TY - JOUR A1 - Obu, Jaroslav A1 - Lantuit, Hugues A1 - Fritz, Michael A1 - Pollard, Wayne H. A1 - Sachs, Torsten A1 - Guenther, Frank T1 - Relation between planimetric and volumetric measurements of permafrost coast erosion: a case study from Herschel Island, western Canadian Arctic JF - Polar research : a Norwegian journal of Polar research N2 - Ice-rich permafrost coasts often undergo rapid erosion, which results in land loss and release of considerable amounts of sediment, organic carbon and nutrients, impacting the near-shore ecosystems. Because of the lack of volumetric erosion data, Arctic coastal erosion studies typically report on planimetric erosion. Our aim is to explore the relationship between planimetric and volumetric coastal erosion measurements and to update the coastal erosion rates on Herschel Island in the Canadian Arctic. We used high-resolution digital elevation models to compute sediment release and compare volumetric data to planimetric estimations of coastline movements digitized from satellite imagery. Our results show that volumetric erosion is locally less variable and likely corresponds better with environmental forcing than planimetric erosion. Average sediment release volumes are in the same range as sediment release volumes calculated from coastline movements combined with cliff height. However, the differences between these estimates are significant for small coastal sections. We attribute the differences between planimetric and volumetric coastal erosion measurements to mass wasting, which is abundant along the coasts of Herschel Island. The average recorded coastline retreat on Herschel Island was 0.68m a(-1) for the period 2000-2011. Erosion rates increased by more than 50% in comparison with the period 1970-2000, which is in accordance with a recently observed increase along the Alaskan Beaufort Sea. The estimated annual sediment release was 28.2 m(3) m(-1) with resulting fluxes of 590 kg C m(-1) and 104 kg N m(-1). KW - Coastal erosion KW - LiDAR KW - carbon fluxes KW - mass wasting KW - landslides KW - digital elevation model Y1 - 2016 U6 - https://doi.org/10.3402/polar.v35.30313 SN - 0800-0395 SN - 1751-8369 VL - 35 SP - 57 EP - 99 PB - Co-Action Publ. CY - Jarfalla ER - TY - JOUR A1 - Malinowski, Radostaw A1 - Höfle, Bernhard A1 - Koenig, Kristina A1 - Groom, Geoff A1 - Schwanghart, Wolfgang A1 - Heckrath, Goswin T1 - Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data JF - ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing N2 - Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques are often hampered on floodplains by the presence of herbaceous vegetation. To address this problem, this study presents the application of full waveform airborne laser scanning (ALS) data for detection of floodwater extent. In general, water surfaces are characterised by low values of backscattered energy due to water absorption of the infrared laser shots, but the exact strength of the recorded laser pulse depends on the area covered by the targets located within a laser pulse footprint area. To account for this we analysed the physical quantity of radio metrically calibrated ALS data, the backscattering coefficient, in relation to water and vegetation coverage within a single laser footprint. The results showed that the backscatter was negatively correlated to water coverage, and that of the three distinguished classes of water coverage (low, medium, and high) only the class with the largest extent of water cover (>70%) had relatively distinct characteristics that can be used for classification of water surfaces. Following the laser footprint analysis, three classifiers, namely AdaBoost with Decision Tree, Naive Bayes and Random Forest, were utilised to classify laser points into flooded and non-flooded classes and to derive the map of flooding extent. The performance of the classifiers is highly dependent on the set of laser points features used. Best performance was achieved by combining radiometric and geometric laser point features. The accuracy of flooding maps based solely on radiometric features resulted in overall accuracies of up to 70% and was limited due to the overlap of the backscattering coefficient values between water and other land cover classes. Our point-based classification methods assure a high mapping accuracy (similar to 89%) and demonstrate the potential of using full-waveform ALS data to detect water surfaces on floodplain areas with limited water surface exposition through the vegetation canopy. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. KW - ALS KW - LiDAR KW - Point cloud KW - Inundation KW - Full-waveform KW - Water Y1 - 2016 U6 - https://doi.org/10.1016/j.isprsjprs.2016.06.009 SN - 0924-2716 SN - 1872-8235 VL - 119 SP - 267 EP - 279 PB - Elsevier CY - Amsterdam ER -