Displaying publications 61 - 80 of 118 in total

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  1. Lee, Yi Yi, Narimah Samat, Wan Manan Wan Muda
    Malays J Nutr, 2017;23(3):397-408.
    MyJurnal
    Introduction: Physical activity has been shown to be beneficial for the prevention of
    obesity and non-communicable diseases. Our contemporary way of life that is technology
    dependent has significantly reduced physical activity. This study aimed to determine
    accelerometer-measured physical activity (moderate-to-vigorous physical activity (MVPA))
    among adults in high and low walkability neighbourhoods in Penang and Kota Bharu,
    Malaysia.

    Methods: Participants (n=490) were sampled using multistage sampling method
    from neighbourhoods with varied levels of walkability using Geographical Information
    System (GIS). Physical activity was measured objectively using Actigraph GT3X+
    accelerometers, worn by the participants on their waists for a period of 5 to 7 days.

    Results:
    The participants had a mean of 13.5 min/day of MVPA. Total MVPA was significantly
    higher among participants in high walkability neighbourhoods (19.7 min/day vs. 9.1 min/
    day). Results from t-test showed that the time spent on MVPA per day was significantly
    lower among participants residing in low walkability neighbourhoods. The final model
    of the MIXED model statistical tests showed that total MVPA was significantly associated
    with BMI, but not with WC measurements, after adjusting for covariates.

    Conclusion: Most
    of the participants had very low MVPA and did not achieve the current physical activity
    recommendations, implying that Malaysian adults residing in these two cities were not
    physically active to achieve health benefits. Results are suggestive of the importance of the
    walkability concept in neighbourhoods in encouraging physical activity and healthy body
    weight among Malaysians.
    Matched MeSH terms: Geographic Information Systems
  2. 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
  3. Liu Yang, Xue Bai, Yinjie Hu, Qiqi Wang, Jun Deng
    Sains Malaysiana, 2017;46:2195-2204.
    The combination of geographic information system and mineral energy data management is helpful to promote the study of mineral energy and its ecological damage and environmental pollution caused by its development and utilization, which has important application value. The Trace Elements in Coal of China Database Management System (TECC) is established in this paper, applying the techniques of B/S three-layer structure, Oracle database, AJAX and WebGIS. TECC is the first database system which aims at managing the data of trace elements in coal in China. It includes data management and analysis module, document management module, trace elements in coal data maintenance module and authority management module. The data entry specification is put forward in the present study and the spatial data is included in TECC system. The system achieves the functions of data query, analysis, management, maintenance and map browsing, thematic map drawing as well as satellite video display, which lay the foundation for the analysis of large data of trace elements in coal. It is a practical platform for the acquisition, management, exchange and sharing of trace element research and geochemical research data of coal.
    Matched MeSH terms: Geographic Information Systems
  4. Loh, Kok Fook, Ponusamy, Ragu, Shattri Mansor, Jamil Ismail
    MyJurnal
    Malaysia is in the process of modernizing its oil palm plantation management, by implementing geo-information technologies which include Remote Sensing (RS), Geographic Information System (GIS), and Spatial Decision Support System (DSS). Agencies with large oil palm plantations such as the Federal Land Development Authority (FELDA), Federal Land Consolidation and Rehabilitation Authority (FELCRA), Guthrie Sdn. Bhd., and Golden Hope Sdn. Bhd. have already incorporated GIS in their plantation management, with limited use of RS and DSS. In 2005, FELCRA, Universiti Putra Malaysia (UPM) and Espatial Resources Sdn. Bhd. (ESR) collaborated in a research project to explore the potentials of geo-informatics for oil palm plantation management. The research was conducted in FELCRA located in Seberang Perak Oil Palm Scheme. In that research, a tool integrating RS, GIS and Analytical Hierarchy Process (AHP) was developed to support decision making for replanting of the existing old palms. RS was used to extract productive stand per hectare; AHP was used to compute the criteria weights for the development of a suitable model; and GIS was used for spatial modelling so as to generate the decision support layer for replanting. This paper highlights the approach adopted in developing the tool with special emphasis on the AHP computation.
