This session is a result of a merge between GI1.3 and GM2.3:
Recent advances in image collection and topographic measurements are providing unprecedented insight into landscape and process characterization across the geosciences. In parallel, the increasing availability of digitised historical images, going back to the late 1800s, together with advances in digital photogrammetry software, have provided new opportunities for assessing and reconstructing long-term surface evolution from local to landscape scale. Such data can extend high-resolution time series into the pre-satellite era and offer exciting potential for distinguishing anthropogenic from natural causes of environmental change. For both historic and contemporary scenarios, augmenting classic techniques with digital imagery and ‘structure from motion’ (SfM) processing has democratized data access and offers a new measurement paradigm to geoscientists.
Such data are now available over spatial scales from millimetres to kilometres, and over durations of single events to lasting time series (e.g. from sub-second to century-duration time-lapse), allowing evaluation of event magnitude and frequency interrelationships. Despite a large volume of historical images available for reprocessing with modern methods, their full potential has not yet been widely exploited and uncertainties remain on the optimal types of information that can be extracted. Substantial opportunities are likely to be exposed by exploring such data resources with machine and deep learning approaches.
The session welcomes submissions from a broad range of geoscience disciplines such as geomorphology, cryosphere, volcanology, hydrology, bio-geosciences, and geology. Our goal is to create a diverse and interdisciplinary session to explore the potential of 2D and 3D image and topographic datasets for reconstructing and interpreting environments and processes, past and present. We aim to exchange experiences of modern photogrammetric and topographic measurement and modelling technologies, along with their associated data processing tools, to highlight their potentials, limitations, and challenges in different environments.
We will have a video meeting on Friday evening starting from 6 pm CEST (UTC+2), in addition to the chat session on Friday morning, as scheduled. Authors will give talks in this video meeting, and there will be room for discussions, with the following agenda:
18:00 - 18:05 - Meeting setting and introduction to the session
18:05 - 18:17 - Amaury Dehecq, "Multidecadal elevation changes from spy satellite images: application to glaciers and landslides".
18:17 - 18:29 - Robert McNabb, "An open-source toolset for automated processing of historic spy photos: sPyMicMac".
18:29 - 18:41 - Penelope How, "PyTrx: a Python-based monoscopic terrestrial photogrammetry toolset for glaciology".
18.41 - 18:53 - Sebastian Flöry, "Development of a 3D Viewer for georeferencing and monoplotting of historical terrestrial images".
18.53 - 19:05 - Luca Carturan, "Use of WWI photos for quantitative reconstructions of glaciers along the Italian-Austrian front".
19:05 - 19:17 - Martino Terrone, "Coupling historical maps and Lidar data to recognize man-made landforms in urban areas".
19:17 - 19:25 - a little break
19:25 - 19:37 - William D. Harcourt. "Observing the cryosphere with millimetre wave radar: The case study of Rhône Glacier".
19.37 - 19:49 - Denis Feurer, "Time-SIFT: a frugal method for leveraging multi-temporal photogrammetric data without ancillary data"
19.49 - 20:01 - Helge Smebye, "Combined aerial and ground-based Structure-from-Motion modelling for a vertical rock wall face to estimate volume of failure"
20:01 - 20:13 - Sara Cucchiaro, "Terrestrial-Aerial-SfM and TLS data fusion for agricultural terrace surveys in complex topographic and land cover conditions".
20:13 - 20:25 - Andreas Mayr, "Close-range sensing and object based analysis of shallow landslides and erosion in grasslands".
20:25 - 20:37 - Kieran Wood, "UAS radiation hot-spot detection and refinement."
20:37 - break and discussion with an open end.
Join the video meeting using the following link:
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Files for download
Chat time: Friday, 8 May 2020, 08:30–10:15
Today, photos play an important role in geoscience and public discussion. When photographical techniques developed during the second half of the 19th century, it took several decades uuntil high mountain areas and specific features could be captured with this technique, as a follow upt o traditional paintings and drawings. In European geography, Friedrich Simony developed the idea of tackling geomorphological processes by time lapse photography. Contemporary literature shows that his technique of combining photography with empirical data and theories was convincing, and that he established a new style of scientific discussion. Still, the comparison of historical with contemporary photography offers scientific insights and information which is not covered by any other type of empirical evidence as measurements, maps or descriptions. For example not only extent, but also firn and debris cover of glaciers, information on type and extent of vegetation, the width and style of roads, details of infrastructure and cultural practices can be tackled from early photographs. Several archives do allow not only acess to photographic documents, but also to metadata. Interdisciplinary effort has to be taken to further analyse this wealth of information.
How to cite: Fischer, A.: The role of repeat photography in establishing theories of transition in high mountain environments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7070, https://doi.org/10.5194/egusphere-egu2020-7070, 2020.
Prior to the satellite era (pre-1970s) knowledge of long-term glacier change is sparse. Although some glacier-wide mass balance datasets are available, few records extend beyond twenty years in length, or indeed, start prior to the 1980s; as such, identifying long-term trends between glacier change and global temperatures is difficult. As a result, extending the record of glacier change will not only help to identify such trends, but may also facilitate more robust understanding of future glacier response under a perturbed and varying climate.
Since the ‘heroic age of Arctic (and Antarctic) exploration’, many photographs of polar environments have been captured and stored for historic interest. These photographs, depicting images of past glaciers and ice sheet margins, have, as of yet, untapped potential to provide important insights into past glacier extent, and long-term behaviour.
Using computer-vision methodologies, we present a unique record of georeferenced 3-D elevation models using declassified aerial imagery dating from the 1930s—1980s at quasi-regular time steps. This study focusses upon two sections (ca. 190 km total length) of the southeast margin of the Greenland Ice Sheet (in the vicinity of Kangerlussuaq Glacier), capturing the history of both land- and marine-terminating outlet glaciers, and local glaciers. We examine quantitative information extracted from these reconstructions, allowing us to ‘back extend’ the record of glacial change in this region, by measuring changes in glacial extent, surface profiles and height (elevation), and calculating volume estimates.
How to cite: Cooper, M., Lewinska, P., Dowdeswell, J., Hancock, E., Smith, W., and Rippin, D.: Unearthing the forgotten record of glacier change in southeast Greenland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19910, https://doi.org/10.5194/egusphere-egu2020-19910, 2020.
Earth’s surface has evolved dramatically over the last 50 years as a consequence of anthropogenic activities and climate change. The observation of such changes at decadal scales is often limited to sparse in-situ observations. The growth of satellite remote-sensing has enabled such monitoring at regional/global scales but generally over less than two decades.
More than 2 million images have been acquired by American reconnaissance (“spy”) satellites on photographic film from the 1960s to the 1980s, and progressively declassified. With near-global coverage and meter to sub-meter resolution, these images have a large potential for many geoscience applications. However the photographic archive represents a unique set of challenges: pre-processing of the scans, correction of the image distortion caused during storing and scanning, poorly known camera positions and parameters. The vast majority of studies using these data rely on tedious manual processing of the data, hindering regional scale applications.
Here, we present the existing datasets and the development of an automated processing pipeline. We will focus in particular on images acquired by the Hexagon mapping camera (1973-1980, 12 missions) at 6-9 m ground resolution. A fully automated workflow has been developed to detect the 1081 fiducial markers present on the image, correct for distortion and stitch the different parts of the image, scanned in multiple sections. The pre-processed images are then used to generate Digital Elevation Models (DEMs) at 24 m resolution with the open-source NASA Ames Stereo Pipeline. The developed workflow is able to automatically solve for the unknown camera positions/orientations and optimally aligns the DEMs to an ancillary DEM for the determination of elevation changes. The application to ~600 images has revealed systematic biases in the retrieved elevation, up to 30 m error, linked to uncertainties in the camera parameters (focal length, lens distortion). We present a methodology to refine these parameters using an ancillary DEM only, without use of manual Ground Control Points. The KH-9 elevation is then validated against existing maps in Europe and Alaska and shows a vertical accuracy of ~5 m (68% interval) to 10-15 m (95% interval), sufficient for the study of large surface deformation (glaciers, landslides).
Finally, we conclude with several use of these data for the estimation of 40 years geodetic glacier mass balance in Europe and Alaska, and irrigation-triggered landslides in South Peru.
How to cite: Dehecq, A., Gardner, A., Alexandrov, O., Shean, D., and Lacroix, P.: Multidecadal elevation changes from spy satellite images: application to glaciers and landslides, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9153, https://doi.org/10.5194/egusphere-egu2020-9153, 2020.
