New satellite-based maps of the growing season north of 50°N

Stein Rune Karlsen; Kjell Arild Høgda; Anne Tolvanen; Bernt Johansen; Arve Elvebakk

doi:10.1117/12.872970

3 November 2010 New satellite-based maps of the growing season north of 50°N

Stein Rune Karlsen, Kjell Arild Høgda, Anne Tolvanen, Bernt Johansen, Arve Elvebakk

Proceedings Volume 7840, Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality; 784023 (2010) https://doi.org/10.1117/12.872970
Event: The Sixth International Symposium on Digital Earth, 2009, Beijing, China

Abstract

In this study we present new satellite-based maps of the growing season of northern areas. The maps show trends and mean date in onset and length of the growing season at different scales north of 50° N. For all the circumpolar area we use the GIMMS-NDVI satellite dataset for the 1982 to 2006 period, and for the Nordic countries we used the MODISNDVI satellite data for the 2000 to 2007 period. The circumpolar maps are not as accurate as the one covering the Nordic countries, this due to lack of ancillary environmental geo-data available that can be included in the mapping process. In particular this is a problem for the Russian part of the circumpolar north. The resulting growing season maps are useful in a broad range of ecological and climatic changes studies. Changes in the timing of the growing season are sensitive bio-indicators of climate change of northern areas, and these changes crucially affects primary industries, such as agriculture, animal husbandry and forestry, as well as the population dynamics of wild mammals and birds. The onset of growing season maps is also useful to improve pollen forecasts, and the maps can be used to improve the global change models.

Citation Download Citation

Stein Rune Karlsen, Kjell Arild Høgda, Anne Tolvanen, Bernt Johansen, and Arve Elvebakk "New satellite-based maps of the growing season north of 50°N", Proc. SPIE 7840, Sixth International Symposium on Digital Earth: Models, Algorithms, and Virtual Reality, 784023 (3 November 2010); https://doi.org/10.1117/12.872970

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