Jasmee Jaafar

Interpretation of Ground Penetrating Radar (GPR) image for detecting and estimating buried pipes and cables

Interpretation of Ground Penetrating Radar (GPR) dataset towards detecting underground utility is a challenging task. The underground utility information such as location, depth and type serves as a reference prior to any construction project in order to avoid damage to the utility during excavation. However, the interpretation of GPR images is a tedious and timely process which requires human intervention. This study proposed a new hyperbola fitting technique to estimate the radius of buried utility (pipes and cables). The method was applied to nine (9) different sizes of buried pipes for radius estimation purposes. The result indicates that the technique is capable of estimating the radius of buried pipes with acceptable result; approximately 97.7% to 99.2% for cable/pipe type with a radius between 45mm to 150mm are detected accurately.

Homogeneous Climate Divisions for Peninsular Malaysia

Abstract Classification of Peninsular Malaysia was delineated by integrating in-situ temperature elements data and Geographical Information System (GIS) raster data. The principal component (PC) analysis was applied to long-term mean monthly temperature elements data for monsoon seasons. The first three principal components were chosen to be statistically significant, accounted for 96.5% of the variability in the 27 variables. These three components are related to the mean monthly variation in minimum temperature during monsoon season (first PC), the mean monthly variation in maximum and the mean temperature in southwest monsoon (second PC), and the mean monthly variation in maximum temperature during northeast monsoon (third PC). Cluster analyses were applied to create clusters of meteorological stations, of which six classes were formed. To determine cluster boundaries, interpolation analysis was applied to generate GIS raster data of factor scores. The supervised classification analysis was then performed to the generated GIS factor data. The result of a maximum likelihood classification produced three clusters when summarized by districts. Final classification results of climate divisions show rational climate regionalization that reveals control on temperature. The use of factor score GIS raster data effectively assists the generation of meteorological station clusters, grouped using only in-situ data.

Development of 7-DOF three-fingered robotic hand for industrial work

The purpose of this project is to design and construct a seven degree of freedom (DOF) three-fingered robotic hand. This project is the continuity from a previous work which has successfully constructed two-DOF robotic finger. In this work, a palm that holds all the three fingers is designed and the design of the current finger is improved. All components are fabricated and assembled to produce a complete robotic hand. SolidWorks software is used to design the palm and finger which considers the selection of motor, spur gears, and appropriate shape of palm. The range of motion is visualized to confirm the design with the desired application. Then, the motion of the proposed hand design is validated based on a control study which is carried out in separate work using Motion Manager Application. It can be observed from the experimental results that the robotic hand is capable of moving according to the proposed mechanism and the desired positions before successfully grasped two types of household objects with all its three fingers. This also proved that the proposed designs worked well for the task assigned by user. Thus, the resulted robotic hand can be potentially applied as the end effectors of an industrial robot for product manipulation in near future.

DEM derived from photogrammetric generated DSM using morphological filter

Digital Elevation Model (DEM) is a terrain model consisting of elevation data and representing the bare earth surface. Meanwhile Digital Surface Model (DSM) describes earth surface that includes nonterrain features such as vegetations and buildings. The most tedious and time consuming method of generating DEM is to gather ground points by conventional ground survey methods such as levelling or Global Positioning System (GPS) observations. An alternative approach is by photogrammetric technology on stereo pairs of aerial photographs. Measurement can be made either semi-automatic with human intervention or fully automatic taking advantage of the image matching algorithm. In built-up area, photogrammetric methods would generate DSM. DEM is produced by filtering out the nonterrain features. In this study the effect of various grid resolutions on the photogrammetric generated DSM and the morphological filtered DEM are investigated. It was observed that the height accuracy of photogrammetric generated DSM deteriorated rapidly above 1m grid resolution. The height Root Mean Square Error (RMSE) of the morphological filtered DEM obtained was 2.5m.