Most large-format analogue aerial photography, especially in the form of roll negatives, is now held in centralised archives, but much still exists elsewhere, notably in the form of positive prints. Whilst many large archiving bodies have been and continue to digitise their holdings of such aerial photography using professional photogrammetric scanners, they are often prohibitive (on the grounds of cost and/or logistics) for use with low-volume, dispersed collections. Therefore, alternative methods are sought, which are presented here. Such alternatives can be subject to relatively poor geometric accuracy, making photogrammetric processing problematic. Here the results of photogrammetric processing with prints digitised using alternative methods are compared and contrasted with digitised roll negatives of the same frames. The quality of resulting elevation data are assessed against reference elevations, using a test site with topography which has remained stable over decades.
How to cite: Ford, A. and Papworth, H.: Digitising archive large-format analogue aerial photography with alternative methods; Implications for photogrammetric processing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20294, https://doi.org/10.5194/egusphere-egu2020-20294, 2020.
Orthomosaics from aerial photographs play a pivotal role in understanding land-use/land cover in broad area and the advent of image processing technology allows us to produce orthoimagery. However, recent advanced technologies are seldom applied to produce historical orthophotos from early or mid 20C old aerial photos in broad extent since they have limited information (e.g. camera position, flying altitude, and yaw) which is critical information for orthomosaics. In this context, this study aims to orthomosaic and georectify historical aerial photographs and validate the horizontal accuracy of orthomosacicked outputs. In order to achieve this, firstly, we collected 117 aerial photographs of 1934 (scale 1:12,000) and 68 of 1951 (scale 1:20,000) from UConn air photo achieve focused on Woodstock town in Connecticut, USA. Secondly, we created GCPs (Ground Control Points) as referenced points where they have not changed over time by overlaying multiple datasets such as LiDAR DEM, hillshade map, recent orthoimagery. Thirdly, we align photos with Control Points (CPs), build a mesh, and build orthomosaics of 1934 and 1951, respectively, using Agisoft Photoscan 1.5. Lastly, calculating RMSE (Root Mean Square Error) and offsets comparing between set of GCPs and CPs from Lidar DEM and set of them digitized from orthomosaics. As a result, RMSE values of GCPs and CPs between 1934 and 1951 mostly show that output of this work is acceptable to use for standard mapping and GIS work or visualization based on ASPRS 1990 horizonal accuracy standard. In addition, we found several factors affect horizontal accuracy of orthomosaics; resolution of aerial photos, spatial distribution of GCPs and CPs, the number of CPs and GCPs, the percentage of lateral overlapping area along flight strips, and margin area. Overall, applying automated orthomosaicking image processing to historical aerial photographs has the potential to represent historical landscape and even detect its change in broad extent.
How to cite: Suh, J. W. and Ouimet, W.: Orthomosaics of Historical Aerial Photographs and Horizontal Accuracy Analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6255, https://doi.org/10.5194/egusphere-egu2020-6255, 2020.
Countrywide surface models from historical panchromatic and true color stereo imagery – a retrospective analysis of forest structures in Switzerland
Mauro Marty1, Lars T. Waser1, Christian Ginzler1
1 Swiss Federal Institute for Forest, Snow and Landscape Research WSL,
Zürcherstrasse 111, CH - 8903 Birmensdorf, Switzerland
Remote sensing methods allow the acquisition of 3D structures of forests over large areas. Active systems, such as Airborne Laser Scanning (ALS) and Synthetic Aperture Radar (SAR) and passive systems, such as multispectral sensors, have been established to acquire 3D and 2.5D data of the earth's surface. Nationwide calculations of surface models with photogrammetric methods from digital stereo aerial images or ALS data are already in operation in some countries (e.g. Switzerland, Austria, some German states).
The availability of historical stereo aerial images allows the calculation of digital surface models from the past using photogrammetric methods. We present a workflow with which we have calculated nationwide surface models for Switzerland for the 1980s, 1990s and 2000s. Current surface models are available from the National Forest Inventory (LFI) Switzerland.
In the context of the Swiss land use and land cover statistics, the Federal Office of Topography (swisstopo) scanned and oriented the analogue black and white stereo aerial photographs with a mean scale of ~1:30'000 of the nationwide flights of 1979 - 84 and1993 - 1997 with 14 µm. The true colour image data from 1998 – 2007 were scanned for the production of the orthoimages swissimage by swisstopo. All these data – the scanned images and the orientation parameters - are also available to the National Forest Inventory (NFI). Within the framework of the NFI, we developed a highly automated workflow to generate digital surface models (DSMs) from many thousands of overlapping frame images covering the whole country. In total, more than 25'000 individual stereo models were processed to nationwide surface models. For their normalization, the digital terrain model of Switzerland 'swissAlti3D' was used. As the image orientation in some areas showed high vertical inaccuracies, corrections had to be made. Data from the Swiss land use and land cover statistics were used for this purpose. At places with constant surface cover since the 1980s (e.g. grassland), correction grids were calculated using the digital terrain model and applied to the surface models.
The results are new data sets on the 2.5D surface of Switzerland from the 1980s, 1990s and 2000s with a high spatial resolution of 1 m. It can be stated that the completeness of the image correlation in forested areas was quite satisfactory. In open areas with agricultural land, however, the matching points were often reduced to the road network, as the meadows and fields in the scanned SW stereo aerial images had very little texture.
This new historical, nationwide data on the horizontal and vertical structure in forests now allows their analysis of changes over the last 40 years.
How to cite: Ginzler, C., Marty, M., and Waser, L. T.: Countrywide surface models from historical panchromatic and true color stereo imagery – a retrospective analysis of forest structures in Switzerland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12741, https://doi.org/10.5194/egusphere-egu2020-12741, 2020.
Mountain regions are disproportionately affected by global warming and changing precipitation conditions. Especially the strong variations within high mountain ranges at the local scale require additional sources in order to quantify changes within this challenging environment. With the emergence of alpine tourism, terrestrial photographs became available by the end of 1800, predating aerial imagery for the selected study areas by 50 years. Due to the earlier availability and oblique acquisition geometry these images are a promising source for quantifying changes within mountainous regions at the local scale. Within the research project SEHAG, methods to process these images and to analyse their potential to quantify and describe environmental changes are developed and applied to study areas in Austria and Italy.
One of the prerequisites for the estimation of changes based on terrestrial imagery is the calculation of the corresponding object point for each pixel in a global coordinate system resulting in a georeferenced orthorectified image. This can be achieved by intersecting the ray defined by the projection center of the camera and each pixel with a digital terrain model, a process known as monoplotting.
So far 1000 terrestrial images with unknown interior and exterior orientation have been collected from various archives for the selected study areas Kaunertal, Horlachtal (both Tyrol, Austria) and Martelltal (South Tyrol, Italy). In order to estimate all camera parameters a 3D viewer for the selection of ground control points has been developed and implemented. The estimation of the exterior and interior orientation is done in OrientAL.
Preliminary results for selected images show, that especially the developed 3D viewer is an important improvement for the selection of well distributed ground control points and the accurate estimation of the exterior and interior orientation. Monoplotting depends on a digital terrain model, which cannot be computed from the terrestrial images alone due to missing overlap and different acquisitions times. Hence, the combination with historical digital terrain models derived from aerial imagery is necessary to minimize errors introduced due to changes in topography until today. While the large amount of terrestrial images with their oblique acquisition geometries can be exploited to fill occluded areas by combining the results from multiple images, the partly missing or inaccurate temporal information poses another limitation.
With this large image collection, for the first time, we are able to evaluate the use of historical oblique terrestrial photographs for change detection in a systematic manner. This will promote knowledge about challenges, limitations and the achievable accuracy of monoplotting within mountainous regions. The work is part of the SEHAG project (project number I 4062) funded by the Austrian Science Fund (FWF).
How to cite: Flöry, S., Ressl, C., Puercher, G., Pfeifer, N., Hollaus, M., Bayr, A., and Karel, W.: Development of a 3D Viewer for georeferencing and monoplotting of historical terrestrial images. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22327, https://doi.org/10.5194/egusphere-egu2020-22327, 2020.
Improving our understanding of the processes governing mass loss from the cryosphere is inhibited by a lack of data at high spatial and temporal resolution. Satellite sensors can provide regional to global scale coverage of glacier processes but fail to resolve processes that occur rapidly, for example glacier calving. To observe these processes, the glaciology community must invest in new techniques that can monitor these processes adequately and fill this major research gap. Here, we will discuss the implementation of an exciting new radar system that is capable of imaging glacial terrain at a high angular resolution and during most weather conditions. The system, named AVTIS2, operates at 94 GHz (~3 mm) and offers a compromise between imaging resolution and penetration through atmospheric obscurants. AVTIS2 scans mechanically across a scene of interest in defined increments of azimuth and elevation angles and generates a 3D data cube of backscattered power. We use a point to maximum power criterion to generate point clouds and construct Digital Elevation Models (DEMs) of the terrain. Because AVTIS2 is a real aperture radar it does not require the phase stability of interferometric radars and can acquire DEMs irrespective of local environmental conditions. In this work, we have used the AVTIS2 radar to map Rhône Glacier in the Swiss Alps, representing the first ever time a millimetre wave radar has been used in this way. To improve our understanding of the performance of AVTIS2 for mapping glaciers, we have characterised the scattering properties of glacial ice at 94 GHz by calculating its Radar Cross Section (RCS). This is key to understanding the performance of AVTIS2 for mapping glaciers. This study represents the first investigation into the reflectivity of ice at millimetre wavelengths and the utility of millimetre wave radar as a surveying tool. We will report on the future application of this instrument in glaciological studies and the unique perspective it can offer.
