Siti Aekbal Salleh

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.

The Integration of 3D GIS and Virtual Technology in the Design and Development of Residential Property Marketing Information System (GRPMIS)

This paper discusses about a research with the aim of investigating the potential integration of 3D GIS and virtual technology in designing and developing residential property marketing information system. The method adopted in this research is a standard system development lifecycle; commencing with the user requirements study, followed by the system design, the system development, the system implementation and finally the system evaluation. This research uses an informal method i.e. semi-structured interview, survey questionnaire and review of the existing information system to establish the user requirements. Ten user requirements were outlined alongside with the examination of four 3D integration and three virtual reality methods. Three out four methods of 3D features integration are selected for the system development. The developed system is tested using the black box and white box testing methods. The prototype system can be used by the real estate agents and property developer as the concept, framework and references for future development of a better conducive property marketing information system as well as simplifying the traditional flow of housing selection which gives positive impacts in the marketing transaction.

Functional relation of land surface albedo with climatological variables: a review on remote sensing techniques and recent research developments

Surface albedo has been documented as one of the Essential Climate Variables (ECV) of the Global Climate Observing System (GCOS) that governs the Earths Radiation Budget. The availability of surface albedo data is necessary for a comprehensive environmental modelling study. Thus, both temporal and spatial scale issues need to be rectified. This study reports about the availability of surface albedo data through in-situ and remote sensing satellite observations. In this paper, we reviewed the existing models for surface albedo derivation and various initiatives taken by related environmental agencies in order to understand the issues of climate with respect to surface albedo. This investigation evaluated the major activities on albedo-related research specifically for the retrieval methods used to derive the albedo values. Two main existing albedo measurement methods are derived through in-situ measurement and remotely sensed observations. In-situ measurement supported with number of instruments and techniques such aspyrheliometers, pyranometers and Baseline Surface Radiation Network (BSRN) and remotely sensed observations using angularly integrated Bi-directional Reflectance Distribution Function (BRDF) by both geostationary and polar orbit satellites. The investigation results reveals that the temporal and spatial scaling is the major issues when the albedo values are needed for microclimatic study, i.e. high-resolution time-series analyses and at heterogeneity and impervious surface. Thus, an improved technique of albedo retrieval at better spatial and temporal scale is required to fulfil the need for such kind of studies. Amongst many others, there are two downscaling methods that have been identified to be used in resolving the spatial scaling biased issues: Smoothing Filter-based Intensity Modulation (SFIM) and Pixel Block Intensity Modulation (PBIM). The temporal issues can be resolved using the multiple regression techniques of land surface temperature, selected air quality parameters, aerosol and daily skylight.

Air quality parameters dependency of remotely-sensed albedo

Land surface albedo has large daily and seasonal variation in many regions. Malaysia, for being located at the tropical region, experiencing constant illumination of sun and receiving two monsoon seasons namely northeast and southwest and two inter-monsoon seasons in Mar-May and during Oct-Nov, the diurnal variation of heat may somewhat be different. This study attempts to investigate the relationship between land surface albedo (LSA) derived from the MODIS with the selected air quality parameters. The objectives includes to determine significance relationship between LSA with ambient temperature and to identify the significance factor of other identified variables such as UVB, windspeed, Humidity and CO2. Using linear trend correlation analyses technique based on Pearson correlation coefficient, the strength and direction of the relationships between MODIS spectrally derived LSA are identified along with the relationship between selected dependent and independent variables were visually inspected.

Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

The Improved Conceptual Design of Web-based GIS Residential Property Marketing Information System

This chapter attempts to show the conceptual design a Web-based GIS Residential Property Marketing Information System (WGRPMIS). This system is intended to be integrated with the virtual GIS technology enabling the consumer to virtually explore the potential property based upon the multi criteria selection through assisted geo-processing query. The proposed system is built using Adobe Flex on ArcGIS Server framework to enable geo-processing and geometric network capabilities. Through the pilot system, the success of 3D and virtual reality integration was revealed. Due to limitations of the query functions and 3D feature complexity taking its toll on the system’s performance, an improved geo-processing scheme is presented in this paper and the conceptual design of this system is revised. The improved query function which includes road network and accessibility were taken into consideration in solving buffer and radius query is developed. The revised conceptual design will further be used in designing the simplified 3D visualization viewer to the Virtual panoramic display.