River morphology monitoring using multitemporal SAR data: preliminary results

Abstract In this paper, we test the capability of satellite synthetic aperture radar (SAR) images to enhance the monitoring of river geomorphological processes. The proposed approach exploits the recently introduced Level-α products. These products are bi-temporal RGB composites in which the association color-object, being physical-based, is stable whatever the scene is considered. This favors the detection of temporary rivers' characteristics for classification purposes in a change-detection environment. The case study was implemented on the Orco river (northwest Italy), where a set of 39 COSMO-SkyMed SAR stripmap images acquired from October 2008 to November 2014 was used to monitor channel planform changes. This preliminary study is devoted to assess the suitability of Level-α images for geomorphologist, with particular reference to the detection of phenomena of interest in river monitoring. This is prior for semi-automatic or automatic classification activities.

[1]  D. Montgomery,et al.  LARGE WOODY DEBRIS JAMS, CHANNEL HYDRAULICS AND HABITAT FORMATION IN LARGE RIVERS , 1996 .

[2]  H. Piégay,et al.  Large woody debris and river geomorphological pattern: examples from S.E. France and S. England , 1997 .

[3]  A. Gurnell,et al.  The distribution of large woody debris accumulations and pools in relation to woodland stream management in a small, low-gradient stream , 1998 .

[4]  S. Lane,et al.  The Measurement of River Channel Morphology Using Digital Photogrammetry , 2000 .

[5]  E. Wohl,et al.  Large woody debris and flow resistance in step-pool channels, Cascade Range, Washington , 2003 .

[6]  Measuring the Surface Roughness of Stream Stones , 2006, Hydrobiologia.

[7]  W. Marcus,et al.  Optical remote mapping of rivers at sub‐meter resolutions and watershed extents , 2008 .

[8]  Tammo S. Steenhuis,et al.  Suitability and Limitations of ENVISAT ASAR for Monitoring Small Reservoirs in a Semiarid Area , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Luca Mao,et al.  Morphological effects of different channel‐forming discharges in a gravel‐bed river , 2009 .

[10]  M. Catone,et al.  Spatial and temporal changes in Aniene river basin (Latium,Italy) using landscape metrics and moving window technique , 2009 .

[11]  W. Bertoldi,et al.  Assessment of morphological changes induced by flow and flood pulses in a gravel bed braided river: The Tagliamento River (Italy) , 2010 .

[12]  W. Marcus,et al.  Remote sensing of rivers: the emergence of a subdiscipline in the river sciences , 2010 .

[13]  R. E. Thomas,et al.  Quantification of braided river channel change using archival digital image analysis , 2010 .

[14]  N. Drake,et al.  The topographic signature of vegetation development along a braided river: Results of a combined analysis of airborne lidar, color air photographs, and ground measurements , 2011 .

[15]  N. Drake,et al.  Interactions between river flows and colonizing vegetation on a braided river: exploring spatial and temporal dynamics in riparian vegetation cover using satellite data , 2011 .

[16]  Antonio Iodice,et al.  Innovative Synthetic Aperture Radar Products for the Management of Land and Water , 2012, 2012 IEEE Global Humanitarian Technology Conference.

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

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

[19]  Mark J. Fonstad.  Hyperspectral Imagery in Fluvial Environments , 2012 .

[20]  N. Surian,et al.  A method for the assessment and analysis of the hydromorphological condition of Italian streams: The Morphological Quality Index (MQI) , 2013 .

[21]  M. Rinaldi,et al.  A review of assessment methods for river hydromorphology , 2015, Environmental Earth Sciences.

[22]  Antonio Iodice,et al.  Modeling Watershed Response in Semiarid Regions With High-Resolution Synthetic Aperture Radars , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[23]  Antonio Iodice,et al.  A New Framework for SAR Multitemporal Data RGB Representation: Rationale and Products , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[24]  A. Iodice,et al.  An end-user-oriented framework for the classification of multitemporal SAR images , 2016 .

[25]  Saskia Foerster,et al.  Bathymetric survey of water reservoirs in north-eastern Brazil based on TanDEM-X satellite data. , 2016, The Science of the total environment.

[26]  Hervé Piégay,et al.  Hierarchical Object-Based Mapping of Riverscape Units and in-Stream Mesohabitats Using LiDAR and VHR Imagery , 2016, Remote. Sens..