Climate, Environment and Biodiversity

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Assessment of urban air quality in Makassar South Sulawesi Indonesia
(Universiti Teknologi Malaysia, 2013) Sattar
An assessment of the urban air quality in Makassar area, which covers SO2, CO, NO2, O3, Pb, and TSP sampled over a period of eleven years (i.e 2001 to 2011), with PM10 monitored for six years (2006-2011) are discussed and presented in this thesis. The air quality data were obtained from secondary measurements made by the Office of Ministry of Environment Sulawesi, Maluku and Papua, the Environment Board of the Province of South Sulawesi, and the Environmental Agency of Makassar City. In addition, the primary data of airborne PM10 concentration sampled on a weekly basis for a period of one year (i.e February 2012 to January 2013) at one Makassar site are also reported. PM10 was sampled using a standard size selective high volume air sampler and analyzed for its elemental, black carbon and ionic species constituents. Results showed that the overall average concentrations of SO2, CO, NO2, O3, Pb, TSP and PM10 measured at eight monitoring sites of Makassar was 74.9 µg/m3, 1007 µg/m3, 42.5 µg/m3, 53.7 µg/m3, 0.70 µg/m3, 179 µg/m3, 53.9 µg/m3, respectively. The concentration of the particulate matter found in the study area was typically influenced by the dry and wet season experienced in the region. A total of nineteen elemental components (i.e Ag, Al, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Si, Ti and Zn), four ionic species (i.e Cl-, NO3 -, SO4 2-, NH4 +) and black carbon, together constituted a mere 28.8% of the PM10 mass concentration, while the remaining 71.2% are yet to be explained. However, the use of a more rigorous source apportionment model based on positive matrix factorization (PMF) successfully identified six major sources of air pollution in the area, which include marine, motor vehicle, road dust, soil dust, industry and biomass burning, each contributing 25%, 24%, 16%, 13%, 12%, and 10% of the particulate mass concentration, respectively
Methane emission inventory and forecasting in Malaysia
(Universiti Teknologi Malaysia, 2013) Yusuf, Rafiu Olasunkanmi
The increase in global surface temperature by 0.74 ± 0.18 °C between 1901 and 2000 as a result of global warming has become a serious threat. It is caused by the emission of greenhouse gases into the atmosphere due to human activities. The major greenhouse gases are carbon dioxide, methane and nitrous oxide. Records show that only carbon dioxide received detailed investigation but not methane, hence the motive behind this study. This study examined the emission of methane from six main sources in Malaysia. Data for the inventories of the production of these six sources were taken from 1980 – 2011 and were used to forecast emissions from 2012 – 2020. The data were sourced from Ministries, Departments and International Agencies. Six categories of animals were studied under livestock with their corresponding methane emissions from 1980 – 2011 computed as follows: cattle: 1993Gg (6.13%), buffaloes: 341Gg (10.8%), sheep: 24Gg (0.8%), goats: 55Gg (1.8%), horses: 3Gg (0.1%), poultry: 161Gg (5.1%), and pigs: 579Gg (18.3%). Methane emissions from the other sources from 1980 to 2011 are rice production: 1617Gg (0.02%), crude oil production: 8016636Gg (99.8%), Wastewater (POME): 11362Gg (0.14%), municipal solid waste landfills: 3294Gg (0.04%), coal mining: 14Gg (0.0002%). Forecasting of methane emissions from 2012 to 2020 were carried out using the Box-Jenkins ARIMA method. There were close similarities between the observed and forecast values. In the year 2020 predicted methane emissions will be cattle: 113Gg (72.2%), buffaloes: 8.0Gg (5.1%), sheep: 1.2Gg (0.8%), goats: 4.2 Gg (2.7%), horses: 0.2Gg (0.1%), pigs: 13.2Gg (8.4%), and poultry: 16.8Gg (10.7%) for the livestock sector. For other sectors the forecast will be wastewater: 836Gg for wastewater, 4.7 Gg for coal production, 503,208 Gg for crude oil production, 50.6 Gg for rice production, and 167 Gg from municipal solid waste landfills. Population and GDP will rise to 33.26 million and 329US $ billion by 2020, respectively. Optimisation was carried out after running a linear regression to determine the significant parameters. The equation developed was a nonlinear programming problem and was solved using sequential quadratic programming (SQL) and implemented on MATLAB environment. Sensitivity analysis carried out on the constraints showed the need to maintain the present livestock and rice production levels. The amount of meat protein currently available far exceeds the dietary protein requirement by more than five times. Several mitigation measures aimed towards reducing future methane emissions in Malaysia were also suggested for the various sources. These are in line with the country’s commitment to reduce greenhouse gas emissions by 40% over the 2005 level by 2020. The use of renewable energy in the energy mix was suggested in line with the government’s five fuel policy and increase in the number of vehicles using gas was also proposed
Integration of the river ecosystem attributes for river health assessment
(Universiti Teknologi Malaysia, 2013) Eh Rak, Aweng
Currently in Malaysia, only physical and chemical components are used as an indicator for river health monitoring and rehabilitation programme. These attributes were used for many years as a basis and reference in rehabilitating rivers in Malaysia and none of them was proven to be successful. Therefore, the aim of this study is to integrate the river ecosystem attributes for the purpose of river health assessment in Malaysia by using benthic macroinvertebrate as the main biological indicator. This study was conducted in Sungai Mengkibol, Sungai Madek and Sungai Dengar in Johor. There were a total of five sampling sites, three for impact stations and two as reference stations, including one highland station. The sampling was conducted six times during November 2008 to June 2010. Surber Net measuring 500 micron mesh size combined with a rectangular quadrate of 30 cm x 30 cm (0.09 m2) were used to sample the benthic macro-invertebrate. Biodiversity Indices was also analyzed. For water quality, six in-situ parameters were measured namely temperature, conductivity, dissolved oxygen (DO), pH, turbidity and salinity using a multi parameter probe as well as a single parameter probe. Meanwhile, field survey form was used to assess river habitat namely river riparian compositions, canopy cover and large woody debris. In addition, Pebble Count Method was used to measure substrate compositions and Valeport ‘Braystoke’ Model 001 Flow Meter was used to gauge the river. Based on the results obtained from the study, it can be suggested that ephemeroptera, plecoptera, and trichoptera index (EPT) taxa could be used as biological indicator for preliminary river health assessment. However, for the detail assessment, physicochemical water quality, river discharge, channel deformation, substrate compositions, riparian and canopy cover and large woody debris need to be evaluated and integrated.
