Zulkiflee Abd Latif

Coupling of remote sensing data and environmental-related parameters for dengue transmission risk assessment in Subang Jaya, Malaysia

In Malaysia, the endemic level of dengue fever (DF) has already changed morbidity indicators, and the magnitude of these incidences in the last few years has surpassed the incidences of all other diseases of compulsory notification. The reasons for the dramatic emergence of DF are complex and not well understood. There are many factors that contribute to the epidemiological conditions that favour viral transmission by the main mosquito vector. This study, therefore, is filling this gap by analysing the impact of dengue incidence at a local (Subang Jaya) scale using environmental factors. Meteorological data and land-use pattern were consolidated using geographic information system (GIS) and its components as an analytical tool. We have shown that weather variables (relative humidity, temperature and precipitation) have significant correlation with DF incidence with seasonal variation. Besides land-use pattern, DF incidence shows the higher distribution in the residential area, followed by commercial and industrial area. This is due to the higher population density in residential area as well as favourable places for the breeding of dengue-carrying Aedes mosquitos created by humans in the residential area, especially one-storey houses. The analysis on the trends of DF incidence towards various housing types indicate that most of the victims’ houses fall into interconnection houses and mixed houses types compared to the independent houses area. The outcome driven from this analysis suggested that each character of the environmental factors has their own risk towards dengue incidence. In line with that, it is possible to develop a dynamic model of DF transmission using the knowledge produced by this comprehensive time series data and the results provided by the different analyses.

Determination of tree species using Worldview-2 data

Determining tree species has involved a lot of studies in the past decades. This is because of the availability of certain tree species to produce a high market value type of wood or that it can be use for meditational purposes. In the old days, conventional method of survey needs to be conducted to identify tree species. This type of method is rather hard to inaccessible area and time consuming. With the advancement of the satellite imaging technology, inaccessible area can be visualize from an satellite image. Worldview-2 image data is one of the proofs of the remote sensing evolving technology that can be used in a lot and varieties of studies. The available of the near infrared band makes it very useful in vegetation analysis. Based on this study that has been conducted to eight sample leaves taken from the Bukit Nanas Forest Reserve, Kuala Lumpur, spectral signature extraction was successfully conducted on the near infrared bandwidth due to its sensitivity towards vegetation. The different of about 5% between the signature extracted from the Spectra Vista GER 1500 and Worldview-2 data indicates that this image can be use successfully for vegetation analysis. However, it is very questionable whether high resolution can successfully delineate tree crown of a tree in a natural forest due to the complexity of the characteristics of the crown which is overlapping each other. This complexity is also a challenge for this study as to relate the spectral signature extracted with the accuracy of the segmentation and classification result. Furthermore it also will give some ideas to researchers as to figure what type of improvements can be made towards this study especially for natural forest.

Balancing water, religion and tourism on Redang Island, Malaysia.

Redang Island (Pulau Redang) is an island off of Peninsular Malaysia that is part of a Marine Park archipelago of corals and thousands of fish and invertebrates. The relatively isolated local community is generally centered on fishing, and Islam guides daily life. Recently, the tourism industry has expanded on the island. New hotels and resorts provide jobs, but also expose the locals to western culture and touristic behavior, which may clash with deeply traditional community values. Further, the tourism industry may be putting a strain on the natural resources, especially the quantity and quality of freshwater. The island village may become divided between those who support the tourism industry and those who do not. Here we present an exploratory investigation into the development–environment–culture dynamics of tourism, water and religion on Redang Island while building collaborations between universities of this Muslim state and the West.

Delineation of tree crown and canopy height using airborne LiDAR and aerial photo

Airborne LiDAR has good potential in giving accurate height of canopy in forestry area and measuring variable characteristics of detected trees This is essentially accomplished by subtracting the last return altitude (ground) from the first corresponding altitude (canopy surface). This research is intended to extract tree crowns and estimate its height by combining both spatial and spectral information from airborne LiDAR and digital aerial photo. Contouring techniqs were adopted in order to extract the tree crown information from digital aerial photo. LiDAR data was used to estimate tree height from Canopy Height Model (CHM). LiDAR data and digital aerial photo were acquired on the 20th September 2009 at Sungai Ayer Tawar plantation using Optech ALTM3070 and DCS digital camera. The results show that low statistical performance in estimating the tree height due to low density of LiDAR points and less of sampling data taken from field observations.

Carbon sinks and tropical forest biomass estimation: a review on role of remote sensing in aboveground-biomass modelling

Abstract Tropical forest embraces a large stock of carbon and contributes to the enormous amount of above- and below-ground biomass and the global carbon cycle. The carbon kept in the above-ground living biomass of trees is typically the largest pool and the most directly impacted by deforestation and degradation. Hence, quantifying carbon stock and fluxes from tropical forests by estimating the above-ground forest biomass is the critical step that will be investigated further in this paper. Remote sensing technology can provide many advantages in quantifying and mapping forest structure and monitoring and mapping above-ground biomass, and is both temporally and spatially accurate. Therefore, a good data-set of biomass which comprises canopy height and canopy structure can provide carbon sequestration potential for forest reserves. This paper reviews a thorough research of biomass estimation using remote sensing and geospatial technologies.Tropical forest embraces a large stock of carbon and contributes to the enormous amount of above- and below-ground biomass and the global carbon cycle. The carbon kept in the above-ground living biomass of trees is typically the largest pool and the most directly impacted by deforestation and degradation. Hence, quantifying carbon stock and fluxes from tropical forests by estimating the above-ground forest biomass is the critical step that will be investigated further in this paper. Remote sensing technology can provide many advantages in quantifying and mapping forest structure and monitoring and mapping above-ground biomass, and is both temporally and spatially accurate. Therefore, a good data-set of biomass which comprises canopy height and canopy structure can provide carbon sequestration potential for forest reserves. This paper reviews a thorough research of biomass estimation using remote sensing and geospatial technologies.

