Estimating Urban Canopy Parameters Using Synthetic Aperture Radar Data

Indumathi Jeyachandran Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah

Search for other papers by Indumathi Jeyachandran in
Current site
Google Scholar
PubMed
Close
,
Steven J. Burian Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah

Search for other papers by Steven J. Burian in
Current site
Google Scholar
PubMed
Close
, and
Stephen W. Stetson Global Environmental Management, Inc., Whistler, British Columbia, Canada

Search for other papers by Stephen W. Stetson in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

This paper introduces a remote sensing–based approach to rapidly derive urban morphological characteristics using radar satellite data. The approach is based on the expectation that the magnitude of the synthetic aperture radar (SAR) backscatter can be related to urban canopy parameters (UCPs) describing the height, density, and roughness of buildings, trees, and other objects in cities. This hypothesis was tested with full-feature terrain elevation and SAR datasets for the Houston, Texas, metropolitan area. The backscatter magnitude was found to vary as expected across the city with higher backscatter values in the downtown tall building district relative to adjacent residential and commercial areas. To demonstrate the concept of using radar backscatter to estimate UCPs, relationships were derived between SAR backscatter and mean height, plan area fraction, and frontal area index of roughness elements (e.g., buildings and trees). In addition, SAR backscatter relationships were derived with roughness lengths computed using morphometric approaches. In all cases, the derived relationships were found to provide estimates of UCPs acceptable for use in meteorological models. Further testing using data from the Salt Lake City, Utah, metropolitan area validated the relationships and identified key areas for improvement for future research, including SAR instrument view angle differences and buildings split between SAR pixels.

Corresponding author address: Indumathi Jeyachandran, Department of Civil and Environmental Engineering, University of Utah, 122 S. Central Campus Drive, Suite 104, Salt Lake City, UT 84112. Email: buddy_indu@yahoo.com

Abstract

This paper introduces a remote sensing–based approach to rapidly derive urban morphological characteristics using radar satellite data. The approach is based on the expectation that the magnitude of the synthetic aperture radar (SAR) backscatter can be related to urban canopy parameters (UCPs) describing the height, density, and roughness of buildings, trees, and other objects in cities. This hypothesis was tested with full-feature terrain elevation and SAR datasets for the Houston, Texas, metropolitan area. The backscatter magnitude was found to vary as expected across the city with higher backscatter values in the downtown tall building district relative to adjacent residential and commercial areas. To demonstrate the concept of using radar backscatter to estimate UCPs, relationships were derived between SAR backscatter and mean height, plan area fraction, and frontal area index of roughness elements (e.g., buildings and trees). In addition, SAR backscatter relationships were derived with roughness lengths computed using morphometric approaches. In all cases, the derived relationships were found to provide estimates of UCPs acceptable for use in meteorological models. Further testing using data from the Salt Lake City, Utah, metropolitan area validated the relationships and identified key areas for improvement for future research, including SAR instrument view angle differences and buildings split between SAR pixels.

Corresponding author address: Indumathi Jeyachandran, Department of Civil and Environmental Engineering, University of Utah, 122 S. Central Campus Drive, Suite 104, Salt Lake City, UT 84112. Email: buddy_indu@yahoo.com

Save
  • Ainsworth, T. L., D. L. Schuler, and J. S. Lee, 2008: Polarimetric SAR characterization of man-made structures in urban areas using normalized circular-pol correlation coefficients. Remote Sens. Environ., 112 , 28762885.

    • Search Google Scholar
    • Export Citation
  • Brown, M. J., 2000: Urban parameterizations for mesoscale meteorological models. Mesoscale Atmospheric Dispersion, Z. Boybeyi, Ed., WIT Press, 193–255.

    • Search Google Scholar
    • Export Citation
  • Brown, M. J., and M. D. Williams, 1998: An urban canopy parameterization for mesoscale meteorological models. Proc. Second Urban Environment Symp., Albuquerque, NM, Amer. Meteor. Soc., 144–147.

    • Search Google Scholar
    • Export Citation
  • Bryan, M. L., 1975: Interpretation of an urban scene using multi-channel radar imagery. Remote Sens. Environ., 4 , 4966.

