Improving remote sensing flood assessment using volunteered geographical data
A new methodology for the generation of flood hazard maps is presented fusing remote sensing and volunteered geographical data. Water pixels are identified utilizing a machine learning classification of two Landsat remote sensing scenes, acquired before and during the flooding event as well as a dig...
Main Authors: | E. Schnebele, G. Cervone |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2013-03-01
|
Series: | Natural Hazards and Earth System Sciences |
Online Access: | http://www.nat-hazards-earth-syst-sci.net/13/669/2013/nhess-13-669-2013.pdf |
Similar Items
-
Real Time Estimation of the Calgary Floods Using Limited Remote Sensing Data
by: Emily Schnebele, et al.
Published: (2014-02-01) -
Road assessment after flood events using non-authoritative data
by: E. Schnebele, et al.
Published: (2014-04-01) -
Integration of Crowdsourced Images, USGS Networks, Remote Sensing, and a Model to Assess Flood Depth during Hurricane Florence
by: Carolynne Hultquist, et al.
Published: (2020-03-01) -
Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest
by: Bidur Devkota, et al.
Published: (2019-08-01) -
Emergency Response Using Volunteered Passenger Aircraft Remote Sensing Data: A Case Study on Flood Damage Mapping
by: Chisheng Wang, et al.
Published: (2019-09-01)