The Effectiveness of a UAV-Based LiDAR Survey to Develop Digital Terrain Models and Topographic Texture Analyses

Author:

Bartmiński Piotr1ORCID,Siłuch Marcin1,Kociuba Waldemar1ORCID

Affiliation:

1. Institute of Earth and Environmental Sciences, Maria Curie-Skłodowska University in Lublin, 20-031 Lublin, Poland

Abstract

This study presents a comparison of data acquired from three LiDAR sensors from different manufacturers, i.e., Yellow Scan Mapper (YSM), AlphaAir 450 Airborne LiDAR System CHC Navigation (CHC) and DJI Zenmuse L1 (L1). The same area was surveyed with laser sensors mounted on the DIJ Matrice 300 RTK UAV platform. In order to compare the data, a diverse test area located in the north-western part of the Lublin Province in eastern Poland was selected. The test area was a gully system with high vegetation cover. In order to compare the UAV information, LiDAR reference data were used, which were collected within the ISOK project (acquired for the whole area of Poland). In order to examine the differentiation of the acquired data, both classified point clouds and DTM products calculated on the basis of point clouds acquired from individual sensors were compared. The analyses showed that the largest average height differences between terrain models calculated from point clouds were recorded between the CHC sensor and the base data, exceeding 2.5 m. The smallest differences were recorded between the L1 sensor and ISOK data—RMSE was 0.31 m. The use of UAVs to acquire very high resolution data can only be used locally and must be subject to very stringent landing site preparation procedures, as well as data processing in DTM and its derivatives.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference60 articles.

1. Chirici, D.G., and Gianinetto, M. (2019). Trends in Earth Observation: Earth Observation Advancements in a Changing World, Associazione Italiana di Telerilevamento.

2. De Jong, S.M., and van der Meer, F.D. (2004). Remote Sensing Image Analysis: Including the Spatial Domain, Kluwer Academic.

3. Sensing Biodiversity;Turner;Science,2014

4. A Novel Automatic Method for the Fusion of ALS and TLS LiDAR Data for Robust Assessment of Tree Crown Structure;Paris;IEEE Trans. Geosci. Remote Sens.,2017

5. Gaussian Decomposition and Calibration of a Novel Small-Footprint Full-Waveform Digitising Airborne Laser Scanner;Wagner;ISPRS J. Photogramm. Remote Sens.,2006

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