We do our best to achieve our vision, “A sustainable world where ecological information is available and accessible to anyone.” We incorporate a set of different tools such as in-situ observations, remote sensing, ecosystem models across a range of different scales from leaf to the globe. Field observation forms the foundation of the lab research activities. We use the field data to evaluate satellite remote sensing data, improve ecosystem models, advance our understandings of ecological processes. BESS is the platform that integrates all lab research works to achieve our vision. Overall research scheme follows.


Below figure shows our overall strategy to achieve our vision. A series of satellite remote sensing serves as forcing to BESS. To calibrate/validate remote sensing data, we monitor ground based spectral information from a super site. As super site is expensive, we build inexpensive spectral sensing network too. Those super site and spectral sensing network are used to calibrate satellite data and evaluate/improve BESS. We are adding new modules into BESS for general applications to the important issues that humanity face.



Near-surface remote sensing

  • To better monitor structure, function and metabolism of ecosystems  at multiple scales, automatically in real time, we develop, test, improve Smart Surface Sensing System (4S) which include Raspberry micro computer, LED-sensors,  RaspberryPi camera, Arduino and Wifi.  LED-sensors basically measure spectral reflectances, gap fractions, and fPAR. RaspberryPi camera measures gap fractions.


  • We are measuring spectral reflectance from a set of instruments that include sun-induced chlorophyll fluorescence at O2A band (QEPro, Ocean Optics Inc.), hyperspectral reflectance in VIS-NIR domain (Jaz, Ocean Optics Inc.), broad-band spectral reflectance from LED-sensors, hyperspectral imager (Pika, RESONON Inc.) and hyperspectroradiometer over a full shortwave domain (ASD-FieldSpec, ASD Inc.).
  • We are enthusiastic in developing new sensors or new algorithms in data processing and analysis. Some results are published as below.
    • Hwang, Y., Ryu, Y.*, Kimm, H., Jiang, C., Lang, M., Macfarlane, C., Sonnentag, O. (2016) Correction for light scattering combined with sub-pixel classification improves estimation of gap fraction from digital cover photography. Agricultural and Forest Meteorology 222, 32-44 [PDF] (2016.05)
    • Song, Y., & Ryu, Y.* (2015). Seasonal changes in vertical canopy structure in a temperate broadleaved forest in Korea. Ecological Research, 30, 821-831 [PDF] (2015. 9)
    • Ryu, Y.*, Lee, G., Jeon, S., Song, Y., & Kimm, H. (2014). Monitoring multi-layer canopy spring phenology of temperate deciduous and evergreen forests using low-cost spectral sensors. Remote Sensing of Environment, 149, 227-238 [PDF] (2014. 6)
    • Kobayashi, H., Ryu, Y.*, Baldocchi, D.D., Welles, J.M., & Norman, J.M. (2013). On the correct estimation of gap fraction: how to remove scattered radiation in the gap fraction measurements? Agricultural and Forest Meteorology, 174-175: 170-183 [PDF] (2013. 6)
    • Ryu, Y.*, Verfaillie, J., Macfarlane, C., Kobayashi, H., Sonnentag, O., Vargas, R., Ma, S., & Baldocchi, D.D. (2012). Continuous observation of tree leaf area index at ecosystem scale using upward-pointing digital cameras. Remote Sensing of Environment, 126, 116-125 [PDF] (2012. 11)
    • Ryu, Y.*,Baldocchi, D.D., Verfaillie, J., Ma, S., Falk, M., Ruiz-Mercado, Il, Hehn, T., Sonnentag, O. (2010). Testing the performance of a novel spectral reflectance sensor, built with light emitting diodes (LEDs), to monitor ecosystem metabolism, structure and function. Agricultural and Forest Meteorology. 150, 1597-1606[PDF] (2010. 12)

Eddy flux tower

  • We contribute to KoFlux, AsiaFlux and FLUXNET through taking the lead in a paddy rice flux tower site in Cherwon (CRK) which equips with CO2, H2O and CH4 flux instruments. This site is supported by National Center for Agro Meteorology (NCAM).
  • We deploy a series of near-surface sensors to automatically monitor sun-induced chlorophyll fluorescence, vegetation indices, leaf area index and fPAR.
  • We used this data to evaluate and improve a satellite-based rice growth model, BESS-Rice.


Urban ecology

  • We  investigate carbon, water, and energy cycles in urban ecosystems. We are eager to apply our theoretical, experimental expertise to park and open space planning and management.
  • First attempt started from an urban park, Seoul Forest Park funded by NRF-Junior. We measured soil organic stocks, soil respiration, leaf area index and photosynthetic parameters to understand carbon stocks and fluxes in the park.
  • We extended our urban ecology work into tree water use grown in impervious surfaces, urban heat mitigation by roof top materials.
  • Some results were published as follows:
    • Lee, S., Ryu, Y.*, Jiang, C. (2015) Urban heat mitigation by roof surface materials during the East Asian summer monsoon. Environmental Research Letters 10, 124012 [PDF] (2015.12)
    • Kimm, H., Ryu, Y.* (2015) Seasonal variations in photosynthetic parameters and leaf area index in an urban park. Urban Forestry & Urban Greening 14, 1059-1067 [PDF] (2015.12)
    • Bae, J., & Ryu, Y.* (2015). Land use and land cover changes explain spatial and temporal variations of the soil organic carbon stocks in a constructed urban park. Landscape and Urban Planning, 136, 57-67 [PDF] (2015. 4)

Breathing Earth System Simulator (BESS)

  • BESS is the integrator of all research activities in our lab. It is MODIS-derived biophysical model that couples atmospheric and canopy radiative transfers, leaf energy balance, transpiration, canopy conductance and photosynthesis.
    • Ryu Y*, Baldocchi DD, Kobayashi H, van Ingen C, LiJ, Black TA, Beringer J, van Gorsel E, Knohl A, Law BE & Roupsard O (2011) Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales. Global Biogeochemical Cycles, 25, GB4017, doi:10.1029/2011GB004053 [PDF] (2011. 12)
    • Song, Y., Ryu, Y.*, & Jeon, S. (2014). Interannual variability of regional evapotranspiration under precipitation extremes: A case study of the Youngsan River basin in Korea. Journal of Hydrology, 519, 3531-3540[PDF] (2014. 11)
  • It was originally developed at UC Berkeley while Youngryel was PhD student. Since then, BESS has been upgraded. We are incorporating new modules into BESS such as BESS-Rice and BESS-SiF. We plan to add BESS-Tundra, BESS-Urban in the future.
  • BESS offers gross primary production, evaporation, solar radiation, canopy conductance maps at 1 km, 8-daily interval, globally between 2000 and 2015 (will be extended whenever MODIS data is updated). The maps are open to public through HERE.
  • Below global monthly animations were made from Chongya’s recent manuscript.



Several invited lectures

Keynote speak in Global Vegetation Monitoring and Modelling, Avigon, France 2014

Invited speak in Microsoft eScience + IEEE International Conference on e-Science in Beijing, China, 2013