Title | Remote sensing of grassland-shrubland vegetation water content in the shortwave domain |
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Author | Davidson, A; Wang, S ; Wilmshurst, J |
Source | International Journal of Applied Earth Observation and Geoinformation vol. 8, no. 4, 2006 p. 225-236, https://doi.org/10.1016/j.jag.2005.10.002 |
Year | 2006 |
Alt Series | Natural Resources Canada, Contribution Series 20181400 |
Publisher | Elsevier BV |
Document | serial |
Lang. | English |
Media | paper; on-line; digital |
File format | pdf |
Subjects | geophysics; remote sensing |
Program | Canada Centre for Remote Sensing Divsion |
Released | 2006 12 01 |
Abstract | This study compares the ability of spectral approaches operating in the shortwave optical domain to predict absolute and relative vegetation water content (AWC and RWC, respectively) across northern
prairie grassland-shrubland. We collected vegetation water content and spectral radiometer data over plots of comparable ground resolution (0.5 m) at seven field sites in the Canadian mixed grass prairie in June 2004. We then aggregated observations
to scale these data "up" to an observational scale consistent with that of Landsat-TM satellite imagery (30 m). This allowed us to assess abilities of three spectral approaches to predict AWC and RWC at both observational scales. These approaches
were: individual vegetation indices, a combination of spectral bands and a combination of spectral derivatives. Our results showed that (a) the band-combination approach provides the most accurate and precise estimates of AWC and RWC at both 0.5 and
30 m sampling resolutions; (b) the combination of bands providing the greatest predictive abilities are those that emphasize the contrast in reflectance between the NIR and SWIR spectral regions; (c) the band-combination approach predicts AWC with
much greater accuracy and precision than RWC and (d) the predictive ability of the band-combination approach decreases only slightly when plot-level data are aggregated to a 30 m sampling resolution. These results are generally consistent with the
results of other studies and with theory. While our results suggest that simple spectral methods (e.g. linear band-combinations or indices) are good predictors of AWC over grazed and ungrazed grassland-shrubland landscapes at plot- and Landsat
spatial resolutions, they are less encouraging for the estimation of RWC. Despite their good predictive abilities, the temporal and geographical portabilities of the spectral approaches for estimating AWC must be further assessed before they can be
considered reliable and robust predictive tools. Thus, the further testing of these techniques over larger geographical extents is required |
GEOSCAN ID | 311754 |
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