Seven good reasons for integrating terrestrial and marine spatial datasets in changing environments

A comprehensive understanding of environmental changes taking place in coastal regions relies on accurate integration of both terrestrial and submerged geo-environmental datasets. However, this practice is hardly implemented because of the high (or even prohibitive) survey costs required for submerged areas and the frequent low accessibility of shallow areas. In addition, geoscientists are used to working on land or at sea independently, making the integration even more challenging. Undoubtedly new methods and techniques of offshore investigation adopted over the last 50 years and the latest advances in computer vision have played a crucial role in allowing a seamless combination of terrestrial and marine data. Although efforts towards an innovative integration of geo-environmental data from above to underwater are still in their infancy, we have identified seven topics for which this integration could be of tremendous benefit for environmental research: (1) geomorphological mapping; (2) Late-Quaternary changes of coastal landscapes; (3) geoarchaeology; (4) geoheritage and geodiversity; (5) geohazards; (6) marine and landscape ecology; and (7) coastal planning and management. Our review indicates that the realization of seamless DTMs appears to be the basic condition to operate a comprehensive integration of marine and terrestrial data sets, so far exhaustively achieved in very few case studies. Technology and interdisciplinarity will be therefore critical for the development of a holistic approach to understand our changing environments and design appropriate management measures accordingly

Laser scanning applications in fluvial studies

Peer reviewe

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

Object-based mapping of temperate marine habitats from multi-resolution remote sensing data

PhD ThesisHabitat maps are needed to inform marine spatial planning but current methods of field survey and data interpretation are time-consuming and subjective. Object-based image analysis (OBIA) and remote sensing could deliver objective, cost-effective solutions informed by ecological knowledge. OBIA enables development of automated workflows to segment imagery, creating ecologically meaningful objects which are then classified based on spectral or geometric properties, relationships to other objects and contextual data. Successfully applied to terrestrial and tropical marine habitats for over a decade, turbidity and lack of suitable remotely sensed data had limited OBIA’s use in temperate seas to date. This thesis evaluates the potential of OBIA and remote sensing to inform designation, management and monitoring of temperate Marine Protected Areas (MPAs) through four studies conducted in English North Sea MPAs. An initial study developed OBIA workflows to produce circalittoral habitat maps from acoustic data using sequential threshold-based and nearest neighbour classifications. These methods produced accurate substratum maps over large areas but could not reliably predict distribution of species communities from purely physical data under largely homogeneous environmental conditions. OBIA methods were then tested in an intertidal MPA with fine-scale habitat heterogeneity using high resolution imagery collected by unmanned aerial vehicle. Topographic models were created from the imagery using photogrammetry. Validation of these models through comparison with ground truth measurements showed high vertical accuracy and the ability to detect decimetre-scale features. The topographic and spectral layers were interpreted simultaneously using OBIA, producing habitat maps at two thematic scales. Classifier comparison showed that Random Forests Abstract ii outperformed the nearest neighbour approach, while a knowledge-based rule set produced accurate results but requires further research to improve reproducibility. The final study applied OBIA methods to aerial and LiDAR time-series, demonstrating that despite considerable variability in the data, pre- and post-classification change detection methods had sufficient accuracy to monitor deviation from a background level of natural environmental fluctuation. This thesis demonstrates the potential of OBIA and remote sensing for large-scale rapid assessment, detailed surveillance and change detection, providing insight to inform choice of classifier, sampling protocol and thematic scale which should aid wider adoption of these methods in temperate MPAs.Natural Environment Research Council and Natural Englan

Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review

International audienceThe study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data.In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT

Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry

Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process oriented investigations of flow hydraulics, sediment dynamics and in-stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through-water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. Whilst the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM-photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary-winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02m) for two different river systems over channel lengths of 50- 100m. Errors in submerged areas range from 0.016m to 0.089m, which can be reduced to between 0.008m and 0.053m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM-photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10m to a few hundred metres)