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Flood can be assessed through flood vulnerability, risk, and susceptibility analysis using remote sensing, geographic information system, and hydrological modelling. In this chapter, different stages, complexities, and processes of flood vulnerability, risk, and susceptibility assessment were discussed. The study reveals that flood vulnerability should be assessed based on four aspects: physical, social, economic, and environmental. Flood risk should be assessed by three stages: risk analysis, disaster relief, and preparedness, whereas flood susceptibility assessment involves three processes. Overall, it was found that the responsible factors vary as per the local conditions, which need to be carefully analyzed and selected. Furthermore, the role of remote sensing and geographic information system in flood risk management were found important especially in flood risk mapping and in the selection of responsible flooding factors.

Remote sensing and geographic information system techniques were used for prioritization of flood vulnerability zones based on integrated parameters. Estimation of various linear and shape morphometric parameters, spatial and temporal land use and land cover changes (2005–2015), soil loss and sediment yield were performed for each river basin and utilized for the flood vulnerability zones. Further, ranks were assigned on the basis of changes in the parameters' value in areas/distribution of areas. To prioritize, five categories were classified: ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’ in terms of priority. The final prioritization of the integrated analysis revealed that 16 and 5 river basins fall under high and very high priority respectively. It is concluded that these river basins will be selected to conduct hydrological modelling for flood analysis. Validation results support the presented methodology and showed that in the 2014 Kelantan flood, the water level rose drastically in high and very high priority river basins situated in midstream. © 2018 John Wiley & Sons, Ltd.

Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters are important due to health impact. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. Seasonal aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Terra satellites, for the 10 years period of 2000 - 2010 were used to test 7 different spatial interpolation methods in the present study. The accuracy of estimations was assessed through visual analysis as well as independent validation based on basic statistics, such as root mean square error (RMSE) and correlation coefficient. Based on the RMSE and R values of predictions made using measured values from 2000 to 2010, Radial Basis Functions (RBFs) yielded the best results for spring, summer and winter and ordinary kriging yielded the best results for fall.

We have investigated the average P-wave travel-time residuals for some stations around Southern Thailand, Peninsular Malaysia and Singapore at regional distances. Six years (January, 2010–December, 2015) record of events from central and northern Sumatra was obtained from the digital seismic archives of Integrated Research Institute for Seismology (IRIS). The criteria used for the data selection are designed to be above the magnitude of mb 4.5, depth less than 200 km and an epicentral distance shorter than 1000 km. Within this window a total number of 152 earthquakes were obtained. Furthermore, data were filtered based on the clarity of the seismic phases that are manually picked. A total of 1088 P-wave arrivals and 962 S-wave arrivals were hand-picked from 10 seismic stations around the Peninsula. Three stations IPM, KUM, and KOM from Peninsular Malaysia, four stations BTDF, NTU, BESC and KAPK from Singapore and three stations SURA, SRIT and SKLT located in the southern part of Thailand are used. Station NTU was chosen as the Ref. station because it recorded the large number of events. Travel-times were calculated using three 1-D models (Preliminary Ref. Earth Model PREM (Dziewonski and Anderson, 1981, IASP91, and Lienert et al., 1986) and an adopted two-point ray tracing algorithm. For the three models, we corroborate our calculated travel-times with the results from the use of TAUP travel-time calculation software. Relative to station NTU, our results show that the average P wave travel-time residual for PREM model ranges from −0.16 to 0.45 s for BESC and IPM respectively. For IASP91 model, the average residual ranges from −0.25 to 0.24 s for SRIT and SKLT respectively, and ranges from −0.22 to 0.30 s for KAPK and IPM respectively for Lienert et al. (1986) model. Generally, most stations have slightly positive residuals relative to station NTU. These corrections reflect the difference between actual and estimated model velocities along ray paths to stations and can compensate for heterogeneous velocity structure near individual stations. The computed average travel-time residuals can reduce errors attributable to station correction in the inversion of hypocentral parameters around the Peninsula. Due to the heterogeneity occasioned by the numerous fault systems, a better 1-D velocity model for the Peninsula is desired for more reliable hypocentral inversion and other seismic investigations.

Topographic and climatic changes are the main causes of abrupt flooding in tropical areas. It is the need to find out exact causes and effects of these changes. Numerical modeling techniques plays a vital role for such studies due to their use of hydrological parameters which are strongly linked with topographic changes. In this review, some of the widely used models utilizing hydrological and river modeling parameters and their estimation in data sparse region are discussed. Shortcomings of 1D and 2D numerical models and the possible improvements over these models through 3D modeling are also discussed. It is found that the HEC-RAS and FLO 2D model are best in terms of economical and accurate flood analysis for river and floodplain modeling respectively. Limitations of FLO 2D in floodplain modeling mainly such as floodplain elevation differences and its vertical roughness in grids were found which can be improve through 3D model. Therefore, 3D model was found to be more suitable than 1D and 2D models in terms of vertical accuracy in grid cells. It was also found that 3D models for open channel flows already developed recently but not for floodplain. Hence, it was suggested that a 3D model for floodplain should be developed by considering all hydrological and high resolution topographic parameter's models, discussed in this review, to enhance the findings of causes and effects of flooding.

