Papers by Muhammad Zulkarnain Abd Rahman
Journal of Information System and Technology Management
Landslide activity identification is critical for landslide inventory mapping. A detailed landsli... more Landslide activity identification is critical for landslide inventory mapping. A detailed landslide inventory map is highly required for various purposes such as landslide susceptibility, hazard, and risk assessments. This paper proposes a novel approach based on vegetation anomalies indicator (VAI) and applying machine learning method namely support vector machine (SVM) to identify status of natural-terrain landslides. First, high resolution airborne LiDAR data and satellite imagery were used to derive landslide-related VAIs, including tree height irregularities, canopy gap, density of different layer of vegetation, vegetation type, vegetation indices, root strength index (RSI), and distribution of water-loving trees. Then, SVM is utilized with different setting of parameter using grid search optimization. SVM Radial Basis Function (RBF) recorded the best optimal pair value with 0.062 and 0.092 misclassification rate for deep seated and shallow translational landslide, respectively...
This paper presents a new method for individual tree measurement from Airborne LiDAR data. This m... more This paper presents a new method for individual tree measurement from Airborne LiDAR data. This method involves 3 steps; 1) individual tree crown delineation based on density of high points (DHP), 2) tree filtering, and 3) measurement of tree trunk diameter at breast height (DBH). In the second step, a special tree filtering algorithm is introduced which combines a histogram analysis and region growing (RG) segmentation method. In forest area, undergrowth vegetation is considered as noise and it should be removed to ease the DBH measurement process of trees. The DBH measurement on point cloud is done based on two steps; 1) three-dimensional line fitted on points of tree trunk, and 2) histogram analysis of distances between points and the line. It shows that more than 60% trees are successfully filtered and compared to the actual DBH measurement in the field the DBH estimations on point cloud have the root mean square error of 0.18 m.
Computational Speed and Qualitative Assessment of Real-Time Image Stitching Algorithm
2021 International Conference on Communication, Control and Information Sciences (ICCISc), 2021
In remote sensing and environmental mapping, Unmanned Aerial Vehicle (UAV) has been used extensiv... more In remote sensing and environmental mapping, Unmanned Aerial Vehicle (UAV) has been used extensively to capture images. For many years, digital maps are generated by using a method called image stitching. It is a method of combining multiple images to produce a segmented panorama. Since this method has been commonly used, many users produce an accurate map by using commercial software. However, a downside of this commercial software is a long computational time which is not appropriate for immediate mapping activities at chaos areas in particularly during rescue missions. This paper proposes a method to speed up the process of map generation by using a revised real-time image stitching algorithm including the qualitative assessments. In this research, the images are extracted from a video taken by a drone that flies in a dedicated flight path. These videos are then immediately transmitted to a ground station for further image processing and computation. The overlapping images are stitched and later undergoes features extraction process to identify the common features between the images. These common features are used to compute homography matrix which beneficial for image wrapping. The finding of this study suggests that ORB and AKAZE are the most suitable descriptors to be used in real-time image stitching because of their fast computational speed at adequate level quality. For instance, at 5 number of skip frame, ORB is at least 2-fold faster than AKAZE and goes up to 10-fold faster than BRISK.
IOP Conference Series: Earth and Environmental Science, 2018
Spatio-temporal analysis of Kilim River using Very High-Resolution (VHR) satellite image between ... more Spatio-temporal analysis of Kilim River using Very High-Resolution (VHR) satellite image between the years of 2005 and 2012 are vital to assess river morphological changes and erosion detection over the specific time duration. Therefore, this study utilizes remote sensing and Geographical Information System (GIS) capabilities to identify the channel migration and shifting as well as to calculate the rate of erosion and accretion. Classification of the river from Quickbird and WorldView-2 images is carry out using Maximum Likelihood Classification (MLC) technique whereas feature selection tool performs to extract river feature from the raw image. Subsequently, river feature been overlaid to identify the changes of riverbank pattern and to calculate the rate of riverbank erosion in terms of area. The result shows the total area of erosion is 27252.959 m 2 and the total area of accretion is 6079.999 m 2. A maximum erosion of 6993.102 m 2 detected at Section E while maximum accretion of 681.026 m 2 spotted at Section D. The rates of riverbank erosion are 3406.62 m 2 /year while the rates for accretion are 759.999 m 2 /years between 2005 and 2012. Hence, the output of this study enables Langkawi Development Authority (LADA) and other stakeholders to recognize the specific location, which severely affected by erosion and accretion as well as to spot the area experienced huge river channel shifting.
