Remote sensing and probabilistic sampling based forest...

G - Physics – 06 – K

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G06K 9/00 (2006.01) G06F 17/10 (2006.01) G06T 7/00 (2006.01)

Patent

CA 2656595

A remote sensing and probabilistic sampling based forest inventory method can correlate aerial data, such as LiDAR, CIR, and/or Hyperspectral data with actual sampled and measured ground data to facilitate obtainment, e.g., prediction, of a more accurate forest inventory. The resulting inventory can represent an empirical description of the height, DBH and species of every tree within the sample area. The use of probabilistic sampling methods can greatly improve the accuracy and reliability of the forest inventory.

La présente invention concerne une télédétection et un échantillonnage probabiliste, reposant sur un procédé permettant d'inventorier les forêts, qui peuvent corréler les données aériennes, telles LiDAR, CIR et/ou des données hyperspectrales avec des données de terrain échantillonnées et mesurées en vue de faciliter l'obtention, par exemple, ou la prévision d'un inventaire des forêts plus précis. L'inventaire ainsi obtenu peut correspondre à une description empirique de la hauteur, du diamètre à hauteur d'homme et de l'espèce de chaque arbre présent dans la zone d'échantillonnage. L'utilisation de procédés d'échantillonnage probabiliste permet d'accroître sensiblement la précision et la fiabilité de l'inventaire d'une forêt.

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