Total suspended sediment (TSS) plays a significant role in the environment. Many researchers show that TSS has a high correlation with the red portion of the visible light spectrum. The correlation is highly dependent on geography of the study area. The aim of this study was to develop specific algorithms utilizing corrected MODIS Terra 250-m surface reflectance (Rrs) product (MOD09) to map TSS over the Penang coastal area. Field measurements of TSS were performed during two cruise trips that were conducted on 8 December 2008 and 29 January 2010 over the Penang coastal area. The relationship between TSS and the surface reflectance of MOD09 was analysed using regression analysis. The developed algorithm showed that Rrs are highly correlated with the in-situ TSS with R2 is 0.838. The result shows that the Rrs product could be used to estimate TSS over the Penang area.

Gulf of Martaban is located at the north of Andaman, and is one of the world most turbid areas. The presence of suspended sediment concentration (SSC) in the water body could reduce the underwater transmittance. This study has been conducted to investigate the variation of SSC over the Gulf of Martaban. Remote sensing reflectance (Rrs) of 667 nm is used as a proxy to represent the sediment SSC variation over the study area. The data for the period of July 2002 to March 2014 acquired from MODIS Aqua 4 km resolution are used in this study. As a result, there is no obvious yearly variation in the SSC cover area. The SSC variation over this study area is found to be seasonal. High homogenous SSC covers area observably during the northeast (NE) monsoon season that occurs from December to January. The sediment cover area could reach the latitude of 15°N that located at the south of the gulf. During southwest (SW) monsoon season that occurs from May to September, low and sparse SSC cover area is observed. As a consequence, the area covered by the SSC is higher during the NE monsoon season as compared to the SW monsoon season. Hence, the SSC cover area during the NE monsoon season is greater than the yearly averaged SSC cover area. Meanwhile the SSC cover area during the rainy SW monsoon season is less than the yearly and NE monsoon season.

A prediction at a regional scale of groundwater productivity potential mapping in an area is subjected to uncertainties that must be efficiently managed for enhancing decision making. This study explored the potential of a GIS-based Dempster–Shafer theory (DST) model as a spatial prediction model to offer solution to this problem. Seven criteria/factors regarded as positive indicators to the existence of promising groundwater reservoir in a given study area were selected and weighted in a probability-based DST approach to compute degrees of belief functions component indexes. The results of the computed belief function indexes values were processed in GIS environment to generate belief functions maps among which the uncertainty index map established uncertainty result of relatively low range of

The present study analyzes and quantifies the spatial–temporal variability of outgoing longwave radiation (OLR) over peninsular Malaysia using the continuous wavelet transform (CWT) from 2003 to 2010. The goal is to understand the long-term variability of OLR over Malaysia in terms of time–frequency variations in relation to the monsoon period and other weather phenomena. The study regions selected were the west coast, east coast, and southern part of peninsular Malaysia. The OLR variation characteristics in time and space derived from wavelet transform were found to be distinctly different in these three regions. In these three regions, OLR showed significant periodicities dominated by the annual cycle, followed by a semiannual cycle. The west coast of peninsular Malaysia has a lower annual component compared to the other regions because of the rain-sheltering effect by the mountain range that blocked the heavy rainfall from northeast monsoon winds. Besides that, the results show that the wet and dry spells coincide with local monsoon and intermonsoon periods. Meanwhile, the results also revealed that the semiannual variation is statistically significant during 2004–06. The strong semiannual variation is coincident with several droughts that resulted from the strong El Niño events in 2004–06. In addition, the phase plot of wavelet coefficients shows that the variations at various scales are in phase, which coincided with the sudden variations of OLR, indicating heavy flood occurrences in the southern part of peninsular Malaysia. The results show that CWT is a powerful tool for analysis of phenomena involving multiscale interactions that exhibit localization in both time and frequency.

The potency of the Indonesian geothermal resources able to supply 40% of world’s demand on the geothermal resources. These resources are spread over 251 locations at 33 provinces having the total potential energy of 27.149 MW. One of these geothermal resources is Tinggi Raja located at Distric of Dolok Marawa, Simalungun Regency, North Sumatera 449385 E – 473025 E and 324105 N - 349545 N. This paper reports the study on mapping of the prospect of geothermal resource area by utilizing a remote sensing. The remote sensing consisted of Landsat 8 OLI which was published on February 8th 2015 and June 29th 2015 with Path 129 Row 58 as input data for ENVI 4.7 and ArcGIS 10 as mapping tools. Calculated land surface temperature (LST) was essential for mapping and calculating a geothermal resources. In this study, land surface temperature was used as the Thermal Infrared images obtained from the thermal infrared remote sensor. The highest achieved LST was 310.889587 K. The obtained LST distribution indicated the location of the geothermal potential.