How to cite: Harcourt, W. D., Macfarlane, D. G., Robertson, D. A., Rea, B., and Spagnolo, M.: Observing the cryosphere with millimetre wave radar: The case study of Rhône Glacier, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-595, https://doi.org/10.5194/egusphere-egu2020-595, 2020.
The geometric characterization of riverbed material is fundamental piece of information for the management of river basins because it allows, for example, the determination of bed-load and hydrodynamics roughness and the study of geo-morphological phenomenona.
However information such the grading curve are not easily achievable by means of traditional field sampling methods, mostly intrusive, and to the hydraulic conditions of rivers that may have high water levels and strong flows.
Multibeam sonars represent an important alternative to traditional survey methods. Nowadays, thanks to advanced scientific knowledge, it is possible to make full use of an equipment increasingly accurate and precise. State of the art solutions have dimensions compact enough to be installed on remotly piloted vehicles and allow to obtained high resolution digital surface models of river beds. The feasibility of having models of such quality and the possibility to conduct surveys more frequently, allowing the monitoring of sedimentation and erosion phenomena as well as the dynamics of the armouring layer, have motivated the development of advanced and innovative technology to analyse these models.
The aim of this work is the development of a workflow that provides an effective method to characterize riverbed material. In order to achieve this target we start from an advanced and original survey technique, that allows to obtain high resolution digital surface models, and use an appropriate post-processing procedure.
We introduce first some results obtained from the analysis of digital surface models produced in laboratory or relative to well known site. In particular advanced techniques for the study of 3D model and the detection and geometric characterization of forms are investigated.
Then we present some data acquired at high resolution (few centimeters) with a multibeam sonar mounted on a remote controlled vessel. Field surveys were conducted in real fluvial environment with the aim of produce qualitative and quantitative information about the surface layer of riverbed.
Even considering some sources of uncertainty that may be present from field survey to modeling, the obtained results show how it is possible to identify and geometrically characterize several of the forms present on the surfaces analyzed.
How to cite: Rover, S., Avancini, G., and Vitti, A.: Management and analysis of high resolution multibeam sonar surveys for geometry characterization of riverbed material, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-981, https://doi.org/10.5194/egusphere-egu2020-981, 2020.
Latest advances in lightweight aerial platforms, miniaturized RTK DGPS positioning and IMUs make now it possible to build multitemporal photogrammetric datasets with centrimetric accuracies. Together with the increase of very high-resolution topographic data availability, algorithms that came from the computer vision community also provoked a marked resurgence of interest on archival photogrammetric data. Recently, Feurer and Vinatier (2018) proposed a method that rely on the invariance properties of the feature detection algorithms such as SIFT to estimate orientations in a single multi-temporal block. This method allows for an inherent co-registration of processed multi-temporal photogrammetric datasets and hence detection and mapping of 3-D change from past imagery. This work demonstrated that – in the case of archival aerial imagery – the Time-SIFT method enables the processing of multi-temporal photogrammetric imagery without ancillary data.
However, the potential of the Time-SIFT method had to be checked for in various contexts and spatio-temporal scales. More, the Time-SIFT method may allow to cope with the lack of precise positioning, in the case of image acquisitions made with frugal acquisition systems for instance. Hence this study proposes to apply the Time-SIFT method on five contrasting test cases. Their time and space scales vary from a domain of several square-centimeters to domains of several tens of kilometers, with time spans varying from the minutes to the decades. The test cases rely within different disciplines of geosciences, from soil science to vulcanology. Our works showed that the Time-SIFT methods succeeds through this whole range of spatio-temporal scales, and show even some unexpected robustness in context of strong changes due to vegetation and/or presence of water in coastal areas. These results demonstrate that the Time-SIFT method has a potential to tackle a wide variety of multi-temporal photogrammetric datasets, in particular in contexts where additional and calibration data are scarce.
How to cite: Feurer, D., Bemis, S., Coulouma, G., Mabrouk, H., Massuel, S., Barbosa, R. V., Thomas, Y., Ammann, J., and Vinatier, F.: Time-SIFT : a frugal method for leveraging multi-temporal photogrammetric data without ancillary data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10187, https://doi.org/10.5194/egusphere-egu2020-10187, 2020.
Unoccupied Aerial Systems (UAS) are ideal tools for responding to nuclear incidents where large outdoor areas have become contaminated with a radiological hazard. They are advantageous because rapid response radiation surveys can be conducted while the human operator remains at a safe distance and avoids direct contamination of the platform. During fieldwork within the Chernobyl Exclusion Zone (Ukraine), an airborne platform was equipped with a GNSS enabled gamma spectrometer and used to survey an area surrounding a known highly contaminated building (a ‘hot-spot’), resulting in a radiation intensity map. The detected radiation pattern, however, was ‘blurred’ since the intensity recorded at any point counted nadir emissions, but also emissions from all sources within line-of-sight; The ‘hot-spot’ had an influence far outside its ground footprint. Methods exist to correct for errors introduced by varying terrain altitude, however, they do not remove the unwanted blurring. Hence, small point sources appear as broad regions of contamination which is entirely an artefact of the measurement process. The effect is further accentuated with increasing height above ground hence understanding and correcting for this phenomenon is particularly relevant to data collected using UAS. Here, we present a novel algorithm to refine the detected pattern to more accurately recover the ground-truth.
A forward model of the system is created which describes the relationship between the unknown ground-truth and the aerial measurements. Gamma ray emissions from a point source obey the inverse square law of spatial dilution and have an exponential attenuation in air. To model both effects, geometric information of the scene is required and is provided by the geotagged spectrometer data and photogrammetrically processed DEMs of the surveyed terrain. The resulting model is hyper-cube of linear equations, where every aerial measurement point is assumed to be influenced by every ground sample point. By finding the inverse solution of this system, the ground-truth radiation pattern is estimated in more detail. The Kaczmarz method is advantageous because a large system of equations can be broken down into smaller sub-routines and solved iteratively. A caveat is that the solution might settle to false positive. The refinement algorithm will be presented with simulated results, controlled laboratory experiments using robotic arms and sealed radioactive sources, and finally applied to a real-world data set collected in the Chernobyl Exclusion Zone.
How to cite: Wood, K., Connor, D., Groen, S., Smith, D., White, S., Martin, P., Verbelen, Y., Holland, E., Richardson, T., and Scott, T.: UAS radiation hot-spot detection and refinement, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1744, https://doi.org/10.5194/egusphere-egu2020-1744, 2020.
Steep volcano flanks are geomorphological systems highly responsive to both exogenous dynamics and endogenous forcing. While the external (gravitational) processes lead to a shift of material from steeper slopes to areas with lower gradients (erosion of loose deposits, rockfall of lavas/welded material), magmatic and tectonic activity can have either a constructional (accumulation) or a destructive effect (triggering moderate- to large-scale mass-wasting). Remotely sensed data have often been used to map areas affected by lithological and morphological changes, i.e. to identify areas impacted by eruptive and post-eruptive (landslides or floods) phenomena, as well as to quantify topographic changes.
In this work, the geomorphological evolution of the Sciara del Fuoco (SdF) depression on the Island of Stromboli (Italy) between July 2010 and October 2019 has been reconstructed by using multi-temporal, multi-platform remote sensing data. Digital elevation models (DEMs) from PLEIADES-1 tri-stereo images and from LiDAR acquisitions allowed the topographic changes estimation. Data comprised also high-spatial-resolution (QUICKBIRD) and moderate spatial resolution (SENTINEL-2) satellite images allowing to map areas affected by major lithological and morphological changes. SdF was selected being the optimal test-site for monitoring the effect of volcanic eruption on steep-slope volcano flank, since: i) it is affected by persistent volcanic activity, ii) it is prone to mass-wasting phenomena, and iii) it is one of the best studied and, among all, monitored volcano on Earth, providing exceptional validation data and ground-truth constrains.
During the analysed period, the volcano experienced two eruptions (summer 2014 and summer 2019), with the emplacement of two lava flow fields on the SdF. Before the 2014 effusion and in between the two eruptions, geomorphological changes consisted of volcanoclastic sedimentation and some overflows outside the crater. The effusive (and partially explosive) activity produced larger topographic changes, related to the emplacement of the two lava flow fields and to the accumulation of a volcaniclastic wedge on the SdF. This work shows that, at Stromboli, the emplacements of lava flow fields were preceded and accompanied by the accumulation of volcanoclastic wedges on the SdF. The quantification of these volcanoclastic wedges is relevant because they are composed of the same material that was involved in the 30 December 2002 tsunamigenic landslide, besides being located in the same area.
