Skip to main content

Advertisement

SpringerLink
Log in

Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Structural physical habitat attributes include indices of stream size, channel gradient, substrate size, habitat complexity, and riparian vegetation cover and structure. The Environmental Monitoring and Assessment Program (EMAP) is designed to assess the status and trends of ecological resources at different scales. High-resolution remote sensing provides unique capabilities in detecting a variety of features and indicators of environmental health and condition. LIDAR is an airborne scanning laser system that provides data on topography, channel dimensions (width, depth), slope, channel complexity (residual pools, volume, morphometric complexity, hydraulic roughness), riparian vegetation (height and density), dimensions of riparian zone, anthropogenic alterations and disturbances, and channel and riparian interaction. Hyperspectral aerial imagery offers the advantage of high spectral and spatial resolution allowing for the detection and identification of riparian vegetation and natural and anthropogenic features at a resolution not possible with satellite imagery. When combined, or fused, these technologies comprise a powerful geospatial data set for assessing and monitoring lentic and lotic environmental characteristics and condition.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Arcement, G. J., Jr., & Schneider, V. R. (1989). Guide for selecting manning’s roughness coefficients for natural channels and flood plains. US Geological Survey Water-Supply Paper 2339.

  • Barbour, M. T., & Stribling, J. B. (1991). Use of habitat assessment in evaluating the biological integrity of stream communities. In G. Gibson (Ed.), Biological criteria: Research and regulation, proceedings of a symposium, 12–13 December 1990, Arlington, Virginia. EPA-440-5-91-005. Washington, D.C.: Office of Water, U.S. Environmental Protection Agency.

    Google Scholar 

  • Barbour, M. T., Diamond, J. M., & Yoder, C. O. (1996). Biological assessment strategies: Applications and limitations. In D. R. Grothe, K. L. Dickson, & D. K. Reed-Judkins (Eds.), Whole effluent toxicity testing: An evaluation of methods and prediction of receiving system impacts (pp. 245–270). Pensacola, Florida: SETAC.

    Google Scholar 

  • Barbour, M. T., Gerritsen, J., Snyder, B. D., & Stribling, J. B. (1999). Rapid bioassessment protocols for use in streams and wadeable rivers: Periphyton, benthic macroinvertebrates and, (2nd ed.). EPA 841-B-99-002. U.S. Washington, D.C.: Environmental Protection Agency, Office of Water.

    Google Scholar 

  • Bazzani, M., Cecchi, G., Pantani, L., & Ralmondi, V. (1998). LIDAR measurement of light attenuation in water. In G. Cecchi, & E. Zilioli (Eds.), SPIE proceedings, earth surface remote sensing II (Vol. 3496, pp. 223–227).

  • Benson, M. A., & Dalrymple, T. (1967). General field and office procedures for indirect discharge measurements (p. 30). U.S. Geological Survey Techniques of Water-Resources Investigations book 3, chap. Al.

  • California Department of Fish and Game (CDFG) (2003). California stream bioassessment procedure: Protocol brief for biological and physical/habitat assessment in wadeable streams. Water Pollution Control Laboratory, Aquatic Bioassessment Laboratory revision date—December 2003.

  • Congalton, R. G., Birch, K., Jones, R., & Schriever, J. (2002). Evaluating remotely sensed techniques for mapping riparian vegetation. Computers and Electronics in Agriculture, 37(1–3), 113–126.

    Article  Google Scholar 

  • Coops, N. C., Hilker, T., Wulder, M. A., St-Onge, B., Newnham, G., Siggins, A., et al. (2007). Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR. Trees Structure and Function, 21, 295–310.

    Google Scholar 

  • CSIRO (2003). Determination of SRA habitat indicators by remote sensing: Technical scoping document. Technical Report 28/03, Environmental Remote Sensing Group, CSIRO Land and Water, Canberra, April.

  • Drake, N. A., Mackin, S., & Settle, J. J. (1999). Mapping vegetation, soils and geology in semi-arid shrublands using spectral matching and mixture modeling of SWIR AVIRIS Imagery. Remote Sensing of Environment, 68, 12–25.

    Article  Google Scholar 

  • Farid, A., Goodrich, D. C., & Sorooshian, S. (2006). Using airborne LIDAR to discern age classes of cottonwood trees in a riparian area. Western Journal of Applied Forestry, 21(3), 149–158.

