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Open AccessArticle

Need for Pre-Harvest Clearing of Understory Vegetation Determined by Airborne Laser Scanning

1
School of Forest Sciences, University of Eastern Finland, Yliopistokatu 7, P.O. Box 111, FI-80101 Joensuu, Finland
2
Savonia University of Applied Sciences, Opiskelijankatu 3, FI-78210 Varkaus, Finland
*
Author to whom correspondence should be addressed.
Forests 2020, 11(3), 294; https://doi.org/10.3390/f11030294
Received: 6 February 2020 / Revised: 2 March 2020 / Accepted: 3 March 2020 / Published: 6 March 2020
(This article belongs to the Section Forest Inventory, Quantitative Methods and Remote Sensing)
The methodology presented here can assist in evaluating the need for pre-harvest clearing. In the long term, similar approaches may help with managing electronic standing sales and enhance the operational environment of roundwood e-marketplaces. In cut-to-length harvesting, pre-harvest clearing is needed when the understory vegetation hinders the visibility of the stems to be harvested. It can facilitate the work of the harvester operators and thereby enhance the productivity and quality of the harvesting operation. Information about where pre-harvest clearing is required is often not available, however, or else it has to be collected during time-consuming field visits. We report here on the development and evaluation of airborne laser scanning (ALS)-based models for estimating the need for pre-harvest clearing. The reference data consisted of 99 circular field sample plots that were photographed and in which stems with diameters at breast height from one to seven centimeters were measured. An online e-questionnaire survey responded to by 66 forest professionals classified the sample plots into five categories ranging from no need for pre-harvest clearing to compulsory pre-harvest clearing. A linear discriminant analysis was used to estimate the need for pre-harvest clearing with an accuracy of 63.6%, whereas a linear model-based method that predicted the understory stem density assessed the need with an accuracy of 64.6%. Use of this method could deliver information about the understory vegetation, offer guidelines for clearing the understory, and reduce the number of field visits before harvesting, thus reducing costs. View Full-Text
Keywords: pre-harvest clearing operations; harvesting productivity; understory trees; undergrowth vegetation; Light Detection and Ranging (LiDAR); operator’s visibility; remote sensing; geographic information system (GIS); linear discriminant analysis (LDA); linear model pre-harvest clearing operations; harvesting productivity; understory trees; undergrowth vegetation; Light Detection and Ranging (LiDAR); operator’s visibility; remote sensing; geographic information system (GIS); linear discriminant analysis (LDA); linear model
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Sanz, B.; Malinen, J.; Heiskanen, J.; Tokola, T. Need for Pre-Harvest Clearing of Understory Vegetation Determined by Airborne Laser Scanning. Forests 2020, 11, 294.

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