Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning

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Laser scanning applications in fluvial studies

Peer reviewe

Modern empirical and modelling study approaches in fluvial geomorphology to elucidate sub-bend-scale meander dynamics

Major developments in theory and modelling techniques have taken place within the past couple of decades in the field of the fluvial geomorphology. In this review, we examine the state-of-the-art empirical and modelling approaches and discuss their potential benefits and shortcomings in deepening understanding of the sub-bend-scale fluvial geomorphology of meander bends. Meandering rivers represent very complex 3D flow and sedimentary processes. We focus on high-resolution techniques which have improved the spatial and temporal resolution of the data and thereby enabled investigation of processes, which have been thus far beyond the capacity of the measurement techniques. This review covers the measurement techniques applied in the field and in laboratory circumstances as well as the close-range remote sensing techniques and computational approaches. We discuss the key research questions in fluvial geomorphology of meander bends and demonstrate how the contemporary approaches have been and could be applied to solve these questions.</jats:p

Predicting vegetation characteristics in a changing environment by means of laser scanning

Accurate and up-to-date information concerning vegetation characteristics is needed for decision-making from individual-tree-level management activities to the strategic planning of forest resources. Outdated information may lead to unbeneficial or even wrong decisions, at least when it comes to the timing of management activities. Airborne laser scanning (ALS) has so far been successfully used for applications involving detailed vegetation mapping because of its capability to simultaneously produce accurate information on vegetation and ground surfaces. The aim of this dissertation was to develop methods for characterizing vegetation and its changes in varying environments. A method called multisource single-tree inventory (MS-STI) was developed in substudy I to update urban tree attributes. In MS-STI stem map was produced with terrestrial laser scanning (TLS) and by combining the stem map with predictors derived from ALS data it was possible to obtain improved estimates of diameter-at-breast height but also to produce new attributes such as height and crown size. Boat-based mobile laser scanning (MLS) data were employed in substudy II to map riverbank vegetation and identify changes. The overall classification accuracy of 73% was obtained, which is similar to accuracies found in other studies. With multi-temporal MLS data sets changes in vegetation were mapped year to year. In substudy III, open access ALS data were combined with multisource national forest inventory (NFI) data to investigate the drivers associated to wind damage. The special interest was in ALS-based predictors to map areas with wind disturbance and apply logistic regression to produce a continuous probability surface of wind predisposition to identify areas most likely to experience wind damage. The results demonstrated that a combination of ALS and multisource NFI in the modelling approach increased the prediction accuracy from 76% to 81%. The dissertation showed the capability of ALS and MLS for characterizing vegetation and mapping changes in varying environments. The developed applications could increase and expand the utilization of multi-temporal 3D data sets as well as increase data value. The results of this dissertation can be utilized in producing more accurate, diverse, and up-to-date information for decision-making related to natural resources.Luonnonvaroja koskevaa päätöksentekoa varten tarvitaan luotettavaa ja ajantasaista tietoa, oli kyse sitten yksittäiseen puuhun liittyvistä toimenpiteistä tai laajojen alueiden strategisesta suunnittelusta. Vanhentunut tieto voi johtaa epäedullisiin