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Open AccessArticle

Modeling Stand Height, Volume, and Biomass from Very High Spatial Resolution Satellite Imagery and Samples of Airborne LiDAR

Canadian Forest service, Pacific Forestry Centre, Natural Resources Canada, Victoria, BC V8Z 1M5, Canada
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Remote Sens. 2013, 5(5), 2308-2326; https://doi.org/10.3390/rs5052308
Received: 14 March 2013 / Revised: 27 April 2013 / Accepted: 29 April 2013 / Published: 14 May 2013
Plot-based sampling with ground measurements or photography is typically used to establish and maintain National Forest Inventories (NFI). The re-measurement phase of the Canadian NFI is an opportunity to develop novel methods for the estimation of forest attributes such as stand height, crown closure, volume, and aboveground biomass (AGB) from satellite, rather than, airborne imagery. Based on panchromatic Very High Spatial Resolution (VHSR) images and Light Detection and Ranging (LiDAR) data acquired in the Yukon Territory, Canada, we propose an approach for boreal forest stand attribute characterization. Stand and tree objects are delineated, followed by modeling of stand height, volume, and AGB using metrics derived from the stand and tree crown objects. The calibration and validation of the models are based on co-located LiDAR-derived estimates. A k-nearest neighbor approach provided the best accuracy for stand height estimation (R2 = 0.76, RMSE = 1.95 m). Linear regression models were the most efficient for estimating stand volume (R2 = 0.94, RMSE = 9.6 m3/ha) and AGB (R2 = 0.92, RMSE = 22.2 t/ha). This study was implemented for one Canadian ecozone and demonstrated the capacity of a methodology to produce forest inventory attributes with acceptable accuracies offering potential to be applied to other boreal regions. View Full-Text
Keywords: panchromatic; sample; LiDAR; boreal; forest; crown; modeling; height; volume; biomass; Landsat panchromatic; sample; LiDAR; boreal; forest; crown; modeling; height; volume; biomass; Landsat
MDPI and ACS Style

Mora, B.; Wulder, M.A.; White, J.C.; Hobart, G. Modeling Stand Height, Volume, and Biomass from Very High Spatial Resolution Satellite Imagery and Samples of Airborne LiDAR. Remote Sens. 2013, 5, 2308-2326.

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