Results 111 to 120 of about 2,677 (203)

A reduced latency regional gap-filling method for SMAP using random forest regression. [PDF]

iScience, 2023
Wang X, Lü H, Crow WT, Corzo G, Zhu Y, Su J, Zheng J, Gou Q.   +7 more
europepmc   +1 more source

Long-Term Pan-Arctic Evaluation of a Sentinel-1 SAR Sea Ice Extent Product and Insights into Model Integration

Remote Sensing
Reliable sea ice extent (SIE) information is essential for Arctic navigation, climate research, and resource exploration. Synthetic Aperture Radar (SAR), with its all-weather, high-resolution capabilities, is well suited for SIE extraction.
Haotian Yuan, Qing Guo, Yongzheng Ren, Han Fu, Xiao-Ming Li   +4 more
doaj   +1 more source

Multi-Source Soil Moisture Data Fusion Based on Spherical Cap Harmonic Analysis and Helmert Variance Component Estimation in the Western U.S. [PDF]

Sensors (Basel), 2023
Chen H, Chen P, Wang R, Qiu L, Tang F, Xiong M.   +5 more
europepmc   +1 more source

Expanding NASA's Land, Atmosphere Near Real-Time Capability for EOS (LANCE) [PDF]

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made ...
Braun, Jessica, Davidson, Carol C., Davies, Diane, Ding, Feng, Durbin, Phil B, Ederer, Gregory, Fu, Gary, Gumley, Liam, Harrison, Sherry, Masuoka, Ed, Michael, Karen, Olsina, Otmar, Pollicelli, Frederick S., Prins, Elaine, Protack, Steve, Rinsland, Pamela Livingstone, Schmaltz, Jeffrey, Slayback, Daniel A., Wong, Min Minnie, Ye, Gang, Ziskin, Daniel   +20 more
core   +1 more source

Interannual change of sea-ice motion in the Arctic [PDF]

, 2016
GRENE北極気候変動研究事業 第1回特別セミナー : 北極海航路の利用実現に向けて 日時　2014年11月17日（月） 場所　東京海洋大学品川キャンパス ...

core   +1 more source

Assimilation of ACSPO VIIRS and REMSS AMSR2 into OSTIA

, 2016
Presentation given at the 17th GHRSST science meeting (XVII), Washington DC, USA, June 6 - 10, 2016.
openaire   +1 more source

Assessing the Sensitivity of Snow Depth Retrieval Algorithms to Inter-Sensor Brightness Temperature Differences

Remote Sensing
Passive microwave remote sensing provides indispensable observations for constructing long-term snow depth records, which are critical for climatology, hydrology, and operational applications.
Guangjin Liu, Lingmei Jiang, Huizhen Cui, Jinmei Pan, Jianwei Yang, Min Wu   +5 more
doaj   +1 more source

Data Assimilation Enhancements to Air Force Weathers Land Information System [PDF]

The United States Air Force (USAF) has a proud and storied tradition of enabling significant advancements in the area of characterizing and modeling land state information.
, , , , , Allen, Mark, Arsenault, Kristi, Baker, Samantha, Barker, Dale, Best, Martin, Bindlish, Rajat, Blank, Lindsay, Bovis, Keir, Boyd, Douglas, Cetola, Jeffrey, Charlton-Perez, Cristina, Chen, Sue, Craig, Robert, Creighton, Glenn, DeLuca, Cecelia, Dharssi, Imtiaz, Dunlap, Rocky, Elliott, Wayne, Eylander, John, Farrar, Michael, Floyd, Jack, Geiger, James V, Gomez, Breogan, Harrold, Michelle, Hertneky, Tracy, Horner, Michael, Hummel, Corey, Jacob, Jossy, Keane, James, Kemp, Eric M, Kuchera, Evan, Kumar, Sujay V, Kumar, Vinod, Kwon, Yonghwan, Lewiston, Ted, Martinelli, Jason, McDonald, Patrick, McMillen, John, Mocko, David, Moore, Stuart, Nance, Louisa, Navari, Mahdi, O’Neill, Peggy, Pankiewicz, George, Park, SeiYoung, Peters-Lidard, Christa, Puskar, Michael, Renshaw, Richard, Rentschler, Scott, Rheingrover, Scott, Ritz, Richard, Rosen, Daniel, Rosenberg, Robert, Rugg, Steven, Sayfi, Elias, Smith, Jason, Steinle, Peter, Uddstrom, Michael, Vuyowich, Carrie, Wang, Shugong, Wang, Zhuo, Wegiel, Jerry, Win-Gildenmeister, Minna, Wright, Nathan, Yoon, Yeosang   +69 more
core   +1 more source

Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling

, 2017
Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight.
AE Hoerl, D Buckingham, J Bongard, J Dong, J Dozier, J Martinec, J Rees, JR Koza, K Krawiec, M Hollander, M Schmidt, M Tedesco, MD Schmidt, R Tibshirani, TH Painter, WR Tobler   +15 more
core   +1 more source

Application of a Machine Learning Algorithm in Generating an Evapotranspiration Data Product From Coupled Thermal Infrared and Microwave Satellite Observations. [PDF]

Front Big Data, 2022
Fang L, Zhan X, Kalluri S, Yu P, Hain C, Anderson M, Laszlo I.   +6 more
europepmc   +1 more source