@Article{ShinzatoShiCooTomGas:2017:InArIn,
author = "Shinzato, Emily Tsiemi and Shimabukuro, Yosio Edemir and Coops,
Nicholas C. and Tompalski, Piotr and Gasparoto, Esthevan A. G.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {University of British
Columbia} and {University of British Columbia} and {Universidade
de S{\~a}o Paulo (USP)}",
title = "Integrating area-based and individual tree detection approaches
for estimating tree volume in plantation inventory using aerial
image and airborne laser scanning data",
journal = "Iforest Biogeosciences and Forestry",
year = "2017",
volume = "10",
pages = "296--302",
month = "Feb.",
keywords = "orest Inventory, Airborne Laser Scanning, Treetop Detection,
Eucalyptus Plantation, Area-based Approach, LiDAR.",
abstract = "Remote sensing has been increasingly used to assist forest
inventory. Airborne Laser Scanning (ALS) systems can accurately
estimate tree height in forests, and are being combined with more
traditional optical images that provide further details about the
horizontal structure of forests. To predict forest attributes two
main techniques are applied to process ALS data: the Area Based
Approach (ABA), and the Individual Tree Detection (ITD). The first
part of this study was focused on the effectiveness of integrating
ALS data and aerial imagery to estimate the wood volume in
Eucalyptus urograndis plantations using the ABA approach. To this
aim, we analyzed three different approaches: (1) using only ALS
points cloud metrics (RMSE = 6.84%); (2) using only the variables
derived from aerial images (RMSE = 8.45%); and (3) the integration
of both 1 and 2 (RMSE = 5.23%), which underestimated the true
volume by 2.98%. To estimate individual tree volumes we first
detected individual trees and corrected the density estimate for
detecting mean difference, with an error of 0.37 trees per hectare
and RMSE of 12.68%. Next, we downscaled the total volume
prediction to single tree level. Our approach showed a better
result of the overall volume in comparison with the traditional
forest inventory. There is a remarkable advantage in using the
Individual Tree Detection approach, as it allows for a spatial
representation of the number of trees sampled, as well as their
volume per unit area - an important metric in the management of
forest resources.",
doi = "10.3832/ifor1880-009",
url = "http://dx.doi.org/10.3832/ifor1880-009",
issn = "1971-7458",
language = "en",
targetfile = "shinzato_integrating.pdf",
urlaccessdate = "27 abr. 2024"
}