Next Article in Journal
High-Resolution Remote Sensing Data Classification over Urban Areas Using Random Forest Ensemble and Fully Connected Conditional Random Field
Previous Article in Journal
Wicked Water Points: The Quest for an Error Free National Water Point Database
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessCommunication
ISPRS Int. J. Geo-Inf. 2017, 6(8), 243; doi:10.3390/ijgi6080243

Nationwide Point Cloud—The Future Topographic Core Data

1
School of Engineering, Aalto University, P.O. Box 14100, FI-00076 Aalto, Finland
2
Finnish Geospatial Research Institute FGI, Geodeetinrinne 2, FI-02430 Masala, Finland
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 7 June 2017 / Revised: 7 July 2017 / Accepted: 3 August 2017 / Published: 8 August 2017
View Full-Text   |   Download PDF [6595 KB, uploaded 8 August 2017]   |  

Abstract

Topographic databases maintained by national mapping agencies are currently the most common nationwide data sets in geo-information. The application of laser scanning as source data for surveying is increasing. Along with this development, several analysis methods that utilize dense point clouds have been introduced. We present the concept of producing a dense nationwide point cloud, produced from multiple sensors and containing multispectral information, as the national core data for geo-information. Geo-information products, such as digital terrain and elevation models and 3D building models, are produced automatically from these data. We outline the data acquisition, processing, and application of the point cloud. As a national data set, a dense multispectral point cloud could produce significant cost savings via improved automation in mapping and a reduction of overlapping surveying efforts. View Full-Text
Keywords: point cloud; multispectral; laser scanning; mobile laser scanning; data integration point cloud; multispectral; laser scanning; mobile laser scanning; data integration
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Virtanen, J.-P.; Kukko, A.; Kaartinen, H.; Jaakkola, A.; Turppa, T.; Hyyppä, H.; Hyyppä, J. Nationwide Point Cloud—The Future Topographic Core Data. ISPRS Int. J. Geo-Inf. 2017, 6, 243.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top