tai jopa vääriin ratkaisuihin, erityisesti hoitotoimenpiteiden ajoituksen osalta. Ilmalaserkeilaus on menetelmä, jossa yksityiskohtaista kolmiulotteista tietoa tuotetaan esimerkiksi lentokoneeseen tai helikopteriin asennetun laserkeilaimen avulla. Laserkeilan mittaa etäisyyttä kohteeseen laserpulssin kulkuajan perusteella. Ilmalaserkeilaus on jo operatiivisessa käytössä metsävaratiedonkeruussa Pohjoismaissa sillä sen avulla voidaan tuottaa tarkkaa tietoa samanaikaisesti sekä maanpinnan korkeudesta ja maaston muodoista että kasvillisuuden pituudesta ja tiheydestä. Maastolaserkeilauksella tarkoitetaan pienemmän alueen inventointiin soveltuvaa menetelmää, jossa laserkeilain on kolmijalan päällä tai liikkuvalla alustalla. Väitöskirjan tavoitteena oli kehittää menetelmiä kasvillisuuden ominaisuuksien ennustamiseen laserkeilauksen avulla erilaisissa ympäristöissä. Väitöskirja koostuu kolmesta osajulkaisusta, joista ensimmäisessä kehitettiin monilähteinen yksittäisten puiden inventointimenetelmä kaupunkipuiden tunnusten päivittämiseen. Kyseisessä menetelmässä maastolaserkeilauksen avulla tuotettiin puukartta, joka yhdistettiin ilmalaserkeilauksella saatuihin tietoihin. Ilmalaserkeilauksesta saatujen yksittäisten puiden latvojen pituus- ja tiheystunnusten avulla voitiin parantaa kaupunkipuiden läpimittatietoja sekä tuottaa uusia tunnuksia kuten pituus ja latvuksen koko lisättäväksi kaupunkipuurekisterin tietokantaan. Toisessa osajulkaisussa käytettiin veneeseen asennettua laserkeilainta jokiympäristön kasvillisuuden kartoittamiseen sekä kasvillisuudessa tapahtuneiden muutosten havainnoimiseen. Kasvillisuus ja paljas maa oli mahdollista erotella 73 prosentin tarkkuudella, vastaaviin tarkkuuksiin on päästy myös aiemmissa tutkimuksissa, joissa tosin hyödynnettiin tarkempaa maastoaineistoa. Useampiaikaisilla aineistoilla oli mahdollista kartoittaa vuosien välillä tapahtuneita kasvillisuuden muutoksia. Kolmannessa osajulkaisussa hyödynnettiin avoimesti saatavilla olevaa ilmalaserkeilaus- ja monilähteistä valtion metsien inventoinnin (VMI) aineistoa tuulituhojen kartoittamiseen sekä ennustamiseen. Osajulkaisussa ennustettiin tuulituhoriskin suuruutta ilmalaserkeilauksesta saatavien maanpinnan korkeuden ja kasvillisuuden pituuden sekä monilähde-VMI-aineistosta saadun puulajitiedon avulla. Tarkoituksena oli selvittää tuhoriskille erityisen alttiit alueet mahdollisia metsänhoitotoimenpiteitä varten. Puulajitieto lisäsi tuulituhojen kartoitustarkkuutta 76 prosentista 81 prosenttiin. Väitöskirja esitteli erilaisilta alustoilta tehtävän laserkeilauksen kykyä kasvillisuuden luonnehtimiseen sekä muutosten huomioimiseen erilaisissa ympäristöissä monipuolista päätöksentekoa varten. Kaupunkiympäristöissä yksittäisten puiden tunnukset ovat kohdennettujen toimenpiteiden kannalta tärkeitä, kun taas tietoa jokiympäristöjen kasvillisuudesta ja sen muutoksista voidaan hyödyntää päivitettäessä tulvariskimalleja. Tieto tuulituhoille riskialttiista alueista voi auttaa metsänomistajia ja ammattilaisia metsänhoitotoimenpiteiden suunnittelussa. Väitöskirjassa kehitettyjen menetelmien avulla voidaan laajentaa useampiaikaisten laserkeilausaineistojen hyödyntämistä sekä saada lisäarvoa aineistoista. Väitöskirjan tuloksia voidaan hyödyntää tarkemman, monipuolisemman ja ajantasaisemman tiedon tuottamisessa erilaisessa luonnonvaroja koskevassa suunnittelussa ja päätöksenteossa

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

Evaluation of Long-Range Mobile Mapping System (MMS) and Close-Range Photogrammetry for Deformation Monitoring. A Case Study of Cortes de Pallás in Valencia (Spain)

none8openDi Stefano, Francesco; Cabrelles, Miriam; García-Asenjo, Luis; Lerma, José Luis; Malinverni, Eva Savina; Baselga, Sergio; Garrigues, Pascual; Pierdicca, RobertoDi Stefano, Francesco; Cabrelles, Miriam; García-Asenjo, Luis; Lerma, José Luis; Malinverni, Eva Savina; Baselga, Sergio; Garrigues, Pascual; Pierdicca, Robert

An evaluation DEM accuracy acquired using a small unmanned aerial vehicle across a riverine environment

