZ) is essential, which is defined based on various thematic layers, including geology, geomorphology, slope, aspect, drainage density, lineament density, topographic wetness index (TWI), topographic ruggedness index (TRI), and land use/land cover (LULC). The processing and analysis of this information were carried out using Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) methods. The validity of the results was trained and tested using Receiver Operating Characteristic (ROC) curves, which showed training and testing accuracies of 0.713 and 0.701, respectively. The GPZ map was classified into five classes such as very high, high, moderate, low, and very low. The study revealed that approximately 45% of the area falls under the moderate GPZ, while only 30% of the region is classified as having a high GPZ. The area receives high rainfall but has very high surface runoff due to no proper developed soil and lack of water conservation structures. Every summer season show a declined groundwater level. In this context, results of study area are useful to maintain the groundwater under climate change and summer season. The GPZ map plays an important role in implementing artificial recharge structures (ARS), such as percolation ponds, tube wells, bore wells, cement nala bunds (CNBs), continuous contour trenching (CCTs), and others for development of ground level. This study is significant for developing sustainable groundwater management policies in semi-arid regions, that are experiencing climate change. Proper groundwater potential mapping and watershed development policies can help mitigate the effects of drought, climate change, and water scarcity, while preserving the ecosystem in the Limestone, Shales, and Sandstone compact rock region. The results of this study are essential for farmers, regional planners, policy-makers, climate change experts, and local governments, enabling them to understand the groundwater development possibilities in the study area.
    Matched MeSH terms: Geographic Information Systems*
  3. Tella A, Balogun AL
    Environ Sci Pollut Res Int, 2022 Dec;29(57):86109-86125.
    PMID: 34533750 DOI: 10.1007/s11356-021-16150-0
    Rapid urbanization has caused severe deterioration of air quality globally, leading to increased hospitalization and premature deaths. Therefore, accurate prediction of air quality is crucial for mitigation planning to support urban sustainability and resilience. Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). Incorporating PM in AQI studies is crucial because of its easily inhalable micro-size which has adverse impacts on ecology, environment, and human health. Accurate and timely prediction of the air quality index can ensure adequate intervention to aid air quality management. Therefore, this study undertakes a spatial hazard assessment of the air quality index using particulate matter with a diameter of 10 μm or lesser (PM10) in Selangor, Malaysia, by developing four machine learning models: eXtreme Gradient Boosting (XGBoost), random forest (RF), K-nearest neighbour (KNN), and Naive Bayes (NB). Spatially processed data such as NDVI, SAVI, BU, LST, Ws, slope, elevation, and road density was used for the modelling. The model was trained with 70% of the dataset, while 30% was used for cross-validation. Results showed that XGBoost has the highest overall accuracy and precision of 0.989 and 0.995, followed by random forest (0.989, 0.993), K-nearest neighbour (0.987, 0.984), and Naive Bayes (0.917, 0.922), respectively. The spatial air quality maps were generated by integrating the geographical information system (GIS) with the four MLAs, which correlated with Malaysia's air pollution index. The maps indicate that air quality in Selangor is satisfactory and posed no threats to health. Nevertheless, the two algorithms with the best performance (XGBoost and RF) indicate that a high percentage of the air quality is moderate. The study concludes that successful air pollution management policies such as green infrastructure practice, improvement of energy efficiency, and restrictions on heavy-duty vehicles can be adopted in Selangor and other Southeast Asian cities to prevent deterioration of air quality in the future.
    Matched MeSH terms: Geographic Information Systems
  4. Hassan SI, Alam MM, Zia MYI, Rashid M, Illahi U, Su'ud MM
    Sensors (Basel), 2022 Nov 07;22(21).
    PMID: 36366269 DOI: 10.3390/s22218567
    Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode.
    Matched MeSH terms: Geographic Information Systems
  5. Abdullah N, Al-Wesabi OA, Mohammed BA, Al-Mekhlafi ZG, Alazmi M, Alsaffar M, et al.
    Int J Environ Res Public Health, 2022 Oct 11;19(20).
    PMID: 36293647 DOI: 10.3390/ijerph192013066
    Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception. Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities' administration systems. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. However, from another perspective, the population and residents' attitudes directly affect the control of the waste management system. The conventional waste collection system does not cover all areas in the city. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is 'full,' 'not full,' or 'empty.' This paper uses IoT in the container and trucks that secure the overflow and separation of waste. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Issues relating to the sustainability of organic waste management are conceptually analyzed. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time.
