| Title | A method for detecting large-scale forest cover change using coarse spatial resolution imagery |
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| Author | Fraser, R H ;
Abuelgasim, A; Latifovic, R |
| Source | Remote Sensing of Environment vol. 95, issue 4, 2005 p. 414-427, https://doi.org/10.1016/j.rse.2004.12.014 |
| Image |  |
| Year | 2005 |
| Alt Series | Earth Sciences Sector, Contribution Series 2004407 |
| Publisher | Elsevier BV |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Province | Quebec |
| NTS | 12K; 12L |
| Area | Havre St-Pierre; Aquanish |
| Lat/Long WENS | -64.0000 -60.0000 51.0000 50.0000 |
| Subjects | geophysics; Nature and Environment; vegetation; vegetation history; remote sensing; satellite imagery; mapping techniques; computer mapping |
| Illustrations | equations; tables; location maps; Landsat images |
| Program | Reducing Canada's Vulnerability to Climate Change
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| Released | 2005 04 01 |
| Abstract | Many large countries, including Canada, rely on earth observation as a practical and cost-effective means of monitoring their vast inland ecosystems. A potentially efficient approach is one that
detects vegetation changes over a hierarchy of spatial scales ranging from coarse to fine. This paper presents a Change Screening Analysis Technique (Change-SAT) designed as a coarse filter to identify the location and timing of large (> 5-10 km2)
forest cover changes caused by anthropogenic and natural disturbances at an annual, continental scale. The method uses change metrics derived from 1 km multi-temporal SPOT VEGETATION and NOAA AVHRR imagery (reflectance, temperature, and texture
information) and ancillary spatial variables (proximity to active fires, roads, and forest tenures) in combination with logistic regression and decision tree classifiers. Major forest changes of interest include wildfires, insect defoliation, forest
harvesting, and flooding. Change-SAT was tested for 1998-2000 using an independent sample of change and no-change sites over Canada. Overall accuracy was 94% and commission error, especially critical for large-area change applications, was less than
1%. Regions identified as having major or widespread changes could be targeted for more detailed investigation and mapping using field visits, aerial survey, or fine resolution EO methods, such as those being applied under Canadian monitoring
programs. This multi-resolution approach could be used as part of a forest monitoring system to report on carbon stocks and forest stewardship. |
| GEOSCAN ID | 220265 |
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