PLEIADES tri-stereo and LiDAR DEMs have been quantitatively and qualitatively compared, providing a first indication on the differences between two largely used methods for modelling topography. Although there are small artefacts in smaller ridges and valleys, there is still a clear consistency between the two DEMs for the main valleys and ridges. This analysis can be used by the volcanological community and the civil protection authorities in case of a cost-benefit analysis for planning the best method for updating topography and quantify morphological changes of an active volcano.
How to cite: Di Traglia, F., Fornaciai, A., Favalli, M., Nolesini, T., and Casagli, N.: Geomorphological response to volcanic activity at Stromboli volcano using multi-platform remote sensing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3134, https://doi.org/10.5194/egusphere-egu2020-3134, 2020.
Sea cliff shapes and erosion rates are controlled by several factors. Among them, rock resistance, whose strength results from lithology and rock structure, are pointed as major factors. Erosion is expected to focus on discontinuities where the rock mass is weakest (faults, fractures, joints and strata bounds), but understanding the control of discontinuities on the spatial and temporal pattern of erosion remains challenging. To analyze and quantify how rock structures control erosion, we monitored the evolution of a 400-m-long stretch of well-structured sedimentary cliffs: the Socoa cliff (Basque Country, France). The rock, known as the Socoa flysch formation, is a 45°-seaward-tilted, shore-parallel-striking, decimeter-thick repeating sequence of sandstone, mudstone, marl and limestone beds. Cliff-face erosion was observed and quantified using 6 ground-based Structure-from-Motion (SfM) surveys, spanning 5.7 years between 2011 and 2017. To compare with longer term data, a multi-decadal (54 years) cliff-top retreat rate was also assessed using SfM-orthorectified archive aerial photographs spanning the period 1954-2008. During the ground-based survey, the 13 250 m² cliff face released 4500 blocks larger than 1.45*10-3 m3 for a total rock volume eroded of 170 m3. This rock lost volume equates to an average cliff retreat rate of 3.4 mm/yr. It is slightly slower than the 54 years-average cliff top retreat rate of 10.8 ± 1.8 mm/yr. In elevation, the maximum erosive activity is positioned about 2 m above high spring tides. The geographic position of rock scars is controlled by tectonic discontinuities. Alongshore, hot-spots of erosion are focused where major faults cross-cut the cliff face. Around these geographic hotspots, the depth of detached blocks is controlled by bed thickness, removing one or several beds at once. The surficial extent of detached blocks on the cliff-face is controlled by orthogonal secondary tectonic joint sets. These joints do not stop on lithological bed limits but rather on mechanical limits encompassing several lithological beds at once. As a process, we explain block detachment and cliff collapse by a cycle of erosion nucleation on discontinuities, radial erosion propagation around the nuclei and finally, cliff collapse crisis affecting the cliff top. We demonstrate that block production is concentrated around faults (nucleation) that focus erosion and allows for the radial development of sea caves close to cliff foot. Then, block production occurs mainly around those caves by radial detachment processes at free edges or fractures (propagation). It may lead, exceptionally, to high-magnitude events, during which slab collapse can affect the cliff from base to top (crisis).
How to cite: Regard, V., Prémaillon, M., Dewez, T. J. B., Rosser, N. J., and Carretier, S.: Role of discontinuities in spatial pattern of sea cliff erosion: case of a seaward dipping flysch cliff (Socoa, Basque Country, France), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3930, https://doi.org/10.5194/egusphere-egu2020-3930, 2020.
Close-range sensing methods for topographic data acquisition, such as Structure-from-Motion with multi-view stereo (SfM-MVS) photogrammetry and laser scanning from the ground or from unmanned aerial systems (UAS), have strongly improved over the last decade. As they are providing data with sub-decimetre resolution and accuracy, these methods open new possibilities for bridging the gap between local in-situ observations and area-wide space-borne or aerial remote sensing. For assessments of shallow landslides and erosion patches, which are wide-spread phenomena in mountain grasslands, the potential of close-range sensing is two-fold: Firstly, it could provide accurate reference data for assessing the geometric accuracy of a catchment or regional scale eroded area monitoring based on aerial or satellite remote sensing systems. Secondly, selected sites can be monitored at a very detailed local scale to reveal processes of secondary erosion or natural vegetation succession and slope stabilisation. Furthermore, high-resolution 4D data from multi-temporal close-range sensing make it possible to quantify volumes and rates of displacement at erosion features. In this contribution, we propose to exploit this potential of close-range sensing for landslide and erosion studies with object-based approaches for raster and 3D point cloud analyses. Assuming that erosion features can be discriminated from undisturbed grassland and from trees and shrubs, based on their morphometric and spectral signatures, we show how computer vision and machine learning techniques help to detect and label these features automatically as spatial objects in the data. We combine this object detection and labelling with 2.5D differential elevation models and with 3D deformation analysis of point clouds. This strategy addresses one of the key challenges of automatically analysing close-range sensing data in geomorphological studies, i.e. linking geometric information (such as the size and shape of erosion features or the surface change across a time series) with semantic information (e.g. separating vegetation from complex ground structures). In three case studies from recent projects in the Alps, where we acquired data by UAS, terrestrial laser scanning and terrestrial photogrammetry, we demonstrate the use of these new methodological developments. The methods tested can reliably detect changes with minimum magnitudes of centimetre to decimetre level, depending primarily on the specific data acquisition setup. By automatically relating these changes to erosion features of different scales (i.e. both at entire eroded areas and at their components, e.g. collapsing parts of the scarp), such analyses can provide valuable insights regarding process dynamics. In our tests, close-range sensing and automated data analysis workflows helped to understand both the development of new eroded areas as well as their enlargement by secondary erosion processes or episodic landslide reactivation. Based on the experience from these case studies, we also discuss the main challenges and limitations of these methods for erosion monitoring applications.
How to cite: Mayr, A., Rutzinger, M., Bremer, M., and Geitner, C.: Close-range sensing and object-based analysis of shallow landslides and erosion in grasslands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19847, https://doi.org/10.5194/egusphere-egu2020-19847, 2020.
The situation of the geographical map of Europe in the time interval precursor of the imperial occupation in Bukovina, was fueled by the change of the balance of forces. Territorial entities with unstable administration, depending on an imperial structure, have constituted a currency of exchange due to agreements independent of the will of the indigenous population. The upper country of Moldova did not benefit from a consistent geographical research, the first territorial representations stopped at the Carpathian mountains as a natural border of the Central European world. The first maps of Moldova are studied with a focus towards the north of the territory, identifying settlements with economic importance in the future region of Bukovina. Cutting some geographical elements represents an interest for the territorial entity in which the cartographic projection is edited.
The objectives of the paper are: 1) geographical analysis of northern Moldova during the period preceding the occupation of the Habsburg Empire, 2) identifying the degree of geodemographic and economic homogeneity of northern Moldova, and 3) research of natural geographical factors in determining the reasons of Bukovina’s annexation.
The paper highlights the period prior to the occupation, identifying geographical data about the Upper Country of Moldova, cartographic transpositions, geodemographic characteristics, economic aspects, travel impressions. These combined elements identify the degree of territorial homogeneity between the future region of Bukovina and the geographical area remaining as the principality of Moldova. The natural potential of the northwestern region of Moldova is identified in comparison with the rest of the territory. The geographical causes of the annexation of the north of Moldova are analyzed, identifying aspects other than those of spatial continuity with Galicia, geopolitical and administrative elements. The natural setting can be an element of harmony with the imperial center as a motivation for the occupation of colonization and harmonious integration of ethnic minorities.
The Carpathian Mountains have been a long-standing eastern border for the expansion of Central-European powers. Looking at an imperial map it is found that Bukovina is in the eastern extremity that cuts the territory of Moldova in the northwest. The natural geographical area of Bukovina is identified as a miniature Austria, a mountainous area in the west with wide depressions and boreal landscape, and in the east a flat plateau favorable to agricultural crops. The temperate-continental climate with Scandinavian-Baltic shades may play a role of interest for an Anglo-Saxon people adapted to this type of climate. ,,The country of beeches", reflects a geographical landscape being predominantly identifiable in western and central Europe. Natural resources are more important in terms of value and quantity compared to other regions of Moldova that have not entered the imperial sphere.
The conclusions also involve a research of the degree of natural attractiveness in the motivation of occupying the northwestern part of Moldova. The research methodology involves the transposition of historical information into geographic data, comparative analysis and cartographic method.
Keywords: Bukovina, Moldova, geography, contrast.
