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A comparison of FIA plot data derived from image pixels and image objectsAuthor(s): Charles E. Werstak
Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 440-447.
Publication Series: Paper (invited, offered, keynote)
Station: Northern Research Station
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DescriptionThe use of Forest Inventory and Analysis (FIA) plot data for producing continuous and thematic maps of forest attributes (e.g., forest type, canopy cover, volume, and biomass) at the regional level from satellite imagery can be challenging due to differences in scale. Specifically, classification errors that may result from assumptions made between what the field data represent and what the corresponding spectral information of the image pixels depict. This investigation aimed at determining whether image objects derived from Landsat TM imagery can be used as an alternative to a 3 by 3 neighborhood of pixels for characterizing forested FIA plots. Results showed strong positive correlations between the different scales of base map units across all of the image derivatives. Further examination of the data using the Wilcoxon signed rank test for paired samples indicated that in most cases, finer level image objects were a better representation of the 3 by 3 neighborhood of pixels than coarser ones and some image derivatives performed better than others. The same tests were applied to a subset of plots dominated by quaking aspen (Populus tremuloides Michx.) with similar results. Information gained may provide further insight into object based segmentation and classification methods using FIA plot data, satellite imagery, and ancillary geospatial data.
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CitationWerstak, Charles E., Jr. 2012. A comparison of FIA plot data derived from image pixels and image objects. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 440-447.
Keywordsstatistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring
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