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Mustafa Ridha Mezaal
Mustafa Ridha Mezaal
University Putra Malaysia / Middle Technical University
没有经过验证的电子邮件地址
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引用次数
引用次数
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Optimized neural architecture for automatic landslide detection from high-resolution airborne laser scanning data
MR Mezaal, B Pradhan, MI Sameen, HZ Mohd Shafri, ZM Yusoff
Applied Sciences 7 (7), 730, 2017
952017
Improving landslide detection from airborne laser scanning data using optimized Dempster–Shafer
MR Mezaal, B Pradhan, HM Rizeei
Remote Sensing 10 (7), 1029, 2018
862018
An improved algorithm for identifying shallow and deep-seated landslides in dense tropical forest from airborne laser scanning data
MR Mezaal, B Pradhan
Catena 167, 147-159, 2018
612018
Integration of ant colony optimization and object-based analysis for LiDAR data classification
MI Sameen, B Pradhan, HZM Shafri, MR Mezaal, H bin Hamid
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017
382017
Data mining-aided automatic landslide detection using airborne laser scanning data in densely forested tropical areas
B Pradhan, MR Mezaal
Korean Journal of Remote Sensing, 2018
252018
Automatic landslide detection using Dempster–Shafer theory from LiDAR-derived data and orthophotos
MR Mezaal, B Pradhan, HZM Shafri, ZM Yusoff
Geomatics, natural hazards and risk 8 (2), 1935-1954, 2017
252017
Landslide detection using a saliency feature enhancement technique from LiDAR-derived DEM and orthophotos
B Pradhan, HAH Al-Najjar, MI Sameen, MR Mezaal, AM Alamri
Ieee Access 8, 121942-121954, 2020
222020
Optimized rule sets for automatic landslide characteristic detection in a highly vegetated forests
B Pradhan, MR Mezaal
Laser Scanning Applications in Landslide Assessment, 51-68, 2017
142017
Optimized hierarchical rule-based classification for differentiating shallow and deep-seated landslide using high-resolution LiDAR data
MR Mezaal, B Pradhan, HZM Shafri, H Mojaddadi, ZM Yusoff
GCEC 2017: Proceedings of the 1st Global Civil Engineering Conference 1, 825-848, 2019
122019
Fusion of Airborne Hyperspectral and WorldView2 Multispectral Images for Detailed Urban Land Cover Classification A case Study of Kuala Lumpur Malaysia
AM Noori, SF Hasan, QM Ajaj, MR Mezaal, H Shafri, MA Shareef
International Journal of Engineering & Technology 7 (4.37), 202-206, 2018
112018
A Framework for Improving Urban Land Cover Using Object and Pixel-Based Techniques via Remotely Sensed Data.
AS Mahmoud, MR Mezaal, MR Hameed, AS Naje
Nature Environment & Pollution Technology 21, 2022
62022
Dynamics of Land Use and Land Cover Change Using Geospatial Techniques–A Case Study of Baghdad, Iraq
MR Mezaal, AS Mahmoud, MA Jasim, AS Naje
Ecological Engineering & Environmental Technology 23, 2022
52022
Response Time Analysis of Firefighting Operations Using ArcGIS Network Analyst in Puchong Fire Station Malaysia
AMFAMN Mustafa Ridha Mezaal, Ammar Shaker
Solid State Technology 63 (6), 2020
32020
Autor Sura Sami
SM Sulaiman, MR Mezaal, AAA Al-Attar
Ecol. Eng 5, 1-10, 2023
22023
Assessing the effects of copolymer modifier addition on asphalt attributes: Towards achieving performance optimization
ZH Al-Saffar, HGM Hasan, M Alamri, AA Al-Attar, AJ Hamad, ...
Construction and Building Materials 420, 135645, 2024
12024
Enhancement the Elevations of GNSS Technique Via Calibrating Geoid Separation of Electronic Gravity Model 2008: A Case Study: Maysan, Iraq
MR Mezaal, AM Fanos, HA Alkanaani, HH Mohammed
Solid State Technology 63 (6), 18341-18352, 2020
2020
OPTIMIZED TECHNIQUES FOR LANDSLIDE DETECTION AND CHARACTERISTICS USING LiDAR DATA
MR MEZAAL
2018
Evaluation of Machine Learning Models for Predicting Soil Texture Using Sentinel-1A SAR and Topographic Information
SM Sulaiman, MR Mezaal, AAA Al-Attar
Ecological Engineering & Environmental Technology 25 (11), 0
Comparative analysis of integrating and combining thermal TIRS and OLI data to superior change Detection using Geospatial Techniques
H Dibs, HA Hasab, MR Mezaal, N Al-Ansari
Landslide Detection Using a Saliency Feature Enhancement Technique from LiDAR-derived DEM and Orthophotos
I SAMEEN, MR MEZAAL, AM ALAMRI
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