Fast modelling of tidal phenomenon for the Straits of Malacca using laplace spatial interpolation technique
(Universiti Teknologi Malaysia, 2014) Kanchana Gunathilaka, Malavige Don Eranda
Tidal observations are commonly used for tide modelling to increase the reliability of the results of tide prediction. Most of the existing tidal computation techniques such as fourth order biharmonic and discrete tidal zoning technique are include several parameters like tidal constituents, datum and residual. Over 400 tidal constituents have being identified are being used in tidal computational and it makes the computation process are extensive and more tedious. In addition, it is not suitable for onboard and real-time application to have continuous results. Therefore, this study was conducted to develop an application that can provide accurate near-realtime tidal correction for bathymetric reduction based on the observed tides on tide gauge. Spatial interpolation technique is used to find the numerical solution of Laplace’s Equation for tidal field. First, the appropriate boundary condition coefficients were tested and determined by using simulated test basins. For the real test, data from ten tidal stations were selected as the known stations and another ten stations were selected as the check stations such that to cover both sides of the Straits of Malacca. Best solution was obtained with the boundary condition factor a = 0.9 at coastline and the optimum convergence was achieved with the relaxation coefficient r =1.62. The computation of spatial interpolation was developed using Matlab software to provide fast, accurate and continuous tidal corrections for onboard bathymetric reduction which is termed as Direct Tidal Observation Spatial Interpolation Technique (DTOSIT). The computed tides were compared to the value of tidal observation at shore tidal station and also value of sea surface height from satellite altimetry at offshore. In addition to that, a new concept termed as Ceaseless Co-tidal Charts (CCTC) was also developed by adopting the tidal zoning and conventional co-tidal charts. This has minimized the discontinuity of the tidal values in crossing the zones. The statistical results showed correlation of 0.9 between the observed and the modelled tidal values. DTOSIT tidal modelling results slightly higher correlation than the predicted CCTC tides as it used the observed tide in the modelling. The standard deviations of the computed datum levels were around 0.1m and satisfied the International Hydrographic Organization’s standards for the datum requirement
Trends and prediction of air pollutants in Pasir Gudang Industrial Area, Johor, Malaysia
(Universiti Teknologi Malaysia, 2014) Afzali, Afsaneh
The trends and prediction of the air quality of Pasir Gudang industrial area in Johor are discussed and presented in this thesis. An attempt was also made to study the pollutants concentrations recorded by the Larkin monitoring station. However, studies on the trends, meteorological influences and the predictions of atmospheric pollution were given a greater emphasis for the Pasir Gudang industrial area. The statistical analysis based on a simple correlation coefficient and regression analysis showed that although there is a relationship between each pollutant i.e ozone (O3), particulate Matter with diameter of 10 micrometers or less (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO) concentrations and a combination of meteorological parameters such as wind speed, temperature, humidity rate and solar radiation in Pasir Gudang with the correlation coefficient (r) of 0.64, 0.42, 0.71, 0.55 and 0.49, respectively, the inclusion of the previous day’s pollutants concentrations significantly presents better prediction models with the correlation coefficient of 0.73, 0.68, 0.83, 0.68 and 0.67, respectively. Subsequently, the prediction of PM10 based on its previous day’s concentrations through artificial neural network resulted in a much better model prediction with the value of r=0.69 and 0.70 compared to the statistical model with the value of r=0.64. The spatial variation of SO2, NO2 and PM10 emitted from various industrial sources in Pasir Gudang were also predicted using American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) air dispersion model. The Weather Research and Forecasting (WRF) model was applied to simulate the required meteorological variables for the selected date i.e 2-16 July, 2010. The WRF output values i.e. temperature, wind speed and wind direction were compared with the onsite measured data in Pasir Gudang, Senai, KLIA and Kluang stations. The results showed the accuracy of WRF model performance in simulating temperature and wind speed with the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) value of less than 2.8 and 3.5, respectively, while it has some difficulties in simulating the wind direction near a coastal area. The maximum ground level concentration of pollutants i.e SO2, NO2 and PM10 simulated through AERMOD coupled with WRF in Pasir Gudang industrial area was 36.2, 59.8 and 5.4 ug/m3, respectively, which were within the Malaysia ambient air quality guidelines over the receptor grid. The evaluation of AERMOD through the quantile-quantile (Q-Q) plots showed that most of the predicted and observed pair points are lying close to the one-to-one line. Besides, the sensitivity of AERMOD model to its input parameters i.e stack characteristics and meteorological variables showed that the model is more sensitive to stack gas temperature and stack height as well as wind speed.