Fluvial systems offer a challenging and varied environment for topographic survey, displaying a rapidly varying morphology, diversevegetation assemblage and varying degree of submergence. Traditionally theodolite or GPS based systems have been used to capture cross-section and break of slope based data which has subsequently been interpolated to generate a topographic surface. Advances in survey technology has resulted in an improved ability to capture larger volumes of data with infrared terrestrial and aerial LiDAR systems capturing high-density (<0.02m) data across terrestrial surfaces but instruments are expensive and cumbersome and fail to survey through water. The rise of Structure from Motion (SfM) photogrammetry, coupled with unmanned aerial vehicles (UAVs), has potential to rapidly record information needed to derive elevation data at reach scale with sub decimetre density. The approach has the additional advantage over LiDAR of seeing through clear water to capture bed detail, whilst also generating orthorectified photographic mosaics of the survey reach. However, the accuracy of the data has received comparatively little attention. Here we present a survey protocol for UAV deployment and provide a reach scale comparison between a Terrestrial LiDAR Survey (TLS) and SfM UAV survey on the River Sprint near Kendal in England.. Comparative analysis of elevation data between TLS and SfM suggest comparable accuracy and precision across terrestrial surfaces with error lowest over solid surfaces, increasing with vegetation complexity. Submerged SfM data captured bed levels generally to within ±0.2 with only a weak relationship recorded between error and flow depth

On the use of rapid-scan, low point density terrestrial laser scanning (TLS) for structural assessment of complex forest environments

