(2011): Infrastructure assessment for disaster management using multi-sensor and multi-temporal remote sensing imagery, International Journal of Remote Sensing, 32:23,[8575][8576][8577][8578][8579][8580][8581][8582][8583][8584][8585][8586][8587][8588][8589][8590][8591][8592][8593][8594] To link to this article: http://dx.doi.org/10.1080/01431161.2010.542204
PLEASE SCROLL DOWN FOR ARTICLEFull terms and conditions of use: http://www.tandfonline.com/page/terms-andconditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden.The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Vol. 32, No. 23, 10 December 2011, 8575-8594 Infrastructure assessment for disaster management using multi-sensor and multi-temporal remote sensing imagery In this article, a new assessment system is presented to evaluate infrastructure objects such as roads after natural disasters in near-realtime. A particular aim is the exploitation of multi-sensor and multi-temporal imagery together with further geographic information system data in a comprehensive assessment framework. The combination is accomplished combining probabilities derived from the different data sets. The assessment system is applied to two different test scenarios evaluating roads after flooding, yielding very promising results and evaluation values concerning completeness and correctness. The benefit of the data combination, in particular the multi-temporal component, demonstrates the suitability of the proposed method for different application scenarios.
International Journal of Remote Sensing