Landslide susceptibility mapping in central zab basin using satellite data
(Universiti Teknologi Malaysia, 2014-04) Shahabi, Himan
Landslides are among the phenomenon natural disasters which cause lots of fatalities and financial losses all over the world every year. The central Zab basin in the southwest mountainsides of West-Azerbaijan province in Iran was chosen as the study area in this research since it is susceptible to landslide due to its climatic conditions, geology and geomorphologic characteristics, and human activities. In order to explain these landslides, various factors, i.e. slope, aspect, elevation, lithology, Normalized Difference Vegetation Index (NDVI), land cover, precipitation, and distances to fault, drainage and road were used. For better precision, higher speed and facility in the analysis, all the descriptive and spatial information were entered into Geographical Information System (GIS) system. In this research, Digital Elevation Model (DEM) was extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). NDVI and the land cover maps were obtained from the Lansat ETM+ images. Besides, the landslide-inventory map of the study area was identified from SPOT 5. In this study, all the data above input into four statistical methods that include Analytical Hierarchy Process (AHP), Frequency Ratio (FR), Logistic Regression (LR) and Artificial Neural Network (ANN) to produce landslide susceptibility maps. These four methods were validated using R-index analysis and Receiver Operating Characteristic (ROC). Based on the decision support system (DSS), predisposing factors in occurrences of landslides were imported to Automated Land Evaluation System (ALES) software to determine the best options for landslide stability in central Zab basin. The results obtained from the statistical methods showed that, the prediction accuracy were 81%, 86%, 89%, and 92% for AHP, FR, LR and ANN respectively. The map extracted from the ANN model displays higher accuracy as compared to the maps extracted from the other three models. In further study, the findings showed snow melting affected occurrence of landslide in the study area. The importance of snow effect in this basin has also been simulated using a Snowmelt Runoff Model (SRM) as one of the major applications of MODIS-8 satellite images and extraction of Snow Cover Area (SCA) using the Normalized Difference Snow Index (NDSI). The verification results showed satisfactory agreement between the landslide susceptibility maps and the existing data on the landslide locations
Model struktur kompetensi pengurusan fasiliti dan petunjuk prestasi utama Politeknik
(Universiti Teknologi Malaysia, 2014-08) Awang, Mariah
Government transformation has set out in detail the objectives, success measures and set the beginning of a major success in the areas of the country and the major success of the Field Ministry to produce the expected changes. Among factors targeted is to increase the number of high skilled labour to reached 37 per cent by the year 2015. Polytechnic Department Studies is the organization that has accounted for the realization of the mission. One of the Performance Indicator for Polytechnic transformation is whether it is the main institution of the student's choice to continue their studies. Among the main criteria that are considered in the selection of a just institutional study is what the facilities are provided by the institution. However the best facilities also requires for effective facility management, by individuals who are qualified, competent and skilled to manage them. There are some empirical studies that support the implementation of the competency of facility management in the education sectors, present research skills have more to the competency of a lecturer to deliver lessons. As such, then this state has seen there is the need to review the competency of facility management in the education sector, namely higher education, with Polytechnic has become the focus of the study. In terms of methodology, all individuals who manage facilities in 18 of polytechnics have been units of analyses and sampling procedure aims was used. To the validity of instruments, evaluation of the opinion of the expert, pilot test and analysis of factors do and for proving the hypothesis, bootstrapping analysis in SmartPLS was done. In particular, this study has shown there is a link between competency facility management with key performance indicators of the polytechnics transformation plan. This facility management concept described by five variables with 36 items and key performance indicators of the polytechnics transformation plan consists of 14 items. The findings show there are changes to the variable facility management competencies in terms of the variable name. While from the point of impact of facility management competencies against key performance indicators Polytechnic transformation plan, the study was able to prove there are three significant variables that influence and importance. The variable is the field of facility management leadership competencies the organization management and human resources; Management services; and management of operations and maintenance. The findings of this study have contributed to increased understanding of subject's studies and more importantly it also contributed to the development and strengthening of competency theory in facility management
Intelligent geospatial decision support system for Malaysian marine geospatial data infrastructure