Forests fulfill an important role in natural ecosystems, e.g., they provide food, fiber, habitat, and biodiversity, all of which contribute to stable ecosystems. Assessing and modeling the structure and characteristics in forests can lead to a better understanding and management of these resources. Traditional methods for collecting forest traits, known as “forest inventory”, is achieved using rough proxies, such as stem diameter, tree height, and foliar coverage; such parameters are limited in their ability to capture fine-scale structural variation in forest environments. It is in this context that terrestrial laser scanning (TLS) has come to the fore as a tool for addressing the limitations of traditional forest structure evaluation methods. However, there is a need for improving TLS data processing methods. In this work, we developed algorithms to assess the structure of complex forest environments – defined by their stem density, intricate root and stem structures, uneven-aged nature, and variable understory - using data collected by a low-cost, portable TLS system, the Compact Biomass Lidar (CBL). The objectives of this work are listed as follow: 1. Assess the utility of terrestrial lidar scanning (TLS) to accurately map elevation changes (sediment accretion rates) in mangrove forest; 2. Evaluate forest structural attributes, e.g., stems and roots, in complex forest environments toward biophysical characterization of such forests; and 3. Assess canopy-level structural traits (leaf area index; leaf area density) in complex forest environments to estimate biomass in rapidly changing environments. The low-cost system used in this research provides lower-resolution data, in terms of scan angular resolution and resulting point density, when compared to higher-cost commercial systems. As a result, the algorithms developed for evaluating the data collected by such systems should be robust to issues caused by low-resolution 3D point cloud data. The data used in various parts of this work were collected from three mangrove forests on the western Pacific island of Pohnpei in the Federated States of Micronesia, as well as tropical forests in Hawai’i, USA. Mangrove forests underscore the economy of this region, where more than half of the annual household income is derived from these forests. However, these mangrove forests are endangered by sea level rise, which necessitates an evaluation of the resilience of mangrove forests to climate change in order to better protect and manage these ecosystems. This includes the preservation of positive sediment accretion rates, and stimulating the process of root growth, sedimentation, and peat development, all of which are influenced by the forest floor elevation, relative to sea level. Currently, accretion rates are measured using surface elevation tables (SETs), which are posts permanently placed in mangrove sediments. The forest floor is measured annually with respect to the height of the SETs to evaluate changes in elevation (Cahoon et al. 2002). In this work, we evaluated the ability of the CBL system for measuring such elevation changes, to address objective #1. Digital Elevation Models (DEMs) were produced for plots, based on the point cloud resulted from co-registering eight scans, spaced 45 degree, per plot. DEMs are refined and produced using Cloth Simulation Filtering (CSF) and kriging interpolation. CSF was used because it minimizes the user input parameters, and kriging was chosen for this study due its consideration of the overall spatial arrangement of the points using semivariogram analysis, which results in a more robust model. The average consistency of the TLS-derived elevation change was 72%, with and RMSE value of 1.36 mm. However, what truly makes the TLS method more tenable, is the lower standard error (SE) values when compared to manual methods (10-70x lower). In order to achieve our second objective, we assessed structural characteristics of the above-mentioned mangrove forest and also for tropical forests in Hawaii, collected with the same CBL scanner. The same eight scans per plot (20 plots) were co-registered using pairwise registration and the Iterative Closest Point (ICP). We then removed the higher canopy using a normal change rate assessment algorithm. We used a combination of geometric classification techniques, based on the angular orientation of the planes fitted to points (facets), and machine learning 3D segmentation algorithms to detect tree stems and above-ground roots. Mangrove forests are complex forest environments, containing above-ground root mass, which can create confusion for both ground detection and structural assessment algorithms. As a result, we needed to train a supporting classifier on the roots to detect which root lidar returns were classified as stems. The accuracy and precision values for this classifier were assessed via manual investigation of the classification results in all 20 plots. The accuracy and precision for stem classification were found to be 82% and 77%, respectively. The same values for root detection were 76% and 68%, respectively. We simulated the stems using alpha shapes in order to assess their volume in the final step. The consistency of the volume evaluation was found to be 85%. This was obtained by comparing the mean stem volume (m3/ha) from field data and the TLS data in each plot. The reported accuracy is the average value for all 20 plots. Additionally, we compared the diameter-at-breast-height (DBH), recorded in the field, with the TLS-derived DBH to obtain a direct measure of the precision of our stem models. DBH evaluation resulted in an accuracy of 74% and RMSE equaled 7.52 cm. This approach can be used for automatic stem detection and structural assessment in a complex forest environment, and could contribute to biomass assessment in these rapidly changing environments. These stem and root structural assessment efforts were complemented by efforts to estimate canopy-level structural attributes of the tropical Hawai’i forest environment; we specifically estimated the leaf area index (LAI), by implementing a density-based approach. 242 scans were collected using the portable low-cost TLS (CBL), in a Hawaii Volcano National Park (HAVO) flux tower site. LAI was measured for all the plots in the site, using an AccuPAR LP-80 Instrument. The first step in this work involved detection of the higher canopy, using normal change rate assessment. After segmenting the higher canopy from the lidar point clouds, we needed to measure Leaf Area Density (LAD), using a voxel-based approach. We divided the canopy point cloud into five layers in the Z direction, after which each of these five layers were divided into voxels in the X direction. The sizes of these voxels were constrained based on interquartile analysis and the number of points in each voxel. We hypothesized that the power returned to the lidar system from woody materials, like branches, exceeds that from leaves, due to the liquid water absorption of the leaves and higher reflectivity for woody material at the 905 nm lidar wavelength. We evaluated leafy and woody materials using images from projected point clouds and determined the density of these regions to support our hypothesis. The density of points in a 3D grid size of 0.1 m, which was determined by investigating the size of the branches in the lower portion of the higher canopy, was calculated in each of the voxels. Note that “density” in this work is defined as the total number of points per grid cell, divided by the volume of that cell. Subsequently, we fitted a kernel density estimator to these values. The threshold was set based on half of the area under the curve in each of the distributions. The grid cells with a density below the threshold were labeled as leaves, while those cells with a density above the threshold were set as non-leaves. We then modeled the LAI using the point densities derived from TLS point clouds, achieving a R2 value of 0.88. We also estimated the LAI directly from lidar data by using the point densities and calculating leaf area density (LAD), which is defined as the total one-sided leaf area per unit volume. LAI can be obtained as the sum of the LAD values in all the voxels. The accuracy of LAI estimation was found to be 90%. Since the LAI values cannot be considered spatially independent throughout all the plots in this site, we performed a semivariogram analysis on the field-measured LAI data. This analysis showed that the LAI values can be assumed to be independent in plots that are at least 30 m apart. As a result, we divided the data into six subsets, where each of the plots were 30 meter spaced for each subset. LAI model R2 values for these subsets ranged between 0.84 - 0.96. The results bode well for using this method for automatic estimation of LAI values in complex forest environments, using a low-cost, low point density, rapid-scan TLS

Sediment movement in cold-region fluvial environments: Monitoring flow-sediment interaction from rivers to estuaries

