Mapping polar vegetation using UAS

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1 Mapping polar vegetation using UAS Stein Rune Karlsen, Agnar Sivertsen, Andreas Tøllefsen, Rune Storvold, Bernt Johansen Norut Northern Research Institute Anna Zmarz Warsaw University of Technology

2 Content - Polar vegetation (High Arctic and western Antarctic) - NDVI based vegetation mapping - NDVI vs. hyperspectral data in vegetation mapping - Hyperspectral data from UAS vs. from satellite - Summary

3 Polar vegetation - Often only scattered and mostly dominated by moss or lichen

4 Polar vegetation - Often only scattered and mostly dominated by moss or lichen

5 King George Island, Maritime Next season Antarctic Vegetation mapping Jan-Feb 2016 King George Island

6 Vegetation

7 Vegetation Dominant moss: Sanonia uncinata

8 Vegetation Antarctic hair grass (Deschampsia antarctica), dominates in convex slopes and some very disturbed areas

9 Vegetation Antarctic hair grass (Deschampsia antarctica), dominates in convex slopes and some very disturbed areas

10 Vegetation Lichens, mainly Usnea spp. dominates at drier sites at higher altitudes

11 Vegetation

12 Vegetation Wind is a main driver in Antarctic

13 Vegetation Penguins and seals influence the vegetation up to several hundred meters from the seashore

14 Vegetation Penguins and seals influence the vegetation up to several hundred meters from the seashore

15 Vegetation Penguins and seals influence the vegetation up to several hundred meters from the seashore

16 Algae (Prasiola crispa) MONICA A novel approach to monitoring the impact of climate change on Antarctic ecosystems

17 Cryowing Scout Fully electric MTOW: 7 kg Wingspan: 2.5 m Payload capacity: 2 kg Max flying time: 90 min, 100 km 433Mhz telemetry Can be hand launched Strong wind a challenge, flights was possible only three times during a three weeks period in Januray-February 2016

18 NDVI camera (blue, green and near infrared (NIR) bands) bndvi = (NIR-Blue)/(NIR+Blue) General Information Rikola hyperspectral camera Spectral Range: nm

19 Next season

20 Next season

21 (blue, green, NIR bands) - bndvi 7cm pixels

22 Project Organization Fieldwork shows that the study area has 7 main vegetation units 4 different moss vegetation types 2 different grass vegetation types One lichen vegetation types NDVI based vegetation mapping: Very good in detecting even small spots of moss and grass Only two moss vegetation types are well mapped Lichen rich area are not detected by NDVI To map more vegetation types hyperspectral data (Rikola) is needed.

23 Hyperspectral camera (Rikola) on stand in field Study spectral properties of selected dominant plants Project Organization

24 Rikola on stand, 192 Project bands, spectral Organization properties of dominant species

25 Rikola on stand, 192 Project bands, spectral Organization properties of dominant species

26 Rikola on stand, 192 Project bands, spectral Organization properties of dominant species

27 Rikola on stand, 192 Project bands, spectral Organization properties of dominant species

28 Project Organization Selected 15 bands on Rikola, based on the field measurements: 530nm 550nm 570nm 600nm 671nm 685nm 705nm 720nm 740nm 775nm 800nm 850nm 865nm 550nm 685nm 740nm 30 cm pixel Georeferencing is challenging

29 Optical satellite data WP 2 Results WorldView-3 pixel size: Panchromatic: 31cm pixel 8 bands in visible & near-infrared: 1.24 m pixel 8 bands in short-wave infrared: 3.7 m pixel

30 WorldView-2 satellite data - Svalbard, Ny-Ålesund town areas Vegetation maps with 2m pixel, based on 8 multispectral bands

31 Summary WP 2 Results Polar vegetation (High Arctic and Antarctic): often scattered vegetation cover, with dominance of lichen or moss. NDVI in vegetation mapping: - Ultra-high resolution from NDVI camera map even small spots of mosses and vascular plants - NDVI have problem in separating between dominated moss species in wetlands, and sometimes to separate mosses from vascular plants - NDVI not useful in mapping lichen rich vegetation types The high degree of moss and lichen in polar vegetation requires hyperspectral data in vegetation mapping. Difficult to obtain optical satellite data in vegetation mapping in maritime part of Antarctic due to the frequent cloud cover and short snow free season. Use of UAS in maritime Antarctic: Weather a challenge strong wind, on average flights possible only once a week.

32 Vegetation Thank you for your attention!

33 Vegetation Lichens (Caloplaca spp./ Xanthoria spp.)

34 abstract In extreme cold environment, as the maritime part of the western Antarctic or the northern tundra zone on Svalbard, the vegetation cover is scattered and often dominated by mosses and lichen. In the few places where continuous vegetation occur, the plant communities change from meter to meter, depending on the depth of the active layer, and thereby the water table which controls the species composition. For a sensible mapping of such scattered or patchy vegetation ultra-high resolution is needed. We use the Cryowing Scout, a twin engine fully electric UAS with a wingspan of 2.5 m and maximum flying time of 90 minutes. The UAS is hand launched and well suited to be operated in the field with no need of a runway. For this particular experiment the UAS was equipped with two sensors, a NDVI camera providing spatial resolution down to 2 cm, and a hyperspectral camera (Rikola) with spatial resolution of about 20-40cm. First we use the NDVI data to create a mask for vegetated areas, and then we classify the hyperspectral data for the vegetated areas. This method detects most plant associations and even some stands on species level. We present results from this method for the Arctowski region, Admiralty Bay, King George Island, maritime Antarctic.

35 WP 2 Results

36 Aerial Census WP 3 Results

37 Ground Census WP 3 Results