The two papers present recent developments in the project.
Erlandsson et al. (2022) presents an AI technique to accurately assess lichen biomass using satellites.
Wang et al. (2022) present changes in surface temperature in two global datasets, highlighting the high warming rate in Arctic permafrost regions.
See more information in the webinar announcement:
www.mn.uio.no/geo/english/research/projects/emerald/events/webinar/webinar-okt-2022.html
Read the papers:
Rasmus Erlandsson, Jarle W. Bjerke, Eirik A. Finne, Ranga B. Myneni, Shilong Piao, Xuhui Wang, Tarmo Virtanen, Aleksi Räsänen, Timo Kumpula, Tiina H.M. Kolari, Teemu Tahvanainen, Hans Tømmervik. (2022) An artificial intelligence approach to remotely assess pale lichen biomass. Remote Sensing of Environment 280, 113201. https://doi.org/10.1016/j.rse.2022.113201
You-Ren Wang, Dag O. Hessen, Bjørn H. Samset, Frode Stordal (2022) Evaluating global and regional land warming trends in the past decades with both MODIS and ERA5-Land land surface temperature data. Remote Sensing of Environment 280, 113181. https://doi.org/10.1016/j.rse.2022.113181 "