During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

VHR satellite imagery for humanitarian crisis management: A case study

BITELLI, GABRIELE;ELEIAS, MAGDALENA;FRANCI, FRANCESCA
;
MANDANICI, EMANUELE
2017

Abstract

During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.
2017
Proceedings Volume 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017)
1
11
Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/619168
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