Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development
Reference18 articles.
1. Alzir, F. B., Antunes, C. L., Silva, J. C. D. (2003). Object oriented analysis and semantic network for high resolution image classification. Anais XI SBSR, Belo Horizonte, Brasil, INPE (pp. 273–279)
2. Barlow, J., Franklin, S., & Martine, Y. (2006). High spatial resolution satellite imagery, DEM derivatives, and image segmentation for the detection of mass wasting processes. Photogrammetric Engineering and Remote Sensing,72, 687–692.
3. Blaschke, T., Feizizadeh, B., & Hölbling, D. (2014a). Object-based image analysis and digital terrain analysis for locating landslides in the Urmia Lake Basin, Iran. IEEE J Sel Top Appl,7, 4806–4817. https://doi.org/10.1109/JSTARS.2014.2350036.
4. Blaschke, T., Hay, G. J., Kelly, M., Lang, S., Hofmann, P., Addink, E., et al. (2014b). Geographic object-based image analysis—Towards a new paradigm. ISPRS J Photogramm,87, 180–191.
5. Borghuis, A., Chang, K., & Lee, H. (2007). Comparison between automated and manual mapping of typhoon-triggered landslides from SPOT-5 imagery. International Journal of Remote Sensing,28, 1843–1856.
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Comparative landslide susceptibility assessment using information value and frequency ratio bivariate statistical methods: a case study from Northwestern Himalayas, Jammu and Kashmir, India;Arabian Journal of Geosciences;2024-07-10
2. A holistic approach of remote sensing, GIS, and machine learning for shallow landslide susceptibility mapping in Gaganbawada region of Western Ghats, India;Proceedings of the Indian National Science Academy;2024-05-03
3. Comparative Analysis of Machine Learning, Statistical, and MCDA Methods for Rainfall-Induced Landslide Susceptibility Mapping in the Eco-Sensitive Koyna River Basin of India;Indian Geotechnical Journal;2024-04-25
4. Application of GIS-based data-driven bivariate statistical models for landslide prediction: a case study of highly affected landslide prone areas of Teesta River basin;Quaternary Science Advances;2024-01
5. Analysis of February 2023 Thatri Landslide in Doda, Jammu and
Kashmir: Insights from Field Observations, Geotechnical Parameters, and GPR
Survey;Journal of the Geological Society of India;2024-01-01