Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

Final Report of the DAUFIN project

DAUFIN = Data Assimulation within Unifying Framework for Improved river basiN modeling (EC 5th framework Project

Continental-scale high-resolution river geometry and real-time inundation mapping

Flooding is the most threatening natural disaster worldwide considering the fatalities and property damage it causes. Recent flood disasters have raised concerns for accurate and responsive inundation forecast due to the rapid spread and astonishing destructive power of these events. Although recent development in large scale hydrologic simulation has enabled the real-time streamflow simulation operating on millions of river reaches, a framework for converting the forecast discharge into corresponding water surface elevation and inundation maps at a continental-scale is absent to better support local flood response. To accurately map flood inundation extent, a comprehensive description of the geometry of the channel is indispensable. As such, this dissertation presents an innovative approach for estimating river geometry and conducting inundation mapping at a continental-scale with a high spatial resolution. This approach is based on the concept of Height Above Nearest Drainage (HAND). Advanced hydrologic terrain analysis workflows have been designed to derive channel hydraulic properties, stage-discharge rating curves, and inundation extents using HAND. After the mechanism being presented, the implementation of this approach across the contiguous United States has been demonstrated using the 10-meter National Elevation Dataset. The integrity of the outputs has been validated through the comparison with best available references at multiple test sites. Considering the increasingly availability of high-resolution topographic data derived from lidar technology, the dissertation further presents how advanced geomorphic feature extraction tools are integrated into the proposed approach to overcome the challenges associated with the enrichment of terrain details. At last, this dissertation presents how banklines, an essential piece of river geometry characteristic as the boundary differentiates channel zone from floodplain, is detected with enhanced geomorphic feature extraction tools for improving large-scale hydrologic simulation and inundation mapping accuracy.Civil, Architectural, and Environmental Engineerin

Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.Jokien onnistunut hallinta edellyttää virtavesien prosessien ymmärtämistä. Tämä ei ole mahdollista ilman jokien geomorfologian ja hydrologian kvantifiointia sekä niiden spatiotemporaalisten suhteiden tutkimista, eli jokien hydromorfologiaa. Joen topografian mittaaminen, varsinkin uoman vedenalaisen osalle on pitkään ollut työlästä ja aikaa vievää. Virtauskentän kattava mittaaminen on myös ollut haastavaa, sillä seurauksella, että niitä on tehty harvakseltaan luonnollisessa ympäristössä. Viimeaikainen teknologinen kehitys kaukokartoituksessa on mahdollistanut synoptisen tiedon mittaamisen jokiympäristöissä. Tässä väitöstutkimuksessa on kehitetty virtavesien kaukokartoitusta sekä jokien topografian että virtausmittauksen alalla. Useita eri lähikaukokartoitusmenetelmiä yhdistämällä on tehty korkean resoluution yhtenäinen empiirinen malli joen hydromorfologiasta, eli joen uoman ja tulvatasangon topografiasta ja kolmiulotteisesta virtaamakentästä. Empiriaan ja hydrauliseen teoriaan perustuvat optisen kaukokartoituksen menetelmiä testattiin ja arvioitiin käyttämällä normaaliväri-ilmakuvia, kaikuluotain kalibrointia ja referenssimittauksia kivipohjaisessa subarktisessa joessa. Empiiristä optista syvyysmallia kehitettiin edelleen lisäämällä syvän veden säteilyparametrin arviointialgoritmi, joka mahdollisti mallin käytön myös matalavetisissä jokiuomissa. Parametrin vaikutus malliin arvioitiin korkean resoluution matalailmakuvista hiekkapohjaisessa subarktisessa joessa yhdessä ensimmäisistä syvyysmalleista, joka on tehty käyttäen kauko-ohjattua minihelikopteria (eng.UAV, Unmanned Aerial Vehicle). Lähietäisyyden kaukokartoitusmenetelmiä käytettiin edelleen topografisen mallin täydentämiseen, integroimalla joen uoma ja tulvatasanko yhtenäiseksi korkean resoluution topografiaksi. Mobiilia laserkeilausta käytettiin vedenpinnan yläpuolisen osan topografian mittaamiseen korkealla resoluutiolla vene- kärry- ja reppupohjaisten kartoitusalustojen avulla. Monen ajankohdan mobiilin laserkeilauksen ja UAVfotogrammetrian tarkkuutta arvioitiin maalaserikeilausaineiston avulla. Laserkeilattu ja fotogrammetrinen aineisto yhdistettiin, jolloin saatiin kahden vuoden ajalta saumaton digitaalinen maastomalli. Mallin avulla oli mahdollista arvioida koko joen uoman korkean resoluution muutosanalyysin metodologiaa. Kaukokartoitukseen perustuvaa hydromorfologista mallia täydennettiin uniikilla virtauskentän kolmiulotteisella kartoitusaineistolla. Kauko-ohjattavaan veneeseen asennettu akustinen virtausmittauslaite yhdessä tarkan satelliittipaikannusjärjestelmän kanssa mahdollistivat alueellisesti valikoitujen kolmiulotteisten virtausvektoreiden sijainnin määrittämisen kolmiulotteisessa avaruudessa pistepilvenä. Tämän aineiston kolmiulotteinen interpolaatio matriisiksi mahdollisti edelleen volymetrisen virtausanalyysin. Monen ajankohdan alueellinen kolmiulotteinen virtauskenttä osoitti virtausolosuhteiden evoluution kevättulvassa. Vedenalaisen ja kuivan maan topografia yhdessä jokiuoman virtauskenttien kanssa muodosti kattavan mallin joen hydromorfologiasta.Siirretty Doriast

