TU3.R2.1
SATELLITE-DRIVEN MACHINE LEARNING FRAMEWORK FOR SPATIO-TEMPORAL ALGAL BLOOM FORECASTING IN THE INDIAN EXCLUSIVE ECONOMIC ZONE
PUNYA P, RAMA RAO NIDAMANURI, Indian Institute of Space science and Technology
Session:
TU3.R2: Bloom Detection and Others Oral
Track:
Oceans
Location:
Northwest
Presentation Time:
Tuesday, 11 August, 13:45 - 14:00
Session Chair:
Charalambos Chrysostomou, Eratosthenes Center of Excellence
Presentation
Discussion
Resources
No resources available.
Session TU3.R2
TU3.R2.1: SATELLITE-DRIVEN MACHINE LEARNING FRAMEWORK FOR SPATIO-TEMPORAL ALGAL BLOOM FORECASTING IN THE INDIAN EXCLUSIVE ECONOMIC ZONE
PUNYA P, RAMA RAO NIDAMANURI, Indian Institute of Space science and Technology
TU3.R2.2: SURFACE CLUSTERING OF BIOARGO FLOATS DELINEATES THE VERTICAL STRUCTURE OF PHYTOPLANKTON IN THE ATLANTIC BASIN
Greg Silsbe, University of Maryland Center for Environmental Science; Ratnaksha Lele, University of Maryland Baltimore County; Victoria Coles, Xiaoxu Guo, University of Maryland Center for Environmental Science; Sai Vikas Amaraneni, University of Maryland Baltimore County; Sairah Malkin, University of Maryland Center for Environmental Science; Vandana Janeja, University of Maryland Baltimore County
TU3.R2.3: USING BIASES IN SCATTEROMETER DATA TO TRACK ASSOCIATED BIOLOGICAL SIGNALS OF BIOLUMINESCENT MILKY SEAS
Justin Hudson, Steven Miller, Colorado State University
TU3.R2.4: PHYSICS-GUIDED PROBABILISTIC RED TIDE DETECTION FOR GOCI-II
Jong Hyuk Lee, Seungil Baek, Sooyoon Koh, Pusan National university; Jae-Hyun Ahn, Korea Institute of Ocean Science and Technology, Republic of Korea; Wonkook Kim, Pusan National university
TU3.R2.5: Information Theory-Based Causal Analysis Applied to Ocean Satellite Data
Kazuki Kohyama, Kirara Kotani, Takashi Kobayashi, Helen Stewart, Rin Irie, Masaki Hisada, NTT, Inc.
Resources
No resources available.