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Development of hilly areas requiring deforestation and increased human activities has raised many environmental issues in the world. This paper presents the results of investigation to assess the parameters that contribute to the risk to environment by reviewing available reports from Penang Island and surrounding areas. Nine parameters were identified that mostly contribute to the environmental risk. These are casualties of people, soil properties, earth coverage, soil grading characteristics, land use suitability, factor of safety, blasting area, distance between proposed structure to slope and geometry of slope. From these parameters, the rated risk approaches were proposed based on the prediction of occurrences of environmental issues. The rated risks were categorised from very high (5) to very low (1) with high, medium and low in between. The assessments were reviewed and evaluated based on rated risk for the chosen parameters. A map was developed identifying areas of environmental risk. The map can be used to quantify risk to the environment based on the parameters due to the proposed development. The overall result shows that areas PD3 of Tanjung Bungah and PD3, PD8 and PD9 of Paya Terubong have high-rated risk. No development area is classified as very high risk and very low-risk areas. These rating approaches can be used to develop potential risk zoning of proposed development areas. From this zoning guideline or standard, the viability of any proposed development can be measured. [ABSTRACT FROM AUTHOR]

This paper focuses on the observation and behaviours of green turtles for one breeding season at Penang Island. Green turtle breeding behaviours and morphological characteristics were studied at Pantai Kerachut and Teluk Kampi, situated at Penang Island, the northern island of Peninsular Malaysia between December 2012 and August 2013. The findings revealed that from the eight green turtles landed; 106 were emergences, 38 were nests, and 158 digging attempts were made over the duration of one breeding season. The total clutch size deposited ranged from 170 to 979 eggs per turtle, and total nests ranged from three to eight nests per turtle. The inter-nesting interval ranged from 9 to 29 days, and the average was 13.5 days. Longer inter-nesting intervals were due to disturbances from feral dogs, wild pigs, sea-coated otters and night activities of fishermen (use of wide torch lights, sounds of boat engines) especially at Teluk Kampi. Lack of full-time personnel to control at Teluk Kampi was found to be a cause to nest poaching. Based on these findings and observation, the study suggests that Kerachut Turtle Conservation Centre should hire sufficient staffs to patrol the two beaches in order to prevent from human poachers and animal disturbances. [ABSTRACT FROM AUTHOR]

The primary objective of this paper is to identify tourists' perception toward boutique hotel attractive attributes through the detection of those factors that drive guests to this special type of accommodation. Furthermore, this study attempts to find the underlying dimensions of attractive attributes of boutique hotel from tourist after actual experience of this type of accommodation. The empirical study is supported through data from a sample of 133 individuals who stayed in Penang Island boutique hotels. The findings show that hotel guests' perceptions of boutique hotels characteristics have four dimensions, namely: special services, room features, convenient and hotel design. However, results revealed that boutique hotels attractive elements after the actual experience of tourists have four slightly different dimensions special services, hotel facilities, price and location, and hotel design and image. From findings of this research practical suggestions are made to help hotel operators and those wishing and willing to enter the market. Furthermore, this study can help marketers gain substantial insight in order to market and promote this particular segment of the accommodation industry. [ABSTRACT FROM AUTHOR]

