Supplemental material
GIScience & Remote Sensing
Volume 60, 2023 - Issue 1
Open access
1,689
Views
2
CrossRef citations to date
0
Altmetric
Research Article
Enhancing the predictive performance of remote sensing for ecological variables of tidal flats using encoded features from a deep learning model
Logambal Madhuananda Department of Physical Geography, Utrecht University, Utrecht, NetherlandsCorrespondence[email protected]
https://orcid.org/0000-0002-1534-5234View further author information
, https://orcid.org/0000-0002-1534-5234View further author information
Catharina J. M. Philipparta Department of Physical Geography, Utrecht University, Utrecht, Netherlands;b Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research, Texel, Netherlandshttps://orcid.org/0000-0001-7238-9113View further author information
, Jiong Wanga Department of Physical Geography, Utrecht University, Utrecht, Netherlands;c Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, NetherlandsView further author information
, Wiebe Nijlanda Department of Physical Geography, Utrecht University, Utrecht, Netherlandshttps://orcid.org/0000-0002-2665-0947View further author information
, Steven M. de Jonga Department of Physical Geography, Utrecht University, Utrecht, Netherlandshttps://orcid.org/0000-0002-1586-9601View further author information
, Allert I. Bijleveldb Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research, Texel, Netherlandshttps://orcid.org/0000-0002-3159-8944View further author information
& Elisabeth A. Addinka Department of Physical Geography, Utrecht University, Utrecht, Netherlandshttps://orcid.org/0000-0002-0919-6498View further author information
show all
Article: 2163048
|
Received 15 Jun 2022, Accepted 21 Dec 2022, Published online: 03 Jan 2023
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.