In Malaysia, the incidence of Dengue Fever (DF) and Dengue Hemorrhagic Fever (DHF) have risen dramatically in the last twenty years. With the use of Geographical Information System an explanation for the spread and control of these diseases can be obtained. This study aims to develop a spatial modeling that can predict the risks for DF and DHF based on environmental factors such as physical surroundings, land use, rainfall, temperature and GIS application using logistic regression. A total of 16 variables were used in the process of spatial modeling development. At the significant level of 0.05, the results of logistic regression showed that only 10 out of 16 significant variables in the modeling process. The accuracy of the resulting model is 70.3%. A crucial feature of this study is a risk area map for incidence of DF and DHF in the study area. This study also highlights the application of spatial analysis in planning and implementing the process for the prevention and control activities of DF and DHF in Malaysia.
Matched MeSH terms: Geographic Information Systems
This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.
Matched MeSH terms: Geographic Information Systems
An innovative health information system can be used to support the control of tuberculosis (TB) in Malaysia. The existing system of MyTB has helped in the national TB information management and decision-making process. However, the system can be further enhanced by producing a prototype of Geospatial Tuberculosis Information System (GeoTBiS). It is a geospatial decision support system that was initially proposed in Shah Alam, Selangor. Geospatial data has spatio-temporal characteristics that can be used to understand the basic elements of TB aetiology, while geospatial operations are employed to collect, manage and disseminate the data in a geographical information system (GIS) environment. The disease map and epidemiological risk analysis are produced using a global positioning system (GPS), satellite imagery, geostatistical analysis and web mapping services. This GeoTBiS has demonstrated the geospatial capabilities in enhancing the current system functions, and several recommendations towards a practicable application.
Matched MeSH terms: Geographic Information Systems
Spatio-temporal land-use change modeling, simulation, and prediction have become one of the critical issues in the last three decades due to uncertainty, structure, flexibility, accuracy, the ability for improvement, and the capability for integration of available models. Therefore, many types of models such as dynamic, statistical, and machine learning (ML) models have been used in the geographic information system (GIS) environment to fulfill the high-performance requirements of land-use modeling. This paper provides a literature review on models for modeling, simulating, and predicting land-use change to determine the best approach that can realistically simulate land-use changes. Therefore, the general characteristics of conventional and ML models for land-use change are described, and the different techniques used in the design of these models are classified. The strengths and weaknesses of the various dynamic, statistical, and ML models are determined according to the analysis and discussion of the characteristics of these models. The results of the review confirm that ML models are the most powerful models for simulating land-use change because they can include all driving forces of land-use change in the simulation process and simulate linear and non-linear phenomena, which dynamic models and statistical models are unable to do. However, ML models also have limitations. For instance, some ML models are complex, the simulation rules cannot be changed, and it is difficult to understand how ML models work in a system. However, this can be solved via the use of programming languages such as Python, which in turn improve the simulation capabilities of the ML models.
Matched MeSH terms: Geographic Information Systems
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
Previous studies have found positive correlations between mangrove forest extent and fisheries yield but none of these univariate relationships provide a reliable estimate of yield from mangrove area. This study tests the hypothesis that the nursery ground value or natural production of fish and shrimps is related to the hydrogeomorphology settings of mangrove forests by using multivariate redundancy analysis (RDA). The hydrogeomorphological metrics of five mangrove forests imaged by satellite were measured using Geographical Information System (GIS). The RDA indicated that the metrics, including mangrove area, multiple waterways and creeks, mangrove-river interface, waterway surface area and sediment organic matter, influenced the diversity and abundance of fish and shrimps. Larger values of these metrics increase the abundance of economically important fish species of the families Lutjanidae, Haemulidae, Serranidae and economically-important penaeid shrimps. Sediment organic matter also significantly correlates with the distribution and abundance of fish that feed off the bottom such as the Leiognathidae, Clupeidae and Mullidae. Mangrove forests with combinations of large mangrove area, river surface area, high stream ordering and longest mangrove-river interface will provide greater role as nursery grounds for fish and shrimps.
Matched MeSH terms: Geographic Information Systems
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
The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
Matched MeSH terms: Geographic Information Systems
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
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
Managing tropical rain forests is difficult because few long-term field data on forest growth and the impact of harvesting disturbance are available. Growth models may provide a valuable tool for managers of tropical forests, particularly if applied to the extended forest areas of up to 100,000 ha that typically constitute the so-called forest management units (FMUs). We used a stand growth model in a geographic information system (GIS) environment to simulate tropical rain forest growth at the FMU level. We applied the process-based rain forest growth model Formix 3-Q to the 55,000 ha Deramakot Forest Reserve (DFR) in Sabah, Malaysia. The FMU was considered to be composed of single and independent small-scale stands differing in site conditions and forest structure. Field data, which were analyzed with a GIS, comprised a terrestrial forest inventory, site and soil analyses (water, nutrients, slope), the interpretation of aerial photographs of the present vegetation and topographic maps. Different stand types were determined based on a classification of site quality (three classes), slopes (four classes), and present forest structure (four strata). The effects of site quality on tree allometry (height-diameter curve, biomass allometry, leaf area) and growth (increment size) are incorporated into Formix 3-Q. We derived allometric relations and growth factors for different site conditions from the field data. Climax forest structure at the stand level was shown to depend strongly on site conditions. Simulated successional pattern and climax structure were compared with field observations. Based on the current management plan for the DFR, harvesting scenarios were simulated for stands on different sites. The effects of harvesting guidelines on forest structure and the implications for sustainable forest management at Deramakot were analyzed. Based on the stand types and GIS analysis, we also simulated undisturbed regeneration of the logged-over forest in the DFR at the FMU level. The simulations predict slow recovery rates, and regeneration times far exceeding 100 years.