How to cite: Ciubotaru, C., Efros, V., and Diacon, L. D.: Particularities of the current geographical area of Suceava county in the period preceding the imperial occupation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1382, https://doi.org/10.5194/egusphere-egu2020-1382, 2020.
Although the observed global climate change has particularly affected high-alpine regions and these geosystems seem to react very sensitively to changes in external forcing, there is a lack of understanding about the effect of a changing climate upon high-alpine landscapes at the timescale of decades. In the case of rock glaciers, which are common features in high alpine periglacial landscapes, numerous studies suggest a general acceleration of rock glacier displacement rates accompanied by surface lowering. This behaviour has been attributed to the rising permafrost temperature, induced by atmospheric warming and regulated by thermo-hydrological processes. On the other hand, decoupled kinematics of nearby rock glaciers under the same climatic forcing have also been proven. This is attributed to different local topo-climatic conditions and genesis of the investigated rock glaciers. To contribute to the understanding of multi-decadal rock glacier response to climate change, we investigate the morphodynamic changes for selected rock glaciers in the Upper Kauner Valley in the Ötztaler Alps, Austria, a catchment comprising numerous rock glaciers of different size, genesis, elevation, aspect and activity status. This is done for multiple time slices between 1953 and 2017. These changes are analysed with respect to rock glacier characteristics and changes in the meteorological forcing. This work is part of the interdisciplinary and multi-university research project SEHAG (Sensitivity of high alpine geosystems to climate change since 1850), which aims to investigate changes in different processes of alpine geosystems and their interaction.
In order to investigate morphodynamics of the rock glaciers, we use digital photogrammetry to generate orthophotos and digital elevation models from historical aerial images (available since 1953). Additionally, we use digital elevation models generated from three airborne LiDAR surveys within the period 2006-2017. While the diachronic analysis of digital elevation models predominantly addresses vertical surface changes, image correlation of multitemporal digital orthophotos yields information on rates of horizontal displacement. The results for the individual rock glaciers are compared to each other and to meteorological data of nearby weather stations to analyse the response of rock glaciers with different characteristics to changing climate forcing.
How to cite: Fleischer, F., Haas, F., Heckmann, T., Altmann, M., Piermattei, L., Rom, J., and Becht, M.: Multi-decadal (1953 – 2017) response of rock glacier morphodynamics to climate change in the Kauner Valley in the Ötztaler Alps, Austria based on historical aerial images and airborne LiDAR data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8231, https://doi.org/10.5194/egusphere-egu2020-8231, 2020.
First launched in 1971, the KH-9 “Hexagon” reconnaissance satellites were operational until 1986. In addition to the high-resolution main cameras, the satellites had a secondary camera system, the mapping camera, which acquired images at approximately 6-10m ground resolution. These images, declassified in 2002, provide an unparalleled ability to extend records of elevation change over areas of the world where older data, typically from aerial photogrammetry, are missing, unavailable, or unreliable, including High Mountain Asia and the Arctic. These images are not, however, free from challenges. Storage and film processing have introduced warping into the images, and the large film format means that images are scanned in halves which must be precisely re-aligned for photogrammetric processing.
Building on previous efforts, we have developed an open-source toolset, based in python, that performs several of the steps necessary for processing digital elevation models (DEMs) from the raw imagery within MicMac. These include precise re-alignment based on dense keypoint detection, automated detection of the reseau field to aid in un-warping of the images, color balancing to increase contrast in low-contrast areas, and automated detection of ground control points using modern orthorectified satellite images such as Sentinel-2 and Landsat 8, and high-resolution digital elevation models such as ArcticDEM. Each of these tools interface with the MicMac photogrammetry software package that performs each of the steps necessary for DEM extraction.
We have tested this toolset on scenes from Alaska, Iceland, and Norway. Comparison to external elevation datasets such as NASA’s Ice, Cloud and Elevation Satellite (ICESat), ArcticDEM, and national elevation products yields agreement of better than 10 m root mean square error over stable terrain, even in mountainous areas. In particular, we obtain satisfactory results in remote areas where precise ground control measurements are difficult to obtain. This toolset provides the ability to easily extend records of precise elevation change in areas where very little historic data exist. In addition, the GCP matching routine can be used to process other air photo datasets, providing a useful tool for processing older photo archives.
How to cite: McNabb, R., Girod, L., Nuth, C., and Kääb, A.: An open-source toolset for automated processing of historic spy photos: sPyMicMac, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11150, https://doi.org/10.5194/egusphere-egu2020-11150, 2020.
Terrestrial photogrammetry is a growing method for deriving measurements from contemporary and historical imagery of glacial environments, providing unique insights into glacier change at a high spatio-temporal resolution. However, the potential usefulness of terrestrial image data is currently limited by the unavailability of user-friendly toolsets that contain all the photogrammetry processes required. PyTrx is presented here as a Python-alternative toolset to widen the range of monoscopic photogrammetry (i.e. from a single viewpoint) toolsets on offer to the glaciology community. The toolset holds core photogrammetric functions for template generation, feature-tracking, object identification, image registration, and georectification (using a planar projective transformation model), which can be performed on both contemporary and historical imagery. Examples of PyTrx's applications are demonstrated using contemporary time-lapse imagery, including ice flow velocities, surface areas of supraglacial lakes and meltwater plumes, and glacier terminus profiles.
How to cite: How, P., Hulton, N., Buie, L., and Benn, D.: PyTrx: a Python-based monoscopic terrestrial photogrammetry toolset for glaciology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22558, https://doi.org/10.5194/egusphere-egu2020-22558, 2020.
In the last years there is growing interest on urban geomorphology both for the links with landscape planning and for its historical, cultural and scientific interest.
The identification of landforms in urban contexts is particularly difficult due to the progressive stratification of urban phases: the foundation of cities in the Mediterranean area dates back to ancient times and their growth in size is generally significant from the Middle Ages. This makes it frequent to find landforms which date back to more than 1000 years ago: they can be new, man-made landforms or modifications of natural ones, particularly coastal or fluvial features. Land modifications are particularly significant in the last 2 centuries, notably in the second half of the C19th and in the second half of the C20th, two periods identified as the potential start of the Anthropocene.
Anthropogenic terrain features are generally due to excavation and fill: unlike natural landforms which are generally identifiable through field surveys, the former require field observations, cartographical comparisons, multitemporal comparison of topographical views and historical photographs, geognostic investigations and geophysical surveys.
This research presents the results of a multitemporal analysis of the city of Genoa carried out by superimposing data from nineteenth-century historical cartography and topographical data from Remote Sensing. The 1:2.000 scale map of Ignazio Porro, dating back to the first half of the C19th, has been digitalised on Lidar images from 2019 and with 1 m resolution, provided by Genoa Municipality. This methodology, developed with QGIS, has been applied on 5 sample areas particularly significant for their anthropogenic modifications: the area around Sant’Agata bridge in Val Bisagno, the area of Morandi Bridge in Val Polcevera, the road called Circonvallazione a Monte, the Promontory of the Lighthouse and the Via Digione area. Through the overlaying of multitemporal cartographies it was possible to identify and quantify with great precision excavation, landfill and mixed areas, allowing the identification of the most significant anthropogenic landforms. The obtained results have been validated through direct observations and supported by data from the geognostic regional database, revealing the potential of this approach for other urban areas.
How to cite: Terrone, M., Paliaga, G., Piana, P., and Faccini, F.: Coupling historical maps and Lidar data to recognize man-made landforms in urban areas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7826, https://doi.org/10.5194/egusphere-egu2020-7826, 2020.
The knowledge of past fluctuations of glaciers is the key for understanding their dynamics and their climate-related evolution. Glacier mass balance and length changes are the two metrics normally used for reconstructing past fluctuations series of glaciers. However, length change measurements series are often discontinuous and require validation, whereas mass balance measurements are available for only a few glaciers worldwide and only for the latest decades.
In the context of glacier reconstructions, other sources of information such as historical-archival, glacio-archaeological and geomorphological data are of critical importance, because they enable the completion and validation of direct measurement series and their extension into the past, providing spatial and temporal constraints.
A unique source of unexploited historical information dating back to the First World War (WWI, 1915-1918) exists for many glaciers in the Eastern Italian Alps. This information mainly consists of old photos, which however are spread over a multitude of sources, often difficult to access, and in many cases not yet digitized.
We propose a workflow that enables extracting quantitative information from terrestrial photographs taken during the WWI period, aimed at the reconstruction of glacier area, volume and firn lines by means of the monoplotting technique. This method relies on the availability of high-resolution digital elevation models, which became recently available over wide areas thanks to LiDAR and aerial photogrammetry. This work presents the methods applied, and the results obtained, on several case studies in the Adamello-Presanella, Ortles-Cevedale, Dolomites, and Julian Alps.
