<div class="csl-bib-body">
<div class="csl-entry">Farella, E. M., Remondino, F., Cahalane, C., Qin, R., Loghin, A.-M., Di Tullio, M., Haala, N., & Mills, J. (2023). Geometric processing of very high-resolution satellite imagery: quality assessment for 3d mapping needs. In B. Hejmanowska, D. Iwaszczuk, K. Bakuła, & F. Remondino (Eds.), <i>2nd GEOBENCH Workshop on Evaluation and BENCHmarking of Sensors, Systems and GEOspatial Data in Photogrammetry and Remote Sensing</i> (pp. 47–54). ISPRS. https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-47-2023</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/190730
-
dc.description.abstract
In recent decades, the geospatial domain has benefitted from technological advances in sensors, methodologies, and processing tools to expand capabilities in mapping applications. Airborne techniques (LiDAR and aerial photogrammetry) generally provide most of the data used for this purpose. However, despite the relevant accuracy of these technologies and the high spatial resolution of airborne data, updates are not sufficiently regular due to significant flight costs and logistics. New possibilities to fill this information gap have emerged with the advent of Very High Resolution (VHR) optical satellite images in the early 2000s. In addition to the high temporal resolution of the cost-effective datasets and their sub-meter geometric resolutions, the synoptic coverage is an unprecedented opportunity for mapping remote areas, multi-temporal analyses, updating datasets and disaster management. For all these reasons, VHR satellite imagery is clearly a relevant study for National Mapping and Cadastral Agencies (NMCAs). This work, supported by EuroSDR, summarises a series of experimental analyses carried out over diverse landscapes to explore the potential of VHR imagery for large-scale mapping.
en
dc.language.iso
en
-
dc.relation.ispartofseries
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
-
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
-
dc.subject
high-resolution satellite images
en
dc.subject
optical
en
dc.subject
3D processing
en
dc.subject
DSM
en
dc.subject
NMCAs
en
dc.subject
mapping
en
dc.title
Geometric processing of very high-resolution satellite imagery: quality assessment for 3d mapping needs
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.contributor.affiliation
Fondazione Bruno Kessler, Italy
-
dc.contributor.affiliation
Fondazione Bruno Kessler, Italy
-
dc.contributor.affiliation
National University of Ireland, Maynooth, Ireland
-
dc.contributor.affiliation
The Ohio State University, United States of America (the)
-
dc.contributor.affiliation
GMatics, Italy
-
dc.contributor.affiliation
University of Stuttgart, Germany
-
dc.contributor.affiliation
Newcastle University, United Kingdom of Great Britain and Northern Ireland (the)