منابع مشابه
Complex picture for likelihood of ENSO-driven flood hazard
El Niño and La Niña events, the extremes of ENSO climate variability, influence river flow and flooding at the global scale. Estimates of the historical probability of extreme (high or low) precipitation are used to provide vital information on the likelihood of adverse impacts during extreme ENSO events. However, the nonlinearity between precipitation and flood magnitude motivates the need for...
متن کاملLandslide Hazard Automated Zonation (LHAZ) system
The degree of hazard due to landslide in any region is difficult to assess manually. An automated system having capability to correlate causes contributing automated landslide hazard is expected to be an efficient alternative. The objective of this paper is to explain LHAZ (Landslide Hazard Automated Zonation) system, an automated system that has been developed to determine the intensity and ex...
متن کاملurban flood hazard zonation using gis and fuzzy-ahp analysis (case study: tehran city)
accelerated process of urbanization and global warming make urban flood one of the most important issues in urban planning. tehran recently has been affected by the flooding and its damages. high intensity rainfall and uncontrolled urban development and main inefficient networks of drainage system are the main reasons. this research uses an efficient approach for flood hazard assessment in tehr...
متن کاملFlood Hazard Mapping using Aster Image data with GIS
Flood is one of the most devastating natural hazards which lead to the loss of lives, properties and resources. It has therefore become important to create easily read, rapidly accessible flood hazard map, which will prioritize the mitigation effects. This study addresses the need for an efficient and cost-effective methodology for preparing flood hazard maps in Ghana, particularly those region...
متن کاملData-Driven Flood Detection using Neural Networks
This paper describes the approaches used by our team (MultiBrasil) for the Multimedia Satellite Task at MediaEval 2017. For both disaster image retrieval and flood-detection in satellite images, we employ neural networks for end-to-end learning. Specifically, for the first subtask, we exploit Convolutional Networks and Relation Networks while, for the latter, dilated Convolutional Networks were...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Environmental Management
سال: 2021
ISSN: 0301-4797
DOI: 10.1016/j.jenvman.2021.112986