Vote for your favorite mineral in #MinCup25! - Dioptase vs. Wavellite
It's a green, green world for kiwi #wavellite vs desert emerald #dioptase.
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Halabisky, Meghan, Miller, Dan, Stewart, Anthony J., Yahnke, Amy, Lorigan, Daniel, Brasel, Tate, Moskal, Ludmila Monika (2023) The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators. Hydrology and Earth System Sciences, 27 (20) 3687-3699 doi:10.5194/hess-27-3687-2023

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleThe Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators
JournalHydrology and Earth System Sciences
AuthorsHalabisky, MeghanAuthor
Miller, DanAuthor
Stewart, Anthony J.Author
Yahnke, AmyAuthor
Lorigan, DanielAuthor
Brasel, TateAuthor
Moskal, Ludmila MonikaAuthor
Year2023 (October 20)Volume27
Issue20
PublisherCopernicus GmbH
DOIdoi:10.5194/hess-27-3687-2023Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID16909770Long-form Identifiermindat:1:5:16909770:9
GUID0
Full ReferenceHalabisky, Meghan, Miller, Dan, Stewart, Anthony J., Yahnke, Amy, Lorigan, Daniel, Brasel, Tate, Moskal, Ludmila Monika (2023) The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators. Hydrology and Earth System Sciences, 27 (20) 3687-3699 doi:10.5194/hess-27-3687-2023
Plain TextHalabisky, Meghan, Miller, Dan, Stewart, Anthony J., Yahnke, Amy, Lorigan, Daniel, Brasel, Tate, Moskal, Ludmila Monika (2023) The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators. Hydrology and Earth System Sciences, 27 (20) 3687-3699 doi:10.5194/hess-27-3687-2023
In(2023, October) Hydrology and Earth System Sciences Vol. 27 (20) Copernicus GmbH

See Also

These are possibly similar items as determined by title/reference text matching only.

Stewart, Anthony J., Halabisky, Meghan, Babcock, Chad, Butman, David E., D’Amore, David V., Moskal, L. Monika (2024) Revealing the hidden carbon in forested wetland soils. Nature Communications, 15 (1) doi:10.1038/s41467-024-44888-x
Endo, Yukio, Halabisky, Meghan, Moskal, L. Monika, Koshimura, Shunichi (2020) Wetland Surface Water Detection from Multipath SAR Images Using Gaussian Process-Based Temporal Interpolation. Remote Sensing, 12 (11). doi:10.3390/rs12111756
Halabisky, Meghan, Moskal, L. Monika, Gillespie, Alan, Hannam, Michael (2016) Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984–2011). Remote Sensing of Environment, 177. 171-183 doi:10.1016/j.rse.2016.02.040
Elrashidy, Mennatullah T., Ireson, Andrew M., Razavi, Saman (2023) On the optimal level of complexity for the representation of groundwater-dependent wetland systems in land surface models. Hydrology and Earth System Sciences, 27 (24) 4595-4608 doi:10.5194/hess-27-4595-2023
Roman Quintero, Daniel Camilo, Marino, Pasquale, Santonastaso, Giovanni Francesco, Greco, Roberto (2023) Understanding hydrologic controls of sloping soil response to precipitation through machine learning analysis applied to synthetic data. Hydrology and Earth System Sciences, 27 (22) 4151-4172 doi:10.5194/hess-27-4151-2023
Aguilar, Cristina, Montanari, Alberto, Polo, María-José (2017) Real-time updating of the flood frequency distribution through data assimilation. Hydrology and Earth System Sciences, 21 (7) 3687-3700 doi:10.5194/hess-21-3687-2017
Kennedy, M. P., Murphy, K. J. (2004) Indicators of nitrate in wetland surface and soil-waters: interactions of vegetation and environmental factors. Hydrology and Earth System Sciences, 8 (4) 663-672 doi:10.5194/hess-8-663-2004
Fisher, J., Acreman, M. C. (2004) Wetland nutrient removal: a review of the evidence. Hydrology and Earth System Sciences, 8 (4) 673-685 doi:10.5194/hess-8-673-2004
Di Ciacca, Antoine, Wilson, Scott, Kang, Jasmine, Wöhling, Thomas (2023) Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning. Hydrology and Earth System Sciences, 27 (3) 703-722 doi:10.5194/hess-27-703-2023
Michailovsky, Claire I., Coerver, Bert, Mul, Marloes, Jewitt, Graham (2023) Investigating sources of variability in closing the terrestrial water balance with remote sensing. Hydrology and Earth System Sciences, 27 (23) 4335-4354 doi:10.5194/hess-27-4335-2023
Teferi, E., Uhlenbrook, S., Bewket, W., Wenninger, J., Simane, B. (2010) The use of remote sensing to quantify wetland loss in the Choke Mountain range, Upper Blue Nile basin, Ethiopia. Hydrology and Earth System Sciences, 14 (12) 2415-2428 doi:10.5194/hess-14-2415-2010
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 10, 2025 18:57:30
Go to top of page