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Remote sensing estimates and measures of uncertainty for forest variables at different aggregation levels

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Listed:
  • F. Mauro
  • I. Molina
  • A. García‐Abril
  • R. Valbuena
  • E. Ayuga‐Téllez

Abstract

No abstract is available for this item.

Suggested Citation

  • F. Mauro & I. Molina & A. García‐Abril & R. Valbuena & E. Ayuga‐Téllez, 2016. "Remote sensing estimates and measures of uncertainty for forest variables at different aggregation levels," Environmetrics, John Wiley & Sons, Ltd., vol. 27(4), pages 225-238, June.
    • Handle: RePEc:wly:envmet:v:27:y:2016:i:4:p:225-238
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    Cited by:

    1. Steen Magnussen & Johannes Breidenbach, 2020. "Retrieval of among-stand variances from one observation per stand," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 66(4), pages 133-149.
    2. Steen MAGNUSSEN, 2018. "An estimation strategy to protect against over-estimating precision in a LiDAR-based prediction of a stand mean," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 64(12), pages 497-505.
    3. Francisco Mauro & Vicente J Monleon & Hailemariam Temesgen & Kevin R Ford, 2017. "Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-14, December.

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