Vote for your favorite mineral in #MinCup25! - Carpathite vs. Tugtupite
Battle of mineralogical oddities as organic mineral #carpathite battles against vs #tugtupite, a mineral that looks like reindeer blood!
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

Liu, Lingling, Zhang, Xiaoyang, Yu, Yunyue, Guo, Wei (2017) Real-time and short-term predictions of spring phenology in North America from VIIRS data. Remote Sensing of Environment, 194. 89-99 doi:10.1016/j.rse.2017.03.009

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleReal-time and short-term predictions of spring phenology in North America from VIIRS data
JournalRemote Sensing of Environment
AuthorsLiu, LinglingAuthor
Zhang, XiaoyangAuthor
Yu, YunyueAuthor
Guo, WeiAuthor
Year2017 (June)Volume194
PublisherElsevier BV
DOIdoi:10.1016/j.rse.2017.03.009Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9442045Long-form Identifiermindat:1:5:9442045:6
GUID0
Full ReferenceLiu, Lingling, Zhang, Xiaoyang, Yu, Yunyue, Guo, Wei (2017) Real-time and short-term predictions of spring phenology in North America from VIIRS data. Remote Sensing of Environment, 194. 89-99 doi:10.1016/j.rse.2017.03.009
Plain TextLiu, Lingling, Zhang, Xiaoyang, Yu, Yunyue, Guo, Wei (2017) Real-time and short-term predictions of spring phenology in North America from VIIRS data. Remote Sensing of Environment, 194. 89-99 doi:10.1016/j.rse.2017.03.009
In(n.d.) Remote Sensing of Environment Vol. 194. Elsevier BV

See Also

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

Liu, Lingling, Zhang, Xiaoyang, Yu, Yunyue, Gao, Feng, Yang, Zhengwei (2018) Real-Time Monitoring of Crop Phenology in the Midwestern United States Using VIIRS Observations. Remote Sensing, 10 (10). doi:10.3390/rs10101540
Zhang, Xiaoyang, Wang, Jianmin, Gao, Feng, Liu, Yan, Schaaf, Crystal, Friedl, Mark, Yu, Yunyue, Jayavelu, Senthilnath, Gray, Joshua, Liu, Lingling, Yan, Dong, Henebry, Geoffrey M. (2017) Exploration of scaling effects on coarse resolution land surface phenology. Remote Sensing of Environment, 190. 318-330 doi:10.1016/j.rse.2017.01.001
Moon, Minkyu, Zhang, Xiaoyang, Henebry, Geoffrey M., Liu, Lingling, Gray, Josh M., Melaas, Eli K., Friedl, Mark A. (2019) Long-term continuity in land surface phenology measurements: A comparative assessment of the MODIS land cover dynamics and VIIRS land surface phenology products. Remote Sensing of Environment, 226. 74-92 doi:10.1016/j.rse.2019.03.034
Zhang, Xiaoyang, Liu, Lingling, Liu, Yan, Jayavelu, Senthilnath, Wang, Jianmin, Moon, Minkyu, Henebry, Geoffrey M., Friedl, Mark A., Schaaf, Crystal B. (2018) Generation and evaluation of the VIIRS land surface phenology product. Remote Sensing of Environment, 216. 212-229 doi:10.1016/j.rse.2018.06.047
Gao, Shuai; Zhang, Xiaoyang; Shen, Yu; Tran, Khuong H.; Ye, Yongchang; Liu, Yuxia (2025) Improvement of land surface phenology monitoring by fusing VIIRS observations with GOES-16/17 ABI time series. Remote Sensing of Environment, 326. doi:10.1016/j.rse.2025.114803
White, Michael A., Nemani, Ramakrishna R. (2006) Real-time monitoring and short-term forecasting of land surface phenology. Remote Sensing of Environment, 104 (1). 43-49 doi:10.1016/j.rse.2006.04.014
Yan, Dong, Zhang, Xiaoyang, Yu, Yunyue, Guo, Wei (2017) Characterizing Land Cover Impacts on the Responses of Land Surface Phenology to the Rainy Season in the Congo Basin. Remote Sensing, 9 (5). doi:10.3390/rs9050461
Peng, Dailiang, Wang, Yan, Xian, George, Huete, Alfredo R., Huang, Wenjiang, Shen, Miaogen, Wang, Fumin, Yu, Le, Liu, Liangyun, Xie, Qiaoyun, Liu, Lingling, Zhang, Xiaoyang (2021) Investigation of land surface phenology detections in shrublands using multiple scale satellite data. Remote Sensing of Environment, 252. 112133pp. doi:10.1016/j.rse.2020.112133
Zhang, Xiaoyang (2015) Reconstruction of a complete global time series of daily vegetation index trajectory from long-term AVHRR data. Remote Sensing of Environment, 156. 457-472 doi:10.1016/j.rse.2014.10.012
Zhang, Xiaoyang, Liu, Lingling, Yan, Dong (2017) Comparisons of global land surface seasonality and phenology derived from AVHRR, MODIS, and VIIRS data. Journal of Geophysical Research: Biogeosciences, 122. 1506-1525 doi:10.1002/2017jg003811
Yan, Dong, Zhang, Xiaoyang, Yu, Yunyue, Guo, Wei (2016) A Comparison of Tropical Rainforest Phenology Retrieved From Geostationary (SEVIRI) and Polar-Orbiting (MODIS) Sensors Across the Congo Basin. IEEE Transactions on Geoscience and Remote Sensing, 54 (8) 4867-4881 doi:10.1109/tgrs.2016.2552462
 
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 Β© 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 20, 2025 17:16:52
Go to top of page