Science Service System

Summary of Proposal LAN2377

TitleTerraSAR-X Staring Spotlight mode for damage assessment, looting monitoring and prospection of archaeological features in semi-arid environment
Investigator Tapete, Deodato - Natural Environment Research Council, British Geological Survey
Team Members
Prof Donoghue, Daniel - Durham University, Geography
Prof Philip, Graham - Durham University, Archaeology
Dr. Cigna, Francesca - Natural Environment Research Council, British Geological Survey
SummaryThis project aims to demonstrate the scientific potential of the new TerraSAR-X Staring SpotLight mode (ST) to support cutting-edge research and real-world applications of damage assessment, looting monitoring and prospection of archaeological features in semi-arid environments. We will explore the specific new contribution that ST can add in this field of the Land Environment Application Domain thanks to its unprecedented level of resolution (less than 1m), alongside its complementary exploitability with the metre-resolution existing modes StripMap (SM), SpotLight (SL) and High Resolution SpotLight (HS). The latter capability will be investigated with regard to multi-scale mapping of surface changes, as well as multi-temporal change detection. The study areas are distributed in selected regions of Near-Middle East, and include: (i) the Hellenistic-Roman Age Apamea and the UNESCO-WHL site of Palmyra, Syria; (ii) the Syrian city of Homs and its surrounding cultural landscape; (iii) Carchemish and tells in north-eastern Syria - south-eastern Turkey; (iv) the Great Wall of Gorgan in north-eastern Iran, close to the Caspian Sea along the frontiers of the Sasanian Empire. The site selection provides a representative sample of diverse environmental contexts and associated hazards, to assess the performance of ST for: (i) change detection; (ii) damage assessment; (iii) looting monitoring; and (iv) prospection of subtle and vanishing archaeological features, at a level of resolution that can nowadays be achieved by archaeologists and geoscientists mainly with panchromatic VHR optical imagery. Both single-image and multi-pass approaches will be used, so that ST can be scientifically evaluated in respect of its specific discrimination capability in the spatial and temporal dimensions, respectively. ST acquisitions will be acquired over the selected sites, for which the cm-level resolution is considered crucial for feature extraction and detection of change patterns at the scale of building to single architectural element. Comparison will be done with (nearly-)simultaneous existing modes data, and the expected improvement that can be achieved by means of ST will be quantitatively rated. Potentials of multi-temporal monitoring will be assessed via repeat-pass ST acquired during the 2-year project (2014-2015). We will implement and refine the amplitude change detection, and interferometric approaches (DInSAR and coherence change detection) that have been successfully developed with medium-resolution C-band imagery for purposes of condition monitoring and looting detection (Tapete et al., 2012, 2013; Cigna et al., 2013). We will explore the feasibility and potential of ST acquisitions to create a seamlessly continuity with the SM, SL and HS data. To this purpose, new ST acquisitions will be compared with selected SM, SL and/or HS images from the archive, thereby making the best out of the timeliness of the latter that provide picture of the Syrian and Iranian sites prior to the occurrence of major destruction events or significant alteration due to human and environmental changes. Benefits achievable to image the evolving scenario in the Syrian sites currently under conflict will provide proof of concept of the possible use of ST in humanitarian and hazard emergencies, in support to both science and society. The outcomes of this research will be interpreted complementarily with field data from extensive and detailed archaeological surveys undertaken since the 1970s, and forthcoming missions. Comparison will also be done with recent research based on 1960s CORONA, 2000s VHR GeoEye, QuickBird and WorldView-1 data. The results of the project will include: maps of damage assessment and change detection, image interpretation keys showing correlation between backscatter signal, typologies of surface features and type of damage/condition; and feature extraction.

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DLR 2004-2016