Evaluating the Differences of Gridding Techniques for Digital Elevation Models Generation and Their Influence on the Modeling of Stony Debris Flows Routing: A Case Study From Rovina di Cancia Basin (North-Eastern Italian Alps)

Debris \ufb02ows are among the most hazardous phenomena in mountain areas. To cope with debris \ufb02ow hazard, it is common to delineate the risk-prone areas through routing models. The most important input to debris \ufb02ow routing models are the topographic data, usually in the form of Digital Elevation Models (DEMs). The quality of DEMs depends on the accuracy, density, and spatial distribution of the sampled points; on the characteristics of the surface; and on the applied gridding methodology. Therefore, the choice of the interpolation method affects the realistic representation of the channel and fan morphology, and thus potentially the debris \ufb02ow routing modeling outcomes. In this paper, we initially investigate the performance of common interpolation methods (i.e., linear triangulation, natural neighbor, nearest neighbor, Inverse Distance to a Power, ANUDEM, Radial Basis Functions, and ordinary kriging) in building DEMs with the complex topography of a debris \ufb02ow channel located in the Venetian Dolomites (North-eastern Italian Alps), by using small footprint full- waveform Light Detection And Ranging (LiDAR) data. The investigation is carried out through a combination of statistical analysis of vertical accuracy, algorithm robustness, and spatial clustering of vertical errors, and multi-criteria shape reliability assessment. After that, we examine the in\ufb02uence of the tested interpolation algorithms on the performance of a Geographic Information System (GIS)-based cell model for simulating stony debris \ufb02ows routing. In detail, we investigate both the correlation between the DEMs heights uncertainty resulting from the gridding procedure and that on the corresponding simulated erosion/deposition depths, both the effect of interpolation algorithms on simulated areas, erosion and deposition volumes, solid-liquid discharges, and channel morphology after the event. The comparison among the tested interpolation methods highlights that the ANUDEM and ordinary kriging algorithms are not suitable for building DEMs with complex topography. Conversely, the linear triangulation, the natural neighbor algorithm, and the thin-plate spline plus tension and completely regularized spline functions ensure the best trade-off among accuracy and shape reliability. Anyway, the evaluation of the effects of gridding techniques on debris \ufb02ow routing modeling reveals that the choice of the interpolation algorithm does not signi\ufb01cantly affect the model outcomes

The debris flow occurred at ru secco creek, venetian dolomites, on 4 august 2015: Analysis of the phenomenon, its characteristics and reproduction by models

