Rosilawati Zainol

A GIS-based water quality model for sustainable tourism planning of Bertam River in Cameron Highlands, Malaysia

AbstractCameron Highlands is experiencing rapid development as a popular tourist destination in Malaysia. This causes a rapid boost in construction and other tourism-related activities, such as the growth of vegetables, fruits and flowers. Due to that, the water quality of rivers in the highlands has been adversely affected. In this study, Bertam River, as one of the main streams in Cameron Highlands, was monitored to assess its suitability for recreational activities and conservation. Seven sampling points were selected in the river and tributaries: dissolved oxygen, biochemical and chemical oxygen demands (BOD and COD), total suspended solids (TSS), ammonia nitrate (NH3–N) and pH were measured and the water quality index (WQI) was computed during high and average water flow. In addition, water quality surface data were generated from the sampling points using the interpolation technique of geographic information system to predict values of unknown locations. Results show that TSS, BOD and NH3–N contribute most to the pollution of the waters. This is due to earthworks in the highlands as well as poorly treated sewage discharges from hotels, rest houses and apartments. WQI results indicate that Bertam River and its tributaries are classified as class II, III and IV, which require extensive treatment before utilization in most of the locations. Consequently, to improve the water quality of the rivers, recommendations have been made to ensure that some sampling points with potentials for recreational activities attain class II and subsequently class I in the near future.

Application of Geographic Information System (GIS) and Analytic Network Process (ANP) for Sustainable Tourism Planning in Cameron Highlands, Malaysia

This paper discusses an approach based on an integrated use of GIS and ANP for sustainable tourism planning of Cameron Highlands, Malaysia. ANP was utilized to evaluate the relative priorities for the sustainable tourism development of the highland based on chosen criteria and indicators (elements). Pair wise comparison technique was used in order to evaluate possible alternatives from different perspectives. Having derived the weights from the pairwise comparison method, unweighted supermatrix, weighted supermatrix and the limit supermatrix were then computed. The limit supermatrix was normalized to derive the priorities; the result was then transferred into GIS framework. Elements evaluated and ranked are represented by criterion maps. The criterion maps were evaluated by reclassifying the data layers, to represent different needs for the sustainable tourism development of the highland. Spatial models reflecting the views of experts involved were aggregated using the weighted sum method of GIS. Subsequently sustainable tourism development model was generated, which will ensure that future generations benefit from the natural endowments of Cameron Highlands.

Analytic network process (ANP)-based spatial decision support system (SDSS) for sustainable tourism planning in Cameron Highlands, Malaysia

Sustainable approach to tourism development is rarely addressed among authorities and participants. This research presents an approach based on an integrated use of analytic network process (ANP) and geographic information system (GIS) for sustainable tourism planning in Cameron Highlands, Malaysia. ANP was utilized to evaluate the relative priorities for the sustainable tourism development of the highlands based on chosen criteria. ANP results were then transferred into GIS environment and attached to their respective criterion maps. Subsequently, GIS-based sustainable tourism map was generated, which defines the various types of tourism activities that are compatible with the highlands according to the sensitivity of the highland’s environment. The final output was validated using Cameron Highlands Local Plan.

SPATIAL ASSESSMENT OF THE IMPACT OF FLOOD TO MELAKA’S ECONOMY

Melaka used to be a significant trading state in the 16th century. It had attracted traders from various continents to be its trading partners. Many of these traders had left their footprint enormously. Over the years, these tangible and intangible historical assets have been an attraction to tourism sector which contributes significantly to Malaysian GDP. However, due to the impact of climate change and rapid urban development in Melaka, the flood has posed a risk to Melaka’s economy especially in the tourism sector. To protect its interest, Melaka has taken proactive measures in mitigating flood incidences. Thus, this study intends to examine the impact of the flood on Melaka’s economy from 2012 to 2016 using spatial assessments. This study employs a quantitative approach by using secondary data obtained from the Department of Statistics Malaysia and the Department of Irrigation and Drainage. Moran’s I, Local Indicator and Spatial Association and Bivariate Moran’s I were used to analyze the data spatially. Findings show the mitigation measures taken have relieved the risk posed by floods towards economic activities in Melaka as a whole.

Evaluation of GoogleMap as source of tourist spatial information

The availability of online GIS (Geographic Information Systems) maps has provided a new source of spatial information to tourists. However these maps have yet to be evaluated of their effectiveness. This has challenged scholars to further investigate methods of evaluating geographic information retrieval. Therefore the main objective of this paper is to evaluate the effectiveness of GoogleMap as one of the online GIS maps providers. System testing is used to assess three different study areas namely, Shah Alam, Kuala Lumpur and Taiping. To facilitate this assessment a query list consists of 78 keywords are gathered. Precision and recall measures are also used as an evaluation method. Findings show that GoogleMap Malaysia is bias towards places that are well-known and fed with abundant information by users. Therefore area that has more information and bigger in size has higher score levels of recall and precision percentage as compared to smaller and isolated areas that have lesser information.