(Universiti Teknologi Malaysia, 2014-08) Hamid-Mosaku, Isa Adekunle
Marine resources for different uses and activities are characterised by multi-dimensional concepts, criteria, multi-participants, and multiple-use conflicts. In addition, the fuzzy nature in the marine environment has attendant features that increase the complexity of the environment, thus, necessitating the quest for multiple alternative solutions and adequate evaluation, particularly within the context of Marine Geospatial Data Infrastructure (MGDI). However, in the literature of MGDI, there has yet to be a concerted research effort and framework towards holistic consideration of decision making prospects using multi-criteria evaluation (MCE) and intelligent algorithms for effective and informed decision beyond the classical methods. This research, therefore, aims to develop and validate an intelligent decision support system for Malaysian MGDI. An integrated framework built on mixed method research design serves as the mode of inquiry. Initially, the quantitative methodology, comprising of Dynamic Analytic Network Process (DANP) model, comprehensive evaluation index system (CEIS), MCE extensions, geographic information system’s spatial interaction modelling (SIM), and hydrographic data acquisition sub-system was implemented. Within this framework, a case study validation was employed for the qualitative aspect to predict the most viable geospatial extents within Malaysian waters for exploitation of deep sea marine fishery. Quantitative findings showed that the model has an elucidated CEIS with a DANP network model of 7 criteria, 28 sub-criteria, and 145 performance indicators, with 5 alternatives. In the MCE, computed priority values for Analytic Hierarchy Process (AHP) and Fuzzy AHP are different though their rankings are the same. In addition, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy TOPSIS results from the MCE extensions showed that they were similarly ranked for the Exclusive Economic Zone (EEZ) (200 nm) area as predicted by the DANP model. Furthermore, re-arrangement of the priorities in sensitivity analysis enhanced the final judgment for the criteria being evaluated; and for the SIM. Qualitatively, the validation of the DANP through the prediction has cumulated a computed value of 76.39 nm (141.47 Km) where this would be the most viable and economical deep sea fishery exploitation location in Malaysian waters and within the EEZ. In this study, MGDI decision and MgdiEureka are newly formulated terminologies to depict decisions in the realms of MGDI initiatives and the developed applications. The framework would serve as an improved marine geospatial planning for various stakeholders prior to decision making
Spatial data infrastructure framework and tools for the integration of heterogeneously distributed data sets
(Universiti Teknologi Malaysia, 2014-10) Mohammed, Abdul Salam
Absence of inter-agency coordination has created diverse methods and practices in the generation and maintenance of spatial data in the Emirate of Abu Dhabi. Consequently spatial data sets from various agencies are inconsistent and thus hampering the smooth vertical and horizontal integration for various inter-agency applications. Many technical inconsistencies such as differences in datum projections, accuracy levels, semantic and schema for geographic feature re-presentation exist in the data sets. International successful practices has been studied extensively to understand growing demand for the geospatial data sets, its availability, methods used to maintain it, and mechanisms evolved to make it easily available for cross jurisdictional utilization. Spatial data activities of Saudi Arabia, Qatar and the United Arab Emirates have also been reviewed. Considering the differences in the capacity of the region compare to international best practices, tools and techniques that are familiar to the various users are given preference for developing systems in various agencies. Therefore, developing common data models that accommodate most data sets commonly used by the agencies becoming a priority. These models are developed based on minimum data standards based on tools and techniques that are familiar to the United Arab Emirates. Maximum care is taken to preserve prevailing configuration of the geospatial data sets maintenance environment belonging to the respective custodians. To resolve the absence of data documentation, metadata content standards has been developed with minimum details that are sufficient enough for facilitating the development of data model and data translations rules. Opens Geographic Information System standards, tools and available data models with appropriate revisions or modifications are used to suit the purpose. Tools and techniques have been designed and developed for metadata content standards and subsequent metadata generation. Design and development of common data model and subsequent data translation tools for integrating data sets into the common data model are also developed. Finally web mapping tools is adapted to portray the integrated data sets. As a proof of concept, sample data sets are selected to test and analyse the tools and techniques that are adopted in the design and development of system for integrating spatial data sets. It has been found that the integrated data sets are consistent and commonly be used by the agencies. Finally a future initiative for further improvement of Spatial Data Infrastructure implementation has been recommended.