Matched MeSH terms: Geographic Information Systems
This paper presents a compact sized inset-fed rectangular microstrip patch antenna embedded with double-P slots. The proposed antenna has been designed and fabricated on ceramic-PTFE composite material substrate of high dielectric constant value. The measurement results from the fabricated prototype of the antenna show -10 dB reflection coefficient bandwidths of 200 MHz and 300 MHz with center resonant frequency of 1.5 GHz and 4 GHz, respectively. The fabricated antenna has attained gains of 3.52 dBi with 81% radiation efficiency and 5.72 dBi with 87% radiation efficiency for lower band and upper band, respectively. The measured E- and H-plane radiation patterns are also presented for better understanding. Good agreement between the simulation and measurement results and consistent radiation patterns make the proposed antenna suitable for GPS and C-band applications.
Matched MeSH terms: Geographic Information Systems/instrumentation*
Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.
Matched MeSH terms: Geographic Information Systems/standards*
The process of land use change and urban sprawl has been considered as a prominent characteristic of urban development. This study aims to investigate urban growth process in Bandar Abbas city, Iran, focusing on urban sprawl and land use change during 1956-2012. To calculate urban sprawl and land use changes, aerial photos and satellite images are utilized in different time spans. The results demonstrate that urban region area has changed from 403.77 to 4959.59 hectares between 1956 and 2012. Moreover, the population has increased more than 30 times in last six decades. The major part of population growth is related to migration from other parts the country to Bandar Abbas city. Considering the speed of urban sprawl growth rate, the scale and the role of the city have changed from medium and regional to large scale and transregional. Due to natural and structural limitations, more than 80% of barren lands, stone cliffs, beach zone, and agricultural lands are occupied by built-up areas. Our results revealed that the irregular expansion of Bandar Abbas city must be controlled so that sustainable development could be achieved.
Matched MeSH terms: Geographic Information Systems/statistics & numerical data*
In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.
Matched MeSH terms: Geographic Information Systems*
This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.
Matched MeSH terms: Geographic Information Systems/economics
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*
Nowadays, one of the most important challenges in heterogeneous networks is the connection consistency between the mobile station and the base stations. Furthermore, along the roaming process between the mobile station and the base station, the system performance degrades significantly due to the interferences from neighboring base stations, handovers to inaccurate base station and inappropriate technology selection. In this paper, several algorithms are proposed to improve mobile station performance and seamless mobility across the long-term evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) technologies, along with a minimum number of redundant handovers. Firstly, the enhanced global positioning system (GPS) and the novel received signal strength (RSS) prediction approaches are suggested to predict the target base station accurately. Then, the multiple criteria with two thresholds algorithm is proposed to prioritize the selection between LTE and WiMAX as the target technology. In addition, this study also covers the intercell and cochannel interference reduction by adjusting the frequency reuse ratio 3 (FRR3) to work with LTE and WiMAX. The obtained results demonstrate high next base station prediction efficiency and high accuracy for both horizontal and vertical handovers. Moreover, the received signal strength is kept at levels higher than the threshold, while maintaining low connection cost and delay within acceptable levels. In order to highlight the combination of the proposed algorithms' performance, it is compared with the existing RSS and multiple criteria handover decision algorithms.
Matched MeSH terms: Geographic Information Systems
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
Bukit Merah Reservoir is the main potable and irrigation water source for Kerian District, Perak State, Malaysia. For the past two decades, the reservoir has experienced water stress. Land-use activities have been identified as the contributor of the sedimentation. The Soil and Water Assessment Tool (SWAT) was used to simulate and quantify the impacts of land-use change in the reservoir watershed. The SWAT was calibrated and two scenarios were constructed representing projected land use in the year 2015 and hypothetical land use to represent extensive land-use change in the catchment area. The simulation results based on 17 years of rainfall records indicate that average water quantity will not be significantly affected but the ground water storage will decrease and suspended sediment will increase. Ground water decrease and sediment yield increase will exacerbate the Bukit Merah Reservoir operation problem.
Matched MeSH terms: Geographic Information Systems