Comprehensive studies reflecting sediment flux in seasonal cold-region fluvial environments via local sediment processes are rare in the literature. To understand sediment flux, flow-sediment interaction needs to be studied in multiple parts of the river network. In addition, seasonal variation, characterized by snow and ice cover, needs to be considered in cold regions. In this study, I aim to provide new insights into sediment movement in coldregion river networks by studying flow-sediment interaction in river and estuary environments. The study is conducted by combining conventional field measurements, flow measurements, close-range remote sensing and hydrodynamic modelling to gain detailed information about sediment processes under seasonally varying conditions. The comparison of bathymetric mapping methods and monitoring of seasonal and annual morphological changes in shallow river channels is based on close-range remote sensing approaches. Flow conditions are either measured with ADCP or modelled with hydrodynamic modelling to estimate flowsediment interaction in river and estuary environments. Water sampling and sediment trapping are used to measure suspended sediment concentration and sedimentation rates, respectively. The combination of multiple approaches is expected to provide more detailed information than a single method. This study is conducted in the meandering, sand-bedded, subarctic Pulmankijoki River and hemiboreal non-tidal brackish water estuary of the Baltic Sea. The study’s results suggest that sediment movement in cold-region fluvial environments is episodic and controlled by low- and high-energy conditions. Sediment movement is strongest during high-energy events, such as discharge peaks, strong wind conditions and rapid sea level changes, and during low-energy conditions, sediment movement is calm and mostly depositional. Sediment movement is characterized by a combination of local and regional conditions. Although processes are primarily driven by a variation in discharge and sea level, local conditions, such as channel shape, estuary ice cover and salinity stratification also control sediment movement. This study shows the benefits of a multimethod approach in sediment movement studies, especially in flow-sediment interaction. Changes in geomorphic units or estuary sedimentation can be explained with measured or modelled flow conditions. In addition, the combination of multiple remote sensing applications, including LiDAR, photogrammetric mapping and sonar, are needed for highly detailed river environment mapping, enabling detailed change detection and further sediment load estimations. Sediment movement in cold-region river systems will most likely change due to expected temperature increases and discharge regime shifts caused by climate change. As spring-thaw-induced high-energy conditions in duration and magnitude will be substituted by shorter autumn and winter discharge peaks, sediment movement in river and estuary environments is expected to decrease during the spring thaw. This process may reflect the development and maintenance of geomorphic units in river channels and sediment-rich plume development in estuaries. In addition, coastal sedimentation will most likely increase due to sea ice cover loss, decreasing snow cover and increasing rainfall. The findings of this thesis can be applied to cold-region fluvial environments, in which strong spring-thaw-induced discharge peaks characterize discharge regime. Further, the thesis improves the understanding of sediment movement and monitoring in cold-region fluvial environments and provides background information for habitat modelling, river restoration, sediment load estimation and nutrient load modelling.Sedimentin kulkeutuminen kylmän alueen virtavesissä – virtaus-sedimenttidynamiikan monitorointi Tämä väitöskirja käsittelee sedimenttivuota kylmän ilmaston virtavesissä. Sedimenttivuohon vaikuttavat uomaverkoston paikalliset