Potential of C and X Band SAR for Shrub Growth Monitoring in Sub-Arctic Environments

The Arctic and sub-Arctic environments have seen a rapid growth of shrub vegetation at the expense of the Arctic tundra in recent decades. In order to develop better tools to assess and understand this phenomenon, the sensitivity of multi-polarized SAR backscattering at C and X band to shrub density and height is studied under various conditions. RADARSAT-2 and TerraSAR-X images were acquired from November 2011 to March 2012 over the Umiujaq community in northern Quebec (56.55°N, 76.55°W) and compared to in situ measurements of shrub vegetation density and height collected during the summer of 2009. The results show that σ0 is sensitive to changes in shrub coverage up to 20% and is sensitive to changes in shrub height up to around 1 m. The cross-polarized backscattering (σ0 HV ) displays the best sensitivity to both shrub height and density, and RADARSAT-2 is more sensitive to shrub height, as TerraSAR-X tends to saturate more rapidly with increasing volume scattering from the shrub branches. These results demonstrate that SAR data could provide essential information, not only on the spatial expansion of shrub vegetation, but also on its vertical growth, especially at early stages of colonization.

[1]  Jiancheng Shi,et al.  Estimation of snow water equivalence using SIR-C/X-SAR. I. Inferring snow density and subsurface properties , 2000, IEEE Trans. Geosci. Remote. Sens..

[2]  Kamal Sarabandi,et al.  Michigan microwave canopy scattering model , 1990 .

[3]  Kamal Sarabandi,et al.  Sahelian-Grassland Parameter Estimation from Backscattered Radar Response , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[4]  Jon Holmgren,et al.  Snow-Shrub Interactions in Arctic Tundra: A Hypothesis with Climatic Implications , 2001 .

[5]  D. Morton,et al.  Satellite‐based evidence for shrub and graminoid tundra expansion in northern Quebec from 1986 to 2010 , 2012 .

[6]  Christian Mätzler,et al.  Microwave permittivity of dry sand , 1996, IEEE Trans. Geosci. Remote. Sens..

[7]  Kamal Sarabandi,et al.  Estimation of forest biophysical characteristics in Northern Michigan with SIR-C/X-SAR , 1995, IEEE Trans. Geosci. Remote. Sens..

[8]  Christian Mätzler,et al.  Microwave permittivity of dry snow , 1996, IEEE Trans. Geosci. Remote. Sens..

[9]  Jiancheng Shi,et al.  Estimation of snow water equivalence using SIR-C/X-SAR. II. Inferring snow depth and particle size , 2000, IEEE Trans. Geosci. Remote. Sens..

[10]  Jiancheng Shi.  Estimation of snow water equivalence using SIR-C/X-SAR , 1998, Asia-Pacific Environmental Remote Sensing.

[11]  Giles M. Foody,et al.  Relationship between green leaf biomass volumetric density and ERS-2 SAR backscatter of four vegetation formations in the semi-arid zone of Israel , 2001 .

[12]  M. Sturm,et al.  Climate change: Increasing shrub abundance in the Arctic , 2001, Nature.

[13]  S. Goetz,et al.  Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities , 2011, Environmental Research Letters.

[14]  C. Breed,et al.  AIRSAR studies of woody shrub density in semiarid rangeland: Jornada del Muerto, New Mexico , 1998 .

[15]  Thomas L. Ainsworth,et al.  Improved Sigma Filter for Speckle Filtering of SAR Imagery , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Ramata Magagi,et al.  Quantitative analysis of RADARSAT SAR data over a sparse forest canopy , 2002, IEEE Trans. Geosci. Remote. Sens..

[17]  Fawwaz T. Ulaby,et al.  Using Mimics To Model L-band Multiangle and Multitemporal Backscatter From A Walnut Orchard , 1990 .

[18]  John A. Richards,et al.  The effect of changing environmental conditions on microwave signatures of forest ecosystems - Preliminary results of the March 1988 Alaskan aircraft SAR experiment , 1990 .

[19]  J. Schimel,et al.  Increased snow depth affects microbial activity and nitrogen mineralization in two Arctic tundra communities , 2004 .

[20]  Ramata Magagi,et al.  Use of ground observations to simulate the seasonal changes in the backscattering coefficient of the subarctic forest , 2002, IEEE Trans. Geosci. Remote. Sens..

[21]  Richard M. Lucas,et al.  Radar backscattering model for multilayer mixed-species forests , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Pascale Ropars,et al.  Shrub expansion at the forest–tundra ecotone: spatial heterogeneity linked to local topography , 2012 .

[23]  Marc L. Imhoff,et al.  A theoretical analysis of the effect of forest structure on synthetic aperture radar backscatter and the remote sensing of biomass , 1995, IEEE Transactions on Geoscience and Remote Sensing.

[24]  G. Schaepman‐Strub,et al.  The response of Arctic vegetation to the summer climate: relation between shrub cover, NDVI, surface albedo and temperature , 2011 .

[25]  Maxim Neumann,et al.  Assessing Performance of L- and P-Band Polarimetric Interferometric SAR Data in Estimating Boreal Forest Above-Ground Biomass , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Monique Bernier,et al.  The use of RADARSAT-2 and TerraSAR-X data for the evaluation of snow characteristics in subarctic regions , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[27]  Claude R. Duguay,et al.  CoReH2O - A Ku- and X-Band SAR Mission for Snow and Ice Monitoring , 2008 .

[28]  Steven F. Oberbauer,et al.  Plot-scale evidence of tundra vegetation change and links to recent summer warming. , 2012 .

[29]  Sushma Panigrahy,et al.  Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density , 2006 .

[30]  Kamal Sarabandi,et al.  Microwave Radar and Radiometric Remote Sensing , 2013 .

[31]  Simon Yueh,et al.  Retrieval of snow parameters from Ku-band and X-band radar backscatter measurements , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.

[32]  G. Schiavon,et al.  The SIR-C/X-SAR experiment on Montespertoli: Sensitivity to hydrological parameters , 1999 .

[33]  E. Pottier,et al.  Interpretation of a RADARSAT-2 fully polarimetric time-series for snow cover studies in an Alpine context – first results , 2012 .

[34]  Giacomo Fontanelli,et al.  Evaluation of vegetation effect on the retrieval of snow parameters from backscattering measurements: A contribution to CoReH2O mission , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[35]  Kari Luojus,et al.  Monitoring of snow cover properties during the spring melting period in forested areas , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.

[36]  Ranga B. Myneni,et al.  Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems , 2004 .

[37]  J. Welker,et al.  Winter Biological Processes Could Help Convert Arctic Tundra to Shrubland , 2005 .

[38]  Esther Lévesque,et al.  Recent expansion of erect shrubs in the Low Arctic: evidence from Eastern Nunavik , 2012 .

[39]  Jennie R. McLaren,et al.  Does NDVI reflect variation in the structural attributes associated with increasing shrub dominance in arctic tundra? , 2011 .

[40]  Emanuele Santi,et al.  Impact of Vegetation in the Retrieval of Snow Parameters from Backscattering Measurements at the X- and Ku-bands , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[41]  Heiko Balzter,et al.  Retrieval of timber volume and snow water equivalent over a Finnish boreal forest from airborne polarimetric Synthetic Aperture Radar , 2002 .