Monitoring restored riparian vegetation: how can recent developments in remote sensing sciences help?

Riparian vegetation restoration projects require appropriate tools to monitor actions efficiency. On a large scale remote sensing approaches can provide continuous and detailed data to describe riparian vegetation. In this paper, we illustrated recent developments and perspectives for riparian vegetation monitoring purposes through three examples of image sources: Light Detection And Ranging (LiDAR), radar and Unmanned Aerial Vehicule (UAV) images. We notably focused on the potential of such images to provide 3D information for narrow strips of riparian vegetation with high temporal resolution to allow fine monitoring following restoration program. LiDAR data allows canopy structure identification with a high accuracy level and automatic classifications for heterogeneous riparian corridors. Radar images allow a good identification of riparian vegetation but also of the structure and phenology of vegetation through time with an analysis of the Shannon entropy of the signal. The UAV system used here is a very flexible approach that can easily provide RGB mosaic but also a local digital surface model with very high spatial resolution. Lastly, we discuss the advantages and limitations of each approach from an applied perspective, in terms of flexibility, resolution and technicality.

[1]  R. Dowling,et al.  Vegetation classification of the riparian zone along the Brisbane River, Queensland, Australia, using light detection and ranging (lidar) data and forward looking digital video , 2003 .

[2]  Karin S. Fassnacht,et al.  Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites , 1999 .

[3]  J. Pereira,et al.  Spectral separability of riparian forests from small and medium-sized rivers across a latitudinal gradient using multispectral imagery , 2013 .

[4]  Hervé Piégay,et al.  Hyperspatial Imagery in Riverine Environments , 2012 .

[5]  J. Reitberger,et al.  3D segmentation of single trees exploiting full waveform LIDAR data , 2009 .

[6]  George P. Malanson,et al.  Riparian landscapes: Frontmatter , 1993 .

[7]  F. H. Dawson,et al.  Quality assessment using River Habitat Survey data , 1998 .

[8]  A. Rango,et al.  Image Processing and Classification Procedures for Analysis of Sub-decimeter Imagery Acquired with an Unmanned Aircraft over Arid Rangelands , 2011 .

[9]  R. Dunford,et al.  Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest , 2009 .

[10]  L. Vierling,et al.  Lidar: shedding new light on habitat characterization and modeling , 2008 .

[11]  R. Dunford,et al.  Potential and constraints of UAV technology for the characterisation of Mediterranean riparian forest: a case study of the Drôme, France , 2007 .

[12]  Scott J. Goetz,et al.  REMOTE SENSING OF RIPARIAN BUFFERS: PAST PROGRESS AND FUTURE PROSPECTS 1 , 2006 .

[13]  Using GIS in the mapping and analysis of landscape and vegetation patterns along streams in southern Ireland , 2006 .

[14]  S. Rood,et al.  Riparia: Ecology, Conservation, and Management of Streamside Communities , 2006 .

[15]  Frédéric Baret,et al.  Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots , 2008, Sensors.

[16]  C. Feld Response of three lotic assemblages to riparian and catchment-scale land use: implications for designing catchment monitoring programmes , 2013 .

[17]  Alain Pietroniro,et al.  Towards operational monitoring of a northern wetland using geomatics-based techniques , 2005 .

[18]  S. Ormerod A golden age of river restoration science , 2004 .

[19]  J. Meyer,et al.  Standards for ecologically successful river restoration , 2005 .

[20]  R. Brooks,et al.  A Stream–Wetland–Riparian (SWR) index for assessing condition of aquatic ecosystems in small watersheds along the Atlantic slope of the eastern U.S. , 2009, Environmental monitoring and assessment.

[21]  S. Dufour,et al.  From the myth of a lost paradise to targeted river restoration: forget natural references and focus on human benefits , 2009 .

[22]  Louise H. Kellogg,et al.  Extracting and Visualizing Structural Features in Environmental Point Cloud LiDaR Data Sets , 2011, Topological Methods in Data Analysis and Visualization.

[23]  Xi Min Cui,et al.  Classification of Airborne Lidar Data by Echo , 2012 .

[24]  S. Durrieu,et al.  Improving the quantification of land cover pressure on stream ecological status at the riparian scale using High Spatial Resolution Imagery , 2011 .

[25]  M. R. Fernandes,et al.  Riparian vegetation metrics as tools for guiding ecological restoration in riverscapes. , 2011 .

[26]  Ryan R. Jensen,et al.  Introduction—Small-Scale Unmanned Aerial Systems for Environmental Remote Sensing , 2011 .

[27]  X. Yang Integrated use of remote sensing and geographic information systems in riparian vegetation delineation and mapping , 2007 .

[28]  N. Coops,et al.  Application of high spatial resolution satellite imagery for riparian and forest ecosystem classification , 2007 .

[29]  H. Piégay,et al.  Localisation et caractérisation des géomorphosites fluviaux à l'échelle des réseaux hydrographiques, exemples d'applications géomatiques dans le bassin de la Drôme. , 2010 .

