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.
|Journal||International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives|
|Publication status||Published - 20 Aug 2019|
|Event||2019 GeoInformation for Disaster Management, Gi4DM 2019 - Prague|
Duration: 3 Sep 2019 → 6 Sep 2019
Scopus subject areas
- Information Systems
- Geography, Planning and Development