Prediction of groundwater resources potential is a spatial decision problem that involves a set of multiple evaluation parameters. In order to produce a groundwater resources potential prediction model of higher reliability and precision in a given study area, the effects of all the important parameters that can contribute to the groundwater occurrence in the area must be integrated. However, the methodology of integrating these parameters such that the relative importance of each is reflected is still a challenge that has not been efficiently handled. In this study, the principle of multi-criteria decision analysis in the context of the analytical hierarchy process is proposed as a technique that can yield a prediction model of higher reliability and precision. The proposed technique was applied to geoelectric and geologic parameters, derived from the results of the interpretation of 2D resistivity imaging data acquired from the study area. The advantage of the proposed technique is that it reduces bias in decision making. The main objective of the study is to produce groundwater potential map for the area. Furthermore, an attempt was also made in the study to characterize the aquifer of the area by estimating the Dar-Zarrouk parameters, using the integration of borehole and 2D resistivity data. The success rate (accuracy) of the prediction was established to be 80 %. Furthermore, the regression line fitted to the aquifer transmissivity and transverse resistance data shows linear relationship with a high regression coefficient of 0.79. The prediction success rate obtained showed that the method proposed in this study is reliable, accurate, and an improved technique of integrating multiple parameters for holistic evaluation of groundwater resources.

MASW surveys carried at a number of sites in Pulau Pinang, Malaysia, showed complicated dispersion curves which consequently made the inversion into soil shear velocity model ambiguous. This research work details effort to define the source of these complicated dispersion curves. As a starting point, the complexity of the phase velocity spectrum is assumed to be due to either the surveying parameters or the elastic properties of the soil structures. For the former, the surveying was carried out using different parameters. The complexities were persistent for the different surveying parameters, an indication that the elastic properties of the soil structure could be the reason. In order to exploit this assumption, a synthetic modelling approach was adopted using information from borehole, literature and geologically plausible models. Results suggest that the presence of irregular variation in the stiffness of the soil layers, high stiffness contrast and relatively shallow bedrock, results in a quite complex f-v spectrum, especially at frequencies lower than 20Hz, making it difficult to accurately extract the dispersion curve below this frequency. As such, for MASW technique, especially in complex geological situations as demonstrated, great care should be taken during the data processing and inversion to obtain a model that accurately depicts the subsurface.

The present study used pixel-based soil erosion analysis through Revised Universal Soil Loss Equation (RUSLE) and a sediment yield model. The main motive of this study is to find soil erosion probability zones and accordingly prioritise watersheds using remote sensing and Geographic Information System (GIS) techniques in Kelantan state, Peninsular Malaysia. The catchment was divided into 82 watersheds and soil loss of the catchment was calculated. Soil loss and sediment yield were divided into five categories ranging from very low to very high. Maximum area of the very high soil-loss category was observed in uncultivated land and the maximum area of very low soil-loss category was in forest. Soil erosion probability zones were also divided into five categories in which 36.1% of the area experienced zero soil erosion and 20.1% and 17.8% represented very high and high probability zones respectively. The maximum very high and high probability zones were 61.6% and 28.5% of the watershed area respectively. Prioritisation was according to the area covered by very high and high soil erosion probability zones, which showed that out of 82 watersheds, two had the very high and high priority categories respectively. The overall results indicate that high rainfall and agricultural activities enhanced the soil erosion rate on steep slopes in the catchment. Pixel-based soil erosion analysis through remote sensing and GIS was a very effective tool in finding accurate causes of soil erosion. Furthermore, it was suggested that agricultural activities and deforestation should be stopped on steep slopes because of their contribution in increasing soil erosion.

In the present study, flood hazard zone is identified by morphometric analysis of Batang Padang catchment, Perak, Peninsular Malaysia using remote sensing and GIS techniques. Survey of Malaysia topographic map and ASTER GDEM is used for the study and Geographical Information System (GIS) is used for the delineation of linear, aerial and relief aspect of the seven sub-watersheds (SW) of the catchment (350.47 km2 area). Horton (1945) stream ordering method was used for stream ordering of the catchment. The analysis has revealed that the total number of stream segments is maximum in first order streams and decreases as the stream order increases but deviation behaviour in stream length except in two sub-watersheds. Variation in bifurcation ratio, high drainage density, dendritic drainage pattern with fine texture, high stream frequency, low drainage intensity, steep slope, form factor, circularity ratio and elongation ratio were determined which indicate that the area falls under high flood zone. Furthermore, on the basis of above analysis a flood hazard zone map also developed.

