Development of transferable rule-sets for urban areas using QuickBird satellite imagery by Tathiri, Anahita, Mohd Shafri, Helmi Zulhaidi, Hamedianfar, Alireza

“…Although rule-based object-based classification can often perform better than the supervised approaches, its attribute selection is very time consuming and hardly transferable between different urban areas. The purpose of this study is to identify transferable rule-sets for different areas from QuickBird satellite imagery for urban areas consisting heterogeneous man-made and natural features. …”
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Improving detailed rule-based feature extraction of urban areas from WorldView-2 image and lidar data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

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Performance of Sentinel-2A remote sensing system for urban area mapping in Malaysia via pixel-based and OBIA methods by Amir Tan, Adhwa, Mohd Shafri, Helmi Zulhaidi, Shaharum, Nur Shafira Nisa

“…This study aimed to investigate and assess the capability of Sentinel-2A imagery in mapping urban areas in Malaysia by comparing its performance against the established Landsat-8 data as well as the fusion datasets from combining Landsat-8 and Sentinel-2A datasets and using Wavelet transform (WT), Brovey transform (BT) and principal component analysis. …”

Factors affecting the eco-environment identification through change detection analysis by using remote sensing and GIS: a case study of Tikrit, Iraq by Hadi, Sinan Jasim, Mohd Shafri, Helmi Zulhaidi, Mahir, Mustafa D.

“…However, between 2000 and 2010, the urban area increased dramatically by 47.5%, due to the war which led to migration from Baghdad (Iraq Capital) to Tikrit. …”
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A comparison of hyperspectral data and worldview-2 images to detect impervious surface. by Taherzadeh, Ebrahim, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ashurov, Ravshan

“…In this study, airborne hyperspectral data and Worldview-2 image were used to classify urban area .The main goal of this study are to compare the hyperspectral data and worldview 2 images and shows the potential of worldview 2 images for detection the impervious surface from the same area. …”
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Monitoring Land Cover Changes in Halabja City, Iraq. by Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Al-doski, Jwan

“…During 1986 to 1990 land use / land cover changes a lot with a huge decrease about 40.8% in cultivated area whereas, urban area, Shrub Land and bare land classes increased by 57.9 %, 67.1 % and14 % respectively.…”
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Using hyperspectral remote sensing data in urban mapping over Kuala Lumpur by Taherzadeh, Ebrahim, Mohd Shafri, Helmi Zulhaidi

“…This study serves as a pioneering effort in the application of hyperspectral sensing for urban area in Malaysia.…”
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Spatio-temporal Analysis of Urban and Population Growths in Tripoli using Remotely Sensed Data and GIS. by Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Al-sharif, Abubakr A. A.

“…Also to understand and assess the interchangeable relationship of urban growth and population growth of study area. Urban area extents in different time periods were extracted by supervised classification method of the satellite imageries. …”
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Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery by Jebur, Mustafa Neamah, Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Tehrany, Mahyat Shafapour

“…The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively.…”

Deep learning approach for building detection using LiDAR–orthophoto fusion by Nahhas, Faten Hamed, Mohd Shafri, Helmi Zulhaidi, Sameen, Maher Ibrahim, Pradhan, Biswajeet, Mansor, Shattri

“…The proposed model was evaluated on two datasets selected from an urban area with different building types. Results show that the dimensionality reduction by the autoencoder approach from 21 features to 10 features can improve detection accuracy from 86.06% to 86.19% in the working area and from 77.92% to 78.26% in the testing area. …”
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Fusion of multispectral imagery and LiDAR data for roofing materials and roofing surface conditions assessment by Norman, Masayu, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Yusuf, Badronnisa, Mohd Radzali, Nurul Ain Wahida

“…Therefore, rule-based classification via LS fusion technique was utilized to identify suitable rooftops for the development of harvested rainwater system in the urban area. Findings indicate that the degradation status of a roof in heterogenous urban environments could be determined from satellite observation and the quality of roof-based harvested rainwater affected by roofing materials and roofing surface conditions can be analysed effectively.…”
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Modeling of CO emissions from traffic vehicles using artificial neural networks by Al-Gbur, Omer Saud Azeez, Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Shukla, Nagesh, Lee, Chang Wook, Rizeei, Hossein Mojaddadi

“…The hybrid model was developed based on the integration of GIS and the optimized Artificial Neural Network algorithm that combined with the Correlation based Feature Selection (CFS) algorithm to predict the daily vehicular CO emissions and generate prediction maps at a microscale level in a small urban area by using a field survey and open source data, which are the main contributions to this paper. …”
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Support vector machine classification to detect land cover changes in Halabja city, Iraq by Al-Doski, Jwan M. Mohammed, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi

“…Also, some changes in urban areas were detected that have already been identified as bombed areas particularly around the main roads of Halabja city.…”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…Although object-based image analysis (OBIA) has been used for detailed classification of urban areas, its attribute selection and knowledge discovery have been time consuming and subjective to analysts' performance. …”

Development of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…Urban areas consist of spectrally and spatially heterogeneous features. …”
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Development of a generic model for the detection of roof materials based on an object-based approach using WorldView-2 satellite imagery by Taherzadeh, Ebrahim, Mohd Shafri, Helmi Zulhaidi

“…The detection of impervious surface (IS) in heterogeneous urban areas is one of the most challenging tasks in urban remote sensing. …”
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Using scenario modelling for adapting to urbanization and water scarcity: towards a sustainable city in semi-arid areas by Hanoon, Sadeq Khaleefah, Abdullah, Ahmad Fikri, Mohd Shafri, Helmi Zulhaidi, Wayayok, Aimrun

“…This study reviews previous studies that examined future scenarios of urban areas under the challenges of rapid population growth, urban sprawl and water scarcity in order to improve supported decision-making (SDM). …”

Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

“…Airborne hyperspectral sensors with high spectral and spatial resolutions can be employed for detailed characterization of urban areas. This study aims to develop a procedure that is instrumental for automated knowledge discovery and mapping of urban surface materials from a large feature space of hyperspectral images. …”
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Six decades of urban growth using remote sensing and GIS in the city of Bandar Abbas, Iran by Dadras, Mohsen, Mohd Shafri, Helmi Zulhaidi, Ahmad, Noordin, Pradhan, Biswajeet, Safarpour, Sahabeh

“…Growth was calculated through Shannon's entropy model. The urbanized area increased from 403.77 ha to 4959.59 ha from 1956 to 2012, a rate almost five times that of the population growth observed in the same period. …”
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Mapping heterogeneous urban landscapes from the fusion of digital surface model and unmanned aerial vehicle-based images using adaptive multiscale image segmentation and classifica... by Gibril, Mohamed Barakat A., Kalantar, Bahareh, Al-Ruzouq, Rami, Ueda, Naonori, Saeidi, Vahideh, Shanableh, Abdallah, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi

“…In this study, adaptive hierarchical image segmentation optimization, multilevel feature selection, and multiscale (MS) supervised machine learning (ML) models were integrated to accurately generate detailed maps for heterogeneous urban areas from the fusion of the UHSR orthomosaic and digital surface model (DSM). …”
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