Proceedings of the 3rd International Conference on Civil, Offshore and Environmental Engineering (ICCOEE 2016, Malaysia, 15-17 Aug 2016), 2016
Digital elevation model (DEM) is the most common surface topography data used to derive river net... more Digital elevation model (DEM) is the most common surface topography data used to derive river network. DEM comes with different resolutions and can generate various topographic and hydrological features. This study investigates the effects DEM’s threshold values from different sources in deriving stream networks using Geospatial Hydrologic Modelling Extension (HEC-GeoHMS). DEMs of 30m resolution were acquired from SRTM, ASTER, and NEXTMap data. In addition, topographic DEM were derived from con-tour data of 20 m interval to generate the stream network on the sub-basin of Jawi river, Penang, Malaysia. Subsequently, spatial comparison was made with the existing drainage networks derived from the Malaysian Department of Irrigation and Drainage (DID). The analysis reveals that the drainage network from SRTM with threshold values of 40 was closest to the referenced drainage. The result has signifies the most appropri-ate values for an effective stream threshold network to be considered suitable for future river sub-basin analy-sis.
This paper briefly introduced the theory and framework of geospatial site selection (GSS) and dis... more This paper briefly introduced the theory and framework of geospatial site selection (GSS) and discussed the application and framework of artificial neural networks (ANNs). The related literature on the use of ANNs as decision rules in GSS is scarce from 2000 till 2015. As this study found, ANNs are not only adaptable to dynamic changes but also capable of improving the objectivity of acquisition in GSS, reducing time consumption, and providing high validation. ANNs make for a powerful tool for solving geospatial decision-making problems by enabling geospatial decision makers to implement their constraints and imprecise concepts. This tool offers a way to represent and handle uncertainty. Specifically, ANNs are decision rules implemented to enhance conventional GSS frameworks. The main assumption in implementing ANNs in GSS is that the current characteristics of existing sites are indicative of the degree of suitability of new locations with similar characteristics. GSS requires several input criteria that embody specific requirements and the desired site characteristics, which could contribute to geospatial sites. In this study, the proposed framework consists of four stages for implementing ANNs in GSS. A multilayer feed-forward network with a backpropagation algorithm was used to train the networks from prior sites to assess, generalize, and evaluate the outputs on the basis of the inputs for the new sites. Two metrics, namely, confusion matrix and receiver operating characteristic tests, were utilized to achieve high accuracy and validation. Results proved that ANNs provide reasonable and efficient results as an accurate and inexpensive quantitative technique for GSS.
Pemahaman berkenaan penerbitan atas talian (online) mampu meningkatkan kesedaran para akademik da... more Pemahaman berkenaan penerbitan atas talian (online) mampu meningkatkan kesedaran para akademik dalam memastikan penarafan Universiti Sains Malaysia (USM) dianjak ke taraf antarabangsa. Jurnal penerbitan atas talian mampu menjadi rujukan antarabangsa dan hasil kertas kerja tersebut akan dirujuk (cite). Maka wujudnya pengiktirafan penulis melalui h-indeks bagi menunjukkan hasil kertas kerja dirujuk. H-indeks adalah indeks yang mengukur kedua-dua produktiviti berdasarkan set jurnal dan bilangan petikan sitasi (citation) adalah seperti dalam Rajah 1 (Wikipedia, 2013). Secara amnya, semakin tinggi nilai h-indeks semakin tinggi hasil jurnalnya dihargai melalui pendekatan sitasi. Walau bagaimanapun, sekiranya seseorang sarjana tersebut menghasilkan banyak jurnal tetapi bilangan sitasi rendah maka sarjana tersebut akan memperoleh h-indeks yang rendah. Oleh itu, bilangan jurnal yang dihasilkan perlu mementingkan bilangan sitasi bagi memastikan jurnal tersebut dirujuk dan menunjukkan berlakun...