Multi-resolution remote sensing data in landslide activity inventory mapping
IOP Conference Series: Earth and Environmental Science, 2018
This paper reviews an application of multi-resolution remote sensing data in landslide activity i... more This paper reviews an application of multi-resolution remote sensing data in landslide activity inventory mapping. Landslide activity is an important component for landslide study. On that basis, remote sensing technology become a standard method in getting and deriving the information related to landslide events. The capability of remote sensing technology in acquiring the geospatial data have accelerate the process of landslide activity inventory mapping. A general overview of several remote sensing techniques applied to landslides is given, followed by a review of landslide characteristics and landslide activity inventory mapping. This paper also emphasizes on the role of vegetation anomalies as bio-indicator for landslide activity inventory mapping. Five (5) indicators have been listed together with the findings from previous research. This kind of approach has opening a new perspective of landslide activity inventory mapping which integrating with multi-resolution remote sensing data that significantly increase the effectiveness of any landslide studies.
Flood Risk Assessment for Kota Tinggi, Johor, Malaysia
Geospatial Technology for Water Resource Applications, 2016
A massive flood event, which hit Kelantan in 2014, has contributed a major destruction particular... more A massive flood event, which hit Kelantan in 2014, has contributed a major destruction particularly at Kuala Krai district. An alternative approach to overcome this flood episode is by constructing dams. In this study, two dams proposed at the upstream of Galas and Lebir river, near Kuala Krai. This paper aims to assess the implementation of the proposed dams which is a structural approach at the upstream area to reduce flood hazard in Kelantan using a hydrodynamic model. A coupled of 1D and 2D hydrodynamic model have been tested to simulate the occurrence of flood events in Kelantan due to the proposed dams. The Digital Terrain Model (DTM) has been generated by combining the data sources; i.e. from Airborne LiDAR and SRTM. The design of proposed dams were defined based on 50 years flood characteristics proposed by UPEN and simulated into the DTM with different magnitudes of flood. The flow hydrograph and water level for 25, 100 and 200-year return period are generated as input data...
International Journal of Built Environment and Sustainability, 2019
Airborne Light Detection and Ranging (LiDAR) has been very effectively used in collecting terrain... more Airborne Light Detection and Ranging (LiDAR) has been very effectively used in collecting terrain information over different scales of area. Inevitably, filtering the non-ground returns is the major step of digital terrain model (DTM) generation and this step poses the greatest challenge especially for tropical forest environment which consists of steep undulating terrain and mostly covered by a relatively thick canopy density. The aim of this research is to assess the performance of the Progressive Morphological (PM) algorithm after the implementation of local slope value in the ground filtering process. The improvement on the PM filtering method was done by employing local slope values obtained either using initial filtering of airborne LiDAR data or ground survey data. The filtering process has been performed with recursive mode and it stops after the results of the filtering does not show any improvement and the DTM error larger than the previous iteration. The revised PM filter...
The effects of climate change on flood hazards in Kelantan River Basin Malaysia
IOP Conference Series: Earth and Environmental Science, 2021
Climate change has had a significant impact on the hydrological cycle, causing changes in precipi... more Climate change has had a significant impact on the hydrological cycle, causing changes in precipitation patterns in both frequency and magnitude. The aim of this study is to assess the effect of climate change on flood hazards in Kelantan River Basin, Malaysia. A distributed hydrological model called Rainfall-Runoff-Inundation (RRI) simulates floods under current and future climate scenarios. The Climate Change Factor (CCF) is a tool for forecasting future climate scenarios. The storm used in this analysis had 50-year and 100-year recurrence intervals every 24 hours (ARI). The finding shows that the streamflow in Guillemard station will increase in the future for both the 50- and 100-year ARI. The streamflow increased to 10329 m3/s from 8434.9 m3/s in the current state and to 11220.2 m3/s from 9157.4 m3/s in the 50- and 100-year ARI, respectively. In both cases, the 100-year ARI flood magnitude is significantly less than the 50-year ARI flood extent (current and future). However, th...
