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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.

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.

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.

This study proposes an integrated Geographic Information System (GIS)Fuzzy Multi-Criteria Decision Making (F-MCDM)model to assess the impacts of flood on residential property prices. Triangular Fuzzy numbers was implemented to address limitationssuch as uncertainty, bias and ambiguity inherent in the conventional Analytic Network Process (ANP) flood model criteria ranking thereby improving the accuracy and reliability of the susceptibility model. The developed Fuzzy-ANP's (F-ANP) pair-wise comparison technique was used to rankthe relative importance of nine flood conditioning criteria based on experts' input. Utilizing GIS and re-mote sensing data and techniques on Kelantan, a perennially flooded state in Malaysia, FANP based criterion maps weregenerated and aggregated to produce flood susceptibility maps of the area, showing the flood vulnerability levels of different locations. A 10-year inventory of real estate prices from the National Property Information Centre (NAPIC), Malaysia was analyzed to investigate the trend in market prices of residential properties situated in the high flood probable zones highlighted by the spatial F-ANP model. Model validation results showed that 59.42% and 36.23% of past flood events fall within the very high and high susceptible locations ofthe susceptibility map respectively, confirming its high accuracy. A weak positive correlation also exists between the highly susceptible flood class and housing locations vs market prices. We conclude that the ensemble GIS-FANP flood susceptibility modelcan produce maps capable of conveying accurate risk information to a broad range of stakeholders thereby facilitating decision making. However, other factors such as supply and demand, construction cost, macro-economy and micro-economy tend to also exert some influence on real estate prices, together with location in hazard-prone areas. [ABSTRACT FROM AUTHOR]

Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications. [ABSTRACT FROM AUTHOR]

In this paper, optimum routing was developed based on the travel salesman method and integrated in Arclnfo GIS using linear programming. The results of the optimized travel distances and times for residential waste collection and routing to disposal site were used to calculate the number and type of required track collection, labour requirement, costing of waste collection and to determine the overall solid waste management efficiency through waste management operation research methods. The objective of the study was to optimize residential collection and hauling to disposal site through operation cost minimization for Petaling Jaya Municipality in the state of Selangor, Malaysia. The study determined that with optimized routes and recycling possibilities, the total cost of waste collections could be reduced from RM90,372 to RM20,967, with a reduction of 76.8%. It was also revealed that optimum routes might not necessarily be the shortest distance from point A to point B as travel time maybe high on short distances due to traffic congestion and the presence of many traffic lights. Techniques and methods developed using general GIS have proven effective in route optimization and allowed management of data to suit local conditions and limitations of waste management for the studied area. Thus, scenarios of travel distances, time and waste quantity value generated from the GIS enabled appropriate determination of the number of waste trucks and labour requirements for the operation and the overall calculation of costs of waste management based on the operation research methods used in the study. [ABSTRACT FROM AUTHOR]

In this study a GIS model was developed and spatial analytical techniques performed to identify and select a suitable location for a waste transfer station in the sprawling suburban town of Petaling Jaya. The lack of a transfer station in urban centres of Malaysia has caused many problems and affects the efficiency of waste collection and disposal. With diminishing space for landfills and the increasing cost of solid waste management, the need for urban solid-waste recycling has become very important. However, finding a place for waste to be efficiently sorted before unwanted waste can be carried to disposal landfills has social and physical constraints. This study applies GIS techniques and analysis for site selection and identifies an acceptable area. In the model, environmental, physical and social constraints were taken into account, resulting in the selection of a potential area that is acceptable to the residents of the area because it is out of range of causing public nuisance and within minimum travelling distance for collection vehicles. The results show that the potential location for the transfer station should be in proximity of the industrial area of Petaling Jaya, allowing for the possible sale of recyclable materials to local industries. The location is also sited near a major highway to allow quick transportation of the rest of the unwanted waste to the landfill. [ABSTRACT FROM AUTHOR]

This paper summarizes the findings of the maximum flood prone area mapping at Kelantan river basin, Malaysia, using multiple logistic regression model with the aid of GIS tools and remote sensing data. To map the maximum flood prone areas, at first the flood extent areas were extracted from RADARSAT 1 images and supported with ground data, existing reports and field notes. To evaluate the factors associated with flood prone areas, a spatial database was constructed from a topographical map, geological map, hydrological map, Global Positioning System (GPS) data, land cover map, SPOTS satellite image, digital elevation model (DEM), and precipitation data. Nine major parameters were extracted for the logistic regression analysis to determine each factor's rating, and the ratings were computed for flood prone area mapping analysis. Results indicate that flood prone area mapping which can be termed as susceptibility map can be performed at 1:25,000 which is comparable to some conventional medium scaled flood hazard map. The flood prone areas delineated on these map correspond to areas that would be inundated by significant flooding (approximately the 100 year flood). Qualitatively, the model seems to give reasonable results with accuracy observed was 84%. [ABSTRACT FROM AUTHOR]

Land use changes over the period I 978 to 1992 and 1992 to 2004 and geomorphometric characteristics (hypsometric curve, hypsometric integral, drainage density and length of overland flow) were investigated to analyse the susceptibility of Galaundu and Pokhare Khola watersheds, Dhading district, mid-mountain region of Nepal to surface erosion and soil degradation. The study used air photo interpretation of 1978 and 1992 and remote sensing imagery (Landsat TM of 2002) interpretation and hypsometric analyses using geographic information system (GIS) techniques. Land use change analyses show a decrease mainly in rainfed upland (Ban) and forest but an increase in irrigated paddy land (Khet) and shrub during the period 1978 and 1992. Increase in Khet and shrub land and continued decrease in Ban, mainly due to conversion to Khet have been observed during 1992 to 2004. Hypsometric curves and integrals were found to be concave in shape and of low values (0.48 and 0.50 for Galaundu and Pokhare respectively) indicating that both watersheds are at the deteriorating stage. Drainage densities of 5. I and 5.14 for Galaundu and Pokhare respectively are low with corresponding values of long lengths of overland flow (98 and 97 m) which make both watersheds vulnerable to soil erosion and land degradation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Geochemical signature of copper deposits using stream sediment data. • Factor analysis to determine geochemical prospectivity index (GPMI). • The geographic information system is used to define the spatial distribution of the anomalies. • Evaluation of potential mineral resources at the scale of the Anti-Atlas. The present work aims to identify the geochemical signatures of copper deposits in the Igherm area (Anti-Atlas, Morocco) using stream sediment data. We applied factor analysis on the data normalized by log transformation. This approach identified three geochemical data associations (F1, F2, and F3) which were then used to calculate the values of the geochemical prospectivity index (GPMI). The results indicated that the large GMPI Cu values correlate strongly with the surface indices. A concentration-surface (C-A) fractal classification was applied to separate the geochemical anomalies from the regional background. To recognize and geo-position the significant geochemical signatures of the deposit, we applied the prediction zone (P-A) plot. A geographic information system (GIS) was used to define the spatial distribution of the anomalies at the sub-watershed level. The results represent the first approach to evaluating potential mineral resources at the scale of the Anti-Atlas: 90% of the anomalous sub-catchments mapped are located along the Precambrian-Cambrian transition (Base Series), 67% are traversed by major tectonic faults, and 40% contain copper showings and/or deposits. The remaining 60% are devoid of any visible surface copper occurrences. They constitute promising areas for future exploration of Cu deposits hidden under the Cambrian cover. [ABSTRACT FROM AUTHOR]