Exploring the Dunes: The Correlations between Vegetation Cover Pattern and Morphology for Sediment Retention Assessment Using Airborne Multisensor Acquisition

Coastal sand dunes are highly dynamic aeolian landforms where different spatial patterns can be observed due to the complex interactions and relationships between landforms and land cover. Sediment distribution related to vegetation types is explored here on a single ridge dune system by using an airborne hyperspectral and light detection and ranging (LiDAR) remote sensing dataset. A correlation model is applied to describe the continuum of dune cover typologies, determine the class metrics from landscape ecology and the morphology parameters, and extract the relationship intensity among them. As a main result, the mixture of different vegetation types such as herbaceous, shrubs, and trees classes shows to be a key element for the sediment distribution pattern and a proxy for dune sediment retention capacity, and the anthropic fingerprints can play an even major role influencing both ecological and morphological features. The novelty of the approach is mostly based on the synergistic use of LiDAR with hyperspectral that allowed (i) the benefit from already existing processing methods to simplify the way to obtain thematic maps and coastal metrics and (ii) an improved detection of natural and anthropic landscape.

[1]  Maria Laura Carranza,et al.  Combining land cover mapping of coastal dunes with vegetation analysis , 2005 .

[2]  D. Ciccarelli,et al.  Development of a coastal dune vulnerability index for Mediterranean ecosystems: A useful tool for coastal managers? , 2017 .

[3]  Andrea Taramelli,et al.  FHYL: Field spectral libraries, airborne hyperspectral images and topographic and bathymetric LiDAR data for complex coastal mapping , 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

[4]  A. Baas.  Chaos, fractals and self-organization in coastal geomorphology: simulating dune landscapes in vegetated environments , 2002 .

[5]  G. Sterk,et al.  Modelling wind‐blown sediment transport around single vegetation elements , 2011 .

[6]  J. Brock,et al.  The Emerging Role of Lidar Remote Sensing in Coastal Research and Resource Management , 2009 .

[7]  G. Metternicht,et al.  Estimating Erosion Surface Features by Linear Mixture Modeling , 1998 .

[8]  M. Martínez,et al.  A Perspective on Coastal Dunes , 2008 .

[9]  Marco Dubbini,et al.  Using Unmanned Aerial Vehicles (UAV) for High-Resolution Reconstruction of Topography: The Structure from Motion Approach on Coastal Environments , 2013, Remote. Sens..

[10]  A. Baas,et al.  The influence of different environmental and climatic conditions on vegetated aeolian dune landscape development and response , 2008 .

[11]  A. Baas,et al.  Ecogeomorphic state variables and phase‐space construction for quantifying the evolution of vegetated aeolian landscapes , 2010 .

[12]  Orencio Durán,et al.  Vegetation controls on the maximum size of coastal dunes , 2013, Proceedings of the National Academy of Sciences.

[13]  A. Taramelli,et al.  Integrated coastal zone management at Marina di Carrara Harbor: sediment management and policy making , 2011 .

[14]  R. Holman,et al.  Evaluation of Airborne Topographic Lidar* for Quantifying Beach Changes , 2003 .

[15]  A. Cracknell.  Remote sensing techniques in estuaries and coastal zones an update , 1999 .

[16]  Ibon Galparsoro,et al.  Coastal and estuarine habitat mapping, using LIDAR height and intensity and multi-spectral imagery , 2008 .

[17]  V. Pillar,et al.  Coastal Vegetation Zonation and Dune Morphology in Some Mediterranean Ecosystems , 2007 .

[18]  Quan Sun,et al.  ractional vegetation cover estimation in arid and semi-arid environments using J-1 satellite hyperspectral data , 2012 .

[19]  M. Cormier,et al.  Geomorphic evidence for tilting at a continental transform: The Karamursel Basin along the North Anatolian Fault, Turkey , 2010 .

[20]  J. Keijsers,et al.  Vegetation and sedimentation on coastal foredunes , 2015 .

[21]  E. Valentini,et al.  Detection of Natural and Anthropic Features on Small Islands , 2017, Journal of Coastal Research.

[22]  Andrea Taramelli,et al.  Nearshore Sandbar Classification of Sabaudia (Italy) with LiDAR Data: The FHyL Approach , 2020, Remote. Sens..

[23]  A. Baas,et al.  Modelling vegetated dune landscapes , 2007 .

[24]  R. Leinfelder,et al.  A formal Anthropocene is compatible with but distinct from its diachronous anthropogenic counterparts: a response to W.F. Ruddiman’s ‘three flaws in defining a formal Anthropocene’ , 2019, Progress in Physical Geography: Earth and Environment.

[25]  Christopher Small,et al.  Spectroscopy of sediments in the Ganges–Brahmaputra delta: Spectral effects of moisture, grain size and lithology , 2009 .