    Matched MeSH terms: Geographic Information Systems
  6. Yong CZ, Odolinski R, Zaminpardaz S, Moore M, Rubinov E, Er J, et al.
    Sensors (Basel), 2021 Dec 13;21(24).
    PMID: 34960412 DOI: 10.3390/s21248318
    The recent development of the smartphone Global Navigation Satellite System (GNSS) chipsets, such as Broadcom BCM47755 and Qualcomm Snapdragon 855 embedded, makes instantaneous and cm level real-time kinematic (RTK) positioning possible with Android-based smartphones. In this contribution we investigate the instantaneous single-baseline RTK performance of Samsung Galaxy S20 and Google Pixel 4 (GP4) smartphones with such chipsets, while making use of dual-frequency L1 + L5 Global Positioning System (GPS), E1 + E5a Galileo, L1 + L5 Quasi-Zenith Satellite System (QZSS) and B1 BeiDou Navigation Satellite System (BDS) code and phase observations in Dunedin, New Zealand. The effects of locating the smartphones in an upright and lying down position were evaluated, and we show that the choice of smartphone configuration can affect the positioning performance even in a zero-baseline setup. In particular, we found non-zero mean and linear trends in the double-differenced carrier-phase residuals for one of the smartphone models when lying down, which become absent when in an upright position. This implies that the two assessed smartphones have different antenna gain pattern and antenna sensitivity to interferences. Finally, we demonstrate, for the first time, a near hundred percent (98.7% to 99.9%) instantaneous RTK integer least-squares success rate for one of the smartphone models and cm level positioning precision while using short-baseline experiments with internal and external antennas, respectively.
    Matched MeSH terms: Geographic Information Systems
  7. Mohidem NA, Osman M, Muharam FM, Mohd Elias S, Shaharudin R, Hashim Z
    Geospat Health, 2021 Oct 19;16(2).
    PMID: 34672178 DOI: 10.4081/gh.2021.980
    In the last few decades, public health surveillance has increasingly applied statistical methods to analyze the spatial disease distributions. Nevertheless, contact tracing and follow up control measures for tuberculosis (TB) patients remain challenging because public health officers often lack the programming skills needed to utilize the software appropriately. This study aimed to develop a more user-friendly application by applying the CodeIgniter framework for server development, ArcGIS JavaScript for data display and a web application based on JavaScript and Hypertext Preprocessor to build the server's interface, while a webGIS technology was used for mapping. The performance of this approach was tested based on 3325 TB cases and their sociodemographic data, such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency status, and smoking status between 1st January 2013 and 31st December 2017 in Gombak, Selangor, Malaysia. These data were collected from the Gombak District Health Office and Rawang Health Clinic. Latitude and longitude of the location for each case was geocoded by uploading spatial data using Google Earth and the main output was an interactive map displaying location of each case. Filters are available for the selection of the various sociodemographic factors of interest. The application developed should assist public health experts to utilize spatial data for the surveillance purposes comprehensively as well as for the drafting of regulations aimed at to reducing mortality and morbidity and thus minimizing the public health impact of the disease.
    Matched MeSH terms: Geographic Information Systems*
  8. Rahim MH, Dom NC, Ismail SNS, Mulud ZA, Abdullah S, Pradhan B
    One Health, 2021 Jun;12:100222.
    PMID: 33553566 DOI: 10.1016/j.onehlt.2021.100222
    This study has highlighted the trend of recently-reported dengue cases after the implementation of the Movement Control Orders (MCOs) caused due to COVID-19 pandemic in Malaysia. The researchers used the dengue surveillance data published by the Malaysian Ministry of Health during the 3 phases of MCO (which ranged between 17th March 2020 and 28th April 2020) was used for determining the cumulative number of dengue patients. Thereafter, the dengue cases were mapped using the Geographical Information System (GIS). The results indicated that during the 42 days of MCO in Peninsular Malaysia, 11,242 total cases of dengue were reported. The daily trend of the dengue cases showed a decrease from 7268 cases that occurred before the MCOs to 4662 dengue cases that occurred during the initial 14 days of the COVID-19 pandemic (i.e., MCO I), to 3075 cases occurring during the MCO II and 3505 dengue cases noted during MCO III. The central peninsular region showed a maximal decrease in new dengue cases (52.62%), followed by the northern peninsular region (1.89%); eastern coastal region (1.25%) and the southern peninsular region (1.14%) during the initial MCO implementation. However, an increase in the new dengue cases was noted during the MCO III period, wherein all states showed an increase in the new dengue cases as compared during MCO II. The decrease in the pattern was not solely based on the MCO, hence, further investigation is necessary after considering different influencing factors. These results have important implication for future large-scale risk assessment, planning and hazard mitigation on dengue management.