[30]  W. Cohen,et al.  Lidar Remote Sensing for Ecosystem Studies , 2002 .

[31]  Guillaume Forget,et al.  Ecological Restoration of Headwaters in a Rural Landscape (Normandy, France): A Passive Approach Taking Hedge Networks into Account for Riparian Tree Recruitment , 2013 .

[32]  G. W. Geerling,et al.  Mapping river floodplain ecotopes by segmentation of spectral (CASI) and structural (LiDAR) remote sensing data , 2009 .

[33]  N. Prat,et al.  A simple field method for assessing the ecological quality of riparian habitat in rivers and streams: QBR index , 2003 .

[34]  J. Brasington,et al.  Retrieval of vegetative fluid resistance terms for rigid stems using airborne lidar. , 2008 .

[35]  R. Brooks,et al.  Development of a reference-based method for identifying and scoring indicators of condition for coastal plain riparian reaches , 2007 .

[36]  Jong-Sen Lee,et al.  Refined filtering of image noise using local statistics , 1981 .

[37]  S. Dufour,et al.  Image Utilisation for the Study and Management of Riparian Vegetation: Overview and Applications , 2012 .

[38]  R. Dunford,et al.  Analysis of Post-flood Recruitment Patterns in Braided-Channel Rivers at Multiple Scales Based on an Image Series Collected by Unmanned Aerial Vehicles, Ultra-light Aerial Vehicles, and Satellites , 2011 .

[39]  A. Gillespie,et al.  Fluvial Remote Sensing for Science and Management: Carbonneau/Fluvial Remote Sensing for Science and Management , 2012 .

[40]  A. L. Abbott,et al.  UAV-Based Stereo Vision for Rapid Aerial Terrain Mapping , 2011 .

[41]  H. Piégay,et al.  Localisation et caractérisation semi-automatique des géomorphosites fluviaux potentiels. Exemples d’applications à partir d’outils géomatiques dans le bassin de la Drôme (France) , 2010 .

[42]  A. Iital,et al.  Large‐scale relationships between basin and riparian land cover and the ecological status of European rivers , 2010 .

[43]  Peter Axelsson,et al.  Processing of laser scanner data-algorithms and applications , 1999 .

[44]  E. Vivoni,et al.  Riparian vegetation mapping for hydraulic roughness estimation using very high resolution remote sensing data fusion. , 2010 .

[45]  S. Phinn,et al.  Comparison of image and rapid field assessments of riparian zone condition in Australian tropical savannas , 2007 .

[46]  J. Brasington,et al.  Object-based land cover classification using airborne LiDAR , 2008 .

[47]  Irena Hajnsek,et al.  RICE MONITORING IN SPAIN BY MEANS OF TIME SERIES OF TERRASAR-X DUAL-POL IMAGES , 2009 .

[48]  P. Lejeune,et al.  Design of a watercourse and riparian strip monitoring system for environmental management , 2009, Environmental monitoring and assessment.

[49]  Hervé Piégay,et al.  Fluvial remote sensing for science and management. , 2012 .

[50]  Patrice E. Carbonneau,et al.  An automated georeferencing tool for watershed scale fluvial remote sensing , 2010 .

[51]  E. Pottier,et al.  Polarimetric Radar Imaging: From Basics to Applications , 2009 .

[52]  S. Phinn,et al.  Integration of LiDAR and QuickBird imagery for mapping riparian biophysical parameters and land cover types in Australian tropical savannas , 2010 .

[53]  Thomas Blaschke,et al.  Automatic Geographic Object Based Mapping of Streambed and Riparian Zone Extent from LiDAR Data in a Temperate Rural Urban Environment, Australia , 2011, Remote. Sens..

[54]  C. Delacourt,et al.  Very high spatial resolution imagery for channel bathymetry and topography from an unmanned mapping controlled platform , 2007 .

[55]  Benoît St-Onge L'altimétrie laser à balayage , 2004, Rev. Int. Géomatique.

[56]  G. Malanson Riparian landscapes: Organizing the landscape , 1993 .

[57]  S. Sorooshian,et al.  Using Airborne Lidar to Discern Age Classes of Cottonwood Trees in a Riparian Area , 2006 .

[58]  S. Durrieu,et al.  Object-based image analysis for operational fine-scale regional mapping of land cover within river corridors from multispectral imagery and thematic data , 2012 .

[59]  Stuart R. Phinn,et al.  Mapping of riparian zone attributes using discrete return LiDAR, QuickBird and SPOT-5 imagery: Assessing accuracy and costs , 2010 .

[60]  Stefan Buckreuss,et al.  TerraSAR-X Ground Segment Management Plan , 2005 .

[61]  Eric Pottier,et al.  One year wetland survey investigations from quad-pol RADARSAT-2 time-series SAR images , 2012 .