  • Burian, S. J., M. J. Brown, and S. P. Linger, 2002: Morphological analysis using 3D building databases: Los Angeles, California. Los Alamos National Laboratory Rep. LA-UR-02-0781, 66 pp.

    • Search Google Scholar
    • Export Citation
  • Burian, S. J., S. R. K. Maddula, S. P. Velugubantla, and M. J. Brown, 2003: Morphological analysis using 3D building databases: Los Angeles, California. Los Alamos National Laboratory Rep. LA-UR-03-8633, 73 pp.

    • Search Google Scholar
    • Export Citation
  • Burian, S. J., M. J. Brown, J. Ching, M. L. Cheuk, M. Yuan, W. Han, and A. T. McKinnon, 2004a: Urban morphological analysis for mesoscale meteorological and dispersion modeling applications: Current issues. Preprints, Fifth Conf. on Urban Environment, Vancouver, BC, Canada, Amer. Meteor. Soc., 9.1. [Available online at http://ams.confex.com/ams/pdfpapers/80276.pdf].

    • Search Google Scholar
    • Export Citation
  • Burian, S. J., S. W. Stetson, W. Han, J. Ching, and D. Byun, 2004b: High-resolution dataset of urban canopy parameters for Houston, Texas. Preprints, Fifth Conf. on Urban Environment, Vancouver, BC, Canada, Amer. Meteor. Soc., 9.3. [Available online at http://ams.confex.com/ams/pdfpapers/80263.pdf].

    • Search Google Scholar
    • Export Citation
  • Burian, S. J., A. T. McKinnon, J. Hartman, W. Han, I. Jeyachandran, and M. J. Brown, 2005: National Building Statistics Database, version 1. Los Alamos National Laboratory Unclassified Rep., 28 pp.

    • Search Google Scholar
    • Export Citation
  • Burian, S. J., M. J. Brown, T. N. McPherson, J. Hartman, W. Han, I. Jeyachandran, and J. F. Rush, 2006: Emerging urban databases for meteorological and dispersion modeling. Preprints, Sixth Symp. on Urban Environment, Atlanta, GA, Amer. Meteor. Soc., 5.2. [Available online at http://ams.confex.com/ams/pdfpapers/103023.pdf].

    • Search Google Scholar
    • Export Citation
  • Burian, S. J., N. Augustus, I. Jeyachandran, and M. Brown, 2008: National Building Statistics Database, version 2. Los Alamos National Laboratory Rep. LA-UR-08-1921, 33 pp.

    • Search Google Scholar
    • Export Citation
  • Chen, F., H. Kusaka, M. Tewari, J-W. Bao, and H. Hirakuchi, 2004: Utilizing the coupled WRF/LSM/urban modeling system with detailed urban classification to simulate the urban heat island phenomena over the greater Houston area. Preprints, Fifth Conf. on Urban Environment, Vancouver, BC, Canada, Amer. Meteor. Soc., 9.11. [Available online at http://ams.confex.com/ams/pdfpapers/79765.pdf].

    • Search Google Scholar
    • Export Citation
  • Deroin, J-P., A. Company, and A. Simonin, 1997: Empirical model for interpreting the relationship between backscattering and arid land surface roughness as seen with the SAR. IEEE Trans. Geosci. Remote Sens., 35 , 8692.

    • Search Google Scholar
    • Export Citation
  • Dubois, P. C., J. van Zyl, and T. Engman, 1995: Measuring soil moisture with imaging radars. IEEE Trans. Geosci. Remote Sens., 33 , 915926.

    • Search Google Scholar
    • Export Citation
  • Dupont, S., T. L. Otte, and J. K. S. Ching, 2004: Simulation of meteorological fields within and above urban and rural canopies with a mesoscale model. Bound.-Layer Meteor., 113 , 111158.

    • Search Google Scholar
    • Export Citation
  • Evans, D. L., T. G. Farr, and J. J. van Zyl, 1992: Estimates of surface roughness derived from synthetic aperture radar (SAR) data. IEEE Trans. Geosci. Remote Sens., 30 , 382389.