Landslide susceptibility mapping using LiDAR derived factors and frequency ratio model: Ulu Klang area, Malaysia

Landslides are one of the most important natural hazards which have been a major focus of investigation for international community. The consequences from its occurrences are highly contributed to enormous damages and economical losses in Malaysia. This has been recognized by many professional authorities and has led to a number of landslide hazard and risk mapping both in qualitative and quantitative ways. In this research, LiDAR data was used to generate landslide geomorphological surface. The landslide conditioning factors considered for the study area were slope gradient, curvature, topographic wetness index and soil type. The correlation of each parameter with landslide occurrences was then measured by using probabilistic based frequency ratio method and landslide susceptibility map was produced. The landslide susceptibility map can be very useful for general landuse planning.

GIS multi-criteria for power plant site selection

Malaysia has been well enough qualified in order to operate own nuclear power plant for the long term energy needs preparation in electricity demands. The government has taking a step forward in order to reduce the reliance on gas. In this study, the role of AHP and GIS in determining the optimum location of nuclear power plant is explained, criteria for the site selection are outlined and the results for finding the optimum location of nuclear power plant are included. Raub District in Pahang was selected as a study site due to its topography meeting most of the investigated criteria. Seven criteria are considered in this analysis such as low population density, residential area, the access of the river, topography, land use, electricity infrastructure and land ownership. Moreover, the following steps are performed such as represent the criteria in GIS layers, undergo the GIS analysis in order to get the several propose sites and classify the criteria according to the weight value. The site suitability map is effective for assessing and reveals the rates of suitability for the nuclear power plant. The results of the site suitability assessment showed that Site E located at Ulu Dong was the most suitable area for locating the nuclear power plant, with covers an area of 10063.86 acres or 38% of the total area Furthermore, the map provides the foundation for decision makers in develop the nuclear power plant location.

Measurement of dengue epidemic spreading pattern using density analysis method: retrospective spatial statistical study of dengue in Subang Jaya, Malaysia, 2006-2010

BACKGROUND Dengue has emerged as one of the major public health problems in Malaysia. The Ministry of Health, Malaysia, is committed in monitoring and controlling this disease for many years. The objective of this study is to analyze the dengue outbreak pattern on a monthly basis in Subang Jaya in terms of their spatial dissemination and hotspot identification. METHODS Collated dengue cases data covering a 5-year period (2006-2010) retrieved from a municipal surveillance system of Subang Jaya were georeferenced and then converted into Geographical Information System format. Average nearest neighbor (ANN) analysis and kernel density (KD) estimation were used to assess the spatial dissemination of dengue cases and detect dengue hotspots, respectively. RESULTS The spatial patterns of dengue fever cases during the 5-year period were spatially clustered (with R values < 1) based on the monthly frequency data. The hotspot map produced by the KD techniques showed a spatially diffused pattern. CONCLUSION The methodology used in the study and the result obtained could be useful not only for documentation by epidemiologists but also for active surveillance of dengue outbreak in a locality.

Application of Airborne LiDAR-Derived Parameters and Probabilistic-Based Frequency Ratio Model in Landslide Susceptibility Mapping

The escalating number of occurrences of natural hazards such as landslides has raised a great interest among the geoscientists. Due to the extremely high number of point’s returns, airborne LiDAR permits the formation of more accurate DEM compared to other space borne and airborne remote sensing techniques. This study aims to assess the capability of LiDAR derived parameters in landslide susceptibility mapping. Due to frequent occurrence of landslides, Ulu Klang in Selangor state in Malaysia has been considered as application site. A high resolution of airborne LiDAR DEM was constructed to produce topographic attributes such as slope, curvature and aspect. These data were utilized to derive secondary deliverables of landslide parameters such as topographic wetness index (TWI), surface area ratio (SAR) and stream power index (SPI). A probabilistic based frequency ratio model was applied to establish the spatial relationship between the landslide locations and each landslide related factors. Subsequently, factor ratings were summed up to yield Landslide Susceptibility Index (LSI) and finally a landslide susceptibility map was prepared. To test the model performance, receiver operating characteristics (ROC) curve was carried out together with area under curve (AUC) analysis. The produced landslide susceptibility map demonstrated that high resolution airborne LiDAR data has huge potential in landslide susceptibility mapping.

GIS-based estimation of rooftop solar photovoltaic potential using LiDAR

Solar photovoltaic (PV) technology now become a new trend for the home builders and buyers of the twentieth century, in order to have not only good in structure, but also more environmentally friendly. Understanding the rooftop PV potential is important for planning, accommodate grid capacity, and many more, this paper demonstrate the technique utilizing the LiDAR data merge with the Geographical Information System to determine the suitable location to locate the PV solar panels. There are five criteria that had been used to select the best location which is generate the ground mask, aspect mask, slope mask, human mask and high radiation layer. Based on the output of the suitable location, the estimating number of solar panel can be generate based on the calculation of one-and half square area meter was used as a required area for each solar panel. This new understanding of roof area distribution and potential PV outputs will guide energy policy formulation in Georgetown area and will inform future research in solar PV deployment and its geographical potential.