    Google Scholar 

  • Farid, A., Rautenkranz, D., Goodrich, D. C., Marsh, S. E., & Sorooshian, S. (2008) Riparian vegetation classification from airborne laser scanning data with an emphasis on cottonwood trees. Canadian Journal of Remote Sensing, 32(1), 15–19.

    Google Scholar 

  • Field, D., Biber, P., Kenworthy, W. J., Worthy, L. D., & Finkbeiner, M. (2003). Remote sensing of seagrass with AVIRIS and high altitude aerial photography. Presented at American Society of Photogrammetry and Remote Sensing, Anchorage, AK, May 5–8.

  • Fitzpatrick, F. A., Waite, I. R., D’Arconte, P. J., Meador, M. R., Maupin, M. A., & Gurtz, M. E. (1998). Revised methods for characterizing stream habitat in the national water-quality assessment program (p. 67). U.S. Geological Survey Water-Resources Investigations Report 98-4052.

  • Gebhardt, K., Leonard, S., Staidl, G., & Prichard, D. (1990). Riparian area management: Riparian classification review (p. 56). TR 1737-5. Denver, CO: US Department of Interior, Bureau of Land Management, Service Center.

    Google Scholar 

  • Gerth, W. J., & Herlihy, A. T. (2006). Effect of sampling different habitat types in regional macroinvertebrate bioassessment surveys. Journal North American Benthological Society, 25(2), 501–512.

    Article  Google Scholar 

  • Griffith, M. B., Kaufmann, P. R., Herlihy, A. T., & Hill, B. H. (2001). Analysis of macroinvertebrate assemblages in relation to environmental gradients in Rocky Mountain streams. Ecological Applications, 11(2), 489–505.

    Article  Google Scholar 

  • Griffith, M. B., Husby, P., Hall, R. K., Kaufmann, P. R., & Hill, B. H. (2003). Analysis of macroinvertebrate assemblages in relation to environmental gradients among lotic habitats of California’s Central Valley. Environmental Monitoring and Assessment, 82, 281–309.

    Article  Google Scholar 

  • Harding, D. J., & Berghoff, G. S. (2000). Fault scarp detection beneath dense vegetation cover: Airborne LIDAR Mapping of the Seattle Fault Zone, Bainbridge Island, Washington State. In Proceedings of the american society of photogrammetry and remote sensing annual conference (p. 11). Washington, D.C., May.

  • Harding, D. J., Lefsky, M. A., Parker, G. G., & Blair, J. B. (2001). Laser altimeter canopy height profiles methods and validation for closed-canopy, Broadleaf Forests. Remote Sensing of Environment, 76, 283–297.

    Article  Google Scholar 

  • Herlihy, A. T., Larsen, D. P., Paulsen, S. G., Urquhart, N. S., & Rosenbaum, B. J. (2000). Designing a spatially balanced, randomized site selection process for regional stream surveys: The EMAP mid-Atlantic pilot study. Environmental Monitoring and Assessment, 63, 95–113.

    Article  CAS  Google Scholar 

  • Hudak, A. T., Lefsky, M. A., Cohen, W. B., & Berterretche, M. (2002). Integration of LIDAR and Landsat ETM+ data for estimating and mapping forest canopy height. Remote Sensing of the Environment, 82, 397–416.

    Article  Google Scholar 

  • Jones, K. B., Heggem, D. T., Wade, T. G., Neale, A. C., Ebert, D. W., Nash, M. S., et al. (2000). Assessing landscape condition relative to water resources in the Western United States: A strategic approach. Environmental Monitoring and Assessment, 64, 227–245.

    Article  CAS  Google Scholar 

  • Kaufmann, P. R. (1993). Physical habitat. In R. M. Hughes (Ed.), Stream indicator and design workshop, U.S. environmental protection agency (pp. 59–69). EPA/600/R-93/138. Corvallis, OR: Office of Research and Development.

    Google Scholar 

  • Kaufmann, P. R., & Robison, E. G. (1998). Physical habitat characterization. In J. M. Lazorchak, D. J. Klemm, D. V. Peck (Eds.), Environmental monitoring and assessment program—surface waters: Field operations and methods manual for measuring the ecological condition of wadeable streams (pp. 77–118). EPA/620/ R-94/004F. Washington, D.C.: U.S. Environmental Protection Agency, Office of Research and Development.

    Google Scholar 

  • Kaufmann, P. R., Levine, P., Robison, E. G., Seeliger, C., & Peck, D. V. (1999). Quantifying physical habitat in wadeable streams. EPA/620/R-99/003. Corvallis, OR: U.S. Environmental Protection Agency, Office of Research and Development.

