Displaying publications 81 - 100 of 118 in total

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  1. Fulltext A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
    Kzar AA, Mat Jafri MZ, Mutter KN, Syahreza S
    Int J Environ Res Public Health, 2016 Jan;13(1).
    PMID: 26729148 DOI: 10.3390/ijerph13010092
    Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA) was used with remote sensing imagery to classify the total suspended solids (TSS) concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS) image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS). The TSS concentration measurements were conducted in a lab and used for validation (real data), classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R) and root mean square error (RMSE) were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977) and lower RMSE (2.887). In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis). Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the adopted MHNNA with remote sensing techniques (as based on ALOS images).
    Matched MeSH terms: Geographic Information Systems
  2. Fulltext Association between Availability of Neighborhood Fast Food Outlets and Overweight Among 5⁻18 Year-Old Children in Peninsular Malaysia: A Cross-Sectional Study
    Chee Cheong K, Yoon Ling C, Kuang Hock L, Mohd Ghazali S, Chien Huey T, Che Ibrahim MK, et al.
    Int J Environ Res Public Health, 2019 02 18;16(4).
    PMID: 30781699 DOI: 10.3390/ijerph16040593
    A growing number of fast-food outlets in close proximity to residential areas raises a question as to its impact on childhood overweight and obesity. This study aimed at determining the relationship between the availability of fast-food outlets that were in close proximity to residential areas and overweight among Malaysian children aged 5 to 18 years. Measurement data on the weight and height of 5544 children (2797 boys, 2747 girls) were obtained from the National Health and Morbidity Survey 2011. Overweight (including obesity) is defined as BMI-for-age z-score > +1 SD based on the WHO growth reference. Geographic information system geospatial analysis was performed to determine the number of fast-food outlets within 1000 m radius from the children's residential address. Multiple logistic regression was conducted to examine the association between the availability of fast-food outlets (none or more than one outlet) and overweight with adjustment for age, sex, ethnicity, monthly household income, parental educational level, residential area and supermarket density. Our results showed that the prevalence of overweight was 25.0% and there was a statistically significant association between the density of fast-food outlets and overweight (odds ratio: 1.23, 95% confidence interval: 1.03, 1.47). Our study suggested that the availability of fast-food outlets with close proximity in residential areas was significantly associated with being overweight among children. Limiting the number of fast-food outlets in residential areas could have a significant effect in reducing the prevalence of overweight among Malaysian children.
    Matched MeSH terms: Geographic Information Systems
  3. Fulltext Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
    Nhu VH, Mohammadi A, Shahabi H, Ahmad BB, Al-Ansari N, Shirzadi A, et al.
    Int J Environ Res Public Health, 2020 07 08;17(14).
    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
  4. Fulltext IoT-Based Waste Management System in Formal and Informal Public Areas in Mecca
    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
  5. Analysis of dental services distribution in Malaysia: a geographic information systems - based approach
    Md Bohari NF, Kruger E, John J, Tennant M
    Int Dent J, 2019 Jun;69(3):223-229.
    PMID: 30565655 DOI: 10.1111/idj.12454
    OBJECTIVE: The aim of this study was to analyse, in detail, the distribution of primary dental clinics in relation to the Malaysian population and relative population wealth, to test the hypothesis that an uneven distribution of dental services exists in Malaysia.

    METHOD: This 2016 study located every dental practice in Malaysia (private and public) and mapped these practices against population, using Geographic Information Systems (GIS) tools. Population clusters within 5, 10 and 20 km of a dental clinic were identified, and clinic-to-population ratios were ascertained. Population data were obtained from the Population and Housing Census of Malaysia 2010. Population relative wealth was obtained from the 2014 Report on Household Income and Basic Amenities Survey for Malaysia. The physical address for each dental practice in Malaysia was gathered from the Official Portal of Ministry of Health Malaysia. All data for analysis were extracted from the integrated database in Quantum GIS (QGIS) into Microsoft Excel.

    RESULT: The population of Malaysia (24.9 million) was distributed across 127 districts, with 119 (94%) having at least one dental clinic. Sixty-four districts had fewer than 10 dental clinics, and 11.3% of Malaysians did not reside in the catchment of 20 km from any dental clinic. The total dental clinic-to-population ratio was 1:9,000: for public dental clinics it was 1:38,000 and for private clinics it was 1:13,000.

    CONCLUSION: Dental services were distributed relative to high population density, were unevenly distributed across Malaysia and the majority of people with the highest inaccessibility to a dental service resided in Malaysian Borneo.

    Matched MeSH terms: Geographic Information Systems*
  6. Fulltext Public health experience in the ‘Snow Country’ Niigata, Japan
    Syaqirah Akmal, Nizam Baharom
    Int J Public Health Res, 2012;2(2):184-191.
