All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.
Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.
Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.
Original Submission Date Received: .
- Journals
-
- Active Journals
- Find a Journal
- Proceedings Series
-
- Topics
- Information
-
- For Authors
- For Reviewers
- For Editors
- For Librarians
- For Publishers
- For Societies
- For Conference Organizers
- Open Access Policy
- Institutional Open Access Program
- Special Issues Guidelines
- Editorial Process
- Research and Publication Ethics
- Article Processing Charges
- Awards
- Testimonials
-
- Author Services
- Initiatives
-
- Sciforum
- MDPI Books
- Preprints.org
- Scilit
- SciProfiles
- Encyclopedia
- JAMS
- Proceedings Series
-
- About
-
- Overview
- Contact
- Careers
- News
- Press
- Blog
-
Sign In / Sign Up Submit
Journals
Land
Volume 13
Issue 6
10.3390/land13060895
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu
Article Menu
- Academic Editors
- Subscribe SciFeed
- Related Info Link
- More by Authors Links
- Table of Contents
announcement Help format_quote Cite
thumb_up ... Endorse textsms ... Comment
Need Help?
Support
Find support for a specific problem in the support section of our website.
Get Support
Feedback
Please let us know what you think of our products and services.
Give Feedback
Information
Visit our dedicated information section to learn more about MDPI.
Get Information
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Open AccessArticle
by Xinyue Liu SciProfiles Scilit Preprints.org Google Scholar Yanhui Shan SciProfiles Scilit Preprints.org Google Scholar Gang Ai SciProfiles Scilit Preprints.org Google Scholar Zhengfeng Du SciProfiles Scilit Preprints.org Google Scholar Anran Shen SciProfiles Scilit Preprints.org Google Scholar Ningfei Lei SciProfiles Scilit Preprints.org Google Scholar 
Xinyue LiuYanhui ShanGang AiZhengfeng DuAnran ShenNingfei Lei
1
School of Information Engineering, China University of Geosciences (Beijing), Haidian, Beijing 100083, China
2
Beijing Municipal Commission of Planning and Natural Resources, Changping, Beijing 102200, China
*
Authors to whom correspondence should be addressed.
Land 2024, 13(6), 895; https://doi.org/10.3390/land13060895 (registeringDOI)
Submission received: 29 May 2024 / Revised: 12 June 2024 / Accepted: 18 June 2024 / Published: 20 June 2024
(This article belongs to the Special Issue GeoAI for Land Use Observations, Analysis and Forecasting)
Abstract
The Yunshui Cave in Shangfang Mountain, Beijing, is a famous high-altitude karst cave in northern China. As the third scientific survey of Yunshui Cave in history, this is the first time to use the latest LiDAR technology to carry out a related detection survey. Traditional cave measurement methods are limited by natural conditions and make it difficult to reach the destination. Traditional methods mainly rely on experience and obtain data with strong subjectivity, making it difficult to conduct quantitative research and obtain reproducible results in the current information era. Applying LiDAR technology to cave measurement can obtain comprehensive and accurate digital measurement results within the same survey time and reveal many richer and more accurate features of Yunshui Cave. The obtained digital measurement results can be used for 3D modeling as well as provide a large amount of accurate basic data and preliminary materials for subsequent geological, environmental, and archaeological investigation and analysis, as well as cultural and tourism resource development. The rapid geological survey of Shangfang Mountain Yunshui Cave using LiDAR technology shows that LiDAR cave geological survey technology can achieve real-time collection of centimeter-level accuracy and generate billions of points of cloud data, greatly improving survey efficiency and accuracy. At the same time, digital survey results can be obtained. Through modeling and GIS technology, all on-site survey details can be easily moved back to the laboratory for real-scene reproduction, network sharing, and dissemination. This study provides a foundation for future explorations of the Yunshui cave and highlights the potential for LiDAR techniques to enhance our understanding of complex geological structures such as caves.
Keywords: LiDAR (light detection and ranging); karst cave; GIS; surveying and mapping; geologic survey
Share and Cite
MDPI and ACS Style
Liu, X.; Shan, Y.; Ai, G.; Du, Z.; Shen, A.; Lei, N. A Scientific Investigation of the Shangfang Mountain Yunshui Cave in Beijing Based on LiDAR Technology. Land 2024, 13, 895. https://doi.org/10.3390/land13060895
AMA Style
Liu X, Shan Y, Ai G, Du Z, Shen A, Lei N. A Scientific Investigation of the Shangfang Mountain Yunshui Cave in Beijing Based on LiDAR Technology. Land. 2024; 13(6):895. https://doi.org/10.3390/land13060895
Chicago/Turabian Style
Liu, Xinyue, Yanhui Shan, Gang Ai, Zhengfeng Du, Anran Shen, and Ningfei Lei. 2024. "A Scientific Investigation of the Shangfang Mountain Yunshui Cave in Beijing Based on LiDAR Technology" Land 13, no. 6: 895. https://doi.org/10.3390/land13060895
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Article Metrics
Cite
Export citation file: BibTeX | EndNote | RIS
MDPI and ACS Style
Liu, X.; Shan, Y.; Ai, G.; Du, Z.; Shen, A.; Lei, N. A Scientific Investigation of the Shangfang Mountain Yunshui Cave in Beijing Based on LiDAR Technology. Land 2024, 13, 895. https://doi.org/10.3390/land13060895
AMA Style
Liu X, Shan Y, Ai G, Du Z, Shen A, Lei N. A Scientific Investigation of the Shangfang Mountain Yunshui Cave in Beijing Based on LiDAR Technology. Land. 2024; 13(6):895. https://doi.org/10.3390/land13060895
Chicago/Turabian Style
Liu, Xinyue, Yanhui Shan, Gang Ai, Zhengfeng Du, Anran Shen, and Ningfei Lei. 2024. "A Scientific Investigation of the Shangfang Mountain Yunshui Cave in Beijing Based on LiDAR Technology" Land 13, no. 6: 895. https://doi.org/10.3390/land13060895
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Land, EISSN 2073-445X, Published by MDPI
RSS Content Alert
Further Information
Article Processing Charges Pay an Invoice Open Access Policy Contact MDPI Jobs at MDPI
Guidelines
For Authors For Reviewers For Editors For Librarians For Publishers For Societies For Conference Organizers
MDPI Initiatives
Sciforum MDPI Books Preprints.org Scilit SciProfiles Encyclopedia JAMS Proceedings Series
© 1996-2024 MDPI (Basel, Switzerland) unless otherwise stated
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Terms and Conditions Privacy Policy
