Vote for your favorite mineral in #MinCup25! - Chrysotile vs. Pectolite
Two new minerals to launch this year's cup! Hazardous (but useful!) chrysotile faces off against stunning gem pectolite.
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

Diak, George R. (2017) Investigations of improvements to an operational GOES-satellite-data-based insolation system using pyranometer data from the U.S. Climate Reference Network (USCRN). Remote Sensing of Environment, 195. 79-95 doi:10.1016/j.rse.2017.04.002

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleInvestigations of improvements to an operational GOES-satellite-data-based insolation system using pyranometer data from the U.S. Climate Reference Network (USCRN)
JournalRemote Sensing of Environment
AuthorsDiak, George R.Author
Year2017 (June)Volume195
PublisherElsevier BV
DOIdoi:10.1016/j.rse.2017.04.002Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9442079Long-form Identifiermindat:1:5:9442079:3
GUID0
Full ReferenceDiak, George R. (2017) Investigations of improvements to an operational GOES-satellite-data-based insolation system using pyranometer data from the U.S. Climate Reference Network (USCRN). Remote Sensing of Environment, 195. 79-95 doi:10.1016/j.rse.2017.04.002
Plain TextDiak, George R. (2017) Investigations of improvements to an operational GOES-satellite-data-based insolation system using pyranometer data from the U.S. Climate Reference Network (USCRN). Remote Sensing of Environment, 195. 79-95 doi:10.1016/j.rse.2017.04.002
In(n.d.) Remote Sensing of Environment Vol. 195. Elsevier BV

See Also

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

Diak, George R., Gautier, Catherine (1983) Improvements to a Simple Physical Model for Estimating Insolation from GOES Data. Journal of Climate and Applied Meteorology, 22 (3). 505-508 doi:10.1175/1520-0450(1983)022<0505:itaspm>2.0.co;2
S. Ha, Wonsook, R. Diak, George, F. Krajewski, Witold (2020) Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa. Remote Sensing, 12 (14). doi:10.3390/rs12142337
Duan, Zheng, Bastiaanssen, W.G.M. (2013) Estimating water volume variations in lakes and reservoirs from four operational satellite altimetry databases and satellite imagery data. Remote Sensing of Environment, 134. 403-416 doi:10.1016/j.rse.2013.03.010
Röder, Achim, Kuemmerle, Tobias, Hill, Joachim (2005) Extension of retrospective datasets using multiple sensors. An approach to radiometric intercalibration of Landsat TM and MSS data. Remote Sensing of Environment, 95 (2). 195-210 doi:10.1016/j.rse.2004.12.008
Rivas, Raul, Caselles, Vicente (2004) A simplified equation to estimate spatial reference evaporation from remote sensing-based surface temperature and local meteorological data. Remote Sensing of Environment, 93 (1). 68-76 doi:10.1016/j.rse.2004.06.021
He, Jia, Liu, Zhizhao (2021) Water vapor retrieval from MERSI NIR channels of Fengyun-3B satellite using ground-based GPS data. Remote Sensing of Environment, 258. 112384pp. doi:10.1016/j.rse.2021.112384
XIAO, X (2004) Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data. Remote Sensing of Environment, 91 (2). 256-270 doi:10.1016/j.rse.2004.03.010
Kiran Chand, T.R., Badarinath, K.V.S., Krishna Prasad, V., Murthy, M.S.R., Elvidge, Chris D., Tuttle, Benjamin T. (2006) Monitoring forest fires over the Indian region using Defense Meteorological Satellite Program-Operational Linescan System nighttime satellite data. Remote Sensing of Environment, 103 (2). 165-178 doi:10.1016/j.rse.2006.03.010
Jung, Sihun, Im, Jungho, Han, Daehyeon (2025) PARAN: A novel physics-assisted reconstruction adversarial network using geostationary satellite data to reconstruct hourly sea surface temperatures. Remote Sensing of Environment, 323. doi:10.1016/j.rse.2025.114749
Zhang, Junzhe, Okin, Gregory S., Zhou, Bo (2019) Assimilating optical satellite remote sensing images and field data to predict surface indicators in the Western U.S.: Assessing error in satellite predictions based on large geographical datasets with the use of machine learning. Remote Sensing of Environment, 233. 111382pp. doi:10.1016/j.rse.2019.111382
Zakeri, Fatemeh, Mariethoz, Gregoire (2024) Synthesizing long-term satellite imagery consistent with climate data: Application to daily snow cover. Remote Sensing of Environment, 300. 113877 doi:10.1016/j.rse.2023.113877
 
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 1, 2025 10:38:28
Go to top of page