Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud

Benthic habitat complexity can be explained as habitat species that lives in the bottom of seafloor which play an important role in marine biodiversity. Therefore, the existence of benthic habitats can affect the surface complexity such as coral reefs habitats. Rugosity measurement is one of the...

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Main Author: Mohd Sayud, Nur Asikin
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/22528/
http://ir.uitm.edu.my/id/eprint/22528/1/TD_NUR%20ASIKIN%20MOHD%20SAYUD%20AP%20R%2018.5.PDF
id uitm-22528
recordtype eprints
spelling uitm-225282019-01-11T00:58:38Z http://ir.uitm.edu.my/id/eprint/22528/ Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud Mohd Sayud, Nur Asikin Slopes (Physical geography) GC Oceanography Algorithms Benthic habitat complexity can be explained as habitat species that lives in the bottom of seafloor which play an important role in marine biodiversity. Therefore, the existence of benthic habitats can affect the surface complexity such as coral reefs habitats. Rugosity measurement is one of the ways that can be used to understand the complexity of the seafloor. For example, marine biologists using rugosity measurement in order to understand the growth and pattern of the coral reefs and to identify the existing of coral reefs. There are several methods that can be used in determine the rugosity which are using virtual area based rugosity and virtual chain tape rugosity. As for this study, virtual area based is been used which applied to bathymetry data set that has been collected by using R2 Sonic 2020. In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. Thus, focus of this study is to determine the best model that can be used to detect coral reefs area and to know the capabilities of slope variability model. In this study, rugosity is been developed by using QPS Fledermaus software. In ArcGlS software, DEM data will be process by using terrain roughness model that has been derived by using Slope Variability algorithm. Slope surface is been created in BTM by using same of DEM data. Then, accuracy assessment has been done by comparing the model from Fledermaus and BTM with slope variability model as to know the capabilities of those models in detecting the corals reefs area. Results shows in a percentage values which are 92% of similarity for QPS Fledermaus and slope variability model result and lastly 90% of similarity for BTM and slope variability model result. 2018-12 Thesis NonPeerReviewed other en http://ir.uitm.edu.my/id/eprint/22528/1/TD_NUR%20ASIKIN%20MOHD%20SAYUD%20AP%20R%2018.5.PDF Mohd Sayud, Nur Asikin (2018) Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud. Degree thesis, Universiti Teknologi Mara Perlis.
repository_type Digital Repository
institution_category Local University
institution Universiti Teknologi MARA
building UiTM Institutional Repository
collection Online Access
language English
topic Slopes (Physical geography)
GC Oceanography
Algorithms
spellingShingle Slopes (Physical geography)
GC Oceanography
Algorithms
Mohd Sayud, Nur Asikin
Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
description Benthic habitat complexity can be explained as habitat species that lives in the bottom of seafloor which play an important role in marine biodiversity. Therefore, the existence of benthic habitats can affect the surface complexity such as coral reefs habitats. Rugosity measurement is one of the ways that can be used to understand the complexity of the seafloor. For example, marine biologists using rugosity measurement in order to understand the growth and pattern of the coral reefs and to identify the existing of coral reefs. There are several methods that can be used in determine the rugosity which are using virtual area based rugosity and virtual chain tape rugosity. As for this study, virtual area based is been used which applied to bathymetry data set that has been collected by using R2 Sonic 2020. In this study, several models has been created which are from QPS Fledermaus model, BTM model and Slope Variability model. Slope variability model is an algorithm that is being used for detecting terrain roughness. Thus, focus of this study is to determine the best model that can be used to detect coral reefs area and to know the capabilities of slope variability model. In this study, rugosity is been developed by using QPS Fledermaus software. In ArcGlS software, DEM data will be process by using terrain roughness model that has been derived by using Slope Variability algorithm. Slope surface is been created in BTM by using same of DEM data. Then, accuracy assessment has been done by comparing the model from Fledermaus and BTM with slope variability model as to know the capabilities of those models in detecting the corals reefs area. Results shows in a percentage values which are 92% of similarity for QPS Fledermaus and slope variability model result and lastly 90% of similarity for BTM and slope variability model result.
format Thesis
author Mohd Sayud, Nur Asikin
author_facet Mohd Sayud, Nur Asikin
author_sort Mohd Sayud, Nur Asikin
title Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
title_short Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
title_full Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
title_fullStr Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
title_full_unstemmed Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detection / Nur Asikin Mohd Sayud
title_sort comparing seabed roughness result from qps fledermaus software, benthic trrain modeler [btm] and developed model derived frm slope variability algorithm for hard coral reef detection / nur asikin mohd sayud
publishDate 2018
url http://ir.uitm.edu.my/id/eprint/22528/
http://ir.uitm.edu.my/id/eprint/22528/1/TD_NUR%20ASIKIN%20MOHD%20SAYUD%20AP%20R%2018.5.PDF
first_indexed 2023-09-18T23:08:51Z
last_indexed 2023-09-18T23:08:51Z
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