How to cite: Carturan, L., Bondesan, A., Carton, A., Cazorzi, F., Cucchiaro, S., De Marco, J., and Piermattei, L.: Use of WWI photos for quantitative reconstructions of glaciers along the Italian-Austrian front, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22512, https://doi.org/10.5194/egusphere-egu2020-22512, 2020.
The mountain cryosphere has been disproportionally affected by climate warming and changing precipitation conditions since the 19th century. This has caused intense and multiple reactions in high mountain hydrosphere, lithosphere, reliefsphere, biosphere and pedosphere. Although there is general knowledge on climate-related changes of glaciers, little is known about the high-resoluted temporal and spatial development of glaciers in the last century. These knowledge gaps further implicate limitations by simulating past and future development of the mountain cryosphere difficult, as important calibration and validation data are missing.
Topographic maps contain important information, as they are among the most reliable area-wide representations of past landscape for the time before airborne data acquisition. Thus, they offer the opportunity to extract former glacier extents and to close the information gap between the LIA extent, reconstructed from moraine extent, and aerial derived glacier information in the recent past.
However, as maps represent entities of a real world generalized depending e.g. on the intension of mapping, we consider map uncertainties as a crucial aspect for the reconstruction of glaciers from historical data.
In order to assess the accuracy of glacier area and front position from topographic maps, we reconstruct glacier extents under consideration of a comprehensive systematic examination of the uncertainty with regard to position, time and attribute. For this purpose, we use information of 12 topographic maps with a scale of 1:75,000 or larger from Kaunertal, covering a time span of 139 years (1871 – 2010) and analyse the accuracy of the maps focusing on production-related and transformation-oriented uncertainty.
The comparison between the glacier changes, derived from the maps and the original data (if available) as well as those measured in situ, shows that topographic maps are a reliable data source for the reconstruction of glacier front variations and provide vital key information when studying long time series.
How to cite: Knoflach, B., Geitner, C., and Stötter, J.: Topographic maps – an important data source for investigating long-term glacier variations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22543, https://doi.org/10.5194/egusphere-egu2020-22543, 2020.
Since the end of the Little Ice Age, alpine geosystems have been subject to changes due to the effects of ongoing climate change, affecting e.g. the cryosphere, topography, surface materials and morphodynamics, landcover, landuse, and other anthropogenic factors. Our work forms part of the SEHAG project that investigates the sensitivity of alpine geosystems to climate change during that period.
In order to identify and assess such changes, we aim at generating multi-temporal geomorphological maps of three alpine catchments (Upper Kaunertal, Horlachtal, Austria; Val Martello, Italy). In contrast to “traditional” geomorphological maps, we do not use areal, linear and point symbols to represent landforms, their properties, and geomorphic processes. Our approach is entirely based on non-overlapping polygon features that represent a landform- and process-centered subdivision of the catchment. This enables the analysis of the resulting map in a GIS framework with respect to the type, size and other properties of landforms. Most importantly, it allows for the assessment of their spatial configuration (adjacency, topology) within the catchment in terms of toposequences and sediment cascades.
Mapping is based on photogrammetric products of aerial photos, that are orthophotos, digital elevation models (DEMs) and derivatives of the latter. Furthermore, DEMs can be used for the orientation of historical terrestrial photographs, making them an additional mapping basis through monoplotting. Depending on the availability of imagery (area-wide aerial images dating back to the mid of the 20th century; local terrestrial photos starting from the second half of the 19th century), an area-wide geomorphological map representing the present state of the system forms the basis of our investigations. Historical images are then used to “update” the map back into the past wherever differences to the temporally subsequent situation are conspicuous. This especially regards the massive decline of glaciers, but also the build-up and depletion of storage landforms, the development of lakes, and changes in the channel network.
At a later stage, the maps will be used for a network-based, multitemporal assessment of sediment connectivity. Nodes represent landforms contained in the geomorphological map(s), and all kinds of evidence (visible features indicating sediment transfer between adjacent landforms, measurements based on DEMs of difference, connectivity indices) will be used to establish edges that represent (potential) sediment transfer by geomorphic processes. As the configuration of system components and/or the activity of processes changes between maps of subsequent epochs, these changes will affect connectivity measures of the corresponding network model.
How to cite: Heckmann, T., Piermattei, L., Rom, J., Altmann, M., Fleischer, F., Haas, F., and Becht, M.: Multi-temporal geomorphological maps based on historical aerial images for the investigation of geomorphic changes in an Alpine catchment , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22605, https://doi.org/10.5194/egusphere-egu2020-22605, 2020.
The project “Between Land and Sea” was initiated by OREA (Institute for Oriental and European Archaeology) and is an interdisciplinary approach to combine the geology, geomorphology, and paleo-environment of the Chekka region (Lebanon) to investigate the ancient history and its archaeological remains. In the course of the project, the first ever scientific LiDAR (Light Detection and Ranging) data acquisition in Lebanon was conducted in autumn 2018 and a high-resolution DEM (Digital Elevation Model) was calculated. However, this model represents the recent topographical situation, which has changed drastically not only in the archaeologically relevant period up to 5000 years before today but also during the last decades.
To be able to qualitatively and quantitatively record geomorphological processes in the study area and thus understand long-term natural and anthropogenic landscape changes, the recent elevation model is compared with a historical model. The historical elevation model was derived on the base of aerial images of a French overflight from 1962. With the help of SfM (Structure from Motion/Agisoft Metashape) in combination with referencing methods (e.g. ICP), this historical model can be adapted to the LiDAR model. Quantitative analyses of selected areas provide information about surface changes over the last 56 years. But these results give also ideas about landscape evolution over longer time periods. Besides the natural changes, the historical model also reveals major anthropogenic changes since 1962 and shows that possible archaeologically relevant sites have been lost as a result of extensive overprinting due to the construction of buildings, infrastructure, industrial mining or agricultural use.
Our promising results show, that the implementation of historical terrain models based on aerial photographs can lead to a better understanding of the natural landscape development as well as anthropogenic induced changes and thus can also provide important additional information for archeological surveys.
How to cite: Rom, J., Haas, F., Stark, M., Poschenrieder, A., Kopetzky, K., and Genz, H.: Between Land and Sea: An analysis of the landscape changes in the Chekka region (Lebanon) based on airborne LiDAR data and historical aerial images from 1962, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22519, https://doi.org/10.5194/egusphere-egu2020-22519, 2020.
After World War II, aerial photography i.e. vertical or oblique high-resolution aerial images spread rapidly into civil research sectors, such as landscape studies, geologic maps, natural sciences, archaeology, and more. Applying photogrammetric techniques, two or more overlapping historical aerial images can be used to generate an orthophoto and a 3D point cloud, wherefrom a digital elevation model can be derived for the respective epoch. Combining results from different epochs, morphological processes and elevation changes of the surface caused by anthropogenic and natural factors can be assessed. Despite the unequalled potential of such data, their use is not yet fully exploited. Indeed, there is a lack of clear processing workflows applying either traditional photogrammetric techniques or structure from motion (SfM) with camera self-calibration. In fact, on the one hand, many SfM and multi-view stereo software do not deal with scanned images. On the other hand, traditional photogrammetric approaches require information such as a camera calibration protocol with fiducial mark positions. Furthermore, the quality of the generated products is strongly affected by the quality of the scanned images, in terms of the conservation of the original film, scanner resolution, and acquisition parameters like image overlap and flying height.
To process a large dataset of historical images, an approach based on multi-epoch bundle adjustment has been suggested recently. The idea is to jointly orient the images of all epochs of a historical image dataset. This recent approach relies on the robustness of the scale-invariant feature transform (SIFT) algorithm to automatically detect common features between images of the time series located in stable areas. However, this approach cannot be applied to process digital images of alpine environments, characterized by continuous changes also of small magnitude that might be challenging to automatically identify in image space. In this respect, our method implemented in OrientAL, a software developed by TU Wien, identifies stable areas in object space across the entire time series. After the joint orientation of the multi-epoch aerial images, dense image matching is performed independently for each epoch. We tested our method on an image block over the alpine catchment Kaunertal (Austria), captured at nine different epochs with a time span of fifty years. Our method definitely speeds up the process of image orientation of the entire data set, since stable areas do not need to be masked manually in each image. Furthermore, we could improve the orientation of images from epochs with poor overlap. To estimate the improvements obtained with our methods in terms of time and accuracy of the image orientation, we compare our results with photogrammetric and commercial SfM software and we analyse the accuracy of tie points with respect to a reference Lidar point cloud. The work is part of the SEHAG project (project number I 4062) funded by the DFG and FWF.
How to cite: Ressl, C., Karel, W., Piermattei, L., Puercher, G., Hollaus, M., and Pfeifer, N.: Multi-epoch bundle block adjustment for processing large dataset of historical aerial images , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22544, https://doi.org/10.5194/egusphere-egu2020-22544, 2020.