[26]  Andrea Taramelli,et al.  Multisensory data fusion methods for the estimation of beach sediment features: Mineralogical, grain size and moisture , 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

[27]  Andrea Taramelli,et al.  An effective procedure for EUNIS and Natura 2000 habitat type mapping in estuarine ecosystems integrating ecological knowledge and remote sensing analysis , 2015 .

[28]  Andreas C.W. Baas,et al.  Complex systems in aeolian geomorphology , 2007 .

[29]  G. D. Falco,et al.  Climate changes and human impact on the Mistras coastal barrier system (W Sardinia, Italy) , 2018 .

[30]  M. Malavasi,et al.  How does dune morphology shape coastal EC habitats occurrence? A remote sensing approach using airborne LiDAR on the Mediterranean coast , 2016 .

[31]  J. Pelletier,et al.  Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs , 2015 .

[32]  Peter J. Mumby,et al.  Mapping marine environments with IKONOS imagery: enhanced spatial resolution can deliver greater thematic accuracy , 2002 .

[33]  N. Coops,et al.  Assessing the utility of airborne hyperspectral and LiDAR data for species distribution mapping in the coastal Pacific Northwest, Canada , 2010 .

[34]  M. Eppes,et al.  Landscape dynamics fostering the development and persistence of long-lived creosotebush (Larrea tridentata) clones in the Mojave Desert , 2007 .

[35]  A. Acosta,et al.  Are some communities of the coastal dune zonation more susceptible to alien plant invasion , 2010 .

[36]  Li Zhang,et al.  Mapping functional vegetation abundance in a coastal dune environment using a combination of LSMA and MLC: a case study at Kenfig NNR, Wales , 2012 .

[37]  E. Ibrahim,et al.  Suitability of spaceborne multispectral data for inter-tidal sediment characterization: A case study , 2011 .

[38]  Christopher Small,et al.  Global cross-calibration of Landsat spectral mixture models , 2016 .

[39]  C. Hugenholtz,et al.  Reactivation of supply-limited dune fields from blowouts: A conceptual framework for state characterization , 2013 .

[40]  Andrea Taramelli,et al.  A Hybrid Power Law Approach for Spatial and Temporal Pattern Analysis of Salt Marsh Evolution , 2017, Journal of Coastal Research.

[41]  Sarah L. Dance,et al.  Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007. , 2010 .

[42]  C. Sotin,et al.  Mapping microphytobenthos biomass by non-linear inversion of visible-infrared hyperspectral images , 2005 .

[43]  C. Hugenholtz,et al.  Predicting vegetation‐stabilized dune field morphology , 2012 .

[44]  L. Eklundh,et al.  A physically based vegetation index for improved monitoring of plant phenology , 2014 .

[45]  M. Maslin,et al.  Defining the Anthropocene , 2015, Nature.

[46]  P. Hesp.  A review of biological and geomorphological processes involved in the initiation and development of incipient foredunes , 1989 .

[47]  N. Lancaster,et al.  Influence of vegetation cover on sand transport by wind: field studies at Owens Lake, California , 1998 .

[48]  G. Kocurek,et al.  Aeolian dune field self-organization – implications for the formation of simple versus complex dune-field patterns , 2005 .

[49]  V. Pascucci,et al.  New Estimation of the Post Little Ice Age Relative Sea Level Rise , 2019, Geosciences.

[50]  Robert O. Green,et al.  Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS , 1997 .

[51]  The palaeontological record of the Anthropocene , 2018, Geology Today.

[52]  P. Hesp.  Ecological processes and plant adaptations on coastal dunes , 1991 .

[53]  S. Silvestri,et al.  Coupled topographic and vegetation patterns in coastal dunes: Remote sensing observations and ecomorphodynamic implications , 2017 .

[54]  C. Finkl,et al.  Coastal Classification: Systematic Approaches to Consider in the Development of a Comprehensive Scheme , 2004 .

[55]  Christopher Small,et al.  The Landsat ETM+ spectral mixing space , 2004 .

[56]  Corinne Corbau,et al.  Regional variability of coastal dunes observed along the Emilia-Romagna littoral, Italy , 2015 .

[57]  Helena Mitasova,et al.  The effects of interdune vegetation changes on eolian dune field evolution: a numerical‐modeling case study at Jockey's Ridge, North Carolina, USA , 2009 .

[58]  Andrea Taramelli,et al.  Spectral characterization of coastal sediments using Field Spectral Libraries, Airborne Hyperspectral Images and Topographic LiDAR Data (FHyL) , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[59]  David Gilvear,et al.  Mapping intertidal estuarine sediment grain size distributions through airborne remote sensing , 2003 .

[60]  Andrea Taramelli,et al.  Indications of Dynamic Effects on Scaling Relationships Between Channel Sinuosity and Vegetation Patch Size Across a Salt Marsh Platform , 2018, Journal of Geophysical Research: Earth Surface.