Carbon sequestration model of tropical rainforest ecosystem using satellite remote sensing data
(Universiti Teknologi Malaysia, 2014-12) Rasib, Abd. Wahid
Various measurements methods have been used to determine the validity of the information produced for carbon sequestration especially in tropical rainforests. Generally, these methods can be divided into two major categories which are the micrometeorological and biometric approaches. The former uses remote sensing and tower flux and the latter refers to field direct measurement of biomass. Presently, use of a single measurement approach has sometimes caused uncertainty in the accuracy of carbon sequestration in terms of the source or sink of carbon in these forests. Thus, this study proposed and developed a new model for carbon sequestration generated from the integration of remote sensing and biometric approach. This study was carried out in Pasoh Forest Reserve and the model was used for up-scaling to estimate the carbon concentration of the entire forest. Data for remote sensing were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data and the biometric approach was based on tree census and litterfall observations. The results for the years 2000 until 2009 based on the new model showed that the carbon sequestration was a carbon source with increments ranging between -1.421 t ha-1yr-1 to -16.573 t ha-1yr-1, a mean value of -8.526 t ha-1yr-1 and Root Mean Square Error (RMSE) 2.916. The use of the new model revealed that there is a 6% accuracy improvement in the results as compared to a single-based remote sensing model. As a conclusion, the integration of approaches for a new model for carbon sequestration is more efficient than the use of a single approach. Furthermore, the new model is suitable for validating and calibrating global automatic climate products
Persepsi penduduk flat kos rendah terhadap strategi intervensi anteseden dan konsekuen bagi pembuangan sampah
(Universiti Teknologi Malaysia, 2015) Abdul Shukor, Fatin Syazwina
Failure for the implementation of an appropriate strategy for a change of littering behavior is due to the failure of identifying the strategies that are significant. In Malaysia context, there are no empirical studies undertaken to examine the problems of litter disposal particularly relating on behavior change strategies. In facilities management, studies on behavior are included in the scope of behavior management and human capital management to enable the building's main functions operating well. Therefore, this study was undertaken to achieve four objectives, i.e i) To identify antecedent and consequent intervention strategies for littering behavior change in low-cost residential flats ii) To identify implementation activities of antecedent and consequent intervention strategies for littering behavior change in low-cost residential flats iii) To identify indicators for littering behavior change in low-cost residential flats iv) To identify relationship between antecedent and consequent intervention strategies and littering behavior change in low-cost residential flats. In achieving the research objectives, as many as 1137 set of questionnaires were distributed for data collection and only 849 set of questionnaires were returned by respondents. Respondents for this study involve low-cost flat residents in the three areas of the city council which are City Hall of Kuala Lumpur, City Council of Shah Alam and City Council of Petaling Jaya. The samples data were analyzed through descriptive analysis and Structural Equation Modeling (SEMPLS) analysis by using SmartPLS 2.0 software. The results of this study has indicated six significant intervention strategies and five intervention strategies which showed insignificant decisions based on an assessment of the t-value. The six significant intervention strategies are law enforcement, punishment, community education, social norms, community involvement and prompting. Whereas the five insignificant strategies are environmental design, reward, modeling, incentives and campaign
Reduce reuse recycle behavioural intention model in higher education institution accommodation
(Universiti Teknologi Malaysia, 2015-02) Jibril, Jibril Danazimi
The issues of solid waste management in Higher Education Institutions (HEIs) has become more problematic to facilities management units, thus the potential adverse effect has forced a total shift to deal with the situations in our academic environment, as such it needs the potentials to predict the students’ behavioral intentions to engage in the reduce reuse and recycle (3Rs) practice within HEIs accommodations. For this reasons, three related objectives were prompted: To assess the 3Rs behavioral intentions indicators based on Theory of Planned Behaviour (TPB) conceptual model. To analyze the relationship between TPB construct and 3Rs behavioral intentions indicators. To develop and validate 3Rs behavioral intentions model for higher educational institution’s hostel accommodation. To achieve these objectives, two methodologies were employed which involved literature review, and questionnaire survey. The underpinning theory used in this study is the theory of planned behavior (TPB) which possess the three predictors: attitude, subjective norms and perceived behavioral control to predict the 3Rs behavioral intentions. The survey method was used to collect data from the HEIs hostel accommodations within Universiti Teknologi Malaysia (UTM), 544 questionnaires was successfully collected from the student respondents in 13 residential colleges. Subsequently, after validating the data, AMOS 22.0 was used to analyze the TPB constructs, for more parsimonious structural equation model (SEM) fit using confirmatory factor analysis (CFA). Multiple regression analysis (MRA) was later run using SPSS 22.0. The results indicates that all the three predictors are significantly positive and influential thus it affects the students’ behavioral intentions to engage in the 3Rs practice. The behavioral intentions which was influenced by these three TPB predictors, has become the important factors for students to actively engage in 3Rs practice. The study clearly showed that there was a potential for significantly improving the 3Rs behavioral intentions amongst the HEIs students, to engage in the reduce reuse and recycle (3Rs) practice within HEIs accommodations
Comparative model for classification of forest degradation
(Universiti Teknologi Malaysia, 2015-03) Mehdawi, Ahmed A.