    Matched MeSH terms: Geographic Information Systems
  9. Umar HA, Abdul Khanan MF, Ogbonnaya C, Shiru MS, Ahmad A, Baba AI
    Heliyon, 2021 May;7(5):e06999.
    PMID: 34027190 DOI: 10.1016/j.heliyon.2021.e06999
    Over the years, pipelines have been the most economic medium for transporting crude oil to production and distribution facilities in the Niger Delta area of Nigeria. However, damages to the pipelines in this area by interdiction have hampered the continuous flow of crude oil to the facilities. Consequently, the revenue of the government dwindles, and the environment is severely degraded. This study assesses the economic and environmental impacts of pipeline interdiction in the Niger Delta region. Data from National oil spills detection and response agency, Nigeria is used to map spatial distribution of oil spills using Kernel Density Estimation with Geographic Information System. Literature was assessed to synthesize the historical, socioeconomic, and environmental impacts of oil spills and pipeline interdiction. Soil samples were collected from study area to determine the types of hydrocarbon pollutants and their concentrations in comparison with uncontaminated sites in the area. Results show that the range of concentrations of total petroleum hydrocarbon (TPH) for the impacted soil (IMP) was 17.27-58.36 mg/kg; remediated soil (RS) was 11.73-50.78 mg/kg which were higher than the concentrations of 0.68 mg/kg in the control samples (CS). Polycyclic aromatic hydrocarbons (PAH) concentrations were in the range of 0.43-77.54 mg/kg for IMP, 0.42-10.65 mg/kg for RS, against CS value of 0.49 mg/kg while BTEX ranged between 0.02 - 0.38 mg/kg for IMP, 0.01-2.7 for RS against CS value of 0.01. The values of the PAH were higher than the limits of the Department of Petroleum Resources, Nigeria. This study also revealed that pipeline interdiction has affected the livelihood of the inhabitants of the study area and the revenue of the Nigerian government. The major hotspots for oil spills in the Niger Delta region are Bayelsa, Rivers and Delta states.
    Matched MeSH terms: Geographic Information Systems
  10. Tew MM, Hatah E, Arif F, Abdul Wahid MA, Makmor-Bakry M, Abdul Maulad KN
    J Pharm Policy Pract, 2021 Feb 24;14(1):24.
    PMID: 33627199 DOI: 10.1186/s40545-021-00308-9
    BACKGROUND: Minor ailments are defined as common, self-limiting, or uncomplicated conditions that may be diagnosed and managed without a medical intervention. Previous studies reported that pharmacists were able to help patients self-manage minor ailments that led to a reduction of health care burden in other facilities. Nevertheless, public access to community pharmacy and other health care facilities offering services for minor ailments has not yet been explored in Malaysia. Hence, this study aims to determine population access to the above-mentioned services.

    METHOD: According to the reported practice address in 2018, the spatial distribution of health care facilities was mapped and explored using the GIS mapping techniques. The density of health care facilities was analyzed using thematic maps with hot spot analysis. Population to facility ratio was calculated using the projection of the population growth based on 2010 census data, which was the latest available in the year of analysis.

    RESULTS: The study included geographical mapping of 7051 general practitioner clinics (GPC), 3084 community pharmacies (CP), 139 public general hospitals (GHs) and 990 public primary health clinics (PHC). The health care facilities were found to be highly dense in urban areas than in the rural ones. There were six districts that had no CP, 2 had no GPC, and 11 did not have both. The overall ratio of GPC, CP, GH, and PHC to the population was 1:4228, 1:10,200, 1:223,619 and 1:31,397, respectively. Should the coverage for minor ailment services in public health care clinics be extended to community pharmacies, the ratio of facilities to population for each district would be better with 1:4000-8000.

    CONCLUSIONS: The distribution of health care facilities for minor ailment management in Malaysia is relatively good. However, if the scheme for minor ailments were available to community pharmacies, then the patients' access to minor ailments services would be further improved.

    Matched MeSH terms: Geographic Information Systems
  11. Lei J, Booth DT, Rusli MU, Zhang Z
    Zoolog Sci, 2021 Feb;38(1):1-7.
    PMID: 33639712 DOI: 10.2108/zs200071
    Nest predation is the main cause of hatching failure for many turtle populations. For green turtles (Chelonia mydas) nesting at Chagar Hutang in Redang Island, Malaysia, Asian water monitors (Varanus salvator) are a potential nest predator. However, no studies have documented the space use of this species in coastal habitat adjacent to a sea turtle nesting beach to assess its potential impact on turtle nests. Here, we used Global Positioning System (GPS) data loggers to quantify space use of Asian water monitors in order to establish the extent to which they use sea turtle nesting areas. Asian water monitors had a diurnal activity pattern and spent most of their time in rain forest habitat behind the sea turtle nesting beach. The home range occupied by Asian water monitors varied between 0.015 and 0.198 km2 calculated by the Kernel Brownian Bridge method. The space use patterns of individual Asian water monitors varied between individuals. Two males had relatively small home ranges, whereas one male and the female had a relatively large home range. Because tracked Asian water monitors in this study rarely visited the sea turtle nesting areas, it is probable that only a few individuals are responsible for opening nests.
    Matched MeSH terms: Geographic Information Systems
  12. Balogun AL, Yekeen ST, Pradhan B, Wan Yusof KB
    Environ Pollut, 2021 Jan 01;268(Pt A):115812.
    PMID: 33143984 DOI: 10.1016/j.envpol.2020.115812
    This study develops an oil spill environmental vulnerability model for predicting and mapping the oil slick trajectory pattern in Kota Tinggi, Malaysia. The impact of seasonal variations on the vulnerability of the coastal resources to oil spill was modelled by estimating the quantity of coastal resources affected across three climatic seasons (northeast monsoon, southwest monsoon and pre-monsoon). Twelve 100 m3 (10,000 splots) medium oil spill scenarios were simulated using General National Oceanic and Atmospheric Administration Operational Oil Modeling Environment (GNOME) model. The output was integrated with coastal resources, comprising biological, socio-economic and physical shoreline features. Results revealed that the speed of an oil slick (40.8 m per minute) is higher during the pre-monsoon period in a southwestern direction and lower during the northeast monsoon (36.9 m per minute). Evaporation, floating and spreading are the major weathering processes identified in this study, with approximately 70% of the slick reaching the shoreline or remaining in the water column during the first 24 h (h) of the spill. Oil spill impacts were most severe during the southwest monsoon, and physical shoreline resources are the most vulnerable to oil spill in the study area. The study concluded that variation in climatic seasons significantly influence the vulnerability of coastal resources to marine oil spill.
    Matched MeSH terms: Geographic Information Systems
  13. Okyere I, Chuku EO, Ekumah B, Angnuureng DB, Boakye-Appiah JK, Mills DJ, et al.
    Sci Rep, 2020 12 29;10(1):22407.
    PMID: 33376254 DOI: 10.1038/s41598-020-79898-4
    The novel coronavirus is predicted to have dire implications on global food systems including fisheries value chains due to restrictions imposed on human movements in many countries. In Ghana, food production, both agriculture and fisheries, is exempted from restrictions as an essential service. The enforcement of COVID-19 prevention protocols, particularly social distancing, has been widely reported in Ghana's agricultural markets whereas casual observations and media reports on fish landing sites suggest no such enforcements are in place. This study aimed to provide sound scientific evidence as a basis for informed policy direction and intervention for the artisanal fishing sector in these challenging times. We employed an unmanned aerial vehicle in assessing the risk of artisanal fishers to the pandemic using physical distancing as a proxy. From analysis of cumulative distribution function (G-function) of the nearest-neighbour distances, this study underscored crowding at all surveyed fish landing beaches, and identified potential "hotspots" for disease transmission. Aerial measurements taken at times of peak landing beach activity indicated that the highest proportion of people, representing 56%, 48%, 39% and 78% in Elmina, Winneba, Apam and Mumford respectively, were located at distances of less than one metre from their nearest neighbour. Risk of crowding was independent of the population at the landing beaches, suggesting that all categories of fish landing sites along the coast would require equal urgency and measured attention towards preventing and mitigating the spread of the disease.
    Matched MeSH terms: Geographic Information Systems
  14. Md Bohari NF, Sabri NF, Wan Rasdi WND, Mohd Radzi NA, Bakri NN
    Asia Pac J Public Health, 2020 12 24;33(2-3):227-233.
    PMID: 33356376 DOI: 10.1177/1010539520982718
    Although geographic information system-based studies are particularly increasing in other sectors, few have embraced their full potential in health services allocation in Malaysia. This study aimed to produce a visual map on the distribution of smoking cessation clinics (SCCs) in Malaysia and analyze its pattern against the national population of smokers. SCC addresses were obtained from the government website and mapped using geographic information system tools. A total of 199 and 449 private and public SCCs was mapped throughout the country, respectively. The lowest SCC to smoker population ratio was in the state of Negeri Sembilan with 1:3000. The highest SCC to smoker population ratio was in Sabah with 1 SCC for 15 000 smokers. Almost 70% of SCCs were primary health clinics. Smoking cessation clinics were distributed throughout all the states in Malaysia except the state of Sabah.
    Matched MeSH terms: Geographic Information Systems
  15. Mohammadi A, Karimzadeh S, Jalal SJ, Kamran KV, Shahabi H, Homayouni S, et al.
    Sensors (Basel), 2020 Dec 16;20(24).
    PMID: 33339435 DOI: 10.3390/s20247214
    Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs' performance, such as 90-meters' TanDEM-X and 30-meters' SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).
    Matched MeSH terms: Geographic Information Systems
  16. Ahmed JB, Salisu A, Pradhan B, Alamri AM
    Insects, 2020 Oct 24;11(11).
    PMID: 33114307 DOI: 10.3390/insects11110728
    Termite nests have long been suggested to be good indicators of groundwater but only a few studies are available to demonstrate the relationship between the two. This study therefore aims at investigating the most favourable spots for locating groundwater structures on a small parcel of land with conspicuous termite activity. To achieve this, geophysical soundings using the renowned vertical electrical sounding (VES) technique was carried out on the gridded study area. A total of nine VESs with one at the foot of a termitarium were conducted. The VES results were interpreted and assessed via two different techniques: (1) physical evaluation as performed by drillers in the field and (2) integration of primary and secondary geoelectrical parameters in a geographic information system (GIS). The result of the physical evaluation indicated a clear case of subjectivity in the interpretation but was consistent with the choice of VES points 1 and 6 (termitarium location) as being the most prospective points to be considered for drilling. Similarly, the integration of the geoelectrical parameters led to the mapping of the most prospective groundwater portion of the study area with the termitarium chiefly in the center of the most suitable region. This shows that termitaria are valuable landscape features that can be employed as biomarkers in the search of groundwater.
    Matched MeSH terms: Geographic Information Systems
  17. Franch-Pardo I, Napoletano BM, Rosete-Verges F, Billa L
    Sci Total Environ, 2020 Oct 15;739:140033.
    PMID: 32534320 DOI: 10.1016/j.scitotenv.2020.140033
    This study entailed a review of 63 scientific articles on geospatial and spatial-statistical analysis of the geographical dimension of the 2019 coronavirus disease (COVID-19) pandemic. The diversity of themes identified in this paper can be grouped into the following categories of disease mapping: spatiotemporal analysis, health and social geography, environmental variables, data mining, and web-based mapping. Understanding the spatiotemporal dynamics of COVID-19 is essential for its mitigation, as it helps to clarify the extent and impact of the pandemic and can aid decision making, planning and community action. Health geography highlights the interaction of public health officials, affected actors and first responders to improve estimations of disease propagation and likelihoods of new outbreaks. Attempts at interdisciplinary correlation examine health policy interventions for the siting of health/sanitary services and controls, mapping/tracking of human movement, formulation of appropriate scientific and political responses and projection of spatial diffusion and temporal trends. This review concludes that, to fight COVID-19, it is important to face the challenges from an interdisciplinary perspective, with proactive planning, international solidarity and a global perspective. This review provides useful information and insight that can support future bibliographic queries, and also serves as a resource for understanding the evolution of tools used in the management of this major global pandemic of the 21 Century. It is hoped that its findings will inspire new reflections on the COVID-19 pandemic by readers.
    Matched MeSH terms: Geographic Information Systems
  18. Husin MH, Lim YK
    Disabil Rehabil Assist Technol, 2020 08;15(6):701-707.
    PMID: 31729282 DOI: 10.1080/17483107.2019.1615999
    Background/Purpose: Visual impairment is a disability more commonly caused by diseases that lead to several disadvantages to the daily activities amongst those blind. For almost a century since the white cane was first introduced, the cane has remained as the most reliable tool for those affected by blindness.Methods: By using a combination of the capabilities of Internet of Things (IoT) and existing devices, such as mobile phones, an InWalker system is proposed to expand the functionality of the typical white cane, so as to introduce several new features that enhance the safety and confidence amongst people who are blind. As such, this paper explores the existing works and projects to comprehend the motivation and the standard practices for each proposed feature. Each of the strength and drawback has been assessed thoroughly to refine the scope of this project.Results: The proposed project, InWalker, is an intelligent system that has an embedded board system with various sensors to enhance the usability of white cane. The inputs from the sensor are processed on a microcontroller, which then pass the data to a smartphone via Bluetooth for additional features, such as global positioning system (GPS) tracking and SMS services.Conclusions: Based on the initial user testing, the proposed system has successfully fulfilled most of the users' need.Implication for RehabilitationVisual impairment is a disability more commonly caused by diseases that lead to several disadvantages amongst those blind.The white cane has been seen as the most reliable tool for the visual impaired.This tool could be further improved with the integration of additional sensors that works with today's mobile devices.The proposed system, InWalker, is able to improve the overall quality of life among people who are blind through several features: obstacle detection, GPS tracking and a light illumination in dark environments for increased safety.
    Matched MeSH terms: Geographic Information Systems/instrumentation*
  19. Nhu VH, Mohammadi A, Shahabi H, Ahmad BB, Al-Ansari N, Shirzadi A, et al.
    PMID: 32650595 DOI: 10.3390/ijerph17144933
    We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands, Malaysia. The models were trained with a database of 152 landslides compiled using Synthetic Aperture Radar Interferometry, Google Earth images, and field surveys, and 17 conditioning factors (slope, aspect, elevation, distance to road, distance to river, proximity to fault, road density, river density, normalized difference vegetation index, rainfall, land cover, lithology, soil types, curvature, profile curvature, stream power index, and topographic wetness index). We carried out the validation process using the area under the receiver operating characteristic curve (AUC) and several parametric and non-parametric performance metrics, including positive predictive value, negative predictive value, sensitivity, specificity, accuracy, root mean square error, and the Friedman and Wilcoxon sign rank tests. The AB model (AUC = 0.96) performed better than the ensemble AB-ADTree model (AUC = 0.94) and successfully outperformed the ADTree model (AUC = 0.59) in predicting landslide susceptibility. Our findings provide insights into the development of more efficient and accurate landslide predictive models that can be used by decision makers and land-use managers to mitigate landslide hazards.
    Matched MeSH terms: Geographic Information Systems
  20. Pius Owoh N, Mahinderjit Singh M
    Sensors (Basel), 2020 Jun 09;20(11).
    PMID: 32526843 DOI: 10.3390/s20113280
    The proliferation of mobile devices such as smartphones and tablets with embedded sensors and communication features has led to the introduction of a novel sensing paradigm called mobile crowd sensing. Despite its opportunities and advantages over traditional wireless sensor networks, mobile crowd sensing still faces security and privacy issues, among other challenges. Specifically, the security and privacy of sensitive location information of users remain lingering issues, considering the "on" and "off" state of global positioning system sensor in smartphones. To address this problem, this paper proposes "SenseCrypt", a framework that automatically annotates and signcrypts sensitive location information of mobile crowd sensing users. The framework relies on K-means algorithm and a certificateless aggregate signcryption scheme (CLASC). It incorporates spatial coding as the data compression technique and message query telemetry transport as the messaging protocol. Results presented in this paper show that the proposed framework incurs low computational cost and communication overhead. Also, the framework is robust against privileged insider attack, replay and forgery attacks. Confidentiality, integrity and non-repudiation are security services offered by the proposed framework.
    Matched MeSH terms: Geographic Information Systems
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