Physical sea surface parameters such as irradiance reflectance are most commonly used in ocean color remote sensing. Algorithms are developed to relate irradiance reflectance (R) and quantities such as chlorophyll and suspended sediment concentration. The study interpreted how many independent parameters of ALOS satellite data collected can be found to assess the sediment concentration in Langkawi Island, Malaysia by using principal component analysis (PCA). PCA is a technique designed for reducing the dimensionality of multivariate set of data. This method can reduce the variables which are highly correlated with one another without losing any information. In order to extract the reflectance quantities, all satellite data sets have been atmospherically corrected using ATCOR-2. PCA and band ratios were applied on the four independent bands (band 1-4). The result from independent band show that the PC1 and PC2 composed mostly of band 2(RAV2) and band 3 (RAV3) reflectances, while the band ratios show that t...

Aerosol is one of the important factors that will influence the air quality, visibility, clouds, and precipitation processes in the troposphere. In this work, we investigated the variation of aerosol during daytime in Penang, Malaysia in certain days within July 2013. Vertical LIDAR scattering ratio and backscattering profiles, and columnar optical properties (optical depth, Angstrom exponent) of aerosols were measured using Raymetrics LIDAR and a CIMEL sunphotometer respectively. Specifically, we have determined the daytime variation of intensity and distribution level of aerosol, as well as the planetary boundary layer (PBL) and cloud classification. Subsequently, the data of columnar aerosol optical depth (AOD) and size distribution in the atmospheric were used to quantify the properties of aerosol variation during daytime over Penang, Malaysia.

Estuary is an area where the interaction occurs between fresh water and salt water as the semi-closed sea-side communicates directly with the open sea where the salt water of dilution by freshwater flows from land drainage. The characteristics of estuaries are difficult to determine accurately because they are different in terms of their biological, chemical and physical. Because of their natural characteristics such as sheltered, shallow and calm, humans have benefited the estuaries as their source of food, transportation and development sites especially to the inland areas located far from the coast. However, the industrial activities have affected the areas by changing on the natural balance in the estuarine and pollution due to industrialization. In order to observe any changes in the area and to detect the pollution, remote sensing technology has been proven to be effective for observation of water bodies especially for total suspended solids (TSS). In this study, Landsat TM satellite image on 14 December 2009 was used to demonstrate the feasibility of TSS distribution mapping map in the lower Merbok estuary. In order to map the TSS distribution, a multiple regression algorithm was built using multi-band data for retrieval of the water constituent and the data were combined for multi-date regression analysis. In this study, the best R and RMS values were 0.96 and 18.68 mg/l. The coefficients obtained from the regression analysis were then used to map the suspended sediments. From the map analysis, assisted with the river discharge and tidal data, it was observed that the primary controlling factor to the TSS distributions in the area is the river discharge. The second predominant factor is tidal cycles. The presence of tidal cycles tends to increase or decrease the advections of the plume water.

Lidar is a widely used instrument by scientists around the world because of its high temporal and spatial resolution. With these characteristics, the interpretation of lower atmosphere behavior is improved, especially for the structure of the boundary layer, strongly related to air quality in the region. For the first time a backscattering lidar with wavelength 355 nm and Raman capabilities produced by Raymetrics was operated in Universiti Sains Malaysia (USM) in Penang Island. Due to operational constraints, this study will only discuss backscattering signal at 60 degrees zenithal angle shooting. From this study, we found that the lidar signal was extinguished very quickly and with maximum range of 3 kilometers for 30 seconds temporal resolution. The signal was extremely noisy in this study and even after subtracting the backgrounds such as solar radiation in the range corrected signal. Dead-time correction was then applied to improve the lidar signal. The better signal for the near and far ranges of this angle shooting, gluing both analog and photon is necessary. Temporal evolution was plotted to determine the planetary boundary layer (PBL) structure and the altitude of PBL also can be identified. Moreover, cloud distribution and aerosol concentration pattern can be structured from the temporal evolution graph. However, for identifying the tendency of PBL structure in Penang Island, longer period and continuous data acquisition were needed.