The state-of-the-art in surveying of open surface the last few decades is based on Point Cloud processing and interpretation. Lately, similar technology tends to be used for indoor surveying as well. One of the extreme applications is the use of the exact same technology in underground karstic cavities, evolving the methodology used in cave mapping. Geometric and morphometric analysis of the caves or any containing components (speleothems) include various techniques aiming at quantifying their dimensions in order to determine the characteristics and consequently the relationship between the cavity morphology and the surrounding structural, lithological and hydrogeological properties. The purpose of this research is to combine high resolution topographic data acquired with different instruments for both the underground morphology of a karstic cave (Koutouki, Peania, Greece) and the open-air surface above it. The described methodology is based on photogrammetric processing of Unmanned Aerial System image data and the extraction of a point cloud recorded with the use of a handheld laser scanning system. The latter resulted a 3D model of the cave and led to the production of a digital relief for the roof of the cave, which in turn was combined with the digital terrain model of the open-air surface above the cave. The final product is a high-resolution information layer with measurements of the rock thickness between the roof of the underground karstic structure and the open-surface topography with high accuracy.
How to cite: Konsolaki, A. and Vassilakis, E.: Karst Topography Analysis Based on Multi-sensor (UAS & LiDAR) Data Acquisition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2928, https://doi.org/10.5194/egusphere-egu2020-2928, 2020.
The Sajó River in Hungary is a medium-sized sand-bed river along which intensive meander development and bank erosion occur. The process threatens agricultural lands and populated areas extensively. Therefore, preventive river management is needed.
Main geomorphological features, processes and in-channel flow conditions have to be studied in detail in order to reveal main driving factors. Datasets with high spatio-temporal resolution are necessary to identify relevant parameters. However, so far data density at this river is sparse and gauging stations are distributed poorly.
The aim of this study is the improvement of data availability to measure and model hydromorphodynamics of single reaches of the Sajó River. Therefore, multi-temporal field campaigns along selected sub-reaches are conducted with Unmanned Aerial Vehicles (UAV) and Unmanned Water Vehicles (UWV) to survey the topography, the river bed and flow conditions. The channel bathymetry is measured by a single-beam echo sounder mounted on a self-designed remotely controlled boat. The boat also integrates a Mobile Laser Scanner (MLS) to measure the river banks. Furthermore, a panorama camera system is installed to improve the pose estimation of the UWV functioning as a calibrated multi-sensor platform. UAV surveys were performed, using RGB and Thermal Infrared image sequences, to apply image velocimetry algorithms to characterize the river flow at selected cross-sections. ADCP measurements and Terrestrial Laser Scans (TLS) are used for accuracy assessment of the novel datasets.
Eventually, data captured over a 2-years period will be implemented into hydrodynamic modeling of the studied sub-reaches to better understand seasonal variations in channel morphodynamics.
The project has been founded by the DAAD (57448822) and (Tempus Public Foundation & DAAD 307670). The research is also influenced by the HARMONIOUS COST Action (CA16219).
How to cite: Bertalan, L., Sardemann, H., Mader, D., Szopos, N. M., Nagy, B., and Eltner, A.: Geomorphological and hydrological characterization of a meandering river by UAV and UWV applications, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18069, https://doi.org/10.5194/egusphere-egu2020-18069, 2020.
High resolution topographic models generated from repeat unmanned aerial vehicle (UAV) surveys and structure from motion (SfM) are increasingly being used to investigate landscape changes and geomorphic processes. Traditionally, accurate UAV surveys require the use of independently measured ground control points or highly accurate camera position measurements. However, in addition to accuracy in an absolute sense (how well modeled topography matches real topography), model quality can be expressed as accuracy in a comparative sense (the degree to which two models match each other). We present a simple SfM workflow for calculating pairs or sets of models with a high comparative accuracy, without the need for ground control points or a dGNSS equipped UAV. The method is based on the automated detection of common tie points in stable portions of the survey area and, compared to a standard SfM approach without ground control, reduces the level of change detection in our surveys from several meters to 10-15 cm. We apply this approach in a multi-year monitoring campaign of an 8 km stretch of coastal cliffs on the island of Rügen, Germany. We are able to detect numerous mass wasting events as well as bands of more diffuse erosion in chalk sections of the cliff. Both the cliff collapses and the diffuse erosion appear to be strongly influenced by antecedent precipitation over seasonal timescales, with much greater activity during the winter of 2017-2018, following an above average wet summer, than during the subsequent two winters, which both followed relatively dry summers. This points to the influence of subsurface water storage in modulating cliff erosion on Rügen.
How to cite: Cook, K. and Dietze, M.: UAV-derived change detection without ground control points, an example from the cliff coast of Rügen, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11735, https://doi.org/10.5194/egusphere-egu2020-11735, 2020.
In the last two decades, important developments in High-Resolution Topographic (HRT) techniques, methods, sensors, and platforms has greatly improved our ability and opportunities for the characterization of landscapes through sub-metric DTMs (Digital Terrain Models). The choice of the most appropriate platform for HRT surveys must consider the required resolution, the spatial extent, and the features present in the analysed area. In complex topography, inaccessible areas and vegetated environments, the use of a single HRT technique is constrained by several factors. Therefore, data fusion from different acquisition platforms can be a useful solution if we design appropriate workflows for survey planning, data acquisition, post-processing, and uncertainty assessment. We tested this approach in the production of detailed DTMs of ancient agricultural terracing on two sites, Soave (North-east of Italy) and Martelberg in Saint-Martens-Voeren (East Belgium); case study sites for the TerrACE archaeological research project (ERC-2017-ADG: 787790, 2018-2023; https://www.terrace.no/). Both sites presented complex topographic and landcover conditions: the presence of vegetation (common in ancient, often abandoned, terraces) that cover parts of the sub-vertical surfaces (e.g., vertical walls of terraces), steep slopes and large survey areas. Therefore, we carefully designed the data fusion of HRT techniques in order to overcome all these constraints and thereby represent detailed 3D-views of the study sites. An integrated approach employing ground-based and UAV Structure from Motion (SfM) photogrammetry was used to preserve fine-grained topographic detail (via ground-based photos) and capture flat terrace zones at large spatial scale (via UAV images); while terrestrial Laser Scanner (TLS) permitted the accurate survey of the highly vegetated areas and vertical terrace walls. In order to create the point-cloud fusion, a key aspect for consideration when planning the survey planning was the location and distribution of the Ground Control Points (GCPs) for SfM and TLS targets. These are essential for georeferencing and co-registering of the aggregate data during the final merge. In the inaccessible zones of the studied areas, where was impossible to locate the GCPs, we tested the direct georeferencing of the UAV images with differential GNSS, such as PPK (post-processing kinematic). The SfM-TLS technologies allowed us to accurately recognize the topographic features of the entire terrace areas. This point-clouds merge was impossible to obtain without post-processing steps as co-registration process and uncertainty analysis. Even if several studies highlight how co-registration is essential in order to correctly merge HRT data, it is often not addressed in post-processing workflows. In this study, we demonstrated how survey planning and co-registration were fundamental phases for data fusion and allowed us to obtained proper and reliable DTMs. These high-resolution DTMs provided a high level of detail of landscape that was useful to extract valuable information about ancient terrace complexes: morphological features, profiles, sections and scaled plans, simplifying and speeding the archaeologist's field and laboratory work.
How to cite: Cucchiaro, S., Fallu, D. J., Zhang, H., Walsh, K., Van Oost, K., Brown, A. G., and Tarolli, P.: Terrestrial-Aerial-SfM and TLS data fusion for agricultural terrace surveys in complex topographic and land cover conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3459, https://doi.org/10.5194/egusphere-egu2020-3459, 2020.
A rock wall failure occurred along a major highway in south-eastern Norway, shutting down two lanes of traffic for an extended period of time while the road authority inspected and repaired the wall. It was desired to have a high-resolution digital surface model along a 215-m long section of the 34-m tall vertical rock wall that included the failure zone.
A Structure-from-Motion (SfM)-based methodology was selected to achieve the desired resolution on the rock wall face, as well as below the foot and above the head of the wall. Due to the proximity of the wall face to the remaining open lanes of traffic, it was not possible to survey the face of the wall using a remotely piloted aircraft system (RPAS). Therefore, a combined platform photogrammetric surveying technique was employed to ensure optimal photographic coverage and to generate the best possible model. Ground control points (GCP) were distributed and surveyed along the bottom and top of the wall and an RPAS was flown manually over the head of the wall to capture downward facing (nadir) images. A lift crane was also employed to capture images from elevations varying between 20–30 meters with a standoff distance of 15 meters from the wall. Finally, ground-based images were captured using a camera equipped with real-time GNSS from the top of the opposite rock wall (across the highway) with standoff distance of approximately 65 meters.
In total, over 800 images were ingested into a commercial SfM software package. The bundle adjustments were assisted by the GNSS-equipped camera locations and the surveyed GCP were imported to georeference the resulting model. The dense point cloud product was exported to a separate meshing software package for comparison with a second dense surface model that was derived from pre-existing images of the as-built condition of same rock wall face (prior to failure). By subtracting the post-failure model from the pre-failure model, a volume estimate of the material, that was mobilized during the failure, was determined.
The utility of the multi-platform survey technique was demonstrated. The combination of aerial and ground-based photographic surveying techniques provided optimal photographic coverage of the entire length of the rock wall to successfully derive high-resolution surface models and volume estimates.
Keywords: Structure-from-Motion, photogrammetry, digital surface model, natural hazards, ground control.
How to cite: Smebye, H., Salazar, S., and Lysdahl, A.: Combined aerial and ground-based Structure-from-Motion modelling for a vertical rock wall face to estimate volume of failure , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20471, https://doi.org/10.5194/egusphere-egu2020-20471, 2020.
Soil water content is one of the most common physical parameters that cause landslides or debris flow. Therefore, it is of very importance to determine or predict the water content variation due to infiltration of rainfall quickly and non-destructively. This study investigates the hyperspectral informations in the visible near-infrared regions (VNIR, 400nm~1000nm) of different samples of granite soils possessing varying water contents. Totally 162 granite samples were taken from 3 mountain areas. A Partial Least Squares Regression (PLSR) analysis was applied to develop calibration models and prediction models. In the water content variation prediction model, the Area of Reflectance(Near-infrared, NIR) parameter was the most suitable parameter to determine the water content. The results demonstrate that the hyperspectral camera combined with the PLSR model can be a useful and non-destructive tool for the determination of soil water content variation in the weathered granite soils that could be applied to the evaluation of possible instable area in a mountain site.
How to cite: Lim, H., Lee, S.-R., Cheon, E., Lee, D., and Lee, S.: Soil Water Content Variation Regression Analysis Using Hyperspectral Camera in Weathered Granite Soils, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4373, https://doi.org/10.5194/egusphere-egu2020-4373, 2020.
Soil erosion represents one of the most significant environmental problems of the 21st century with severe impacts on terrestrial ecosystems. Traditionally, soil losses by water are determined by runoff plots in situ. Micro-scale devices (<1 m length) are commonly used to monitor soil erosion rates in comparative field studies. This is especially the case in ecological-pedological experiments, investigating e.g. the effect of plant characteristics on erosion processes. The small plot size allows to focus precisely on interrill processes with the smallest possible set of confounding factors and a high number of replications. However, the runoff plot method is labour- and time-intensive, sediment handling can be challenging and the measurement accuracy varies importantly with the applied control of the measurement setup.
To optimize the acquisition of small-scale erosion data from splash and interrill processes, digital methods become more and more of interest. Therefore, we compared the use of photogrammetry with a) terrestrial and b) airborne (UAV) single lens reflex (SLR) cameras as well as c) a terrestrial laser scanner (Leica Scanstation P40) to determine event-based initial erosion rates. Rainfall simulations with the Tübingen rainfall simulator and micro-scale runoff plots (0.4 m × 0.4 m) were conducted on two substrates: a Hortic Anthrosol and sieved sand (0.10-0.45 mm). Runoff plots were exposed to rainfall events with an intensity of 60 mm h-1. The measurements were repeated 5 times per substrate for each method and images of the runoff plot surfaces were captured before and after every event. The overlapping SLR images were processed in Agisoft PhotoScan (Structure from Motion - SfM) to process digital surface models (DSMs) with sub-millimetre resolution (a + b). Laser scans were processed with Leica Cyclone and ESRI ArcGIS (c). We assessed the volume of detached sediment by calculating the differences between multi-temporal DSMs or point clouds. After every rainfall simulation, the discharged sediment was weighed to derive the ground-truth for validation.
The results showed that photogrammetry with digital cameras as well as the use of laser scanners are principally suitable methods to create small-scale 3D point clouds and to map topography differences necessary for initial erosion rate calculation. The processing with common software systems, however, proves to be challenging and high precision is required for recording in the field. All methods overestimated the erosion rates with differences to the weighed sediment delivery from 14 to 45 %. The accuracy was higher for uniform sand than for the Anthrosol treatment. The SfM approach with digital cameras derived better results than the laser scanner used in this study. The terrestrial use of cameras was superior to the airborne use in this small-scale setup, because of the necessary flight altitude to avoid air turbulences on the soil surface. Further development of the measuring techniques and their precise application in the field as well as adapted software processing are still needed. Nevertheless, the methods tested show promising possibilities even for small-scale erosion measurements. Ideas and further suggestions on improvements will be presented at the EGU 2020.
How to cite: Seitz, S., Scholten, T., and Schmidt, K.: Soil erosion monitoring at small scales: Using close range photogrammetry and laser scanning to evaluate initial sediment delivery, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16685, https://doi.org/10.5194/egusphere-egu2020-16685, 2020.
Soil erosion is one of the most prominent environmental problems of major interest to a vast field of research. Due to the complexity, variability and discontinuity of erosional processes, erosion model approaches are non-transferable to different spatial and temporal scales.
The objective of our project is the across-scale modelling of soil erosion, using photogrammetric measurements and optimization methods as well as physical based model approaches. Present process-based models are only valid for the observation scale they are parametrized and validated for. In the observed reality phenomena therefore occur, which are not or only to some extent reproducible by complex model concepts (e.g. development of rills or concentrated runoff within driving lanes). We present the synergetic combination of a physically described model with highly redundant observations from photogrammetric data processing. This enables both the validation of the erosion model EROSION-3D as well as the optimization of its parameters and potentially advancement of the mathematical process description. The photogrammetric observations (RGB and thermal) offer the opportunity of a temporal and spatial differentiated process assessment (splash, sheet and rill erosion, as well as deposition and transport). To this purpose, the acquisition of the respective operating processes and contributing factors, will be nested defined at three different scales (micro plot, single slope and catchment scale) on two sites (loess soil and residual soil).
Flexible cross-scale applicable photogrammetric methods, considering 3D reconstruction and flow measurement, combined with physical-based methods of soil erosion modelling shall enable a better and reliable understanding of soil erosion processes on various spatial and temporal observation scales. Consequently, the implementation of the adjusted model is aimed for to enable a cross-scale description and validation of scale-dependent processes (e.g. discrete consideration of thin sheet flow and rill genesis) to offer new perspectives on both interconnectivity of sediment transport and relationship between event frequency and magnitude.
How to cite: Epple, L., Kaiser, A., Schindewolf, M., and Eltner, A.: High-resolution photogrammetric methods for nested parameterization and validation of a physical-based soil erosion model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18252, https://doi.org/10.5194/egusphere-egu2020-18252, 2020.
Terrestrial laser scanning (TLS) is frequently used for contactless acquiring of highly detailed and accurate three-dimensional (3D) representation of natural landscapes and man-made objects. The advantage of TLS has been exploited in mapping the underground landscapes such as caves formed in various geological settings with variable dimensions extending from narrow passage to grand domes. Highly detailed cave surveying with TLS generates millions of 3D coordinates of cave surface by which mapping of features difficult to be reached and studied directly is possible, e.g. speleothems, ceiling channels, structural rock properties and rock type alongside with the tectonic features influencing overburden stability. Besides the 3D coordinates, intensity of the backscattered laser pulse is recorded in the form of an additional attribute, influenced by various factors including spectral properties of the surface material. The studies published on the use of laser intensity have been mainly focused on the correction of intensity recorded by TLS for objects in the above-ground environment, where atmospheric attenuation, specifically humidity or dust content in the air, is negligible or it is considered constant during scanning. However, caves are specific due to their complex morphology and aerosol in their atmosphere. The presented case study focuses on these aspects in correcting the recorded intensity with a long range TLS Riegl VZ-1000 in the Gouffre Georges cave which formed on the contact of marble and lherzolite in the French Pyrenees. We present complex workflow for elimination of the influencing factors associated with the scanning geometry, including range and incidence angle, taking into account the character and contours of the cave wall surface as a set of facets and effect of atmospheric attenuation. The resulting corrected intensity value depends mostly on the spectral surface properties. Derived reflectance values revealed different lithological layers allowing to analyse their lithological and structural properties. Corrected intensity can be also used in biospeleological studies for mapping and quantification of cave fauna, in speleology for observing structures with higher occurrence of wet areas where active karst processes occur and even in archaeological studies for identification of cave paintings.
How to cite: Nováková, M., Gallay, M., Šupinský, J., Ferré, E., and Sorriaux, P.: Improving the use of laser scanning intensity data in complex 3D mapping of the cave environment: Case study of the Gouffre Georges Cave, France, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18742, https://doi.org/10.5194/egusphere-egu2020-18742, 2020.