On 4 August 2015, a very high intensity storm, 31.5 mm in 20 min (94.5 mm/h), hit the massif of Mount Antelao on the Venetian Dolomites triggering three stony debris \ufb02ows characterized by high magnitude. Two of them occurred in the historical sites of Rovina di Cancia and Rudan Creek and were stopped by the retaining works upstream the inhabited areas, while the third routed along the Ru Secco Creek and progressively reached the resort area and the village of San Vito di Cadore, causing fatalities and damages. The main triggering factor of the Ru Secco debris \ufb02ow was a large rock collapse on the northern cliffs of Mount Antelao occurred the previous autumn. The fallen debris material deposited on the Vallon d\u2019Antrimoia inclined plateau at the base of the collapsed cliffs and, below it, on the Ru Salvela Creek, covering it from the head to the con\ufb02uence with the Ru Secco Creek. The abundant runoff, caused by the high intensity rainfall on 4 August 2015, entrained about 52,500 m3 of the debris material laying on the Vallon d\u2019Antrimoia forming a debris \ufb02ow surge that hit and eroded the debris deposit covering the downstream Ru Salvela Creek, increasing its volume, about 110,000 m3 of mobilized sediments. This debris \ufb02ow routed downstream the con\ufb02uence, \ufb02ooding the parking of a resort area where three people died, and reached the village downstream damaging some buildings. A geomorphological analysis was initially carried out after surveying the whole basin. All liquid and solid-liquid contributions to the phenomenon were recognized together with the areas subjected to erosion and deposition. The elaboration of pre and post-event topographical surveys provided the map of deposition-erosion depths. Using the rainfall estimated by weather radar and corrected by the nearest rain gauge, about 0.8 km far, we estimated runoff by using a rainfall-runoff model designed for the headwater rocky basins of Dolomites. A triggering model provided the debris \ufb02ow hydrographs in the initiation areas, after using the simulated runoff. The initial solid-liquid surge hydrographs were, then, routed downstream by means of a cell model. The comparison between the simulated and estimated deposition-erosion pattern resulted satisfactory. The results of the simulation captured, in fact, the main features of the occurred phenomenon

Flood Prediction and Mitigation in Data-Sparse Environments

In the last three decades many sophisticated tools have been developed that can accurately predict the dynamics of flooding. However, due to the paucity of adequate infrastructure, this technological advancement did not benefit ungauged flood-prone regions in the developing countries in a major way. The overall research theme of this dissertation is to explore the improvement in methodology that is essential for utilising recently developed flood prediction and management tools in the developing world, where ideal model inputs and validation datasets do not exist. This research addresses important issues related to undertaking inundation modelling at different scales, particularly in data-sparse environments. The results indicate that in order to predict dynamics of high magnitude stream flow in data-sparse regions, special attention is required on the choice of the model in relation to the available data and hydraulic characteristics of the event. Adaptations are necessary to create inputs for the models that have been primarily designed for areas with better availability of data. Freely available geospatial information of moderate resolution can often meet the minimum data requirements of hydrological and hydrodynamic models if they are supplemented carefully with limited surveyed/measured information. This thesis also explores the issue of flood mitigation through rainfall-runoff modelling. The purpose of this investigation is to assess the impact of land-use changes at the sub-catchment scale on the overall downstream flood risk. A key component of this study is also quantifying predictive uncertainty in hydrodynamic models based on the Generalised Likelihood Uncertainty Estimation (GLUE) framework. Detailed uncertainty assessment of the model outputs indicates that, in spite of using sparse inputs, the model outputs perform at reasonably low levels of uncertainty both spatially and temporally. These findings have the potential to encourage the flood managers and hydrologists in the developing world to use similar data sets for flood management

GeoFlood: Large-Scale Flood Inundation Mapping Based on High-Resolution Terrain Analysis

Recent floods from intense storms in the southern United States and the unusually active 2017 Atlantic hurricane season have highlighted the need for real‐time flood inundation mapping using high‐resolution topography. High‐resolution topographic data derived from lidar technology reveal unprecedented topographic details and are increasingly available, providing extremely valuable information for improving inundation mapping accuracy. The enrichment of terrain details from these data sets, however, also brings challenges to the application of many classic approaches designed for lower‐resolution data. Advanced methods need to be developed to better use lidar‐derived terrain data for inundation mapping. We present a new workflow, GeoFlood, for flood inundation mapping using high‐resolution terrain inputs that is simple and computationally efficient, thus serving the needs of emergency responders to rapidly identify possibly flooded locations. First, GeoNet, a method for automatic channel network extraction from high‐resolution topographic data, is modified to produce a low‐density, high‐fidelity river network. Then, a Height Above Nearest Drainage (HAND) raster is computed to quantify the elevation difference between each land surface cell and the stream bed cell to which it drains, using the network extracted from high‐resolution terrain data. This HAND raster is then used to compute reach‐average channel hydraulic parameters and synthetic stage‐discharge rating curves. Inundation maps are generated from the HAND raster by obtaining a water depth for a given flood discharge from the synthetic rating curve. We evaluate our approach by applying it in the Onion Creek Watershed in Central Texas, comparing the inundation extent results to Federal Emergency Management Agency 100‐yr floodplains obtained with detailed local hydraulic studies. We show that the inundation extent produced by GeoFlood overlaps with 60%~90% of the Federal Emergency Management Agency floodplain coverage demonstrating that it is able to capture the general inundation patterns and shows significant potential for informing real‐time flood disaster preparedness and response