IOP Conference Series: Earth and Environmental Science, 2018
Land Use/Land Cover (LULC) is essential in planning and management activities especially for cons... more Land Use/Land Cover (LULC) is essential in planning and management activities especially for conserving eco-environment, soil and vegetation research as well as urban planning. Higher resolution imagery and accuracy of LULC for monitoring ecosystem survival are preferred especially when it takes into account environmental issues. Langkawi had faced problems related to environmental issues after it has been designated as a geopark. Therefore, this study aims to map and evaluate digital classification methods of mapping of LULC using Very High Resolution (VHR) Quickbird satellite imagery in one of the Langkawi UNESCO Global Geopark, that is Kilim Karst Geoforest Park (KKGP) which is located at northeast of Langkawi, Kedah, Malaysia. Object-based and pixel-based classification methods were explored and compared. Object-based method involved multi-resolution segmentation part where scale parameter, shape and compactness should be assigned as accurate as possible, so that the image is segmented to homogenous area. Both segmentation and classification processes were conducted in e-Cognition software. While, a supervised classification, Maximum Likelihood Classification (MLC) involved selection of training areas was used for pixel-based method using ERDAS Imagine software. Then, classification accuracies were assessed by comparing both techniques using error matric and Kappa coefficient. The results from the classified image shows that the object-based approach provides more accurate results with an overall accuracy of approximately 87.91% and Kappa coefficient of 0.85 compared to the results achieved by MLC pixel-based classification with 72.21 % accuracy and Kappa coefficient of 0.66. As a conclusion, the results indicated that object-based technique has more advantages to be applied with VHR imagery for better environmental management and conservation actions.
Hydrology, 2019
The advent of satellite rainfall products can provide a solution to the scarcity of observed rain... more The advent of satellite rainfall products can provide a solution to the scarcity of observed rainfall data. The present study aims to evaluate the performance of high spatial-temporal resolution satellite rainfall products (SRPs) and rain gauge data in hydrological modelling and flood inundation mapping. Four SRPs, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) - Early, - Late (IMERG-E, IMERG-L), Global Satellite Mapping of Precipitation-Near Real Time (GSMaP-NRT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks- Cloud Classification System (PERSIANN-CCS) and rain gauge data were used as the primary input to a hydrological model, Rainfall-Runoff-Inundation (RRI) and the simulated flood level and runoff were compared with the observed data using statistical metrics. GSMaP showed the best performance in simulating hourly runoff with the lowest relative bias (RB) and the highest Nash-Sutcliffe efficiency (...
Singapore Journal of Tropical Geography, 2017
The Royal Belum forest reserve is one of the oldest tropical rainforests in the world and it is o... more The Royal Belum forest reserve is one of the oldest tropical rainforests in the world and it is one of the largest virgin forest reserves in Malaysia. However, not many studies have been conducted to understand the ecology of this forest. In this study we estimated the aboveground biomass (AGB) of the forest using diameter at breast height (DBH) and height of trees (h), tree species and hemispherical photographs of tree canopy. We estimated AGB using five allometric equations. Our results demonstrated that the AGB given by the one tree species specific allometric equation does not show any significant differences from the values given by the non-tree species specific allometric equations at tree and plot levels. The AGB of Intsia bijuga species, Koompassia malaccensis species and Shorea genera were comparatively higher, owing to their greater wood density, DBH and h. This has added importance because some of these species are categorized as threatened species. Our results demonstrated that mean AGB values in this forest (293.16 t ha-1) are the highest compared to some studies of other areas in Malaysia, tropical Africa and tropical Bazilian Amazonia, implying that the Royal Belum forest reserve, is an important carbon reservoir.
Forests, 2017
Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been... more Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been driven by advances in remote sensing technology. The conventional approach to biomass estimation heavily relies on the tree species and site-specific allometric equations, which are based on destructive methods. This paper introduces a non-destructive, laser-based approach (terrestrial laser scanner) for individual tree aboveground biomass estimation in the Royal Belum forest reserve, Perak, Malaysia. The study area is in the state park, and it is believed to be one of the oldest rainforests in the world. The point clouds generated for 35 forest plots, using the terrestrial laser scanner, were geo-rectified and cleaned to produce separate point clouds for individual trees. The volumes of tree trunks were estimated based on a cylinder model fitted to the point clouds. The biomasses of tree trunks were calculated by multiplying the volume and the species wood density. The biomasses of branches and leaves were also estimated based on the estimated volume and density values. Branch and leaf volumes were estimated based on the fitted point clouds using an alpha-shape approach. The estimated individual biomass and the total above ground biomass were compared with the aboveground biomass (AGB) value estimated using existing allometric equations and individual tree census data collected in the field. The results show that the combination of a simple single-tree stem reconstruction and wood density can be used to estimate stem biomass comparable to the results usually obtained through existing allometric equations. However, there are several issues associated with the data and method used for branch and leaf biomass estimations, which need further improvement.
