Jagannath Aryal
Jagannath Aryal
Associate Professor, Department of Infrastructure Engineering, The University of Melbourne
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Zitiert von
Zitiert von
Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection
O Ghorbanzadeh, T Blaschke, K Gholamnia, SR Meena, D Tiede, J Aryal
Remote Sensing 11 (2), 196, 2019
Mapping private gardens in urban areas using object-oriented techniques and very high-resolution satellite imagery
R Mathieu, C Freeman, J Aryal
Landscape and urban planning 81 (3), 179-192, 2007
Object-based classification of Ikonos imagery for mapping large-scale vegetation communities in urban areas
R Mathieu, J Aryal, AK Chong
Sensors 7 (11), 2860-2880, 2007
Big data integration shows Australian bush-fire frequency is increasing significantly
R Dutta, A Das, J Aryal
Royal Society open science 3 (2), 150241, 2016
Tracking tourists’ travel with smartphone-based GPS technology: a methodological discussion
A Hardy, S Hyslop, K Booth, B Robards, J Aryal, U Gretzel, R Eccleston
Information Technology & Tourism 17, 255-274, 2017
Landslide detection using multi-scale image segmentation and different machine learning models in the higher himalayas
S Tavakkoli Piralilou, H Shahabi, B Jarihani, O Ghorbanzadeh, ...
Remote Sensing 11 (21), 2575, 2019
Forest fire susceptibility and risk mapping using social/infrastructural vulnerability and environmental variables
O Ghorbanzadeh, T Blaschke, K Gholamnia, J Aryal
Fire 2 (3), 50, 2019
Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping
B Feizizadeh, MS Roodposhti, T Blaschke, J Aryal
Arabian Journal of Geosciences 10, 1-13, 2017
A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping
O Ghorbanzadeh, T Blaschke, J Aryal, K Gholaminia
Journal of Spatial Science 65 (3), 401-418, 2020
A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping
O Ghorbanzadeh, H Rostamzadeh, T Blaschke, K Gholaminia, J Aryal
Natural Hazards 94, 497-517, 2018
Spatial Prediction of Wildfire Susceptibility Using Field Survey GPS Data and Machine Learning Approaches
O Ghorbanzadeh, VK Kamran, T Blaschke, J Aryal, A Naboureh, J Einali, ...
Fire 2 (43), 1-23, 2019
Fuzzy shannon entropy: A hybrid gis-based landslide susceptibility mapping method
M Shadman Roodposhti, J Aryal, H Shahabi, T Safarrad
Entropy 18 (10), 343, 2016
Deep learning-based semantic segmentation of urban features in satellite images: A review and meta-analysis
B Neupane, T Horanont, J Aryal
Remote Sensing 13 (4), 808, 2021
UAV-based slope failure detection using deep-learning convolutional neural networks
O Ghorbanzadeh, SR Meena, T Blaschke, J Aryal
Remote Sensing 11 (17), 2046, 2019
A geospatial approach to assessing soil erosion in a watershed by integrating socio-economic determinants and the RUSLE model
KP Bhandari, J Aryal, R Darnsawasdi
Natural Hazards 75, 321-342, 2015
Cloud Computing in natural hazard modeling systems: Current research trends and future directions
U K.C., S Garg, J Hilton, J Aryal, N Forbes-Smith
International Journal of Disaster Risk Reduction, 2019
Development of an intelligent environmental knowledge system for sustainable agricultural decision support
R Dutta, A Morshed, J Aryal, C D'Este, A Das
Environmental Modelling & Software 52, 264-272, 2014
A novel algorithm for calculating transition potential in cellular automata models of land-use/cover change
MS Roodposhti, J Aryal, BA Bryan
Environmental Modelling & Software 112, 70-81, 2019
Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia
B Melville, A Lucieer, J Aryal
International journal of applied earth observation and geoinformation 66, 46-55, 2018
Predictive habitat modelling to estimate petrel breeding colony sizes: sooty shearwaters (Puffinus griseus) and mottled petrels (Pterodroma inexpectata) on Whenua Hou Island
D Scott, H Moller, DD FletcHer, J Newman, J Aryal, C Bragg, K Charleton
New Zealand Journal of Zoology 36 (3), 291-306, 2009
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