Assessing debris flows using LIDAR differencing: 18 May 2005 Matata event, New Zealand

Abstract

a b s t r a c tThe town of Matata in the Eastern Bay of Plenty (New Zealand) experienced an extreme rainfall event on the 18 May 2005. This event triggered widespread landslips and large debris flows in the Awatarariki and Waitepuru catchments behind Matata. The Light Detection and Ranging technology (LIDAR) data sets flown prior to and following this event have been differenced and used in conjunction with a detailed field study to identify the distribution of debris and major sediment pathways which, from the Awatarariki catchment, transported at least 350,000 ± 50,000 m 3 of debris. Debris flows were initially confined to stream valleys and controlled by the density and hydraulic thrust of the currents, before emerging onto the Awatarariki debris fan where a complex system of unconfined sediment pathways developed. Here, large boulders, clasts, logs and entire homes were deposited as the flows decelerated. Downstream from the debris fan, the pre-existing coastal foredune topography played a significant role in deflecting the more dilute currents that in filled lagoonal swale systems in both directions. The differenced LIDAR data have revealed several sectors characterised by significant variation in clast size, thickness and volume of debris as well as areas where post-debris flow cleanup and grading operations have resulted in man-made levees, sediment dumps, scoured channels and substantial graded areas. The application of differenced LIDAR data to a debris flow event demonstrates the techniques potential as a precise and powerful tool for hazard mapping and assessment.Crown

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

“…Many authors demonstrated that the automatic extraction of geomorphic features from ALS-derived HR-DEMs (see [111]) is a precise and powerful tool for mapping and assessment of shallow landslides and bank erosion, by means of statistical analysis of the variability of the landform curvature [112]; deep-seated landslides, through supervised classification methods [113] or standard signal processing techniques [114]; and debris flows, with differenced ALS data [115]. Exploitation of the automated analysis of ALS data was used for post-event analysis, for instance mapping of earthquake-triggered shallow landslides [116], and detection of typhoon-triggered landslides [117].…”

“…ALS data have been also integrated to hyperspectral images to monitor an earthflow [61]. Many research works demonstrated the potentiality of automatic extraction of geomorphic features from ALS HR-DEMs, including the detection of debris flow as well, see, e.g., [115].…”

Analysis of Debris Flow Behavior Using Airborne Lidar and Image Data

“…Owing to recent progress in photogrammetry and surveying technologies (e.g., LiDAR), it is now possible to produce centimeter-level ultra-high resolution digital elevation models (DEMs) that enable more accurate observations of geomorphologic changes. Many researchers have investigated methods for detecting large-scale landslides and debris flow areas with these technologies for the purpose of monitoring geomorphic changes, calculating the extent of changes and assessing debris flow behavior (McKean and Roering, 2004;Du and Teng, 2007;Tsutsui et al, 2007;Schelidl et al, 2008;Bull et al, 2010;Kim et al, 2014). However, because these studies examined LiDAR DEMs with relatively long intervals between acquisitions (≥5 years), some natural topographic changes were missed.…”

Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition

“…Only a few studies have attempted to develop computer-assisted methods for Remote Sens. 2016, 8,95 3 of 32 extracting landslides from single or multiple pulse LiDAR data via pixel-based analysis [4,12,42]. Schulz [33,43] used a LiDAR DEM to identify the topography of the Puget Sound region of Seattle, USA.…”