Skip to main content

Remote Sensing of Forests Over Time

Change Types, Methods, and Opportunities

  • Chapter
Remote Sensing of Forest Environments

Abstract

Forest change happens constantly at different spatial scales. At the individual tree level, the biochemical and biophysical properties may vary according to environmental conditions; physical appearance such as colour and size may change due to phenology or human disturbance. At the stand level, the structure of forest canopies may change in terms of horizontal measures of canopy closure and gap size and shape and vertical measures of number of layers of understorey, height of each storey, etc. At the watershed level, forest ecosystem change can be evaluated by different landscape measurements such as fragmentation indices, matrix and corridor structure and system complexity. Changes at even larger scales are usually caused by human-induced environmental changes and climate changes.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Adams, J. B., Sabol, D. E., Kapos, V., Almeida Filho, R., Roberts, D. A., Smith, M. O., & Gillespie, A. R. (1995). Classification of multispectral images based on fractions of endmembers: application to land-cover change in the Brizilian Amazon. Remote Sensing of Environment, 52,137–154.

    Article  Google Scholar 

  • Allen, T. R., & Kupfer, J. A. (2001). Spectral response and spatial pattern of Fraser fir mortality and regeneration, Great Smoky Mountains, USA. Plant Ecology, 156, 59–74.

    Article  Google Scholar 

  • Armour, B., Tanaka, A., Ohkura, H., Saito, G. (1998). Radar interferometry for environmental change detection. Lunetta R. S. & Elvidge C. D. (Eds). Remote Sensing Change Detection, Environmental Monitoring Methods and Applications, 245–279. Ann Arbor Press. Chelsea, Michigan, USA.

    Google Scholar 

  • Biging, G. S., Colby, D. R., & Congalton, R. G. (1998). Sampling systems for change detection accuracy assessment. Lunetta, R. S. & Elvidge C. D. (Eds.). Remote Sensing Change Detection, Environmental Monitoring Methods and Applications, 281–308. Ann Arbor Press. Chelsea, Michigan.

    Google Scholar 

  • Bruzzone, L., & Fernandez Prieto, D. (2000). Automatic analysis of the difference image for unsupervised change detection. IEEE Transactions on Geoscience and Remote Sensing, 38,1171–1182.

    Article  Google Scholar 

  • Chalifoux, S., Cavayas, F., & Gray, J. T. (1998). Map-guided approach for automatic detection of Landsat TM images of forest stands damaged by spruce budworm. Photogrammetric Engineering and Remote Sensing, 64, 629–635.

    Google Scholar 

  • Chen, J., Gong, P., He, C, Pu, R., & Shi, P. (in press). Land use/cover change detection using improved change vector analysis. Photogrammetric Engineering and Remote Sensing

    Google Scholar 

  • Cohen, W. B., & Fiorella, M. (1998). Comparison of Methods for Detecting Conifer Forest Change with Thematic Mapper Imagery. Lunetta R.S. & Elvidge C. D. (Eds.). Remote Sensing Change Detection, Environmental Monitoring Methods and Applications, 89–102. Ann Arbor Press. Chelsea, Michigan.

    Google Scholar 

  • Collins, J. B, & Woodcock, C. E. (1994). Change detection using the Gramm-Schmidt transformation applied to mapping forest mortality. Remote Sensing of Environment, 50, 267–279.

    Article  Google Scholar 

  • Collins, J. B., & Woodcock, C. E. (1996). An assessment of several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM data. Remote Sensing of Environment, 56, 66–77.

    Article  Google Scholar 

  • Coppin, P. R., & Bauer, M. E. (1994). Processing of multitemporal Landsat TM imagery to optimize extraction of forest cover change detection. IEEE Transactions on Geoscience and Remote Sensing, 32, 918–927.

    Article  Google Scholar 

  • Coppin, P., Nackaerts, K., Queen, L., & Brewer, K. (2001). Operational monitoring of green biomass change for forest management. Photogrammetric Engineering and Remote Sensing, 67, 603–611.

    Google Scholar 

  • Crist, E. P., (1985). A TM tasseled cap equivalent transformation for reflectance factor data. Remote Sensing of Environment, 17, 301–306.

    Article  Google Scholar 

  • Crist, E. P., & Cicone, R. C. (1984). A physically-based transformation of thematic mapper data-the TM tasseled cap, IEEE Transactions on Geoscience and Remote Sensing, 22, 256–263.

    Article  Google Scholar 

  • Cushman, S.A., & Wallin, D. O. (2000). Rates and patterns of landscape change in the Central Sikhote-alin Mountains, Russian Far East. Landscape Ecology, 15,643–659.

    Article  Google Scholar 

  • Dai, X., & Khorram, S. (1998). The effects of image misregistration on the accuracy of remotely sensed change detection. IEEE Transactions on Geoscience and Remote Sensing, 36, 1566–1577.