    MyJurnal
    In the cold winter month of January 2012, two post graduate students from the Department of Community Health, Universiti Kebangsaan Malaysia (UKM), went on a two weeks field attachment with the Division of International Health (Public Health), Niigata University Graduate School of Medical & Dental Sciences (NU). This report is an account of our first hand learning experience about the public health system and culture in Niigata, Japan. Famously known as the 'Snow Country', Niigata prefecture is approximately 350 kilometers north of Tokyo, in the middle of the west coast of Honshu island, facing the Sea of Japan. It borders on the east with Fukushima prefecture, which was badly affected by the great tsunami disaster in March 2011. Niigata has a population of two and a half million, of which 21.3% is above the age of 65. Niigata University is located in Niigata City, the capital of Niigata prefecture. This attachment was under the UKM-Global Student Mobility Programme (Outbound) and it was taken as an opportunity to improve the memorandum of understanding between UKM and NU. The objectives were to gain knowledge and experience in various public health issues in a developed nation like Japan. Specifically, we were interested to learn about the local public health programmes, the influenza surveillance system, public health programmes for the elderly population, the Geographical Information System (GIS) and the Japanese culture in general. (Copied from article).
    Matched MeSH terms: Geographic Information Systems
  7. Fulltext Do Termitaria Indicate the Presence of Groundwater? A Case Study of Hydrogeophysical Investigation on a Land Parcel with Termite Activity
    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
  8. Fulltext Environmental and socioeconomic impacts of pipeline transport interdiction in Niger Delta, Nigeria
    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
  9. Projection the long-term ungauged rainfall using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model
    Tukimat NNA, Ahmad Syukri NA, Malek MA
    Heliyon, 2019 Sep;5(9):e02456.
    PMID: 31687558 DOI: 10.1016/j.heliyon.2019.e02456
    An accuracy in the hydrological modelling will be affected when having limited data sources especially at ungauged areas. Due to this matter, it will not receiving any significant attention especially on the potential hydrologic extremes. Thus, the objective was to analyse the accuracy of the long-term projected rainfall at ungauged rainfall station using integrated Statistical Downscaling Model and Geographic Information System (SDSM-GIS) model. The SDSM was used as a climate agent to predict the changes of the climate trend in Δ2030s by gauged and ungauged stations. There were five predictors set have been selected to form the local climate at the region which provided by NCEP (validated) and CanESM2-RCP4.5 (projected). According to the statistical analyses, the SDSM was controlled to produce reliable validated results with lesser %MAE (<23%) and higher R. The projected rainfall was suspected to decrease 14% in Δ2030s. All the RCPs agreed the long term rainfall pattern was consistent to the historical with lower annual rainfall intensity. The RCP8.5 shows the least rainfall changes. These findings then used to compare the accuracy of monthly rainfall at control station (Stn 2). The GIS-Kriging method being as an interpolation agent was successfully to produce similar rainfall trend with the control station. The accuracy was estimated to reach 84%. Comparing between ungauged and gauged stations, the small %MAE in the projected monthly results between gauged and ungauged stations as a proved the integrated SDSM-GIS model can producing a reliable long-term rainfall generation at ungauged station.
    Matched MeSH terms: Geographic Information Systems
  10. Fulltext Accessibility and utilization patterns of a mobile medical clinic among vulnerable populations
    Gibson BA, Ghosh D, Morano JP, Altice FL
    Health Place, 2014 Jul;28:153-66.
    PMID: 24853039 DOI: 10.1016/j.healthplace.2014.04.008
    We mapped mobile medical clinic (MMC) clients for spatial distribution of their self-reported locations and travel behaviors to better understand health-seeking and utilization patterns of medically vulnerable populations in Connecticut. Contrary to distance decay literature, we found that a small but significant proportion of clients was traveling substantial distances to receive repeat care at the MMC. Of 8404 total clients, 90.2% lived within 5 miles of a MMC site, yet mean utilization was highest (5.3 visits per client) among those living 11-20 miles of MMCs, primarily for those with substance use disorders. Of clients making >20 visits, 15.0% traveled >10 miles, suggesting that a significant minority of clients traveled to MMC sites because of their need-specific healthcare services, which are not only free but available at an acceptable and accommodating environment. The findings of this study contribute to the important research on healthcare utilization among vulnerable population by focusing on broader dimensions of accessibility in a setting where both mobile and fixed healthcare services coexist.
    Matched MeSH terms: Geographic Information Systems
  11. Temporal and spatial mapping of hand, foot and mouth disease in Sarawak, Malaysia
    Sham NM, Krishnarajah I, Ibrahim NA, Lye MS
    Geospat Health, 2014 May;8(2):503-7.