Flood Impact Assessment using Geospatial Technologies and Hydrodynamic Modelling
Flood occurred when heavy and continuous rainfall exceeding the absorptive capacity of soil and t... more Flood occurred when heavy and continuous rainfall exceeding the absorptive capacity of soil and the flow capacity of rivers, streams, and coastal areas. Land areas that are most subjected to floods are areas situated adjacent to rivers and streams, that are known as floodplain and therefore considered as "flood-prone". These areas are hazardous to development activities if the vulnerability of those activities exceeds an acceptable level. According to the Department of Irrigation and Drainage in Malaysia, about 29, 000 sq. km, or 9% of the total land area and more than 4.82 million people (i.e. 22% of the population) are affected by flooding annually. Damage caused by flooding is estimated about RM 915 million (£160 million). An unprecedented heavy rainfall occurred in Malaysia in December 2006 to January 2007. The consequence of this extreme event has resulted severe impact on few area of Malaysia where Kota Tinggi in Johor state is one the affected area. The objectives o...
Flood Risk Mapping in Kota Tinggi, Malaysia
ABSTRACT According to the Department of Irrigation and Drainage in Malaysia, about 29, 000 sq. km... more ABSTRACT According to the Department of Irrigation and Drainage in Malaysia, about 29, 000 sq. km, or 9% of the total land area and more than 4.82 million people (i.e. 22% of the population) are affected by flooding annually. Damage caused by flooding is estimated about RM 915 million (£160 million). An unprecedented heavy rainfall occurred in Malaysia in December 2006 to January 2007. The consequence of this extreme event has resulted severe impact on few area of Malaysia where Kota Tinggi in Johor state is one the affected area. The objectives of this study are 1) to study the capability of SOBEK for flood simulation, 2) to study the impact of different flood scenarios on those elements in inundated area. Different types of flood maps have been developed where each flood maps is conveyed its spatial information to the end-users. Of these flood maps, flood risk map is very essential as it includes information on the consequences of flooding. Risk results from the interaction of hazard and vulnerability.
Estimation of hydrodynamic roughness over land in tropical environment using lidar data: a case study in Ayer Keroh, Melaka
Parameterization of flood modeling overland has benefited from Airborne LiDAR technologies in man... more Parameterization of flood modeling overland has benefited from Airborne LiDAR technologies in many ways and one of the prominent examples is the estimation of hydrodynamic roughness. Low density airborne LiDAR with relatively low penetration over vegetation canopy under leaf-on condition further complicate the estimation of hydrodynamic roughness in tropical zone. This paper will present a detail investigation on the capability of airborne LiDAR data for hydrodynamic roughness estimation over tropical region in Air Keroh, Melaka, Malaysia. The study area is divided into four landcover classes i.e. building, forest, grassland and paved road. The airborne LiDAR data was obtained using the Optech ALTM 3100 in 2009 with a posting density of about 0.69 point per meter squared. The estimation of composite hydrodynamic roughness consists of four processing stages namely 1) landcover classification, 2) estimation of parameters as required by the hydrodynamic roughness, 3) estimation of hydrodynamic roughness of individual landcover class and 4) estimation of composite hydrodynamic roughness with different spatial resolutions. In the first stage, the landcover classification is performed by using Support Vector Machine (SVM) on the aerial photo of the study area obtained simultaneously with the airborne LiDAR. Estimation of hydrodynamic value for each landcover class requires different hydrodynamic models expressed by Manning's (n), Chezy (c), and Darcy (f) coefficients. The calculation of hydrodynamic roughness for each landcover class should be done separately, in which finally will be merged at specific spatial resolution to produce composite hydrodynamic roughness map represented by the Manning's n coefficient. In the stage of hydrodynamic roughness estimation building, forest, grassland and paved road require estimation of momentum absorption area, tree density, height of grass and area classified as road respectively. These parameters will be estimated by using airborne LiDAR data and aerial photograph. Estimation of tree density requires delineation of individual trees in forest area. Tree density and diameter at breast height (DBH) of individual tree is then estimated for each tree based on allometric equation. The overall accuracy for landcover classification is 96% with user and producer accuracies more than 80%. The results show that based on the airborne LiDAR data, the height of grass and tree DBH can be estimated with about 0.33m and 0.22m RMSE respectively. Finally, the composite hydrodynamic roughness is calculated based on the conventional averaging concept, which integrates different landcover types in a specific piece of land (spatial resolution).
