Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection

作者: Omid Ghorbanzadeh , Thomas Blaschke , Khalil Gholamnia , Sansar Meena , Dirk Tiede

DOI: 10.3390/RS11020196

关键词:

摘要: … landslide detection method achieved a landslide detection … first to use CNNs for landslide detection, but that the potential … we apply CNN methods to landslide detection based on optical …

参考文章(48)
T. Blaschke, Object based image analysis for remote sensing Isprs Journal of Photogrammetry and Remote Sensing. ,vol. 65, pp. 2- 16 ,(2010) , 10.1016/J.ISPRSJPRS.2009.06.004
Daniel Hölbling, Petra Füreder, Francesco Antolini, Francesca Cigna, Nicola Casagli, Stefan Lang, A Semi-Automated Object-Based Approach for Landslide Detection Validated by Persistent Scatterer Interferometry Measures and Landslide Inventories Remote Sensing. ,vol. 4, pp. 1310- 1336 ,(2012) , 10.3390/RS4051310
D. Di Martire, M. De Rosa, V. Pesce, M. A. Santangelo, D. Calcaterra, Landslide hazard and land management in high-density urban areas of Campania region, Italy Natural Hazards and Earth System Sciences. ,vol. 12, pp. 905- 926 ,(2012) , 10.5194/NHESS-12-905-2012
Jie Dou, Kuan-Tsung Chang, Shuisen Chen, Ali Yunus, Jin-King Liu, Huan Xia, Zhongfan Zhu, Automatic Case-Based Reasoning Approach for Landslide Detection: Integration of Object-Oriented Image Analysis and a Genetic Algorithm Remote Sensing. ,vol. 7, pp. 4318- 4342 ,(2015) , 10.3390/RS70404318
Fausto Guzzetti, Alessandro Cesare Mondini, Mauro Cardinali, Federica Fiorucci, Michele Santangelo, Kang-Tsung Chang, Landslide inventory maps: New tools for an old problem Earth-Science Reviews. ,vol. 112, pp. 42- 66 ,(2012) , 10.1016/J.EARSCIREV.2012.02.001
Bakhtiar Feizizadeh, Majid Shadman Roodposhti, Piotr Jankowski, Thomas Blaschke, A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping Computers & Geosciences. ,vol. 73, pp. 208- 221 ,(2014) , 10.1016/J.CAGEO.2014.08.001
J. D. PAOLA, R. A. SCHOWENGERDT, A review and analysis of backpropagation neural networks for classification of remotely-sensed multi-spectral imagery International Journal of Remote Sensing. ,vol. 16, pp. 3033- 3058 ,(1995) , 10.1080/01431169508954607