The Green Turtle (Chelonia mydas) and Olive Ridley Turtle (Lepidochelys olivacea) are the only sea turtles with recorded landings in the Pulau Pinang coastal area. The Green Turtle has been the most abundant and widely distributed sea turtle in this area since it was first surveyed in 1995. Statistical analysis by the Pulau Pinang Department of Fisheries on the distribution of sea turtles from 2001 through 2009 has identified Pantai Kerachut and Telok Kampi as the most strongly preferred beaches for Green Turtle landings, with records for almost every month in every year. Green Turtle tracks and nests have also been found along the coast of Pulau Pinang at Batu Ferringhi, Tanjong Bungah, Pantai Medan, Pantai Belanda, Telok Kumbar, Gertak Sanggul, Moonlight Beach, Telok Duyung, Telok Aling, Telok Bahang and Telok Katapang. The Olive Ridley Turtle is present in smaller numbers; landing and nesting have only been recorded on a few beaches. There are no previous records of Olive Ridley landings at Pantai Kerachut and Telok Kampi, but tracks and nests have been found at Telok Kumbar, Tanjong Bungah, Pantai Medan, Telok Duyung and Gertak Sanggul. A Turtle Conservation Centre has been established at Pantai Kerachut to protect these species from extinction in Pulau Pinang. This paper presents details of the records and distribution of sea turtles in Pulau Pinang from 1995 through 2009. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents the application of remote sensing techniques, digital image analysis and Geographic Information System tools to delineate the degree of landslide hazard and risk areas in the Balik Pulau area in Penang Island, Malaysia. Its causes were analysed through various thematic attribute data layers for the study area. Firstly, landslide locations were identified in the study area from the interpretation of aerial photographs, satellite imageries, field surveys, reports and previous landslide inventories. Topographic, geologic, soil and satellite images were collected and processed using Geographic Information System and image processing tools. There are 12 landslide-inducing parameters considered for the landslide hazard analyses. These parameters are: topographic slope, topographic aspect, plan curvature, distance to drainage and distance to roads, all derived from the topographic database; geology and distance to faults, derived from the geological database; landuse/landcover, derived from Landsat satellite images; soil, derived from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value, derived from SPOT satellite images. In addition, hazard analyses were performed using landslide-occurrence factors with the aid of a statistically based frequency ratio model. Further, landslide risk analysis was carried out using hazard map and socio-economic factors using a geospatial model. This landslide risk map could be used to estimate the risk to population, property and existing infrastructure like transportation networks. Finally, to check the accuracy of the success-rate prediction, the hazard map was validated using the area under curve method. The prediction accuracy of the hazard map was 89%. Based on these results the authors conclude that frequency ratio models can be used to mitigate hazards related to landslides and can aid in land-use planning. [ABSTRACT FROM AUTHOR]

In this paper, an estimate of the expected maximum water levels associated with tide and tsunami interaction is computed along the coastal belts of Penang Island in Peninsular Malaysia. For this purpose, a nonlinear Polar coordinate shallow water model of the Indonesian tsunami of 2004 by Roy et al. (2007b) is used. Appropriate tidal condition is generated in the domain by applying tidal forcing through the western open sea boundary. For studying tide and tsunami interaction, the 2004 Indonesian tsunami is introduced in the previously generated tidal oscillation. The expected maximum possible water level along the coastal belts of Penang Island is estimated based on the interaction of tide and tsunami for different tidal conditions (high and low tidal periods). It is seen that the surge level is very sensitive towards the coastal belts due to interaction during high tide. The west coast of Penang Island is found to be vulnerable for stronger surge due to interaction. The influence of tidal wave on the tsunami wave height towards Penang Island is also investigated. The tide was found to have a significant effect in tsunami enhancement in the coastal regions. [ABSTRACT FROM AUTHOR]

Abstract: Landslide-susceptibility mapping is one of the most critical issues in Malaysia. These landslides can be systematically assessed and mapped through a traditional mapping framework that uses geoinformation technologies (GIT). The main purpose of this paper is to investigate the possible application of an artificial neural network model and its cross-application of weights at three study areas in Malaysia, Penang Island, Cameron Highland and Selangor. Landslide locations were identified in the study areas from the interpretation of aerial photographs, field surveys and inventory reports. A landslide-related spatial database was constructed from topographic, soil, geology, and land-cover maps. For the calculation of the relative weight and importance of each factor to a particular landslide occurrence, an artificial neural network (ANN) method was applied. Landslide susceptibility was analyzed using the landslide occurrence factors provided by the artificial neural network model. Then, the landslide-susceptibility analysis results were validated and cross-validated using the landslide locations as study areas. Different training sites were randomly selected to train the neural network, and nine sets of landslide-susceptibility maps were prepared. The paper then illustrates the verification of those maps using an “area under the curve” (AUC) method. The verification results show that the case of the weight using the same test area showed slightly higher accuracy than the weight used for the cross-applied area. Among the three studied areas, the verification results showed similar accuracy trends while using the weight for the study area itself. Cameron showed the best accuracy and Penang showed the worst accuracy. Generally, the verification results showed satisfactory agreement between the susceptibility map and the existing data on the landslide location. [Copyright &y& Elsevier]