Proceedings of the 3rd International Conference on Civil, Offshore and Environmental Engineering (ICCOEE 2016, Malaysia, 15-17 Aug 2016), 2016
Digital elevation model (DEM) is the most common surface topography data used to derive river net... more Digital elevation model (DEM) is the most common surface topography data used to derive river network. DEM comes with different resolutions and can generate various topographic and hydrological features. This study investigates the effects DEM’s threshold values from different sources in deriving stream networks using Geospatial Hydrologic Modelling Extension (HEC-GeoHMS). DEMs of 30m resolution were acquired from SRTM, ASTER, and NEXTMap data. In addition, topographic DEM were derived from con-tour data of 20 m interval to generate the stream network on the sub-basin of Jawi river, Penang, Malaysia. Subsequently, spatial comparison was made with the existing drainage networks derived from the Malaysian Department of Irrigation and Drainage (DID). The analysis reveals that the drainage network from SRTM with threshold values of 40 was closest to the referenced drainage. The result has signifies the most appropri-ate values for an effective stream threshold network to be considered suitable for future river sub-basin analy-sis.
This paper briefly introduced the theory and framework of geospatial site selection (GSS) and dis... more This paper briefly introduced the theory and framework of geospatial site selection (GSS) and discussed the application and framework of artificial neural networks (ANNs). The related literature on the use of ANNs as decision rules in GSS is scarce from 2000 till 2015. As this study found, ANNs are not only adaptable to dynamic changes but also capable of improving the objectivity of acquisition in GSS, reducing time consumption, and providing high validation. ANNs make for a powerful tool for solving geospatial decision-making problems by enabling geospatial decision makers to implement their constraints and imprecise concepts. This tool offers a way to represent and handle uncertainty. Specifically, ANNs are decision rules implemented to enhance conventional GSS frameworks. The main assumption in implementing ANNs in GSS is that the current characteristics of existing sites are indicative of the degree of suitability of new locations with similar characteristics. GSS requires several input criteria that embody specific requirements and the desired site characteristics, which could contribute to geospatial sites. In this study, the proposed framework consists of four stages for implementing ANNs in GSS. A multilayer feed-forward network with a backpropagation algorithm was used to train the networks from prior sites to assess, generalize, and evaluate the outputs on the basis of the inputs for the new sites. Two metrics, namely, confusion matrix and receiver operating characteristic tests, were utilized to achieve high accuracy and validation. Results proved that ANNs provide reasonable and efficient results as an accurate and inexpensive quantitative technique for GSS.
Pemahaman berkenaan penerbitan atas talian (online) mampu meningkatkan kesedaran para akademik da... more Pemahaman berkenaan penerbitan atas talian (online) mampu meningkatkan kesedaran para akademik dalam memastikan penarafan Universiti Sains Malaysia (USM) dianjak ke taraf antarabangsa. Jurnal penerbitan atas talian mampu menjadi rujukan antarabangsa dan hasil kertas kerja tersebut akan dirujuk (cite). Maka wujudnya pengiktirafan penulis melalui h-indeks bagi menunjukkan hasil kertas kerja dirujuk. H-indeks adalah indeks yang mengukur kedua-dua produktiviti berdasarkan set jurnal dan bilangan petikan sitasi (citation) adalah seperti dalam Rajah 1 (Wikipedia, 2013). Secara amnya, semakin tinggi nilai h-indeks semakin tinggi hasil jurnalnya dihargai melalui pendekatan sitasi. Walau bagaimanapun, sekiranya seseorang sarjana tersebut menghasilkan banyak jurnal tetapi bilangan sitasi rendah maka sarjana tersebut akan memperoleh h-indeks yang rendah. Oleh itu, bilangan jurnal yang dihasilkan perlu mementingkan bilangan sitasi bagi memastikan jurnal tersebut dirujuk dan menunjukkan berlakun...
Journal of Environmental Modeling and Software,, Jan 1, 2003
Geographic Information Systems (GIS) are an efficient and interactive spatial decision support to... more Geographic Information Systems (GIS) are an efficient and interactive spatial decision support tool for flood risk analysis. This paper describes the development of ArcView GIS extension — namely AVHEC-6.avx — to integrate the HEC-6 hydraulic model within GIS environment. The extension was written in an Avenue Script language and Dialog Designer with a series of ‘point and click’ options. It has the capability of analyzing the computed water surface profiles generated from HEC-6 model and producing a related flood map for the Pari River in the ArcView GIS. The user-friendly menu interface guides the user to understand, visualize, build query, conduct repetitious and multiple analytical tasks with HEC-6 outputs. The flood risk model was tested using the hydraulic and hydrological data from the Pari River catchment area. The required sediment input parameters were obtained from field sampling. The results of this study clearly show that GIS provides an effective environment for flood risk analysis and mapping. The present study only concentrates on the flood risk within the boundary of the bunds.
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Papers by Mohd Sanusi Ahamad