tekijät, kuten jokiuoman morfologia sekä rannikoiden jääpeite. Paikallisten tekijöiden vaikutusta sedimenttivuohon on tutkittu kuitenkin verrattain vähän vuodenaikojen mukaan vaihtelevissa virtavesissä. Tutkimalla virtausdynamiikan ja sedimentin vuorovaikutusta uomaverkoston eri osissa, saadaan tietoa sedimenttivuohon vaikuttavista tekijöistä. Tämän väitöskirjan tavoitteena on selvittää sedimentin kulkeutumisen vuodenaikaisvaihtelua ja siihen vaikuttavia tekijöitä. Tutkimuksen pääpaino on virtausdynamiikan ja sedimentin välisessä vuorovaikutuksessa. Tutkimus toteutetaan yhdistelemällä perinteisiä kenttämittauksia, lähikaukokartoitusta sekä virtausmittauksia ja – mallinnuksia. Tutkimuksessa hyödynnetään monipuolisesti erilaisia mittaus- ja mallinnusmenetelmiä. Oletuksena on, että tutkimusmenetelmien monipuolinen yhdistäminen tuottaa tarkempaa tietoa suhteessa yksittäisiin menetelmiin. Ensimmäisessä osatutkimuksessa vertaillaan erilaisten syvyysmallinnustekniikoiden soveltuvuutta matalan kirkasvetisen joen kartoittamiseen. Toinen osatutkimus keskittyy jokiuoman muutostulkintaan ja muutoksen mittaamiseen lähikaukokartoitustekniikoilla. Jokiuoman muutosta tarkastellaan suhteessa mitattuihin virtausnopeuksiin. Kolmas osatutkimus keskittyy sedimenttipitoisen jokipluumin esiintymiseen erilaisissa rannikko-olosuhteissa. Viimeisessä osatutkimuksessa vertaillaan kahden syyskevätkauden (kylmä ja leuto) välisiä sedimentaatioeroja rannikolla hyödyntäen sedimenttikeräimiä ja virtausmallinnusta. Väitöstutkimus toteutettiin subarktisen ja boreaalisen ilmaston virtavesiympäristöissä: Lapissa sijaitsevalla Pulmankijoella ja Saaristomerellä sijaitsevalla Halikonlahdella. Tulokset osoittavat sedimentin kulkeutumisen olevan jaksottaista. Kulkeutuminen on suurimmillaan voimakkaiden virtausolosuhteiden aikana, joita aiheuttavat esimerkiksi korkeat jokivirtaamat sekä voimakkaat tuuliolosuhteet ja nopeat vedenpinnan korkeusvaihtelut rannikolla. Heikkojen virtausolosuhteiden aikana sedimentin kulkeutuminen on maltillista ja sedimentti pääosin kasaantuu. Kulkeutumiseen vaikuttavat sekä paikalliset että alueelliset tekijät. Alueelliset tekijät, kuten jokivirtaaman vaihtelu, merenpinnan korkeusvaihtelut ja tuuliolosuhteet ohjaavat sedimentin kulkeutumista voimakkaimmin, mutta myös paikalliset tekijät, kuten uoman muodot, rannikon jääpeite sekä meriveden kerrostuneisuus vaikuttavat kulkeutumiseen. Yhdistelemällä useita tutkimusmenetelmiä pystytään selvittää virtauksen ja sedimentin kulkeutumiseen vaikuttavia syy-seuraussuhteita. Esimerkiksi mitattujen ja mallinnettujen virtausolosuhteiden avulla on mahdollista selittää jokiuoman geomorfologisten yksiköiden muutoksia ja rannikon sedimentaatiota. Myös jokiuoman korkeusmallien luomiseen tarvitaan usean lähikaukokartoitustekniikan yhdistämistä. Korkeusmallien välisten erojen avulla voidaan arvioida sedimenttikulkeumaa jokiuomassa. Väitöskirjatutkimuksen perusteella ilmastonmuutoksesta aiheutuva ilmakehän lämpeneminen ja virtaamaolosuhteiden muutos vaikuttavat todennäköisesti sedimentin kulkeutumiseen kylmän alueen virtavesissä. Kevättulvien keston ja voimakkuuksien heikkenemisen sekä syys-talvivirtaamien nousun seurauksena sedimentin kulkeutuminen heikkenee kevättulvien aikana ja lisääntyy muina aikoina. Heikentyvien kevättulvien aikana myös virtausnopeudet todennäköisesti alanevat. Virtausnopeuksien heikkeneminen vaikuttanee myös jokiuoma muotoon sekä sedimenttipitoisen jokipluumin käyttäytymiseen rannikoilla. Tuloksien mukaan rannikkoalueiden sedimentaatio oletettavasti kasvaa ilmastonmuutoksesta aiheutuvan jäätalvien lyhenemisen, vesisateiden yleistymisen ja lumipeitteen vähenemisen seurauksena. Väitöskirjan tuloksia voidaan yleistää kylmien alueiden virtavesiympäristöihin, joille on tunnusomaista vuosittainen kevättulva. Tulokset tarjoavat myös taustatietoa vesielinympäristöjen mallintamista varten, jokien kunnostustoimenpiteisiin, sedimenttikulkeuman arviointiin ja ravinnekuormituksien mallintamiseen