Automatic tree stem delineation supporting forest inventory

Matthieu Molinier; Kaj Andersson; Tuomas Häme

doi:10.1109/IGARSS.2011.6129458

Automatic tree stem delineation supporting forest inventory

Matthieu Molinier, Kaj Andersson, Tuomas Häme

BA16 Data-driven solutions

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

The aim of this study was to develop an automatic procedure to detect tree stems in cell phone images. If the stems can be detected, the central projection geometry of the images makes it possible to apply the so called relascope principle to predict the basal area of stems per hectare. The basal area is closely correlated with tree biomass. Images were acquired in an area where detailed tree-wise information is available. The tree stem delineation methods were based on color and edge information to tackle the challenges of occlusions and varying illumination conditions. Geolocalised images can be used as in-situ reference data for remote sensing data analysis to provide wall-to-wall estimates. (10 refs.)

Original language	English
Title of host publication	2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	4465-4468
ISBN (Print)	978-1-58537-193-8
DOIs	https://doi.org/10.1109/IGARSS.2011.6129458
Publication status	Published - 2011
MoE publication type	A4 Article in a conference publication

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title = "Automatic tree stem delineation supporting forest inventory",

abstract = "The aim of this study was to develop an automatic procedure to detect tree stems in cell phone images. If the stems can be detected, the central projection geometry of the images makes it possible to apply the so called relascope principle to predict the basal area of stems per hectare. The basal area is closely correlated with tree biomass. Images were acquired in an area where detailed tree-wise information is available. The tree stem delineation methods were based on color and edge information to tackle the challenges of occlusions and varying illumination conditions. Geolocalised images can be used as in-situ reference data for remote sensing data analysis to provide wall-to-wall estimates. (10 refs.)",

author = "Matthieu Molinier and Kaj Andersson and Tuomas H{\"a}me",

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year = "2011",

doi = "10.1109/IGARSS.2011.6129458",

language = "English",

isbn = "978-1-58537-193-8",

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Automatic tree stem delineation supporting forest inventory. / Molinier, Matthieu; Andersson, Kaj; Häme, Tuomas.

2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011. IEEE Institute of Electrical and Electronic Engineers, 2011. p. 4465-4468.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Andersson, Kaj

AU - Häme, Tuomas

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N2 - The aim of this study was to develop an automatic procedure to detect tree stems in cell phone images. If the stems can be detected, the central projection geometry of the images makes it possible to apply the so called relascope principle to predict the basal area of stems per hectare. The basal area is closely correlated with tree biomass. Images were acquired in an area where detailed tree-wise information is available. The tree stem delineation methods were based on color and edge information to tackle the challenges of occlusions and varying illumination conditions. Geolocalised images can be used as in-situ reference data for remote sensing data analysis to provide wall-to-wall estimates. (10 refs.)

AB - The aim of this study was to develop an automatic procedure to detect tree stems in cell phone images. If the stems can be detected, the central projection geometry of the images makes it possible to apply the so called relascope principle to predict the basal area of stems per hectare. The basal area is closely correlated with tree biomass. Images were acquired in an area where detailed tree-wise information is available. The tree stem delineation methods were based on color and edge information to tackle the challenges of occlusions and varying illumination conditions. Geolocalised images can be used as in-situ reference data for remote sensing data analysis to provide wall-to-wall estimates. (10 refs.)

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DO - 10.1109/IGARSS.2011.6129458

M3 - Conference article in proceedings

SN - 978-1-58537-193-8

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BT - 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011

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