    Article  Google Scholar 

  • Diem, J. E. (2002). Remote sensing of forest health in southern Arizona, USA: evidence for ozone-induced foliar injury. Environ Manage 29, 373–384.

    Article  Google Scholar 

  • Drake, J. B., Dubayah R. O., Clark, D. B., et al. (2002). Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sensing of Environment, 79, 305–319.

    Article  Google Scholar 

  • Foody, G. M., & Boyd, D. S. (1999). Detection of partial land cover change associated with the migration of inner-class transitional zones. International Journal of Remote Sensing, 20,2723–2740.

    Article  Google Scholar 

  • Franklin S. E., (1989). Classification of hemlock looper defoliation using SPOT HRV imagery. Canadian Journal of Remote Sensing, 15, 178–182.

    Google Scholar 

  • Franklin S. E., & Raske, A. G. (1994). Satellite remote sensing of spruce budworm forest defoliation in western Newfoundland. Canadian Journal of Remote Sensing, 20, 37–48.

    Google Scholar 

  • Fung, T., & LeDrew, E. F. (1987). Application of principal component analysis to change detection. Photogrammetric Engineering & Remote Sensing, 53, 1649–1658.

    Google Scholar 

  • Fung T. (1990). An assessment of TM imagery for land cover change detection. IEEE Transactions on Geoscience and Remote Sensing, 28, 681–684.

    Article  Google Scholar 

  • Gong, P. (1993). Change detection using principal component analysis and fuzzy set theory. Canadian Journal of Remote Sensing, 19, 22–29.

    Google Scholar 

  • Gong, P. (forthcoming). Photo-ecometrics for natural resources monitoring. Andrea, G., Fabbri, G. G., & McCammon, R. B. (Eds.). Deposit and Geoenvironmental Models for Resource Exploitation and Environmental Security. Kluwer Academic Press, Dordrecht, The Netherlands.

    Google Scholar 

  • Gong, P. (2002). Remote Sensing and Image Analysis Textbook (web site: http://camfer.cnr.berkeley.edu/~gong/textbook(accessed August 14, 2002)

    Google Scholar 

  • Gong, P., Biging, G., & Standiford, R. (2000). The potential of digital surface model for hardwood rangeland monitoring, Journal of Range Management, 53, 622–626.

    Article  Google Scholar 

  • Gong, P., Biging, G. S., Lee, S. M., Mei, X., Sheng, Y., Pu, R., Xu, B., & Schwarz, K.-P. (1999). Photo-ecometrics for forest inventory, Geographic Information Sciences, 5, 9–14.

    Google Scholar 

  • Gong, P., LeDrew, E. F., & Miller, J. R. (1992) Registration noise reduction in difference images for change detection. International Journal of Remote Sensing, 13, 773–779.

    Article  Google Scholar 

  • Gong, P., Miller, J. R., & Spanner, M. (1994). Forest canopy closure from classification and spectral unmixing: a multi-sensor evaluation of application to an open canopy. IEEE Transactions on Geoscience and Remote Sensing, 32, 1067–1080.

    Article  Google Scholar 

  • Gopal, S., & Woodcock, C. (1996). Remote sensing of forest change using artificial neural networks IEEE Transactions on Geoscience and Remote Sensing, 34, 398–404.

    Article  Google Scholar 

  • Grover, K., Quegan, S., & Freitas, C. D. (1999). Quantitative estimation of tropical forest cover by SAR, IEEE Transactions on Geoscience and Remote Sensing, 37,479–490.

    Article  Google Scholar 

  • Hame, T., Heiler, I., & San Miguel-Ayanz, J. (1998). An unsupervised change detection and recognition system for forestry. International Journal of Remote Sensing, 19, 1079–1099.

    Article  Google Scholar 

  • Hayes, D. J., & Sader, S. A. (2001). Comparison of change detection techniques for monitoring tropical forest clearing and vegetation regrowth in a time series. Photogrammetric Engineering and Remote Sensing, 67, 1067–1075.

    Google Scholar 

  • Hessburg, P. F., Smith, B. G., & Salter, R. B. (2000). Recent changes (1930s–1990s) in spatial patterns of interior northwest forests, USA. Forest Ecology and Management, 136,53–83.

    Article  Google Scholar 

  • Howarth, P. J., & Wickware, G. M. (1981). Procedure for change detection using Landsat digital data. International Journal of Remote Sensing, 2, 277–291.

    Article  Google Scholar 

  • Ingebritsen, S., & Lyon, R. (1985). Principal component analysis of multitemporal image pairs, Intematioanl Journal of Remote Sensing, 6, 687–696.