    PMID: 24893027
    Hand, foot and mouth disease (HFMD) is endemic in Sarawak, Malaysia. In this study, a geographical information system (GIS) was used to investigate the relationship between the reported HFMD cases and the spatial patterns in 11 districts of Sarawak from 2006 to 2012. Within this 7-years period, the highest number of reported HFMD cases occurred in 2006, followed by 2012, 2008, 2009, 2007, 2010 and 2011, in descending order. However, while there was no significant distribution pattern or clustering in the first part of the study period (2006 to 2011) based on Moran's I statistic, spatial autocorrelation (P = 0.068) was observed in 2012.
    Matched MeSH terms: Geographic Information Systems
  12. Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches
    Ngui R, Shafie A, Chua KH, Mistam MS, Al-Mekhlafi HM, Sulaiman WW, et al.
    Geospat Health, 2014 May;8(2):365-76.
    PMID: 24893014
    Soil-transmitted helminth (STH) infections in Malaysia are still highly prevalent, especially in rural and remote communities. Complete estimations of the total disease burden in the country has not been performed, since available data are not easily accessible in the public domain. The current study utilised geographical information system (GIS) to collate and map the distribution of STH infections from available empirical survey data in Peninsular Malaysia, highlighting areas where information is lacking. The assembled database, comprising surveys conducted between 1970 and 2012 in 99 different locations, represents one of the most comprehensive compilations of STH infections in the country. It was found that the geographical distribution of STH varies considerably with no clear pattern across the surveyed locations. Our attempt to generate predictive risk maps of STH infections on the basis of ecological limits such as climate and other environmental factors shows that the prevalence of Ascaris lumbricoides is low along the western coast and the southern part of the country, whilst the prevalence is high in the central plains and in the North. In the present study, we demonstrate that GIS can play an important role in providing data for the implementation of sustainable and effective STH control programmes to policy-makers and authorities in charge.
    Matched MeSH terms: Geographic Information Systems
  13. A climate distribution model of malaria transmission in Sudan
    Musa MI, Shohaimi S, Hashim NR, Krishnarajah I
    Geospat Health, 2012 Nov;7(1):27-36.
    PMID: 23242678
    Malaria remains a major health problem in Sudan. With a population exceeding 39 million, there are around 7.5 million cases and 35,000 deaths every year. The predicted distribution of malaria derived from climate factors such as maximum and minimum temperatures, rainfall and relative humidity was compared with the actual number of malaria cases in Sudan for the period 2004 to 2010. The predictive calculations were done by fuzzy logic suitability (FLS) applied to the numerical distribution of malaria transmission based on the life cycle characteristics of the Anopheles mosquito accounting for the impact of climate factors on malaria transmission. This information is visualized as a series of maps (presented in video format) using a geographical information systems (GIS) approach. The climate factors were found to be suitable for malaria transmission in the period of May to October, whereas the actual case rates of malaria were high from June to November indicating a positive correlation. While comparisons between the prediction model for June and the case rate model for July did not show a high degree of association (18%), the results later in the year were better, reaching the highest level (55%) for October prediction and November case rate.
    Matched MeSH terms: Geographic Information Systems
  14. Risk mapping of dengue in Selangor and Kuala Lumpur, Malaysia
    Hassan H, Shohaimi S, Hashim NR
    Geospat Health, 2012 Nov;7(1):21-5.
    PMID: 23242677
    Dengue fever is a recurring public health problem afflicting thousands of Malaysians annually. In this paper, the risk map for dengue fever in the peninsular Malaysian states of Selangor and Kuala Lumpur was modelled based on co-kriging and geographical information systems. Using population density and rainfall as the model's only input factors, the area with the highest risk for dengue infection was given as Gombak and Petaling, two districts located on opposite sides of Kuala Lumpur city that was also included in the risk assessment. Comparison of the modelled risk map with the dengue case dataset of 2010, obtained from the Ministry of Health of Malaysia, confirmed that the highest number of cases had been found in an area centred on Kuala Lumpur as predicted our risk profiling.
    Matched MeSH terms: Geographic Information Systems
  15. Fulltext Development of a web-geographical information system application for plotting tuberculosis cases
    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*
  16. Fulltext Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia
    Khormi HM, Kumar L
    Geospat Health, 2016 11 21;11(3):416.
