Toward Satellite-Based Estimation of Growing Season Framing Dates in Conditions of Unstable Weather

  • Evgeny PanidiEmail author
  • Ivan Rykin
  • Giovanni Nico
  • Valery Tsepelev
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


This paper described an experiment of developing a complex technique for satellite imagery time series processing when estimating spatial distribution of framing (or changing) calendar dates of the growing seasons. Particularly, we reflected on allocation of growing season framing dates in conditions of unstable weather. As surface air temperature may fluctuate in many cases around bordering values during some days or weeks, the allocation of stable crossing of temperature through the control values (that marks time frames of growing seasons) is a fundamental problem in the case of ground observations. We compared some results of the growing season frames allocation based on ground data observations of the temperature (needed for the verification and calibration purposes), and the estimation results made relying on the data of remotely observed Normalized Difference Water Index (NDWI).


Growing seasons Ground meteorological observations Remote sensing data NDWI 



The MOD9A1 V006 datasets were retrieved from the online LP DAAC2Disk download manager, courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota (

The MODIS Level 1B datasets were acquired from the Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC), located in the Goddard Space Flight Center in Greenbelt, Maryland (

Ground observations data were retrieved from Waisori Web interface, courtesy of the RIHMI-WDC of Roshydromet, Veselov V.M., Pribylskaya I.R., Mirzeabasov O.A. (


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Evgeny Panidi
    • 1
    Email author
  • Ivan Rykin
    • 1
  • Giovanni Nico
    • 1
    • 2
  • Valery Tsepelev
    • 3
  1. 1.Saint Petersburg State UniversitySt. PetersburgRussia
  2. 2.Consiglio Nazionale delle Ricerche, Istituto per le Applicazioni del CalcoloBariItaly
  3. 3.Russian State Hydrometeorological UniversitySt. PetersburgRussia

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