    Google Scholar 

  • Kaufmann, P. R., Faustini, J. M., Larsen, D. P., & Shirazi, M. A. (2008). A roughness-corrected index of relative bed stability for regional stream surveys. Geomorphology, 99, 150–170.

    Article  Google Scholar 

  • Kinzel, P. J., Wright, C. W., Nelson, J. M.,& Burman, A. R. (2007). Evaluation of an experimental LiDAR for surveying a shallow, braided, sand-bedded river. Journal of Hydraulic Engineering, 133(7), 838–842.

    Article  Google Scholar 

  • Klemas, V. (2001). Remote sensing of landscape level coastal environmental indicators. Environmental Management, 1(27), 47–57.

    Article  Google Scholar 

  • Klemm, D. J., Lazorchak, J. M., & Lewis, P. A. (1997) Benthic invertebrate field methods. In J. M. Lazorchak, D. J., Klemm, & D. V. Peck (Eds.), Environmental monitoring and assessment program—surface waters: Field operations and methods for measuring the ecological condition of wadeable streams (p. 160). EPA/620/R-94/004F. US EPA, Cincinnati, OH, 45268: National Exposure Research Laboratory Office of Research and Development, July.

  • Koponen, S., Pulliainen, J., Kallio, K., & Hallikainen, M. (2002). Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, 79, 51–59.

    Article  Google Scholar 

  • Lazorchak, J. M., Klemm, D. J., & Peck, D. V. (1998). Environmental monitoring and assessment program—surface waters: Field operations and methods for measuring the ecological condition of wadeable streams (p. 160). EPA/620/R-94/004F. US EPA, Cincinnati, OH, 45268: National Exposure research Laboratory Office of Research and Development, July.

  • Lefsky, M. A., Cohen, W. B., Parker, G. G., & Harding, D. J. (2002). Lidar remote sensing for ecosystem studies. BioScience, 52, 19–30.

    Article  Google Scholar 

  • Legleiter, C. J. (2003). Spectrally driven classification of high spatial resolution, hyperspectral imagery: A tool for mapping in-stream habitat. Environmental Management, 32(3), 399–411.

    Article  Google Scholar 

  • Legleiter, C. J., & Roberts, D. A. (2005). Effects of channel morphology and sensor spatial resolution on image-derived depth estimates. Remote Sensing of Environment, 95, 231–247.

    Article  Google Scholar 

  • Levien, L., Fiscker, C., Roffers, P., & Maurizi, B. (1998). Statewide change detection using multitemporal remote sensing data. In Proceedings from the first international conference on geospatial information in agriculture & forestry (p. 8). Lake Buena Vista, FL.

  • Lopez, R. D., Heggem, D. T., & Lyon, J. G. (2003). Broad-scale assessment of wetland vulnerability using GIS and landscape-ecological metrics. American Society of Agricultural Engineers, Las Vegas, NV, Abstract with programs, July 27–30.

  • Marcus, W. A. (2002). Mapping of stream microhabitats with high spatial resolution hyperspectral imagery. Journal of Geographical Systems, 4, 113–126.

    Google Scholar 

  • Marcus, W. A., Marston, R. A., Colvard, C. R., Jr., & Gray, R. D. (2002). Mapping the spatial and temporal distributions of large woody debris in rivers of the greater yellowstone ecosystem. USA. Geomorphology, 44(3–4), 323–335.

    Article  Google Scholar 

  • Marcus, W. A., Legleiter, C. J., Aspinall, R. J., Boardman, J. W., & Crabtree, R. L. (2003). High spatial resolution hyperspectral mapping of in-stream habitats, depths, and woody debris in mountain streams. Geomorphology, 55, 363–380.

    Article  Google Scholar 

  • Mars, J., & Crowley, J. (2003). Mapping mine wastes and analyzing areas affected by selenium-rich water runoff in southeast Idaho using AVIRIS imagery and digital elevation data. Remote Sensing of Environment, 84, 422–436.

    Article  Google Scholar 

  • McDonald, M. E. (2000). EMAP overview: objectives, approaches, and achievements. Journal of Environmental Monitoring Assessment, 64, 3–8.

    Google Scholar 

  • Meador, M. R., Hupp, C. R., Cuffney, T. F., & Gurtz, M. E. (1993). Methods for characterizing stream habitat as part of the national water quality assessment program (p. 48). U.S. Geological Survey Open-File Report 93–408.

