The National Museum of Raqqa in Syria has suffered immensely from the ongoing violence since 2011. Much of its valuable collection of movable archaeological heritage (ca. 6000 items) is considered lost. Starting from 500 of the most precious objects of the museum stored in the Raqqa Central Bank and stolen from there in 2013, the pilot project Focus Raqqa created a concrete, workable database to enable identification by Syrian and international police and heritage institutions. The project made a pivotal first step towards potential reconstruction of the Raqqa Museum in the future. The Raqqa museum collection included cuneiform tablets. Some of the tablets were cast before the war to allow detailed study in Europe. Today the tablets have vanished. The pilot project Scanning for Syria safeguarded information from the lost artefacts by making high-resolution three-dimensional scans of the silicone rubber moulds and subsequently physical replicas of the original objects by 3D printing. The short life expectancy (30 years) of the moulds necessitated measures for long- 3 term preservation. The Scanning for Syria team not only succeeded at the preservation and sharing of knowledge in the academic circle. It also told the story of Syrian culture and its people to everyone for raising more voices in the united effort to keep cultural heritage safe in a zone of conflict.@en

Near-continuously acquired terrestrial laser scanning (TLS) data contains valuable information on natural surface dynamics. An important step in geographic analyses is to detect different types of changes that can be observed in a scene. For this, spatiotemporal segmentation is a time series-based method of surface change analysis that removes the need to select analysis periods, providing so-called 4D objects-by-change (4D-OBCs). This involves higher computational effort than pairwise change detection, and efforts scale with (i) the temporal density of input data and (ii) the (variable) spatial extent of delineated changes. These two factors determine the cost and number of Dynamic Time Warping distance calculations to be performed for deriving the metric of time series similarity. We investigate how a reduction of the spatial and temporal resolution of input data influences the delineation of twelve erosion and accumulation forms, using an hourly five-month TLS time series of a sandy beach. We compare the spatial extent of 4D-OBCs obtained at reduced spatial (1.0m to 15.0m with 0.5m steps) and temporal (2h to 96h with 2h steps) resolution to the result from highest-resolution data. Many change delineations achieve acceptable performance with ranges of ±10% to ±100% in delineated object area, depending on the spatial extent of the respective change form. We suggest a locally adaptive approach to identify poor performance at certain resolution levels for the integration in a hierarchical approach. Consequently, the spatial delineation could be performed at high accuracy for specific target changes in a second iteration. This will allow more efficient 3D change analysis towards near-realtime, online TLS-based observation of natural surface changes.

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Geographic observation benefits from the increasing availability of time series of 3D geospatial data, which allow analysis of change processes at high temporal detail and over extensive periods. In this context, the demand for advanced methods to detect and extract topographic surface changes from these 4D geospatial data emerges. Changes in natural scenes occur with varying magnitude, duration, spatial extent, and change rate, and the timing of their occurrence is not known. Standard pairwise change detection requires the selection of fixed analysis periods and the specification of magnitude thresholds to determine accumulation or erosion forms. In settings with continuous surface morphology and dynamic changes to the surface due to material transport, such change forms are typically temporary and may be missed or aggregated if they occur with spatial and/or temporal overlap. This is overcome with the extraction of 4D objects-by-change (4D-OBCs). These objects are obtained by firstly detecting surface changes in the temporal domain at locations in the scene. Subsequently, they are spatially delineated by considering the full history of surface change during region growing from the seed location of a detected change. To perform this spatiotemporal segmentation systematically for entire 3D time series, we develop a fully automatic approach of seed detection and selection, combined with locally adaptive thresholding for region growing of individual objects with varying change properties. We apply our workflow to a five-months hourly time series of around 3,000 terrestrial laser scanning point clouds acquired for coastal monitoring at a sandy beach in The Netherlands. This provides 2,021 4D-OBCs as extracted accumulation or erosion forms. Results are validated through majority agreement of six expert analysts, who evaluate the segmentation performance at sample locations throughout the scene. Accordingly, our method extracts surface changes with an error of omission of 4.7% and an error of commission of 16.6%. We examine the results and provide considerations how postprocessing of segments can further improve the change analysis workflow. The developed approach thereby provides a powerful tool for automatic change analysis in 4D geospatial data, namely to detect and delineate natural surface changes across space and time.

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Zeitserien von 3D-Punktwolken werden zunehmend für die Beobachtung geomorphologischer Phänomene genutzt. Dieser Beitrag untersucht, wie eine veränderte zeit-liche Auflösung die raumzeitliche Abgrenzung von Oberflächenprozessen beeinflusst. Dazu wird eine Zeitserien-basierte Region Growing Segmentierung verwendet. Die Untersuchung erfolgt am Beispiel einer Sandbank an einem Strand in den Niederlanden, der über fünf Mo-nate stündlich mit terrestrischem Laserscanning erfasst wurde. Die Ergebnisse zeigen, dass die zeitliche Prozessabgrenzung maßgeblich vom gewählten Zeitintervall abhängt. Auf Basis dieser Prozessabgrenzung kann die anschließende raumzeitliche Segmentierung auf ausge-dünnten Zeitserien und somit mit reduziertem Berechnungsaufwand erfolgen. … @en

Die nordsyrische Provinzhauptstadt ar-Raqqa ist in den letzten Jahren tragischerweise als «Hauptstadt des Bösen» bekannt geworden. Dabei blickt ar-Raqqa auf eine lange, beeindruckende Kulturgeschichte zurück, die bis in die Jungsteinzeit zurückreicht. Leider hat der unerbittliche Krieg in Syrien ar-Raqqa und sein archäologisches Erbe nicht unberührt gelassen. Im März 2016 begann eine Initiative, die sich zum Ziel gesetzt hat, das Wissen, für das diese Sammlung steht, und das kulturelle Erbe, das sie für die Völker Syriens darstellt,so weit wie möglich zu schützen.@en

Geomorphic processes occur spatially variable and at varying magnitudes, frequencies and velocities, which poses a great challenge to current methods of topographic change analysis. For the quantification of surface change, permanent terrestrial laser scanning (TLS) can generate time series of 3D point clouds at high temporal and spatial resolution. We investigate how the temporal interval influences volume change observed on a sandy beach regarding the temporal detail of the change process and the total volume budget, on which accretion and erosion counteract. We use an hourly time series of TLS point clouds acquired over six weeks in Kijkduin, the Netherlands. A raster-based approach of elevation differencing provides the volume change over time per square meter. We compare the hourly analysis to results of a three- and six-week observation period. For the larger period, a volume increase of 0.3 m³/m² is missed on a forming sand bar before it disappears, which corresponds to half its volume. Generally, a strong relationship is shown between observation interval and observed volume change. An increase from weekly to daily observations leads to a five times larger volume change quantified in total. Another important finding is a temporally variable measurement uncertainty in the 3D time series, which follows the daily course of air temperature. Further experiments are required to fully understand the effect of atmospheric conditions on high-frequency TLS acquisition in beach environments. Continued research of 4D geospatial analysis methods will enable automatic identification of dynamic change and improve the understanding of geomorphic processes. @en