Eddy Covariance Flux Networks to Remote Sensing: Connecting Flux and Remote Sensing Communities via Time- and Space-Synchronized Data Sampling — Australian Meteorological and Oceanographic Society
  1. Schedule
  2. 10(ii). Land surface processes from local to global scales
  3. Eddy Covariance Flux Networks to Remote Sensing: Connecting Flux and Remote Sensing Communities via Time- and Space-Synchronized Data Sampling

Eddy Covariance Flux Networks to Remote Sensing: Connecting Flux and Remote Sensing Communities via Time- and Space-Synchronized Data Sampling (#147)

G. Burba 1 , A. Burkart 2 , J. Gamon 3 , K. Guan 4 , T. Julitta 2 , G. Pastorello 5 , K. Sakowska 6
  1. LI-COR Biosciences / Global Water For Food Institute / University of Nebraska, LINCOLN, NE, United States
  2. JB Hyperspectral Devices UG, Düsseldorf, Germany
  3. Center for Advanced Land Management Information Technologies, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
  4. Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
  5. AmeriFlux Management Project, Computational Research Division, , Lawrence Berkeley National Laboratory, Berkeley, California, USA
  6. Biometeorology Group, Institute of Ecology University of Innsbruck, Innsbruck, Austria

Hundreds of eddy covariance flux stations are presently operating as standalone projects and as parts of regional networks. Many have weather and soil data to help clean, analyze and interpret the flux data. However, most do not have optical proximal sensor measurements, do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and cannot be easily used for validation of remotely sensed products, ecosystem modeling, or upscaling from the field to regional levels.

In 2016-2020, new tools to collect, process, analyze and share time-synchronized flux data from multiple flux stations were developed and deployed globally. Originally designed to automate site and data management and streamline flux data analysis, these tools allow relatively easy matching of tower data with remote sensing data.

Additionally, current flux stations can be augmented with advanced ground-based optical sensors and can use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers and other optical systems.

Over 100 of new flux stations already operational globally can be readily used for the proposed workflow. Over 500 active traditional flux stations can be updated to synchronize their data with remote sensing measurements.

This presentation will show how the new tools are used by major networks, and describe how this approach can be utilized for matching remote sensing and tower data to aid in ground truthing, improve scientific interactions, and promote joint grant writing and other forms of collaboration between the flux and remote sensing communities.

#amos2020