Modelling and mapping of above ground biomass AGB of oil palm plantations in Malaysia using remotely-sensed data

ABSTRACT Estimating accurate above ground biomass (AGB) of oil palm plantation in Malaysia is crucial as it serves as an important indicator to assess the role of oil palm plantations in the global carbon cycle, particularly whether it serves as carbon source or sink. Research on oil palm AGB in Malaysia using remote sensing is almost insignificant and it has known that remote sensing provides easy, inexpensive and less time consuming over larger areas. Therefore, this study focuses on evaluating the potential of Landsat Thematic Mapper (TM) data with combination of field data survey to predict AGB estimates and mapping the oil palm plantations. The relationships of AGB with individual TM bands and various selected vegetation indices were examined. In addition, various possibilities of data transform were explored in statistical analysis. The potential models selected were obtained using backward elimination method where R2, adjusted R2 (R2adj), standard error of estimate (SEE), root mean squared error (RMSE) and Mallows’s Cp criterion were examined in model development and validation. It was found that the most promising model provides moderately good prediction of about 62% of the variability of the AGB with RMSE value of 3.68 tonnes (t) ha-1. In conclusion, Landsat TM offers the low cost AGB estimates and mapping of oil palm plantations with moderate accuracy in Malaysia.

Preliminary study of above ground biomass (AGB) and stem volume of oil palm stands

This preliminary study is a part of data collection for the development of the prediction model for the estimation of oil palm above ground biomass (AGB) and stem volume using remote sensing data. Oil palm agricultural tree crops have been extensively studied in the aspect of botanical and cultivation due to its socio-economic and commercial values. Malaysia is known as the worlds top producers of palm oil with current planted area of plantations around 4.69 million ha. There is an abundance potential of biomass and renewable energy resources including oil palm in Malaysia. Oil palm residues are the major potential for power generation amounting to about 2400 mega watt. It has been acknowledged that renewable energy could be a key driver in maintaining the balance of economic development that would be anticipated to grow alongside the exponential rise of the global human population and climate change. Despite the importance of oil palm to the country, an accurate and reliable assessment method in resource availability is lacking. Therefore, the need for current inventory on oil palm biomass and stand volume leads this research into ground-based survey using the existing allometric equations. The objectives for this preliminary study are (1) to estimate AGB and stem volume of oil palm plantations of different ages and (2) to study the relationships between oil palm biomass and stem volume with the age of oil palm

A feasibility study of building structural deformation monitoring using Global Positioning System (GPS), terrestrial surveying technique (TST) and crack gauge measurement (CGM)

Deformation of engineering structures is often monitored in order to ensure that the structure is exhibiting safe deformation behaviour. The deformation of high-rise building can be monitored using geodetic surveys and geotechnical/structural measurements. Geodetic surveys include conventional (terrestrial) and satellite (Global Positioning System); wherelse geotechnical/structural measurements detect either by using leasers, tiltmeters, joint-meters and micrometers. This research will discuss the capability of monitoring high and low-rise building structure using geodetic surveys (conventional and satellite) and geotechnical measurement (crack width measurement). Two buildings namely the Twin Tower of Science and Technology Complex and Innovation Centre Building of University Technology MARA (UiTM), Selangor, Malaysia are chosen for the research study. UiTM Twin Tower represents high-rise building, five control points were been established around the building in the monitoring work. Innovation Centre was monitored using nine monitored points. The monitoring exercises are carried out at four (4) different epochs. The Terrestrial and Global Positioning System (GPS) dataset in the monitoring exercise are process and analysed using the intersection technique and Trimble Geomantic Survey (TGO) software. Generally the monitored points for the Twin Tower Building experience movements within 1 mm to 10 mm. For Innovation Centre Building monitored points seem to shift between 1 mm to 9 mm. Detection of movement for both buildings structure seems to be within the allowable tolerance. It is shown that monitoring building structure using the techniques adopted in this study has significant advantages and disadvantages.