    PMID: 27903054 DOI: 10.4081/gh.2016.416
    We used the Model for Interdisciplinary Research on Climate-H climate model with the A2 Special Report on Emissions Scenarios for the years 2050 and 2100 and CLIMEX software for projections to illustrate the potential impact of climate change on the spatial distributions of malaria in China, India, Indochina, Indonesia, and The Philippines based on climate variables such as temperature, moisture, heat, cold and dryness. The model was calibrated using data from several knowledge domains, including geographical distribution records. The areas in which malaria has currently been detected are consistent with those showing high values of the ecoclimatic index in the CLIMEX model. The match between prediction and reality was found to be high. More than 90% of the observed malaria distribution points were associated with the currently known suitable climate conditions. Climate suitability for malaria is projected to decrease in India, southern Myanmar, southern Thailand, eastern Borneo, and the region bordering Cambodia, Malaysia and the Indonesian islands, while it is expected to increase in southern and south-eastern China and Taiwan. The climatic models for Anopheles mosquitoes presented here should be useful for malaria control, monitoring, and management, particularly considering these future climate scenarios.
    Matched MeSH terms: Geographic Information Systems
  17. Fulltext How does exposure to pesticides vary in space and time for residents living near to treated orchards?
    Wong HL, Garthwaite DG, Ramwell CT, Brown CD
    Environ Sci Pollut Res Int, 2017 Dec;24(34):26444-26461.
    PMID: 28948535 DOI: 10.1007/s11356-017-0064-5
    This study investigated changes over 25 years (1987-2012) in pesticide usage in orchards in England and Wales and associated changes to exposure and risk for resident pregnant women living 100 and 1000 m downwind of treated areas. A model was developed to estimate aggregated daily exposure to pesticides via inhaled vapour and indirect dermal contact with contaminated ground, whilst risk was expressed as a hazard quotient (HQ) based on estimated exposure and the no observed (adverse) effect level for reproductive and developmental effects. Results show the largest changes occurred between 1987 and 1996 with total pesticide usage reduced by ca. 25%, exposure per unit of pesticide applied slightly increased, and a reduction in risk per unit exposure by factors of 1.3 to 3. Thereafter, there were no consistent changes in use between 1996 and 2012, with an increase in number of applications to each crop balanced by a decrease in average application rate. Exposure per unit of pesticide applied decreased consistently over this period such that values in 2012 for this metric were 48-65% of those in 1987, and there were further smaller decreases in risk per unit exposure. All aggregated hazard quotients were two to three orders of magnitude smaller than one, despite the inherent simplifications of assuming co-occurrence of exposure to all pesticides and additivity of effects. Hazard quotients at 1000 m were 5 to 16 times smaller than those at 100 m. There were clear signals of the impact of regulatory intervention in improving the fate and hazard profiles of pesticides used in orchards in England and Wales over the period investigated.
    Matched MeSH terms: Geographic Information Systems
  18. An integrated assessment of seawater intrusion in a small tropical island using geophysical, geochemical, and geostatistical techniques
    Kura NU, Ramli MF, Ibrahim S, Sulaiman WN, Aris AZ
    Environ Sci Pollut Res Int, 2014;21(11):7047-64.
    PMID: 24532282 DOI: 10.1007/s11356-014-2598-0
    In this study, geophysics, geochemistry, and geostatistical techniques were integrated to assess seawater intrusion in Kapas Island due to its geological complexity and multiple contamination sources. Five resistivity profiles were measured using an electric resistivity technique. The results reveal very low resistivity <1 Ωm, suggesting either marine clay deposit or seawater intrusion or both along the majority of the resistivity images. As a result, geochemistry was further employed to verify the resistivity evidence. The Chadha and Stiff diagrams classify the island groundwater into Ca-HCO3, Ca-Na-HCO3, Na-HCO3, and Na-Cl water types, with Ca-HCO3 as the dominant. The Mg(2+)/Mg(2+)+Ca(2+), HCO3 (-)/anion, Cl(-)/HCO3 (-), Na(+)/Cl(-), and SO4 (2-)/Cl(-) ratios show that some sampling sites are affected by seawater intrusion; these sampling sites fall within the same areas that show low-resistivity values. The resulting ratios and resistivity values were then used in the geographical information system (GIS) environment to create the geostatistical map of individual indicators. These maps were then overlaid to create the final map showing seawater-affected areas. The final map successfully delineates the area that is actually undergoing seawater intrusion. The proposed technique is not area specific, and hence, it can work in any place with similar completed characteristics or under the influence of multiple contaminants so as to distinguish the area that is truly affected by any targeted pollutants from the rest. This information would provide managers and policy makers with the knowledge of the current situation and will serve as a guide and standard in water research for sustainable management plan.
    Matched MeSH terms: Geographic Information Systems
  19. GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms
    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
  20. Site suitability analysis for sanitary landfills using geospatial methods in a part of southern Peninsular Malaysia
    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
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