Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables

Sakari Tuominen (Corresponding Author), Andras Balazs, Heikki Saari, Ilkkka Pölönen, Janne Sarkeala, Risto Viitala

Research output: Contribution to journalArticleScientificpeer-review

Abstract

In this paper we examine the feasibility of data from unmanned aerial vehicle (UAV)-borne aerial imagery in stand-level forest inventory. As airborne sensor platforms, UAVs offer advantages cost and flexibility over traditional manned aircraft in forest remote sensing applications in small areas, but they lack range and endurance in larger areas. On the other hand, advances in the processing of digital stereo photography make it possible to produce three-dimensional (3D) forest canopy data on the basis of images acquired using simple lightweight digital camera sensors. In this study, an aerial image orthomosaic and 3D photogrammetric canopy height data were derived from the images acquired by a UAV-borne camera sensor. Laser-based digital terrain model was applied for estimating ground elevation. Features extracted from orthoimages and 3D canopy height data were used to estimate forest variables of sample plots. K-nearest neighbor method was used in the estimation, and a genetic algorithm was applied for selecting an appropriate set of features for the estimation task. Among the selected features, 3D canopy features were given the greatest weight in the estimation supplemented by textural image features. Spectral aerial photograph features were given very low weight in the selected feature set. The accuracy of the forest estimates based on a combination of photogrammetric 3D data and orthoimagery from UAV-borne aerial imaging was at a similar level to those based on airborne laser scanning data and aerial imagery acquired using purpose-built aerial camera from the same study area.
Original languageEnglish
Article number1348
Number of pages19
JournalSilva Fennica
Volume49
Issue number5
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

Fingerprint

cameras
sensors (equipment)
imagery
canopy
orthophotography
aircraft
photography
forest inventory
forest canopy
photographs
lasers
remote sensing
laser
image analysis
sensor
airborne sensor
digital terrain model
aerial photograph
genetic algorithm
unmanned aerial vehicles

Keywords

  • forest inventory
  • unmanned aerial system
  • UAV
  • aerial imagery
  • photogrammetric surface model
  • canopy height model

Cite this

Tuominen, Sakari ; Balazs, Andras ; Saari, Heikki ; Pölönen, Ilkkka ; Sarkeala, Janne ; Viitala, Risto. / Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables. In: Silva Fennica. 2015 ; Vol. 49, No. 5.
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abstract = "In this paper we examine the feasibility of data from unmanned aerial vehicle (UAV)-borne aerial imagery in stand-level forest inventory. As airborne sensor platforms, UAVs offer advantages cost and flexibility over traditional manned aircraft in forest remote sensing applications in small areas, but they lack range and endurance in larger areas. On the other hand, advances in the processing of digital stereo photography make it possible to produce three-dimensional (3D) forest canopy data on the basis of images acquired using simple lightweight digital camera sensors. In this study, an aerial image orthomosaic and 3D photogrammetric canopy height data were derived from the images acquired by a UAV-borne camera sensor. Laser-based digital terrain model was applied for estimating ground elevation. Features extracted from orthoimages and 3D canopy height data were used to estimate forest variables of sample plots. K-nearest neighbor method was used in the estimation, and a genetic algorithm was applied for selecting an appropriate set of features for the estimation task. Among the selected features, 3D canopy features were given the greatest weight in the estimation supplemented by textural image features. Spectral aerial photograph features were given very low weight in the selected feature set. The accuracy of the forest estimates based on a combination of photogrammetric 3D data and orthoimagery from UAV-borne aerial imaging was at a similar level to those based on airborne laser scanning data and aerial imagery acquired using purpose-built aerial camera from the same study area.",
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Unmanned aerial system imagery and photogrammetric canopy height data in area-based estimation of forest variables. / Tuominen, Sakari (Corresponding Author); Balazs, Andras; Saari, Heikki; Pölönen, Ilkkka; Sarkeala, Janne; Viitala, Risto.

In: Silva Fennica, Vol. 49, No. 5, 1348, 2015.

Research output: Contribution to journalArticleScientificpeer-review

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