Blumentrath, Stefan; Nowell, Megan Sara; Salberg, Arnt-Børre; Kermit, Martin Andreas; Bakkestuen, Vegar; Erikstad, Lars; Bernhardt, J
Norsk institutt for naturforskning
Antall sider: 20
The Sentinel4Nature project was launched in 2014 with the objective of exploring the potential of using remote sensing techniques to detect and model environmental gradients identified by the Nature in Norway (NiN) classification system. The following report describes the progress of the Sentinel4Nature project to date. Two environmental gradients were selected, namely 1) Re-duced growing season due to prolonged snow-lie and 2) Tree canopy cover. The methodology for modelling these two gradients is discussed. The suitability of Sentinel imagery for the objec-tives of this project has also been explored.
Norway, Oslofjord, Lurøykalven, Hjerkinn, Sunndalen, environmen-tal gradients, reduced growing season due to prolonged snow-lie, tree canopy cover, remote sensing, Sentinel imagery, data fusion, modelling, NiN, PRODEX, ESA, NRS, Norge, Oslofjord, Lurøykalven, Hjerkinn, Sunndalen, Lokale Kom-plekse Miljøvariabler, LKM, snødekkebetinget vekstsesongreduksjon, tresjiktstetthet , fjernmåling, Sentinel, data fusion, modellering, NiN, PRODEX, ESA, NRS