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Your search keyword '"Rasib, Abd Wahid"' showing total 30 results
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30 results on '"Rasib, Abd Wahid"'

11. Landsat 8 data to an invention a permanent seasonal model of water quality parameters in Tigris River-Iraq.

Author

Abbas, Malik R., Rasib, Abd Wahid Bin, Abbas, Talib R., and Ahmad, Baharin Bin

Subjects
*WATER quality, *LANDSAT satellites, *SPRING, *AUTUMN, *SEASONS, *MULTIPLE regression analysis, BABYLON (Extinct city)
Abstract

Empirical models have been developed in this study to predict water quality parameters, with the intention of demonstrating both benefits and the viability of using Landsat 8 spectral images to estimate water quality parameters in one main of the Iraqi Rivers, it is the Tigris River. The study area was along the part of the Tigris River which is located in Baghdad (capital) and Babylon governorate, in the middle part of Iraq. Water quality data archive for the of total dissolved solids (TDS), phosphates (PO4), Sulfate (SO4), and total hardness (TH) of the water Tigris river during four seasons (winter, spring, summer, and autumn) distributed along four years (2013, 2014, 2015 and 2017), was collected from sixteen ground stations along the part of Tigris river. The objective of this study to establish seasonal empirical mathematical models can use them every year during the season time without the need for calibration every time. For this purpose, has been following the different approach when compared with all of the studies which are carried before by collecting data for the same season and for different years. Prior to the establishment of the models, both preprocessing of data as radiometric and atmospheric corrections were applied to the optical data. Through multiple regression analysis between measured water quality parameters of the ground stations and the reflectance of the pixels corresponding to the sampling stations. Statistical models with determination coefficients between 0.89 - 0.95 were generated. Results indicate this novelty approach has generated mathematical models for the open time for any year but in the special season. Another indicator that from a small number of measured parameters can generate reliable models to estimate the concentration of TDS, PO4, SO4, and TH. So models generated from Landsat 8 can be used as a tool to facilitate the environmental, economic, and social management of the surface waters bodies like a Tigris river. [ABSTRACT FROM AUTHOR]

Published
2022
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12. Bridge Pillar Defect Detection using Close Range Thermography Imagery

Author

Rasib, Abd Wahid, primary, Yaacob, Muhammad Latifi Mohd, additional, Idris, Nurul Hawani, additional, Zainuddin, Khairulazhar, additional, Dollah, Rozilawati, additional, Yusof, Norbazlan Mohd, additional, Rahaman, Norisam Abd, additional, Ahmad, Shahrin, additional, Hamid, Norhadi A., additional, and Mhapo, Abdul Manaf, additional

Published
2022
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21. Rubber Leaf Disease Detection from Low Altitude Remote Sensing Techniques

Author

Hamid, Nurmi-Rohayu Abdul, primary, Ghani, Zarawi Abd, additional, Mahsuri, Ikhsan, additional, Yusoff, Muhammad Asraff Mohd, additional, Rasib, Abd Wahid, additional, Yusoff, Abdul Razak Mohd, additional, Rahman, Muhammad Zulkarnain Abdul, additional, Kadir, Wan Hazli Wan, additional, Zainon, Othman, additional, Dollah, Rozilawati, additional, Sari, Muhammad Yazid Abu, additional, and Ahmad, Asmala, additional

Published
2018
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22. Oil Palm Yield Prediction Using Low-Cost Unmanned Aerial Vehicle Platform

Author

Sari, Nasruddin Abu, primary, Rasib, Abd Wahid, additional, Ropi, Nur Amalina Mohd, additional, Ahmad, Asmala, additional, Sari, Mohd Yazid Abu, additional, Suri, Muhammad Akmal, additional, Yusoff, Abd Razak Mohd, additional, Daliman, Shaparas, additional, Shin, Alvin Lau Meng, additional, Zainon, Othman, additional, Dollah, Rozilawati, additional, and Ahmad, Mustaffa Anjang, additional

Published
2018
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24. Per-pixel and sub-pixel classifications of high-resolution satellite data for mangrove species mapping

Author

Kanniah, Kasturi Devi, Wai, Ng Su, Shin, Alvin Lau Meng, and Rasib, Abd. Wahid

Subjects
Uncategorized
Abstract

High spatial resolution sensors such as IKONOS and QuickBird, are expected to classify mangrove species more accurately than coarse spatial resolution satellite images. Conventional per-pixel classification techniques could not improve the classification accuracy when such high-resolution images are applied. Such failure has encouraged the invention of more sophisticated and deterministic techniques i.e. subpixel classifications. In this study, the mangrove forest at Sungai Belungkor, Johor, Malaysia was classified using IKONOS data. Two classification approaches were applied, namely per-pixel and sub-pixel techniques. The conventional per-pixel classifiers used in this study were Maximum Likelihood (ML), Minimum Distance to Mean (MDM) and Contextual Logical Channel (CLC) while the Linear Mixture Model (LMM) was selected as the sub-pixel classification approach. The classification results revealed that the CLC classification with a contrast texture measure at window size 21 x 21 yielded the highest accuracy (82%) in comparison to the ML (68%) or MDM (64%). The spatial distribution of the classified mangrove species and classes coincided with the common mangrove zones in Malaysia. For the results of the LMM, the fraction of pixels measured from the satellite imagery and observed in the field gave a good correlation with an R2 value of 0.83 for Bakau minyak, a moderate correlation with an R2 of approximately 0.71 for Bakau kurap and an R2 of 0.75 for the ‘Others’ type of mangrove species. An error image was also created to compare the best fitting spectrum produced by the inversion of the LMM with the original observed spectrum, where the maximum RMS error was only 5%.

Published
2016
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27. Assessment of biophysical properties of Royal Belum tropical forest, Malaysia.

Author

Kanniah, Kasturi Devi, Tan, Kian Pang, Cracknell, Arthur P., Huete, Alfredo R., Idris, Nurul Hawani, Lau, Alvin Meng Shin, Abd Rahman, Muhammad Zulkarnain, Rasib, Abd Wahid, and Ahmad, Anuar

Subjects
FOREST reserves, RAIN forests, FOREST ecology, FOREST canopies, BIOMASS
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2018
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30. Non-Destructive, Laser-Based Individual Tree Aboveground Biomass Estimation in a Tropical Rainforest.

Author

Abd Rahman, Muhammad Zulkarnain, Abu Bakar, Md Afif, Razak, Khamarrul Azahari, Rasib, Abd Wahid, Kanniah, Kasturi Devi, Wan Kadir, Wan Hazli, Omar, Hamdan, Faidi, Azahari, Kassim, Abd Rahman, and Latif, Zulkiflee Abd

Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2017
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