The spectral characteristics of land cover are basic references in classifying satellite image for geophysics analysis. It can be obtained from the measurements using spectrometer and satellite image processing. The aims of this study to investigate the spectral characteristics of land cover based on the results of measurement using Spectrometer Cropscan MSR 16R and Landsat satellite imagery. The area of study in this research is in Medan, (Deli Serdang, North Sumatera) Indonesia. The scope of this study is the basic survey from the measurements of spectral land cover which is covered several type of land such as a cultivated and managed terrestrial areas, natural and semi-natural, cultivated aquatic or regularly flooded areas, natural and semi-natural aquatic, artificial surfaces and associated areas, bare areas, artificial waterbodies and natural waterbodies. The measurement and verification were conducted using a spectrometer provided their spectral characteristics and Landsat imagery, respectively. The results of the spectral characteristics of land cover shows that each type of land cover have a unique characteristic. The correlation of spectral land cover based on spectrometer Cropscan MSR 16R and Landsat satellite image are above 90 %. However, the land cover of artificial waterbodiese have a correlation under 40 %. That is because the measurement of spectrometer Cropscan MSR 16R and acquisition of Landsat satellite imagery has a time different.

The problem of difficulty in obtaining cloud-free scene at the Equatorial region from satellite platforms can be overcome by using airborne imagery. Airborne digital imagery has proved to be an effective tool for land cover studies. Airborne digital camera imageries were selected in this present study because of the airborne digital image provides higher spatial resolution data for mapping a small study area. The main objective of this study is to classify the RGB bands imageries taken from a low-altitude Cropcam UAV for land cover/use mapping over USM campus, penang Island, Malaysia. A conventional digital camera was used to capture images from an elevation of 320 meter on board on an UAV autopilot. This technique was cheaper and economical compared with other airborne studies. The artificial neural network (NN) and maximum likelihood classifier (MLC) were used to classify the digital imageries captured by using Cropcam UAV over USM campus, Penang Islands, Malaysia. The supervised classifier was chosen based on the highest overall accuracy (

The presence of suspended sediment along coastal water and river mouth could affect water column and benthic process. The concentration of suspended sediments along coastal water is contributed by bottom sediment resuspension. The concentration of sediment over river mouth is cause by the river discharge. The concentrations of the sediment are highly variable over temporal and spatial. Northeast monsoon season that occurs between November-February every year bring along heavy rains and wind to the east coast of Malaysia peninsular. During this season, high sediment resuspension and river discharge carried by the river to the sea. The presence of the sediment along the coastal water and river mouth area can be indicated with the increment in the visible and near infrared region of the electromagnetic spectrum. In this study, remote sensing reflectance (R rs ) of MODIS 667 nm channels acquired from Aqua 4 km resolution is used as a tool to indicate the sediment over the study area. The study has been conducted along the east coast of Malaysia peninsula for the period of 2002–2011. The result shows that, the sediment concentration varies along the coastal line and the river mouth for throughout the entire year.

The objective of this study is to investigate the effects of orography on the rainfall, wind, and cloud systems of the TCs in Malaysia and Indochina. To determine the relationship of the typhoon with the orographic effect, remote sensing techniques such as the Global Digital Elevation Model (GDEM) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite, rainfall data from the Fengyun 2D (FY-2D), and radiosonde data were applied in this study. From this study, the following conclusions can be drawn: 1) rainfall tends to be distributed over high mountain regions; 2) wind flow will change its direction upon encountering any restrictions, especially those of high terrain regions; and 3) cloud patterns are deformed by high mountains and tend to flow with the mountains' structure because of the orographic effects. The regions most affected by Typhoon Ketsana in the study area were Vietnam in Indochina, Sabah in East Malaysia (EM), Kelantan and Terengganu in Peninsular Malaysia (PM). From the comparison among the study areas, it was found that Indochina had the most significant results for the orographic effects on typhoon activity, followed by the tail effects in EM. This phenomenon was found in PM, although it was not as significant as the other study areas. This remote sensing technique allows tropical cyclones to be forecasted and their impacts to be defined, and it allows disaster zones to be determined.

The spread of avian influenza has caused severe deaths in poultry and humans. It is important to understand migratory raptors flyways by monitoring their migration patterns. Ground counting is the oldest and easiest method to count the population of migratory raptors. The observers recognize the species of migratory raptors based on size, colour and song and flying characteristic. However, ground counting of big flocks of migratory raptors often faces difficulties due to the raptors' mobility and size. When the size of the flocks increases, ground counters will tend to produce more errors in their counting. Besides, ground counters will feel tired and easily lost their concentration when waiting for the migratory raptors for a long period of time. Therefore, the accuracy of this ground count method is questionable. This paper proposed the usage of optical remote sensing coupled with the image processing techniques to study the migratory raptors pathways. During the development of the software system, different image processing techniques were evaluated and enhanced for developing this monitoring system. The proposed mathematical thresholding technique is able to segment the raptors image from the background effectively.