The challenges of forest degradation together with its related effects have attracted research from diverse disciplines, resulting in different definitions of the concept. However, according to a number of researchers, the central element of this issue is human intrusion that destroys the state of the environment. Therefore, the focus of this research is to develop a comparative model using a large amount of multi-spectral remote sensing data, such as IKONOS, QUICKBIRD, SPOT, WORLDVIEW-1, Terra-SARX, and fused data to detect forest degradation in Cameron Highlands. The output of this method in line with the performance measurement model. In order to identify the best data, fused data and technique to be employed. Eleven techniques have been used to develop a Comparative technique by applying them on fifteen sets of data. The output of the Comparative technique was used to feed the performance measurement model in order to enhance the accuracy of each classification technique. Moreover, a Performance Measurement Model has been used to verify the results of the Comparative technique; and, these outputs have been validated using the reflectance library. In addition, the conceptual hybrid model proposed in this research will give the opportunity for researchers to establish a fully automatic intelligent model for future work. The results of this research have demonstrated the Neural Network (NN) to be the best Intelligent Technique (IT) with a 0.912 of the Kappa coefficient and 96% of the overall accuracy, Mahalanobis had a 0.795 of the Kappa coefficient and 88% of the overall accuracy and the Maximum likelihood (ML) had a 0.598 of the Kappa coefficient and 72% of the overall accuracy from the best fused image used in this research, which was represented by fusing the IKONOS image with the QUICKBIRD image as finally employed in the Comparative technique for improving the detectability of forest change
Evaluation of different techniques for generating landslide susceptibility map
(Universiti Teknologi Malaysia, 2015-06) Mirnazari, Javad
Landslide is a complex natural phenomenon, which may cause loss of lives and properties around the world. In Iran, for example, most landslide occurrences are shallow, and mainly occur around the western and northern parts of the country. In particular, the Cheshme Kabud rural district, which is located in the western part of Iran, is a region of frequent landslide occurrence as a consequence of inherent and triggering factors. As such, this study seeks to assess the accuracy of the different methods used to generate landslide susceptibility maps. This study also aims to predict the landslide extension to the existing areas in the future. The methods used for the generation of landslide susceptibility maps in the study were Moderation, Artificial Neural Network (ANN) and regressions (logistic, spatial and Geographically Weighted Regression (GWR)). Extension of the existing landslide areas was predicted using Geographically Altitudinal Weighted Regression (GAWR) method. In this study, GeoEye-1 and IKONOS satellite images were used for providing landslide inventory. Nine landslide conditioning factors namely slope, aspect, landuse, lithology, soil type, erosion, distance to roads, distance to rivers, and distance to faults were considered in the analysis. In Moderation method, all the classes of factors were weighted. In this way, the final weighted classes generated a landslide susceptibility map of the Chesme Kabud rural district. The lack of weather stations in the study area posed a significant limitation to the data collection, considering the effect of rain on landslide susceptibility mapping in the area for all the methods. By validating the three methods using the receiver operating characteristic (ROC) technique, the result showed that the Moderation method showed the best performance with a 95% prediction accuracy. The result of the GAWR indicates that, in general, the areas of small landslides will experience more extension than larger landslides in the future
Factors impeding the development of Oman spatial data infrastructure
(Universiti Teknologi Malaysia, 2015-10) Al-Wardi, Ahmed Hamood Mohammed
Spatial Data Infrastructure (SDI) is an innovative concept introduced more than twenty years ago to allow the sharing and reuse of geospatial data. The National Spatial Data Infrastructure (NSDI), an SDI expanded to the national level, is now widely considered as an essential basic infrastructure for a country in this information era. To date countries all over the world, irrespective of their size, economic strength, political stability and population size, have developed, developing or considering developing their own SDI. A number of developed countries had successfully developed an impressive operational SDI while others are still progressively developing theirs. Yet for other countries the SDI development still remains an innovative concept. Understandably, besides the political and economic factors, many interrelated technical and non-technical factors can affect the development of SDI, the complexity of which can increase with the increase in the level of jurisdictions involved in spatial data sharing. Oman was one of the countries that had taken up the early initiative but unfortunately all that was known of the initiative was some feasibility studies conducted by non-national institution. Therefore this research has attempted to investigate the factors impeding the SDI development of Oman as an effort to revive the initiative to develop an operational Oman SDI, seen as an integral infrastructure to Oman’s future development and an important component in disaster and environmental management. Through this study, it was found that SDI is about communications between SDI participants to share spatial data. Through the thorough review of the data gathered from interviews and questionnaires, this research methodology was supported by systematic inspection and analysis of the essential data. The main stumbling block to Oman’s effort in building the SDI is the non-technical factors, including the human aspects entailing the lack of knowledge and awareness of spatial data and use of GIS, lack of knowledge on SDI concept and SDI benefits, and also the lack of cooperation, collaboration and coordination among the participants. It can be concluded that the lack of knowledge and awareness make communication between SDI participants difficult, thus almost impossible for cooperation, collaboration and coordination. This had left Oman with no option but to leave the initiative as an innovative concept, are now identified to be given the highest priority to enable Oman to pave the way forward