    Article  Google Scholar 

  • Jackson, R. D. (1983). Spectral indices in n-space, Remote Sensing of Environment, 13, 400–421.

    Google Scholar 

  • Johnson, R. D., & Kasischke, E. S. (1998). Change vector analysis: a technique for the multispectral monitoring for land cover and condition. International Journal of Remote Sensing, 19,411–426.

    Article  Google Scholar 

  • Jensen, J. R. (1996). Introductory Digital Image Processing, A Remote Sensing Perspective. Prentice Hall, Upper Saddle River, New Jersey.

    Google Scholar 

  • Kauth, R. J., & Thomas, G. S. (1976). The tasseled cap — a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. Proceedings of the Symposium on Machine Processing of Remotely Sensed Data, 4b, 41–51. June 21–July 1, Purdue University, West Lafayette, Indiana.

    Google Scholar 

  • Lambin, E. F., & Strahler, A. H. (1994a). Change vector analysis in multitemporal space: A tool to detect and categorize land-cover change processes using high temporal-resolution satellite data. Remote Sensing of Environment, 48, 231–244.

    Article  Google Scholar 

  • Lambin, E. F., & Strahler, A. H. (1994b). Indicators of land-cover change for change vector analysis in multitemporal space at coarse spatial scales. International Journal of Remote Sensing, 15,2099–2119.

    Article  Google Scholar 

  • Leckie, D. G. (1987). Factors affecting defoliation assessment using Airborne Multispectral Scanner data. Photogrammetric Engineering and Remote Sensing, 53, 1665–1674.

    Google Scholar 

  • Li, Z., Nadon, S., & Cihlar, J. (2000). Satellite detection of Canadian boreal forest fires: Development and application of an algorithm, International Journal of Remote Sensing, 21,3057–3069.

    Article  Google Scholar 

  • Malila, W.A. (1980). Change vector analysis: an approach for detecting forest changes with Landsat. Proc. Symposium Machine Processing of Remotely Sensed Data, 326–336. Purdue University, West Lafayette, Indiana, USA, IEEE, Piscataway, New Jersey, USA.

    Google Scholar 

  • McGarigal, K, & Marks, B. J. (1995). FRAGSTATS spatial pattern analysis program for quantifying landscape structure. Report No PNW-GTR 351, USFS, Pacific Northwest Research Station, Portland.

    Google Scholar 

  • Michalek, J. L., Luczkovich, J. J., & Stofile, R. W. (1993). Multispectral change vector analysis for monitoring coastal marine environments. Photogrammetric Engineering and Remote Sensing, 59, 381–384.

    Google Scholar 

  • Muchoney, D. M., & Haack, B. N. (1994). Change detection for monitoring forest defoliation. Photogrammetric Engineering and Remote Sensing, 60,1243–1251.

    Google Scholar 

  • Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., & Nemani, R. R. (1997). Increased plant growth in the northern high latitudes from 1981–1991. Nature, 386, 698–702.

    Article  Google Scholar 

  • Naesset, E, (2002). Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment, 80, 88–99

    Article  Google Scholar 

  • Nielsen A. A., Conradsen K., & Simpson, J. J. (1998). Multivariate alteration detection and MAF postprocessing in multispectral, bitemproal image data: new approaches to change detection studies. Remote Sensing of Environment, 64, 1–19.

    Article  Google Scholar 

  • Olsson, H. (1994). Changes in satellite-measured reflectances caused by thinning cuttings in boreal forest, Remote Sensing of Environment, 50, 221–230.

    Article  Google Scholar 

  • Olsson H. (1995). Reflectance calibration of thematic mapper data for forest change detection. International Journal of Remote Sensing, 16,81–96.

    Article  Google Scholar 

  • Pellikka, P. (2001). Application of vertical skyward wide-angle photography and airborne video data for phonological studies of beech forests in the German Alps. International Journal of Remote Sensing, 22,2675–2700.

    Article  Google Scholar 

  • Quegan S., Le Toan, T., & Yu, J. J. (2000). Multitemporal ERS SAR analysis applied to forest mapping. IEEE Transactions on Geoscience and Remote Sensing, 38,741–753.

    Article  Google Scholar 

  • Qi Y., & Gong, P. (1996). Metabolic and phenological response of vegetation to temperature gradient: evidence derived from AVHRR data. Geographic Information Sciences, 2, 64–72.

    Google Scholar 

  • Radeloff, V. C, Mladenoff, D. J., & Boyce, M. S. (2000). Effects of interacting disturbances on landscape patterns: budworm defoliation and salvage logging. Ecological Applications, 10,233–247.

    Article  Google Scholar 

  • Remmel, T. K., & Perera, A. H. (2001). Fire mapping in a northern boreal forest: assessing AVHRR/NDVI methods of change detection. Forest Ecology and Management, 152, 119–129.