    Matched MeSH terms: Geographic Information Systems
  5. M. Hamid Ch, M. Ashraf, Qudsia Hamid, Syed Mansoor Sarwar, Zulfiqar Ahmad Saqib
    Sains Malaysiana, 2017;46:413-420.
    Remote Sensing (RS) and Geographical Information Systems (GIS) are widely used for change detection in rivers caused
    by erosion and accretion. Digital image processing techniques and GIS analysis capabilities are used for detecting
    temporal variations of erosion and accretion characteristics between the years 1999 and 2011 in a 40 km long Marala
    Alexandria reach of River Chenab. Landsat satellite images for the years 1999, 2007 and 2011 were processed to analyze
    the river channel migration, changes in the river width and the rate of erosion and accretion. Analyses showed that the
    right bank was under erosion in both time spans, however high rate of deposition is exhibited in middle reaches. The
    maximum erosion was 1569843 m2
    and 1486160 m2
    along the right bank at a distance of 24-28 km downstream of the
    Marala barrage in the time span of 1999-2007 and 2007-2011, respectively. Along right bank mainly there is trend of
    accretion but erosion is much greater between 20 and 28 km reach. Maximum accretion was 5144584 m2
    from 1999-2007
    and 2950110 m2
    from 2007-2011 on the right bank downstream of the Marala Barrage. The derived results of channel
    migration were validated by comparing with SRTM data to assess the accuracy of image classification. Integration of remote
    sensing data with GIS is efficient and economical technique to assess land losses and channel changes in large rivers.
    Matched MeSH terms: Geographic Information Systems
  6. 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*
  7. 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
  8. Mogaji KA, Lim HS
    Environ Monit Assess, 2017 Jul;189(7):321.
    PMID: 28593561 DOI: 10.1007/s10661-017-5990-7
    This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.
    Matched MeSH terms: Geographic Information Systems*
  9. Mohamad N, Abdul Khanan MF, Ahmad A, Md Din AH, Shahabi H
    Sensors (Basel), 2019 Aug 31;19(17).
    PMID: 31480412 DOI: 10.3390/s19173778
    Evaluating water level changes at intertidal zones is complicated because of dynamic tidal inundation. However, water level changes during different tidal phases could be evaluated using a digital surface model (DSM) captured by unmanned aerial vehicle (UAV) with higher vertical accuracy provided by a Global Navigation Satellite System (GNSS). Image acquisition using a multirotor UAV and vertical data collection from GNSS survey were conducted at Kilim River, Langkawi Island, Kedah, Malaysia during two different tidal phases, at high and low tides. Using the Structure from Motion (SFM) algorithm, a DSM and orthomosaics were produced as the main sources of data analysis. GNSS provided horizontal and vertical geo-referencing for both the DSM and orthomosaics during post-processing after field observation at the study area. The DSM vertical accuracy against the tidal data from a tide gauge was about 12.6 cm (0.126 m) for high tide and 34.5 cm (0.345 m) for low tide. Hence, the vertical accuracy of the DSM height is still within a tolerance of ±0.5 m (with GNSS positioning data). These results open new opportunities to explore more validation methods for water level changes using various aerial platforms besides Light Detection and Ranging (LiDAR) and tidal data in the future.
    Matched MeSH terms: Geographic Information Systems
  10. Mohamad Naim Mohamad Rasidi, Mazrura Sahani, Hidayatulfathi Othman, Rozita Hod, Shaharudin Idrus, Zainudin Mohd Ali, et al.
    Sains Malaysiana, 2013;42:1073-1080.