Strategic framework for road maintenance management in Padang Weat Sumatra Indonesia
(Universiti Teknologi Malaysia, 2016) Kamil, Insannul
Nowadays, maintenance management is focused on road infrastructure. However, this has been a standard practice in Australia, New Zealand, United Kingdom and United States of America. In Indonesia and other developing countries, the maintenance management of road infrastructure uses the road’s life cycle as an indicator for the maintenance management priority, rather than the vision, mission, objectives and resources of the road authority’s organization. Thus, the main objective of this research is to develop a Strategic Framework for Road Infrastructure Maintenance Management (SFRMM) that relates to an organization’s vision, mission, objectives and resources. To achieve this objective, a research blueprint was designed as a guidance for the researcher. The process to achieve the objective starts with literature review in areas related to maintenance management, performance indicators and success factors. From this review, 41 indicators were identified and grouped into 15 criteria. The collected data were analysed using a few statistical tools namely Analytic Hierarchy Process (AHP), Natural Cut-off Point Method and Strength Weakness Opportunities and Threat (SWOT) ANALYSIS. As a result, 10 indicators were identified as the critical success factors (CSFs), which are average speed of traffic, implementation of maximum load capacity limit, management of road life, measurement of surface roughness, plot, texture and roughness of road, road quality, travel smoothness, safety of road maintenance, availability of road supporting facilities and pestilent accidents. These factors have been validated by experts who had more than 10 years of working experience in related areas. These factors formed the basis for formulating the SFRMM. As a conclusion, the researcher had demonstrated that the main objective of this research had been achieved. The researcher suggested that this strategic framework that relates to the organization’s vision, mission, objective and resources can be applied to manage the maintenance of other real asset and infrastructure
Developing a sustainable tax efficiency model to reduce property tax non-compliance
(Universiti Teknologi Malaysia, 2016) Ashmat, Ismail
Property tax is one of the most important factors in contributing to the sustainability and function of local authorities. The revenue collected is vital in providing sufficient funding to accommodate the demand for services and facilities of population in the city. However, the effectiveness of tax administration practices in Malaysia is questionable due to the impact of non-compliance of tax payment. Various opinions and arguments in the literature have pointed out that the root cause of this problem lies in the weaknesses of current tax administration. The weaknesses identified from the literature can be categorised as are the taxation procedures, preparation of Valuation List, and governance and legislation. Therefore, the main objective of this research is to develop a sustainable tax efficiency model in tax administration to reduce the property tax non-compliance within the local authorities in Malaysia. In order to explore basic understanding about standard practices of tax administration to reduce property tax non-compliance at the preliminary stage, the interviews have been conducted with the experts in property taxation. This followed by comprehensive data collection through distribution of structured close-ended questionnaires to the valuation officers in Malaysian local authorities that classified as an expert. Delphi Method used for data collection is to obtain the expert’s consensus on relevant questions asked in 3 Rounds. There are 47 experts that have responded the questionnaires in the Round 1 from 149 Malaysian local authorities that been circulated. The sample has been scaled-down into 14 experts in Round 2 and 3, due to the accuracy reason of the feedbacks in Round 1. The responds were analysed descriptively based on Cronbach’s Alpha to test the level of consistency and reliability of the indicators, and Factor Analysis to cut-off the indicators into the most preferred by the experts. This followed by benchmarking approach for the experts to determine where their responses ranked compared to other expert’s responses. The findings have exposed the efficiency indicators to reduce the tax non-compliance. Three major findings in this research are firstly, revenue collection from property tax maintain as the main source of income, secondly, the revenue collection has contributed to the strong financial tool to the local authorities and thirdly, with strong financial tool, local authorities will be sufficient and efficient in providing the services and facilities to the taxpayers. The sustainable tax efficiency model has produced the economic principle o f efficiency indicators than based on social or environmental. In general, Malaysian local authorities have to strategize the valuation procedure and preparation of Valuation List effectively in order to strengthen governance and legislation to reduce the tax non-compliance. Hence, the sustainable tax efficiency model developed in this research can be implemented to reduce property tax non-compliance at local government level
Selection criteria of building material for optimising maintainability
(Universiti Teknologi Malaysia, 2016) Kanniyapan, Gunavathy
