Highly discrete mapping of the growing season time frames and time dynamics

I. Rykin, A. Shagnieva, E. Panidi, V. Tsepelev

Результат исследований: Научные публикации в периодических изданияхстатья в журнале по материалам конференциирецензирование

2 Цитирования (Scopus)


Growing season time frames can be estimated and mapped using the vegetation indexes mapping and analysis. This approach brings significant benefit consisted in the ability of detailed (highly discrete in the meaning of spatial resolution) mapping of spatial differences in growing season stage and length. In comparison with interpolation of ground air temperature (applied when using temperature to detect growing seasons), real spatial resolution raises to kilometers per pixel and higher, while nodes of ground observation network can be spaced by thousands of kilometers in some regions. Our ongoing study is devoted to design a processing chain for mapping of growing season time frames basing on vegetation indexes data with close-to-one-day time resolution. We used MOD09GA dataset as an initial data. Data processing was implemented in Google Earth Engine big geospatial data platform.

Язык оригиналаанглийский
Страницы (с-по)357-361
Число страниц5
ЖурналInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Номер выпуска3/W8
СостояниеОпубликовано - 20 авг 2019
Событие2019 GeoInformation for Disaster Management, Gi4DM 2019 - Prague, Чехия
Продолжительность: 3 сен 20196 сен 2019

Предметные области Scopus

  • Информационные системы
  • География, планирование и развитие


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