This paper summarizes findings of landslide hazard analysis on Penang Island, Malaysia, using frequency ratio, logistic regression, and artificial neural network models with the aid of GIS tools and remote sensing data. Landslide locations were identified and an inventory map was constructed by trained geomorphologists using photo-interpretation from archived aerial photographs supported by field surveys. A SPOT 5 satellite pan sharpened image acquired in January 2005 was used for land-cover classification supported by a topographic map. The above digitally processed images were subsequently combined in a GIS with ancillary data, for example topographical (slope, aspect, curvature, drainage), geological (litho types and lineaments), soil types, and normalized difference vegetation index (NDVI) data, and used to construct a spatial database using GIS and image processing. Three landslide hazard maps were constructed on the basis of landslide inventories and thematic layers, using frequency ratio, logistic regression, and artificial neural network models. Further, each thematic layer’s weight was determined by the back-propagation training method and landslide hazard indices were calculated using the trained back-propagation weights. The results of the analysis were verified and compared using the landslide location data and the accuracy observed was 86.41, 89.59, and 83.55% for frequency ratio, logistic regression, and artificial neural network models, respectively. On the basis of the higher percentages of landslide bodies predicted in very highly hazardous and highly hazardous zones, the results obtained by use of the logistic regression model were slightly more accurate than those from the other models used for landslide hazard analysis. The results from the neural network model suggest the effect of topographic slope is the highest and most important factor with weightage value (1.0), which is more than twice that of the other factors, followed by the NDVI (0.52), and then precipitation (0.42). Further, the results revealed that distance from lineament has the lowest weightage, with a value of 0. This shows that in the study area, fault lines and structural features do not contribute much to landslide triggering. [ABSTRACT FROM AUTHOR]

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/ geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network. [ABSTRACT FROM AUTHOR]

This paper examines international visitors' perceived importance and performance of 12 destination attributes of Penang Island using an Importance-Performance Analysis (IPA). The result was drawn from a questionnaire survey of 803 respondents who visited the island between August and November 2012. The importance-performance analysis grids illustrate that Penang Island performs well in six attributes namely 1) safety and security; 2) image of destination; 3) friendliness of the people; 4) variety of tourism attractions; 5) value for money; and 6) accessibility to the destination. The attribute of cultural and historical uniqueness appears to get too much concentration, and five attributes fell into the Low Priority quadrant. Safety and security was found to be the determining attribute for international visitors. Implications and recommendations for Penang managers and marketers were discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a decision treemodel for specifying the importance of 21 factors causing the landslides in a wide area of Penang Island, Malaysia. These factors are vegetation cover, distance from the fault line, slope angle, cross curvature, slope aspect, distance from road, geology, diagonal length, longitude curvature, rugosity, plan curvature, elevation, rain perception, soil texture, surface area, distance from drainage, roughness, land cover, general curvature, tangent curvature, and profile curvature. Decision tree models are used for prediction, classification, and factors importance and are usually represented by an easy to interpret tree like structure. Four models were created using Chi-squareAutomatic InteractionDetector (CHAID), ExhaustiveCHAID, Classification and Regression Tree (CRT), and Quick-Unbiased-Efficient Statistical Tree (QUEST). Twenty-one factors were extracted using digital elevation models (DEMs) and then used as input variables for the models. A data set of 137570 samples was selected for each variable in the analysis, where 68786 samples represent landslides and 68786 samples represent no landslides. 10-fold crossvalidation was employed for testing the models. The highest accuracy was achieved using Exhaustive CHAID (82.0%) compared to CHAID (81.9%), CRT (75.6%), and QUEST (74.0%) model. Across the four models, five factors were identified as most important factors which are slope angle, distance from drainage, surface area, slope aspect, and cross curvature [ABSTRACT FROM AUTHOR]