    Article  Google Scholar 

  • Richards, J. A., & Jia, X. (1999). Remote Sensing Digital Image Analysis. Springer, Berlin.

    Google Scholar 

  • Rigina O., Baklanov, A., & Hagner, O. (1999). Monitoring of forest damages in the Kola Peninsula, Northern Russia due to smelting industry. Science of the Total Environment, 229,147–163.

    Article  Google Scholar 

  • Rignot, E. J. M., & Vanzyl, J. J. (1993). Change detection techniques for ERS-1 SAR data. IEEE Transactions on Geoscience and Remote Sensing, 31, 1039–1046.

    Article  Google Scholar 

  • Royle, D. D., & Lathrop, R. G., (1997). Monitoring hemlock forest health in New Jersey using Landsat TM data and change detection techniques. Forest Science, 42,327–335.

    Google Scholar 

  • Sheng, Y., Gong, P., & Biging, G. S. (2001). Model-based conifer crown surface reconstruction from high-resolution aerial images. Photogrammetric Engineering and Remote Sensing, 67, 957–965.

    Google Scholar 

  • Silapaswan, C. S., Verbyla, D. L., & McGuire, A. D. (2001). Land cover change on the Seward Peninsula: The use of remote sensing to evaluate the potential influences of climate warming on historical vegetation dynamics. Canadian Journal of Remote Sensing, 27, 542–554.

    Google Scholar 

  • Singh, A. (1989). Digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing, 10, 989–1003.

    Article  Google Scholar 

  • Smits, P. C, & Annoni, A. (2000). Toward specification-driven change detection. IEEE Transactions on Geoscience and Remote Sensing, 38, 1484–1488.

    Article  Google Scholar 

  • Smits, P. C, & Myers, W. L. (2000). Echelon approach to characterize and understand spatial structures of change in multitemporal remote sensing imagery. IEEE Transactions on Geoscience and Remote Sensing, 38, 2299–2309.

    Article  Google Scholar 

  • Sohl, T. L. (1999). Change Analysis in the United Arab Emirates: An Investigation of techniques, Photogrammetric Engineering and Remote Sensing, 65, 475–484.

    Google Scholar 

  • Song, C, Woodcock, C. E., Seto, K., Lenney, M., & Macomber, S. (2001). Classification and change detection using landsat TM data: when and how to correct atmospheric effects? Remote Sensing of Environment, 75, 230–244.

    Article  Google Scholar 

  • Sun, G. Q., & Ranson, K. J., (2000). Modeling lidar returns from forest canopies. IEEE Transactions On Geoscience and Remote Sensing, 38, 2617–2626

    Article  Google Scholar 

  • Tokola, T., Lofman, S., & Erkkila, A. (1999). Relative calibration of multitemporal Landsat data for forest cover change detection. Remote Sensing of Environment, 68, 1–11.

    Article  Google Scholar 

  • Townshend, J. R. G., Justice, C. O., Gurney, C, & McManus, J. (1992). The impact of misregistration on change detection. IEEE Transactions on Geoscience and Remote Sensing, 30,1054–1060.

    Article  Google Scholar 

  • Varjo, J., & Folving, S. (1997). Monitoring of forest changes using unsupervised methods: a case study from boreal forest on mineral soils. Scandinavian Journal of Forest Research, 12,362–369.

    Article  Google Scholar 

  • Verbyla, D. L., & Boles, S. H. (2000). Bias in land cover change estimates due to misregistration. International Journal of Remote Sensing, 3553–3560.

    Google Scholar 

  • Yuan, D., Elvidge C. D., & Lunetta, R. S. (1998). Survey of multispectral methods for land cover change analysis. Lunetta R. S. & Elvidge C. D. (Eds.). Remote Sensing Change Detection, Environmental Monitoring Methods and Applications, 21–39. Ann Arbor Press. Chelsea, Michigan.

    Google Scholar 

  • Zhan, X, Defries R., & Townshend, J. R. G., et al. (2000). The 250 m global land cover change product from the Moderate Resolution Imaging Spectroradiometer of NASA’s Earth Observing System. International Journal of Remote Sensing, 21, 1433–1460.

    Article  Google Scholar 

  • Zheng, D. L., Wallin, D. O., & Hao, Z. Q. (1997). Rates and patterns of landscape change between 1972 and 1988 in the Changbai Mountain area of China and North Korea. Landscape Ecology, 12,241–254.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer Science+Business Media New York

About this chapter

Cite this chapter

Gong, P., Xu, B. (2003). Remote Sensing of Forests Over Time. In: Wulder, M.A., Franklin, S.E. (eds) Remote Sensing of Forest Environments. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0306-4_11

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-0306-4_11

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5014-9

  • Online ISBN: 978-1-4615-0306-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics