Feasibility of Low-Cost LiDAR Scanner Implementation in Forest Sampling Techniques

Author:

Brach Michał1ORCID,Tracz Wiktor1,Krok Grzegorz2,Gąsior Jakub1

Affiliation:

1. Department of Geomatics and Land Management, Institute of Forest Sciences, Warsaw University of Life Sciences, 159 Nowoursynowska St., 02-776 Warsaw, Poland

2. Department of Geomatics, Forest Research Institute, 3 Braci Leśnej Street, 05-090 Sękocin Stary, Poland

Abstract

Despite the growing impact of remote sensing technology in forest inventories globally, there is a continuous need for ground measurements on sample plots. Even though the newest volume assessment methodology requires fewer sample plots, the accuracy of ground-recorded data influences the final accuracy of forest stand modeling. Therefore, effective and economically justified tools are in the continuous interest of foresters. In the presented research, a consumer-grade light detection and ranging (LiDAR) sensor mounted on iPad was used for forest inventory sample plot data collection—including tree location and diameter breast height. In contrast to other similar research, feasibility and user-friendliness were also documented and emphasized. The study was conducted in 63 real sample plots used for the inventory of Polish forests. In total, 776 trees were scanned in 3 types of forest stands: pine, birch, and oak. The root mean square error was 0.28 m for tree locations and 0.06 m for diameter breast height. Various additional analyses were performed to describe the usage of an iPad in tree inventories. It was contended that low-cost LiDAR scanners might be successfully used in real forest conditions and can be considered a reliable and easy-to-implement tool in forest inventory measurements.

Publisher

MDPI AG

Subject

Forestry

Reference63 articles.

1. FAO’s Approach to Support National Forest Assessments for Country Capacity Building;Saket;Backgr. Pap.,2002

2. Scheaffer, R.L., Mendenhall, W.I., Ott, R.L., and Gerow, K.G. (2012). Elementary Survey Sampling, Cengage Learning.

3. Extending Forest Inventories and Monitoring Programmes Using Remote Sensing: A Review;McInerney;IrIsh For.,2011

4. Vidal, C., Alberdi, I.A., Hernández Mateo, L., and Redmond, J.J. (2016). National Forest Inventories, Springer International Publishing.

5. Estimation of Stand Volume of Conifer Forest: A Bayesian Approach Based on Satellite-based Estimate and Forest Register Data;Lee;For. Sci. Technol.,2010

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3