The microhabitats of green turtle ( Chelonia mydas) nests were investigated to identify key factors influencing nesting success by monitoring both successful nests ( n = 43) and aborted nests ( n = 106) created by the same individuals ( n = 9) from September 2013 to September 2014 on Penang Island, Malaysia. The effect of sand particle size on nesting success was significant, suggesting that green turtles tend to abort nesting at sites with sands of particle sizes < 1 mm. In addition, nests were successful at superficial sand temperatures less than 32.95°C. [ABSTRACT FROM AUTHOR]

The pygidicranid earwigs (Dermaptera) of Penang Island, Peninsular Malaysia were re-examined based on material collected in extensive field surveys in 2012-2013 and 2015. Echinosoma roseiventre Kamimura & Nishikawa, sp. n. is described and illustrated, and Cranopygia pallidipennis (de Haan, 1842) is reported from the island for the first time. The taxonomic and nomenclatural problems of the genus Cranopygia sensu Hincks (1959) [A Systematic Monograph of the Dermaptera of the World. Part II. Pygidicranidae excluding Diplatyinae. British Museum (Natural History)] are also discussed. For the members of the subfamily Pygidicraninae from Indo-Austral and Oriental regions, the system, definitions of genera, and key of Hincks (1959) are followed. The genus Mucrocranopygia Steinmann, 1986 is synonymized with Cranopygia Burr, 1908. A key to the males of small Echinosoma from the Oriental region is provided. [ABSTRACT FROM AUTHOR]

Several different stand-alone pole street lighting (SPSL) models, using a light emitting diode (LED) lamp, were tested over a 1-year period on Penang Island in northern Malaysia. The models were powered by lead-lead dioxide batteries, autonomously recharged by a renewable energy power source (RES): either a photovoltaic (PV) generator or an integrated PV/Wind-turbine generator system. The technical requirements and economic impact (capital and operating costs) of these two configurations are analyzed and compared. Additionally, some of these configurations were programmed with an energy load savings scheme. The impact of operating with this scheme was compared to operations performed at full load. Results of this comparative analysis revealed that the most efficient system for the test environment was the PV generator operating with the energy savings scheme. © 2013 American Institute of Chemical Engineers Environ Prog, 33: 283-289, 2014 [ABSTRACT FROM AUTHOR]

Three isolates of Penicillium pimiteouiense were recovered from sandy beach soil samples in Penang Island, Peninsular Malaysia. All the isolates were identified based on morphological characteristics and phylogenetic analysis of internal transcribed spacer regions and P-tubulin gene. This is a first record of P. pimiteouiense in Malaysia. [ABSTRACT FROM AUTHOR]

Slope failure and soil erosion due to increased development activity in hilly areas can be catastrophic and affect the environment and humans' well-being. This article investigates the parameters that contribute to environmental risk. Nine contributing parameters were identified. Rating the risk was proposed based on the prediction of occurrences of environmental issues and were categorized from very high (5) to very low (1) with high, medium, and low in between. The assessments were reviewed and evaluated based on rating for the chosen parameters. Maps quantifying risks were developed identifying areas of environmental risk. The overall result shows that development areas PD3 of Tanjung Bungah, and PD3, PD8, and PD9 of Paya Terubong have high rating of environmental risk. No development area is classified as very high risk or very low risk. The rating can be used to develop zones of potential high risk, and from this zoning guideline the viability can be measured for any proposed development. [ABSTRACT FROM AUTHOR]

The susceptibility of landslides and the effect of landslide-related factors at Penang in Malaysia using the geographic information system (GIS) and remote sensing data have been evaluated. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from Landsat Thermatic Mapper (TM) satellite images; and the vegetation index value from SPOT HRV (High-Resolution Visible) satellite images. Landslide hazardous areas were analyzed and mapped using the landslide-occurrence factors employing the probability-frequency ratio method using the all factors. To assess the effect of these factors, each factor was excluded from the analysis, and its effect verified using the landslide location data. As a result, all factors had relatively positive effects, except lithology, on the landslide susceptibility maps in the study area. [ABSTRACT FROM AUTHOR]