    Penyakit denggi merupakan penyakit bawaan vektor yang menjadi salah satu ancaman utama kesihatan awam di Malaysia. Pemetaan taburan kes denggi daripada aspek reruang-masa boleh menjadi kaedah yang berguna dalam menilai risiko denggi kepada masyarakat. Kajian ini bertujuan untuk memetakan taburan reruang dan reruang-masa kes-kes denggi di dalam daerah Seremban, dijalankan dengan Sistem Maklumat Geografi (GIS) khususnya analisis reruang dan reruang-masa. Analisis taburan reruang menggunakan Indeks Moran, purata kejiranan terdekat (ANN) dan anggaran kepadatan Kernel. Analisis reruang-masa ditentukan dengan indeks kekerapan, jangka masa dan intensiti untuk mengenal pasti kawasan berisiko denggi mengikut masa. Sejumlah 6076 kes denggi dicatatkan di Pejabat Kesihatan Daerah Seremban dari tahun 2003 hingga 2009. Kadar insiden denggi adalah tinggi pada tahun 2003, 2008 dan 2009 dengan nisbah denggi : denggi berdarah adalah 21.6:1. Indeks Moran menunjukkan kes denggi berlaku dalam pengelompokan dengan skor Z adalah 16.384 (p=0.000). Analisis ANN dengan 0.264 (p= 0.000) dengan purata jarak insiden antara kes denggi di dalam kawasan kejiranan adalah 55 m. Anggaran kepadatan Kernel menunjukkan lokasi kawasan panas kes denggi tertumpu di Nilai dan Ampangan. Analisis reruang masa dengan purata nilai tertinggi indeks kekerapan, jangka masa dan intensiti masing-masing melebihi 0.023, 0.614 dan 0.657 di kawasan berisiko tinggi denggi di Nilai, Seremban dan Ampangan. Pengawalan denggi perlu diberi tumpuan kepada kawasan berisiko tinggi ini.
    Matched MeSH terms: Geographic Information Systems
  11. Mohamed M. GahGah, Juhari Mat Akhir, Abdul Ghani M. Rafek, Ibrahim Abdullah
    Sains Malaysiana, 2009;38(6):827-833.
    The aim of this study is to investigate the factors that cause landslides in the area along the new road between Cameron Highlands and Gua Musang. Landslide factors such as lineaments have been extracted from remote sensing data (Landsat TM image) using ERDAS software. A soil map has been produced using field work and laboratory analysis, and the lithology, roads, drainage pattern and rainfall have been digitized using ILWIS software together with the slope angle and elevation from the Digital Elevation Model (DEM). All these parameters, which are vital for landslide hazard assessment, have been integrated into the geographical information system (GIS) for further data processing. Weightage for these landslide relevant factors related to their influence in landslide occurrence using the heuristic method has been carried out. The results from this combination through a modified ‘index overlay with multi class maps’ model was used to produce a landslide hazard zonation map. Five classes of potential landslide hazard have been derived as the following: very low hazard zone 17.27%, low hazard zone 39.35%, medium hazard zone 25.1%, high hazard zone 15.35% and very high hazard zone 2.93%. The results from this work have been checked through the landslide inventory using available aerial photos interpretation and field work, and show that the slope and elevation have the most direct affect on landslide occurrence.
    Matched MeSH terms: Geographic Information Systems
  12. 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
  13. Mohammed Aliyu Modibbo, Mohammed Arif Shahidah, Isah Funtua Abdulkadir, Umar Wali
    MyJurnal
    This paper has evaluated the spatial growth of Bauchi Metropolis from 1976 to 2015
    through the application of Remote Sensing and GIS techniques. Various satellite
    imageries of the metropolis (Landsat MSS of 1976, TM of 1986, 1996 and ETM+ of 2006
    and 2015) were integrated; processed and classified using ERDAS imagine 9.1. The
    results showed an increase in area from 11.68km2
    in 1976 to 12.51km2
    in 1986 to
    32.44km2 in 1996, to 49.66km2
    in 2006 and finally to 89.23km2 in 2015. It is
    recommended that government should provide the required capacities for the use of
    Remote Sensing and GIS in planning for the growth of the town.
    Matched MeSH terms: Geographic Information Systems
  14. 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*
  15. Mohd Dini Hairi Suliman, Mastura Mahmud
    Sains Malaysiana, 2013;42:579-586.
