Using eCognition Definiens for automated detection of snow avalanches from optical imagery

Detection of avalanches from remotely collected optical imagery has been tested through analysis of image properties such as brightness, contrast, and different measures of texture. There have been few publications on the subject, providing an excellent opportunity for new developments. The work conducted at NGI in 2011 aimed at detecting fresh snow avalanches from very-high resolution (VHR) optical imagery. The research presented in this Technical Note has been supported by the Ministry of Petroleum and Energy (OED) through the Norwegian Water Resources and Energy Directorate (NVE).Norges Forskningsråd (NFR

Using eCognition Definiens for automated detection of snow avalanche deposits from very high resolution optical imagery - New developments

The identification of snow avalanche deposits from high resolution optical satellite imagery had been the focus of the project "avalRS” which NGI, together with the Norwegian Computing Centre and Statens Veivesen, had carried out for the European Space Agency (2008-2011; e.g., Frauenfelder et al., 2011). The algorithms developed have produced variable results, often working well in certain situations and poorly in others. In 2011 using the object oriented image processing software eCognition, NGI developed two prototype algorithms on its own. The two algorithms were developed for (i) QuickBird satellite imagery, and (ii) Leica ADS-40 airborne imagery (cf. Lato and Frauenfelder, 2012).Aspart of the continuation of this research program, the algorithms developed in 2011 were published in the journal *Natural Hazards and Earth System Sciences* (Lato et al., 2012a) as well as presented at International conferences, e.g., at the "International Snow Science Workshop 2012” in Anchorage, Alaska (Lato et al., 2012b). Overall the developments have been accepted well within the community, the preliminary results demonstrate the possibility of numerous research and commercial applications. In parallel with the publication and presentation of the research results in 2012, new satellite images containing snow avalanche deposits were tested with the algorithms in eCognition. An overview of the data, the region it represents, as well as a discussion of the results is included in this document.Norges vassdrags- og energidirektorat (NVE), Region Ves

Automated Avalanche Deposit Mapping From VHR Optical Imagery

Using eCognition we developed an algorithm to automatically detect and map avalanche deposits in Very High Resolution (VHR) optical remote sensing imagery acquired from satellites and airplanes. The algorithm relies on a cluster-based object-oriented image interpretation approach which employs segmentation and classification methodologies to identify avalanche deposits. The algorithm is capable of detecting avalanche deposits of varying size, composition, and texture. A discrete analysis of one data set (airborne imagery collected near Davos, Switzerland) demonstrates the capability of the algorithm. By comparing the automated detection results to the manually mapped results for the same image, 33 of the 35 manually digitized slides were correctly identified by the automated method. The automated mapping approach characterized 201 667 m2, of the image as being representative of a fresh snow avalanche, roughly 8.5% of the image. Through a spatial intersection between the manually mapped avalanches and the automatically mapped avalanches, 184 432 m2, or 89%, of the automatically mapped regions are spatially linked to the manually mapped regions. The rate of false positive was less than 1% of the pixels in the image. The initial results of the algorithm are promising, future development and implementation is currently being evaluated. The ability to automatically identify the location and extent of avalanche deposits using VHR optical imagery can assist in the development of detailed regional maps of zones historically prone to avalanches. This in turn can help to validate issued avalanche warnings

Previously hidden landslide processes revealed using distributed acoustic sensing with nanostrain-rate sensitivity

Landslides sometimes creep for decades before undergoing runaway acceleration and catastrophic failure. Observing and monitoring the evolution of strain in time and space is crucial to understand landslide processes, including the transition from slow to fast movement. However, the limited spatial or temporal resolution of existing landslide monitoring instrumentation limits the study of these processes. We employ distributed acoustic sensing strain data below 1 Hertz frequency during a three-day rainfall at the Hollin Hill landslide and quantify strain-rate changes at meter and sub-minute scales. We observe near-surface strain onset at the head scarp, strain acceleration at a developing rupture zone, retrogression towards the scarp, and flow-lobe activity. These processes with displacements of less than 0.5 mm are undetected using other methods. However, the millimeter processes over three days agree with previously observed seasonal landslide patterns. Here, we show landslide processes occurring with nanostrain-rate sensitivity at spatiotemporal resolution previously not possible

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Canadian Geotechnical Colloquium: 3D remote sensing, 4D analysis and visualization in geotechnical engineering: state-of-the-art and outlook

Successful geotechnical projects occur when the design is based on a thorough understanding of the geologic and environmental systems, and the interaction of these systems over time. The ability to examine and track movement through space and time has been an essential part of the geoprofessional’s toolkit since the onset of the practise. Since the early 2000s high resolution 3 dimensional (3D) topographic data have begun to transform how we map and understand movement through time across spatially extensive regions at unprecedented levels of accuracy and confidence. This paper examines how high-resolution 3D topographical data, 4-dimensional (4D) analysis and visualization of data in 3D environments can improve our ability to better understand changes in the morphology and material behaviour through time leading to better decisions and better outcomes. Evolution of advancements made over the past 20 years will be presented through case studies where positive impacts were realized through the adoption of 3D remote sensing and 4D analysis, and cases where data could be used in the future to improve outcomes. The paper will present current research being done to further improve processing techniques and exploit new data collection and computational processing capabilities, pushing the capability of time-dependant 4D geotechnical monitoring to new limits.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Managing Rockfall Risk through Baseline Monitoring of Precursors with a Terrestrial Laser Scanner

Rockfalls represent significant risks to safe and efficient use of transportation corridors. In this paper we address the management of rockfall risk through baseline remote monitoring of susceptible slopes (every 2-4 months) along a transportation corridor along the Fraser River Valley in western Canada with a terrestrial laser scanner and supporting remote sensing technologies. This includes identifying potential rockfall source zones based on incipient signs of failure, tracking kinematics in 3D to better understand the mechanism of failure, estimating potential failure volumes based on bounding joint structure and transmitting this information to the railway operator for an assessment of risk. We demonstrate our approach for one case along the line where we identified several potential failures ranging in volume from 48 m3 to 4200 m3. Our projections of the location of failures were successful, in that volume projections were within 10-55%, and the anticipated kinematics and failure mechanism were consistent with the assessment of post failure rockfall scar geometries. Accurate volume and kinematics estimates are important for the assessment of hazard, risk and the planning of risk mitigation options. In general, this approach can be used to better manage risk from rockfall hazard in communities, transportation corridors or other infrastructure.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author