Maintainability of building facilities partially relies on the selection of building materials. Properly selected materials will minimise defects from common deterioration, improve ease of maintenance, and minimise maintenance cost throughout the designed life of building. Selecting building materials without considering maintainability aspects may result in increased maintenance problem in the post occupancy stage of the building. Previous maintainability studies focused on the good practices or strategies that can be applied during the design and the construction stage to control repetitive problems based on defect analysis of existing building elements. Furthermore, when selecting building material in previous studies, attention were given on performance, sustainability and cost factors, but ignoring maintainability factors of the materials. It can be concluded that there is insufficient attention given to the selection of building material with respect to maintainability, during the design stage. Insufficient consideration on maintainability is the most significant factor that cause deteriorations in the building material at the post occupancy stage, which was identified in previous research. This leads to a knowledge gap about the actual selection criteria for maintainable building material required to optimise building maintainability. This research is carried out to identify the selection criteria of maintainable building material, and the criteria of maintainability at post occupancy stage through the questionnaire survey among practitioners in the fields of architecture, building maintenance and structural engineering. Forty two selection criteria of maintainable building material and six criteria of maintainability in the post occupancy stage has been identified from the literature, and they were tested in two phases of survey and analysis. The major findings of this research are the six criteria, presented in order of most significant: "Technical Properties of Materials", "Documentation and Details", "Mechanical Properties of Materials", "Chemical Properties of Materials", "Material Economy" and "Social Benefit" which need to be given priority in maintainable building material selection. The result of this research can benefit the construction industry since this is the first time a researched guideline on the criteria for maintainable building material selection is made available
Remote sensing based evaluation of uncertainties on modelling of streamflow affected by climate change
(Universiti Teknologi Malaysia, 2016) Tan, Mou Leong
Assessment of the impacts of land-use and climate change on streamflow is vital to develop climate adaptation strategies. However, uncertainties in the climate impact study framework could lead to changes on streamflow impact. The aim of this study is to assess the uncertainties on Digital Elevation Model (DEM), Satellite Precipitation Product (SPP) and climate projection on the modelling of streamflow affected by climate changes. These uncertainties are evaluated and reduced independently. The climate projection uncertainty is addressed through the modification of the Quantifying and Understanding the Earth System - Global Scale Impacts (QUEST-GSI) methodology. Twenty-six modified QUEST-GSI climate scenarios were used as climate inputs into the calibrated Soil and Water Assessment Tool (SWAT) model to evaluate the impacts and uncertainties of climate change on streamflow for three future periods (2015-2034, 2045-2064 and 2075-2094). The selected study areas are the Johor River Basin (JRB) and Kelantan River Basin (KRB), Malaysia. The Shuttle Radar Topography Mission (SRTM) version 4.1 (90m resolution) DEM and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) SPP which show a better performance were selected for the SWAT model modification, calibration and validation. The results indicated that the modified SWAT model could simulate the monthly streamflow well for both basins. Land-use and climate changes from 1985 to 2012 reduced annual streamflow of the JRB and KRB by 5% and 4.2%, respectively. In future, the annual precipitation and temperature of the JRB / KRB are projected to increase by -0.4-10.3% / 0.1-11.2% and 0.6-3.2oC / 0.8-3.3oC, respectively, and that this will lead to an increase of annual streamflow by 0.5-13.3% / 4.4-18.5%. This study showed that satellite data play an important role in providing input data to hydrological models
Cementation factor and carbonate formation properties correlation from well logs data for nasiriya field
(Universiti Teknologi Malaysia, 2016) Kadhim, Fadhil Sarhan
The cementation factor has specific effects on petrophysical and elastic properties of porous media. A comprehensive investigation of carbonate rock properties which have an interlock with the cementation factor was done through core analysis and well log data. Five wells in Nasiriya oilfield, which is one of the giant fields consists of the carbonate reservoirs in the Middle East were used in this study. The study was made across the Mishrif and Yamamma carbonate formations in the Nasiriya oilfield. Neurolog software (V5, 2008) was used to digitize the scanned copies of available logs while Interactive Petrophysics software (IP V3.5, 2008) was used to determine the properties of studied formations. The average cementation factor values were calculated from the F-PHI plot and Gomez methods and compared with Pickett method. Petrophysical and dynamic elastic properties were determined from well logs. In this study, a new approach was introduced to obtain correlations of cementation factor to petrophysical and dynamic elastic properties of Mishrif and Yamamma formations. An artificial neural network platform was used to determine these correlations depending on the determined properties of studied formations. The neural network model used two different training algorithms; Gradient Descent with Momentum and Levenberg–Marquardt. Results show that the plot of average core data and calculated data from IP software of porosity and permeability gave a good correlations coefficient of R2 = 0.86034 to 0.94303. Generally, cementation factor values obtained from all methods are found to be less than two. In addition, cementation factor values also increased with increasing depth of the studied formations. An efficient performance and excellent prediction of cementation factor have been obtained with less than 10-4 and 10-8 mean square error from both artificial neural network models. Three saturation models were used to estimate water saturation of carbonate formations, which are simple Archie equation, dual water model and Indonesian model. The Indonesian water saturation model recorded the lowest percentage error in comparison with water saturation of core samples, and the water saturation in Yamamma formation was higher than in the Mishrif formation. The accurate determination of a cementation factor gives reliable saturation results.

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