    • Search Google Scholar
    • Export Citation
  • Franceschetti, G., A. Iodice, and D. Riccio, 2002: A canonical problem in electromagnetic backscattering from buildings. IEEE Trans. Geosci. Remote Sens., 40 , 17871801.

    • Search Google Scholar
    • Export Citation
  • Gamba, P., and B. Houshmand, 2000: Digital surface models and building extraction: A comparison of IFSAR and lidar data. IEEE Trans. Geosci. Remote Sens., 38 , 19591968.

    • Search Google Scholar
    • Export Citation
  • Gamba, P., B. Houshmand, and M. Saccani, 2000: Detection and extraction of buildings from interferometric SAR data. IEEE Trans. Geosci. Remote Sens., 38 , 611617.

    • Search Google Scholar
    • Export Citation
  • Hasager, C. B., N. W. Nielsen, N. O. Jensen, E. Boegh, J. H. Christensen, E. Dellwik, and H. Soegaard, 2003: Effective roughness calculated from satellite-derived land cover maps and hedge-information used in a weather forecasting model. Bound.-Layer Meteor., 109 , 227254.

    • Search Google Scholar
    • Export Citation
  • Henderson, F. M., and A. J. Lewis, 1998: Principles and Applications of Imaging Radar. 3rd ed. John Wiley & Sons, 866 pp.

  • Holt, T. R., and J. J. Shi, 2004: Mesoscale simulations of the urban environment of Washington, DC: Comparison of COAMPS simulations to DCNet observations and sensitivity of plume transport to an urban canopy parameterization. Preprints, Symp. on Planning, Nowcasting, and Forecasting in the Urban Zone, Seattle, WA, Amer. Meteor. Soc., 4.3. [Available online at http://ams.confex.com/ams/pdfpapers/70917.pdf].

    • Search Google Scholar
    • Export Citation
  • Holt, T. R., and J. Pullen, 2007: Urban canopy modeling of the New York City metropolitan area: A comparison and validation of single- and multilayer parameterizations. Mon. Wea. Rev., 135 , 19061930.

    • Search Google Scholar
    • Export Citation
  • Holt, T. R., S. Chin, M. Leach, and G. Sugiyama, 2002: Sensitivity of mesoscale real-data simulations to an urban canopy parameterization. Preprints, Fourth Symp. on Urban Environment, Norfolk, VA, Amer. Meteor. Soc., 11.13. [Available online at http://ams.confex.com/ams/pdfpapers/36996.pdf].

    • Search Google Scholar
    • Export Citation
  • Lacser, A., and T. L. Otte, 2002: Implementation of an urban canopy parameterization in MM5. Preprints, Fourth Symp. on Urban Environment, Norfolk, VA, Amer. Meteor. Soc., 11.4. [Available online at http://ams.confex.com/ams/pdfpapers/36822.pdf].

    • Search Google Scholar
    • Export Citation
  • Lillesand, T. M., and R. W. Kiefer, 2002: Remote Sensing and Image Interpretation. 4th ed. John Wiley and Sons, 724 pp.

  • Long, N., S. Kermadi, C. Kergomard, P. G. Mestayer, and A. Trébouet, 2003: Urban cover modes and thermodynamic parameters from urban database and satellite data: A comparison for Marseille during ESCOMPTE. Proc. Fifth Int. Conf. on Urban Climate, Łódź, Poland.

    • Search Google Scholar
    • Export Citation
  • Luckman, A., and W. Grey, 2003: Urban building height variance from multibaseline ERS coherence. IEEE Trans. Geosci. Remote Sens., 41 , 20222025.

    • Search Google Scholar
    • Export Citation
  • Macdonald, R. W., R. F. Griffiths, and D. J. Hall, 1998: Improved method for the estimation of surface roughness of obstacle arrays. Atmos. Environ., 32 , 18571864.

    • Search Google Scholar
    • Export Citation
  • Mo, T., J. R. Wang, and T. J. Schmugge, 1988: Estimation of surface roughness parameters from dual-frequency measurements of radar backscattering coefficients. IEEE Trans. Geosci. Remote Sens., 26 , 574579.

    • Search Google Scholar
    • Export Citation
  • Oliver, C., and S. Quegan, 2004: Understanding Synthetic Aperture Radar Images. SciTech Publishing, 465 pp.

  • Otte, T. L., A. Lacser, S. Dupont, and J. K. S. Ching, 2004: Implementation of an urban canopy parameterization in a mesoscale meteorological model. J. Appl. Meteor., 43 , 16481665.

    • Search Google Scholar
    • Export Citation
  • Quartulli, M., and M. Datcu, 2004: Stochastic geometrical modeling for built-up area understanding from a single SAR intensity image with meter resolution. IEEE Trans. Geosci. Remote Sens., 42 , 19962003.

    • Search Google Scholar
    • Export Citation
  • Ratti, C., and P. Richens, 1999: Urban texture analysis with image processing techniques. Proc. CAADFutures99 Conf., Atlanta, GA, 49–64.

    • Search Google Scholar
    • Export Citation
  • Ratti, C., S. Di Sabatino, R. Britter, M. Brown, F. Caton, and S. Burian, 2002: Analysis of 3-D urban databases with respect to pollution dispersion for a number of European and American cities. Water Air Soil Pollut. Focus, 2 , 459469.

    • Search Google Scholar
    • Export Citation
  • Raupach, M. R., 1994: Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Bound.-Layer Meteor., 71 , 211216.

    • Search Google Scholar
    • Export Citation
  • Research Systems Inc., 2005: Envi user’s guide. Research Systems Inc., 234 pp.

  • Richens, P., 1997: Image processing for urban scale environmental modeling. Proc. Int. Conf. on Building Simulation, Prague, Czech Republic, 163–171.

    • Search Google Scholar
    • Export Citation
  • Rozoff, C. M., W. R. Cotton, and J. O. Adegoke, 2003: Simulation of St. Louis, Missouri, land use impacts on thunderstorms. J. Appl. Meteor., 42 , 716738.

    • Search Google Scholar
    • Export Citation
  • Sabins, F. F., 1987: Remote Sensing and Image Interpretation. 2nd ed. Freeman and Company, 439 pp.

  • Shi, J., J. Wang, A. Y. Hsu, P. E. O’Neill, and E. T. Engman, 1997: Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data. IEEE Trans. Geosci. Remote Sens., 35 , 12541266.

    • Search Google Scholar
    • Export Citation
  • Simonetto, E., H. Oriot, and R. Garello, 2005: Rectangular building extraction from stereoscopic airborne radar images. IEEE Trans. Geosci. Remote Sens., 43 , 23862395.

    • Search Google Scholar
    • Export Citation
  • Stetson, S. W., 2004: Surface roughness and zo parameter measured from satellite-based synthetic aperture radar. Global Environmental Management, Inc., Research Rep., 5 pp.

    • Search Google Scholar
    • Export Citation
  • Velugubantla, S. P., S. J. Burian, M. J. Brown, W. Han, A. McKinnon, and T. N. McPherson, 2004: Assessment of methods for creating a national building statistics database for atmospheric dispersion modeling. Preprints, Fifth Conf. on the Urban Environment, Vancouver, BC, Canada, Amer. Meteor. Soc., 9.4. [Available online at http://ams.confex.com/ams/pdfpapers/80284.pdf].

    • Search Google Scholar
    • Export Citation
  • Weeks, R. J., M. Smith, K. Pak, W. H. Li, and A. Gillespie, 1996: Surface roughness, radar backscatter and visible and near-infrared reflectance in Death Valley, California. J. Geophys. Res., 101 , 2307723090.

    • Search Google Scholar
    • Export Citation
  • Weeks, R. J., M. Smith, K. Pak, and A. Gillespie, 1997: Inversions of SIR-C and AIRSAR data for the roughness of geological surfaces. Remote Sens. Environ., 59 , 383396.

    • Search Google Scholar
    • Export Citation
  • Xia, Z. G., and F. M. Henderson, 1997: SAR applications in human settlement detection, population estimation and urban land use pattern analysis: A status report. IEEE Trans. Geosci. Remote Sens., 35 , 7985.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1602 1322 61
PDF Downloads 295 87 20