Digital change detection in forest ecosystems with remote sensing imagery
- 1 April 1996
- journal article
- research article
- Published by Taylor & Francis in Remote Sensing Reviews
- Vol. 13 (3-4), 207-234
- https://doi.org/10.1080/02757259609532305
Abstract
The world's forest ecosystems are in a state of permanent flux at a variety of spatial and temporal scales. Monitoring techniques based on multispectral satellite‐acquired data have demonstrated potential as a means to detect, identify, and map changes in forest cover. This paper, which reviews the methods and the results of digital change detection primarily in temperate forest ecosystems, has two major components. First, the different perspectives from which the variability in the change event has been approached are summarized, and the appropriate choice of digital imagery acquisition dates and interval length for change detection are discussed. In the second part, preprocessing routines to establish a more direct linkage between digital remote sensing data and biophysical phenomena, and the actual change detection methods themselves are reviewed and critically assessed. A case study in temperate forests (north‐central U.S.A.) then serves as an illustration of how the different change detection phases discussed in this paper can be integrated into an efficient and successful monitoring technique. Lastly, new developments in digital change detection such as the use of radar imagery and knowledge‐based expert systems are highlighted.Keywords
This publication has 51 references indexed in Scilit:
- Classification methods on multispectral SPOT imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Change detection using the Gramm-Schmidt transformation applied to mapping forest mortalityRemote Sensing of Environment, 1994
- Fourier analysis of multi-temporal AVHRR data applied to a land cover classificationInternational Journal of Remote Sensing, 1994
- Monitoring vegetation changes in Al Madinah, Saudi Arabia, using Thematic Mapper dataInternational Journal of Remote Sensing, 1993
- Multispectral classification of Landsat-images using neural networksIEEE Transactions on Geoscience and Remote Sensing, 1992
- Change detection with synthetic aperture radarInternational Journal of Remote Sensing, 1992
- Neural Network Approaches Versus Statistical Methods In Classification Of Multisource Remote Sensing DataIEEE Transactions on Geoscience and Remote Sensing, 1990
- Determination of surface reflectance and estimates of atmospheric optical depth and single scattering albedo from Landsat Thematic Mapper dataInternational Journal of Remote Sensing, 1990
- An alternative simple approach to estimate atmospheric correction in multitemporal studiesInternational Journal of Remote Sensing, 1989
- Remote sensing of vegetation change near Inco's Sudbury mining complexesInternational Journal of Remote Sensing, 1987