Migratory birds have been identified to be the dominant sources for spreading the avian influenza/bird flu virus from one country to other country. It is important to have useful technique to monitor the bird migration for accessing the spread of bird flu. In this paper, we proposed the use of Digital Single Lens Reflex camera coupled with image processing technique to quantify the migratory birds. The captured images were downloaded into a computer system for analysis to determine the amount of migratory birds in each image. This system was tested in Kenting National Park in Taiwan during 2010 autumn migratory seasons. The data collected was compared with the photo counted numbers. Camera count, photo count and ground count results were compared and correlated with each other. The results show that the camera count has high coefficient of determination (R2) of 0.974. This indicated that the camera counts are more close to the actual number. In another word, it has high degree of accuracy. Therefore, the camera count can be effectively used to improve the accuracy of ground count.

Sound speed in seawater has been an interest to many researchers since the equations for sound speed was first published by Wilson in 1960. Generally, the speed of sound in water increases with the increasing temperature, salinity and pressure. However, other factors affecting sound speed are minor. Value of sound speed for fresh water and seawater at atmospheric pressure is approximately 1500 ms−1. In this study, the sound speed of Kuala Besar, Kelantan was investigated. This shallow water area is an estuary area where the acoustic environment can change over in very short scales. The sound speed calculation was based on the field observation data of salinity, temperature and depth of Kuala Besar. Medwin formula was used in the calculation. The collected data showed a variation of sound speed between 1058.17–1100.46 ms−1. The sound speed variations followed more the variations in salinity compared to variations in temperature for the stations at the transverse and longitudinal direction of the river. Therefore, in this study, the sound speed values were more influenced by salinity than temperature and followed the fact that salinity varies greatly in estuaries.

Remote sensing techniques have been used to study the impacts of the tropical cyclone. In order to figure out the relationship of typhoon with orography effect, precipitation products are acquired from Feng Yun 2D; and Global Digital Elevation Model (GDEM) from ASTER satellite was applied as well. After combining both the precipitation and elevation products of Peninsular Malaysia (PM), rainfall distribution patterns are distinctly affected by the mountains range. Titiwangsa Mountain range is the major mountain range which is able to influence the movement and distribution of the raining clouds. Normally, Titiwangsa Mountains can separate the raining distribution into 2 parts which is east and west side of the PM. Sometimes, rains can happen at both sides simultaneously when allowable weather conditions exist such as during typhoon activity. The other mountains which are higher than two thousands meters in PM are also able to change the rainfall distribution patterns since some raining clouds are lower than this elevation. 2 types of typhoon tail effects are defined by high low pressure system and centrifugal force reaction.

East Malaysia has few mountains ranges which are believed to affect the cloud and rainfall distribution patterns during severe weather especially typhoon season. The study objectives are to investigate and determine the relationship between the typhoon impacts and the topography of East Malaysia. The highest mountain range in East Malaysia was the Crocker Range in Sabah, which divides the state into half. Mountain ranges in the East tend to follow north-south or northeast-southwest paths, rising to over 4095.2 meters houses by Mount Kinabalu, the highest mountain in the country, as well as Mount Trusmadi (2642m) and Mount Tambuyukon (2579m), the second and third highest peak in the country. Typhoon Ketsana was chosen for this study. The hourly rainfall products were obtained from FengYun-2D geostationary satellite. Radiosonde data from Kota Kinabalu station with Skew-T diagram and hodograph were applied in this study. A total of 5 distinct results were found in this cloud and rainfall-orography interaction during the typhoon activity. First, parts of the cloud were blocked by the Crocker Range and caused to slow down of rainfall event for a moment. Second, the heavy rainfall occurred around these mountains range. Third, the variation of cloud and rainfall distribution pattern was related to the mountain shape. Fourth, if the raining cloud was high enough and there were extra outside energy (typhoon system) the rainfall process may be forced to move forward and pass through these mountains range. Besides that, heavy rainfall distribution was more affected by the high mountains close to the shoreline than the interior region of the island. Based on this study, orography effect was important to the weather forecaster since the high mountain range was able to influence the distribution of the cloud and even rainfall patterns during typhoon season.

3D electrical resistivity imaging was carried out to monitor slope failure in the USM campus. The natural disasters that occur suddenly such as landslides can cause loss of life, and money by damaging roads and cars. The prediction of a landslide before it occurs will reduce or stop these hazards. Geophysical techniques can be used to image slopes and monitor slope failure. The geophysical technique that was used in this study is electrical resistivity imaging. The results from the resistivity sections show that there are two different regions made up of granite, and sand zone. The results show that there are two factors which make the landslide possible. The first factor is the subsurface boulders and the other factor is saturated sand which may results subsidence of the surface.

We attempted to investigate the potential of using satellite image for acquiring data for remote sensing application. This study investigated the potential of using digital satellite image for land cover mapping over AlQasim, Saudi Arabia. Satellite digital imagery has proved to be an effective tool for land cover studies. Supervised classification technique (Maximum Likelihood, ML, Minimum Distance-to- Mean, MDM, Parallelepiped, P) techniques were used in the classification analysis to extract the thematic information from the acquired scenes. Besides that, neutral network also performed in this study. The accuracy of each classification map produced was validated using the reference data sets consisting of a large number of samples collected per category. The study revealed that the ML classifier produced better result. The best supervised classifier was chosen based on the highest overall accuracy and Kappa statistic. The results produced by this study indicated that land cover features could be clearly identified and classified into a land cover map. This study suggested that the land cover types of AlQasim, Saudi Arabia can be accurately mapped.

Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

Nowadays internet video surveillance cameras are widely use in security monitoring. The quantities of installations of these cameras also become more and more. This paper reports that the internet video surveillance cameras can be applied as a remote sensor for monitoring the concentrations of particulate matter less than 10 micron (PM10), so that real time air quality can be monitored at multi location simultaneously. An algorithm was developed based on the regression analysis of relationship between the measured reflectance components from a surface material and the atmosphere. This algorithm converts multispectral image pixel values acquired from these cameras into quantitative values of the concentrations of PM10. These computed PM10 values were compared to other standard values measured by a DustTrakTM meter. The correlation results showed that the newly develop algorithm produced a high degree of accuracy as indicated by high correlation coefficient (R2) and low root-mean-square-error (RMS) values. The preliminary results showed that the accuracy produced by this internet video surveillance camera is slightly better than that from the internet protocol (IP) camera. Basically the spatial resolution of images acquired by the IP camera was poorer compared to the internet video surveillance camera. This is because the images acquired by IP camera had been compressed and there was no compression for the images from the internet video surveillance camera.

Air quality is a major concern in many large cities of the world. This paper studies the relationship between particulate matter of size less than 10-micron meter (PM10) and satellite observation from OCTS. The objective of this study is to map the PM10 distribution in Peninsular Malaysia using visible and thermal bands data. The in-situ PM10 measurements were collected simultaneously with the acquisition of the satellite image. The reflectance values in the visible and digital numbers in the thermal bands were extracted corresponding to the ground-truth locations and later used for algorithm regression analysis of the air quality. A developed algorithm was used to predict the PM10 values from the satellite image. The novelty of this study is the algorithm uses a combination of reflectance measurements from the visible bands and the corresponding apparent temperature values of the thermal band. This study investigates the relationship between the extracted OCTS signals and the PM10 values. The reflectance at 3.55-3.88 micro meter is computed after correction for the emission by the atmosphere. The surface emissivity values were computed based on the NDVI values. The developed algorithm produced a high correlation between the measured and estimated PM10 values of 0.97. Finally, a PM10 map was generated over Peninsular Malaysia using the proposed algorithm. This study has indicated the potential of OCTS satellite data for air quality study.

Remote sensing data have been widely used for land cover mapping using supervised and unsupervised methods. The produced land cover maps are useful for various applications. This paper examines the use of remote sensing data for land cover mapping over Saudi Arabia. Three supervised classification techniques Maximum Likelihood, ML, Minimum Distance-to-Mean, MDM, and Parallelepiped, P were applied to the imageries to extract the thematic information from the acquired scene by using PCI Geomatica software. Training sites were selected within each scene. This study shows that the ML classifier was the best classifier and produced superior results and achieved a high degree of accuracy. The preliminary analysis gave promising results of land cover mapping over Saudi Arabia by using Landsat TM imageries.

The feasibility of using digital camera imagery for estimating the concentration of total suspended sediments (TSS) in the Timah Tasoh reservoir was investigated. Digital images were captured from a low-altitude light aircraft. Three selected images were mosaiced to produce bigger image of the study area. Atmospheric corrections and mosaic sincronourization were performed by using the average digital number of grass in the images as a reference value. Water samples were collected simultaneously with the airborne image acquisition and later analyzed in the laboratory. The color mosaic image was separated into three bands assigned as red, green and blue bands and analysis separately. The digital numbers for each bands corresponding to the ground-truth locations were extracted and used for calibration of the water quality algorithm. A single band second order polynomial algorithm was used in this study due to limited ground-truth data. The calibrated algorithm was used to generate the water quality maps. The proposed algorithm can estimate TSS concentration with linear correlation coefficient square (R2) of 0.98.

An algorithm was developed based on reflectance model of inherent properties of seawater. A digital camera was used to capture digital images of river estuaries of Prai, Muda, and Merbok from a low altitude flying light aircraft. Water samples were collected simultaneously with the airborne image acquisition and later analyzed in the laboratory. Vertical images were captured through a special hole at the floor of the aircraft. Atmospheric correction for multidate images was performed by selecting average digital number of grass as a reference. The digital colour images of the study areas were separated into three bands (red, green and blue) for multi-spectral analysis. The digital numbers for each band corresponding to the sea-truth locations were extracted and used to calibrate the algorithm. The calibrated total suspended solids (TSS) algorithm was then used to generate the water quality maps of the study areas. This study indicates that a digital camera can be a useful tool for airborne remote sensing. The newly developed algorithm can estimate TSS concentration with linear correlation coefficient square (R2) of 0.94.

The selected study area is the Strait of Penang, located in the north western part of peninsula Malaysia. Satellite imagery is employed as an aid to bathymetric charting. The depth sounding points retrieved from published bathymetric chart are used for calibration. Cloud free scene of ADEOS AVNIR data acquired on 14 January 1997 was available for use in the present study. This scene was rectified to the corresponding bathymetric chart. Image locations were related to the chart coordinates through the second degree polynomial transformation equations. Multiband water depth algorithm was used in the calibration analysis. Regression technique was used for calibration of the satellite signals for water depth recorded in the bathymetric map of the selected locations. The correlation coefficient and root- mean-square deviations were examined. The accuracy of calibrated algorithm was further verified using other known sounding points. The calibrated algorithm was then applied to the corresponding image to generate a water depth map. The color coded bathymetric map was used for visual interpretation and assessment of the present water depth pattern.

Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been widely used to address environment and climate change subjects with daily global coverage. Aerosol optical depth (AOD) is retrieved by different algorithms based on the pixel surface, determining between land and ocean. MODIS-Terra and Global Aerosol Robotic Network (AERONET) products can be obtained from the Multi-sensor Aerosol Products Sampling System (MAPSS) for coastal regions during 2000-2010. Using data collected from 83 coastal stations worldwide from AERONET from 2000-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard the Terra satellite. AOD retrieved from MODIS at 0.55μm wavelength has been compared With the AERONET derived AOD, because it is reliable with the major wavelength used by many chemistry transport and climate models as well as previous MODIS validation studies. After removing retrievals with quality flags below1 for Ocean algorithm and below 3 for Land algorithm, The accuracy of AOD retrieved from MODIS Dark Target Ocean algorithms (correlation coefficient R2 is 0.844 and a regression equation of τM = 0.91τA + 0.02 (where subscripts M and A represent MODIS and AERONET respectively), is the greater than the MODIS Dark Target Land algorithms (correlation coefficient R2 is 0.764 and τM = 0.95τA + 0.03) and the Deep Blue algorithm (correlation coefficient R2 is 0.652 and τM = 0.81τA + 0.04). The reasons of the retrieval error in AOD are found to be the various underlying surface reflectance. Therefore, the aerosol models and underlying surface reflectance are the dominant factors which influence the accuracy of MODIS retrieval performance. Generally the MODIS Land algorithm implements better than the Ocean algorithm for coastal sites.

Air pollution index (API) is an index commonly used in Malaysia to determine the air quality level. It is a ground truth data measurement which is unable to unambiguously quantify air quality level at higher atmosphere. On the other hand, aerosol optical depth (AOD) from AERONET data obtained using sun photometer provides reading of the air quality for a column of atmosphere from ground surface. We first determine the quantitative correlation between the API and AOD data collected in Penang, Malaysia, between January – September, 2012, using two independent methods, one based on regression analysis and the other interpolation. Our purpose is to establish a systematic numerical procedure to determine whether aerosol transported in high altitude from other location has occurred. Two independent methods for establishing the quantitative relationship between the API and AOD data were used as a way to facilitate the verification of our approach. In our method, data from southwest monsoon period (August to September) were used as "calibration dataset" to establish the quantitative correlation between the AOD and API data. The established calibrated coefficients is then used to predict the AOD of other months, which are then compared against the data actually measured. Discrepancy between the predicted and measured AOD data can then be interpreted as an indication of whether the atmosphere at high altitude is polluted by aerosol transported from other location. If the predicted AOD is much larger than that measured, back trajectory analysis was applied to identify the aerosol transported source. This procedure is very helpful to investigate the aerosol transportation and distribution patterns during monsoon and non monsoon periods.

The northeast monsoon season (NEMS), which occurs between November and March every year, brings heavy rains and strong wind to the east coast of Peninsular Malaysia. Large sediment resuspension during this season is caused by high waves and river discharge carried by the river to the sea. Sediment is defined in this research as both organic and inorganic materials. Remote sensing reflectance (Rrs) of the Moderate Resolution Spectroradiometer (MODIS) 667 nm channel is used in this study as a Total Suspended Sediment (TSS) index. The data was acquired from Aqua satellite with 9 km resolution. The study was conducted along the eastern coast of Peninsular Malaysia over the period of 2002-2012. The result shows that TSS along the Peninsular Malaysia coastline and the river mouth is highly seasonal. The highest TSS is observed during NEMS with the peak value in November-December every year.