Expectation for the presence of hydrocarbon seepage in onshore tropical region, case study in Miri Sarawak Malaysia
Long term course of hydrocarbon seepage on material sediment and water alters mineralogical compo... more Long term course of hydrocarbon seepage on material sediment and water alters mineralogical composition with corresponding change in chemical and physical properties of rocks and soils. This changes color, hardness, electric, magnetic and radioactive properties of minerals. This alteration product occurs at the surface coincide with the original product of seepage, namely gas emanation, crude oil and brine water effluent resulting change in fertilities rank soils and vegetation manifest which indicated with vegetation stress and bare development. This leads to change refection, absorption accompany with change in albedo, change in surface thermodynamic and emission properties accompany with change in land surface temperature (LST). District of Miri, Serawak state of Malaysia is used for study area. This area is an urban area, located in the tropical region with the complex land cover system around the city. It is potentially having some hydrocarbon seepage due to existing petroleum system. Topographic map of Miri was used to make boundary of internal and external seepage potential area, and LANDSAT ETM+ was used to derivate of albedo and day time land surface temperature. The objective of study is to detect hydrocarbon seepage in onshore area through the investigation of land use / cover anomaly on surface albedo and land surface temperature. Intensive land use / cover classification and corresponding comparison of statistical analysis were performed on albedo, land surface temperature between internal and external seepage potential area. Two dimensional cross plots was also applied to obtain the probable location of seepage. The result clearly shows that the presence of hydrocarbon shifted albedo and LST. The shift was vary with different land use / cover class. The shift was relevant with the resulted pattern of two dimensional cross plots. The cross plots pattern was also shows the probable location of hydrocarbon infected area. According to shift direction, two dimensional cross plots pattern, and employing statistical mean value of albedo and LST in internal seepage potential area for each class allows to expecting the region for the presence of hydrocarbon seepage.
Flood risk mapping using geospatial techniques and hydraulic model
Flood maps are a vital tool to provide various valuable information for reducing flood damage and... more Flood maps are a vital tool to provide various valuable information for reducing flood damage and spatial planning purposes. Only the flood risk map provides the consequences information of flooding, which used as a primary tool to initiative a holistic flood risk management project. Geospatial data such as satellite image and LiDAR data as well as hydrological data are used to produce flood maps with using integrated one and two dimensional hydraulic model. Risk is a production of hazard and vulnerability. Flood Risk is expressed as loss in term of monetary and flood risk zone for quantitative map and qualitative map, respectively. Three different depth damage functions were adopted to estimate the flood damage for three different physical elements. The average flood damage for residential areas is RM 350/m2, RM 200/m2 and RM 100/m2 using United States, The Netherlands and Malaysia damage functions. This study successfully produces flood risk but further study is needed for improve the results
Flood Risk Mapping using Geospatial Technologies and Hydraulic Model
ABSTRACT Flood maps are a vital tool to provide various valuable information for reducing flood d... more ABSTRACT Flood maps are a vital tool to provide various valuable information for reducing flood damage and spatial planning purposes. Only the flood risk map provides the consequences information of flooding, which used as a primary tool to initiative a holistic flood risk management project. Geospatial data such as satellite image and LiDAR data as well as hydrological data are used to produce flood maps with using integrated one and two dimensional hydraulic model. Risk is a production of hazard and vulnerability. Flood Risk is expressed as loss in term of monetary and flood risk zone for quantitative map and qualitative map, respectively. Three different depth damage functions were adopted to estimate the flood damage for three different physical elements. The average flood damage for residential areas is RM 350/m2, RM 200/m2 and RM 100/m2 using United States, The Netherlands and Malaysia damage functions. This study successfully produces flood risk but further study is needed for improve the results.
Uploads
Papers by Muhammad Zulkarnain Abd Rahman