    Kejadian kebakaran hutan yang memberikan implikasi negatif terhadap ekosistem hutan, kepelbagaian biologi, kualiti udara dan struktur tanah dapat dikurangkan melalui sistem pengurusan bencana yang berkesan. Mekanisme pengurusan bencana dapat dibangunkan melalui sistem amaran awal yang tepat serta sistem penyampaian maklumat yang cekap. Penyelidikan ini cuba memberi tumpuan kepada pemetaan potensi kebakaran hutan serta penyampaian maklumat kepada
    pengguna melalui aplikasi WebGIS. Teknologi georuang dan permodelan matematik digunakan bagi mengenal pasti, mengelas serta memetakan kawasan hutan yang berpotensi untuk terbakar. Permodelan model proses analitik hierarki (AHP) serta teknologi georuang yang merangkumi penderiaan jauh, sistem maklumat geografi (GIS) dan pengumpulan data lapangan secara digital telah digunakan untuk negeri Selangor. AHP adalah suatu teknik yang dapat memodel sesuatu
    keputusan yang meliputi objektif menyeluruh, dalam kajian ini untuk mencari kawasan yang berpotensi berlakunya kebakaran hutan. Tiga kriteria iaitu bahan bakar, bentuk topografi dan faktor manusia telah dipilih untuk membina satu reka bentuk hierarki berstruktur yang setiapnya diberikan pemberat. Kemudian hierarki ini dianalisis melalui satu siri perbandingan berpasangan yang diproses secara matematik dan keutamaan diberikan kepada kedudukan yang tinggi untuk mencapai hasil sumbangan pakar yang terlibat secara langsung dengan operasi pemadaman kebakaran hutan
    yang terdiri daripada pegawai Jabatan Bomba dan Penyelamat Malaysia juga dinilai dalam model ini. Hasil kajian mendapati 65% daripada keseluruhan Selangor berpotensi rendah untuk terbakar sementara kawasan seluas 32.83 km persegi iaitu di Bestari Jaya, Ulu Tinggi dan Kuala Langat berpotensi melampau terbakar. Paparan maklumat melalui aplikasi WebGIS ini merupakan satu pendekatan terbaik bagi membantu proses membuat keputusan pada tahap keyakinan yang tinggi dan hampir menyamai keadaan sebenar. Agensi yang terlibat dalam pengurusan bencana
    seperti Jawatankuasa Pengurusan dan Bantuan Bencana (JPBB) Daerah, Negeri dan Pusat serta Jabatan Bomba dan Penyelamat Malaysia dapat menggunakan hasil akhir kajian ini sebagai persediaan menghadapi ancaman kebakaran hutan pada masa akan datang.
    Matched MeSH terms: Geographic Information Systems
  16. Mohd Muzammil Salahuddin, Zulfa Hanan Ashaari
    MyJurnal
    The use of remote sensing in detecting aerosol or air pollution is not widely applied in Malaysia. The large area of coverage provided by remote sensing satellite may well be the solution to the lack of spatial coverage by the local ground air quality monitoring stations. This article discusses the application of remote sensing instruments in air quality monitoring of Malaysia. The remote sensing data is validated using ground truths either from local ground air monitoring stations or the Aerosol Robotic Network (AERONET). The correlation between remote sensing is relatively good with R from 0.5 to 0.9 depending on the satellite used. The correlation is much improved using the mixed effects algorithm applied on MODIS Aerosol Optical Depth (AOD) data. Accuracy of predicted air quality data by remote sensing is generally tested using the Root Mean Squared Error (RMSE) against the ground truths data. Besides the Geographic Information System (GIS) tools are used in manipulating the data from both remote sensing and ground stations so as to produce meaningful results such as spatio-temporal pattern mapping of air pollution. Overall the results showed that the application of remote sensing instruments in air quality monitoring in Malaysia is very useful and can be improved further.
    Matched MeSH terms: Geographic Information Systems
  17. 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*
  18. 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
  19. 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
  20. 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
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