  • Meyers, L. H. (1989). Riparian area management: Inventory and monitoring riparian areas. US Department of the Interior, Bureau of Land Management Report. Technical Reference 1737–3.

  • Morsdorf, F., Meier, E., Kotz, B., Itten, K. I., Dobbertin, M., & Allgower, B. (2001). LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildlland fire management. Remote Sensing of Environment, 92, 353–362.

    Article  Google Scholar 

  • Ohio Environmental Protection Agency (Ohio EPA) (1987). Biological criteria for the protection of aquatic life: Volumes I–III. Columbus, OH: Ohio Environmental Protection Agency.

    Google Scholar 

  • Oklahoma Conservation Commission (OCC) (1993). Development of rapid bioassessment protocols for Oklahoma utilizing characteristics of the diatom community. Oklahoma City, OK: Oklahoma Conservation Commission.

    Google Scholar 

  • Plafkin, J. L., Barbour, M. T., Porter, K. D., Gross, S. K., & Hughes, R. M. (1989). Rapid bioassessment protocols for use in streams and rivers: Benthic macroinvertebrates and fish. U.S. Environmental Protection Agency, Office of Water Regulation and Standards. EPA/444/4-89-001, eight numbered sections plus appendices.

  • Platts, W. S., Megahan, W. F., & Minshall, G. W. (1983). Methods for evaluating stream, riparian, and biotic conditions. USDA Forest Service General Technical Report INT-183.

  • Popescu, S. (2002). Estimating plot-level tree heights with LIDAR: Local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture, 37, 71–95.

    Article  Google Scholar 

  • Prichard, D., Anderson, J., Correll, C., Fogg, J., Gebhardt, K., Krapf, R., et al. (1998). Riparian area management: A user guide to assessing proper functioning condition and the supporting science for lotic areas (p. 126). TR1737-15. Denver, CO: US Department of the Interior, Bureau of Land Management, National Applied Resource Sciences Center.

  • Ritchie, J. C., Seyfried, M. S., Chopping, M. J., & Pachepsky, Y. (2001). Airborne laser technology for measuring rangeland condition. Journal of Range Management, 54, A8–A21.

    Google Scholar 

  • Rosgen, D. (1996). Applied river morphology (p. 390). Pagosa Springs, CO: Wildland Hydrology.

    Google Scholar 

  • Shields, F. D., Jr., Knight, S. S., & Cooper, C. M. (1994). Effects of channel incision on base flow stream habitat and fishes. Environmental Management, 18(1), 43–57.

    Article  Google Scholar 

  • Stevens, L., Jr., & Olsen, A. R. (1999). Spatially restricted surveys over time for aquatic resources. Journal of Agricultural, Biological, and Environmental Statistics, 4(4), 415–428.

    Article  Google Scholar 

  • Valencia, R. A., Wennerhund, J. A., Winstead, R. A., Woods, S., Riley, L., Swanson, E., et al. (1993). Arizona riparian inventory and mapping project (p. 134). Arizona Game and Fish Department.

  • Zonneveld, I. (1974). Aerial photography, remote sensing and ecology. ITC Journal, 4, 553–560.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. USEPA Region IX, WTR2, 75 Hawthorne St., San Francisco, CA, 94105, USA

    Robert K. Hall

  2. University of Florida Sea Grant College Program, Boating and Waterway Program, Bldg. 803, McCarty Dr., Gainesville, FL, 32611-0400, USA

    Russell L. Watkins

  3. USEPA ORD NERL ESD, Las Vegas, NV, 89119, USA

    Daniel T. Heggem

  4. USGS National Center, MS 516, 12201 Sunrise Valley Drive, Reston, VA, 20192-0002, USA

    K. Bruce Jones

  5. USEPA ORD NHEERLWED, Corvallis, OR, 97333, USA

    Philip R. Kaufmann

  6. Bureau of Land Management, Reno, NV, 89520, USA

    Steven B. Moore & Sandra J. Gregory

Authors
  1. Robert K. Hall
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Russell L. Watkins
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daniel T. Heggem
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. K. Bruce Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Philip R. Kaufmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Steven B. Moore
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sandra J. Gregory
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert K. Hall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hall, R.K., Watkins, R.L., Heggem, D.T. et al. Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery. Environ Monit Assess 159, 63–83 (2009). https://doi.org/10.1007/s10661-008-0613-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-008-0613-y

Keywords

Search

Navigation