Drones Map the Environment with 1000 Times the Detail of Satellites and a Million Times More Data Points

When the drone flies 100 meters above the ground, it takes pictures with a 3 x 3 cm resolution. This is 1,000 times better than a satellite, which takes pictures with a 30 x 30 m resolution.

Credit: NIVA

Machine learning and finger prints

Now, as the winter storms are approaching Fosnavåg, Hancke is safely back in his office in Oslo. The drone pictures are carefully saved on his computer, and Hancke has started the process of analysing the pictures. The software he applies uses so-called machine learning; it recognizes patterns in the picture, enabling it to categorize the different elements of the picture. By this, the program tells how much seaweed of each type there is in the area they have photographed. Hancke explains:

– Each family of seaweed has its own colour signature, which the software recognizes. This is due to the combination of wavelengths reflected by the different types of seaweed. Each family gets its own finger print, expressed in colours. The software recognizes the seaweed’s fingerprint, and thereby categorizes the elements in the picture.

Identification by colour is called multi spectral image analysis, which is able to distinguish between different groups of seaweeds. Hancke is optimistic that future analysis involve so-called hyperspectral-image analysis, which has an even higher resolution of colours. The drone photos can then be used to identify the precise amount of each single species of seaweeds, mixed kelp forests, and calculate the amount of epiphytes on the seaweed surfaces.

NIVA tested different drone types during their mapping of the intertidal zone at Søre Sunnmøre, Norway. A rotor drone is seen to the left, whereas the drone to the right is a fixed wing drone.  NIVA researcher Kasper Hancke and drone pilot Robert Poulsen from Spectrofly company to the right.
Credit: NIVA

Have been here before

It is not the first time that NIVA scientists are balancing along the shores at Søre Sunnmøre. One year ago, Hancke’s colleague Trine Bekkby was here to map the littoral zone for Artsdatabanken (Norwegian Biodiversity Information Centre) and the EU project EfficienSea. She found both toothed wreck, oarweed, sugar kelp, tangle, and red algae. In June this year, she came back and continued the work one level up, in the intertidal zone. She did traditional mapping – with camera and note book. As Bekkby had already mapped the distribution of seaweeds in Søre Sunnmøre when Hancke searched for a drone testing site, it made the decision easy. By using her seaweed registrations from Søre Sunnmøre, he can now validate the drone pictures, and improve the machine learning algorithms.

Marine biologist Kasper Hancke (left) at the Norwegian Institute for Water Research (NIVA) says that drones are the future within nature resource mapping and monitoring. Senior researcher in NIVA Trine Bekkby (right) is collecting data on the distribution of seaweeds in field. Bekkby’s field data is used for validation of Hancke’s drone pictures from the same area.

Credit: NIVA

New models for mapping

The mapping project in Søre Sunnmøre has been running since 2016, and is a cooperation between researchers from NIVA, Geological Survey of Norway (NGU), and Institute of Marine Research (HI). The geological and biological data are used to develop a standard method for marine “nature types” mapping according to the classification system of Nature in Norway (NiN).

The ongoing mapping of coastal areas in Søre Sunnmøre is also part of a pilot project, Møre Pilot, under the EU project called EfficienSea. EfficienSea aims to improve the knowledge about where there are vulnerable ecosystems, so that future shipping and building of new constructions can be avoided in the most vulnerable areas.

Using the new, high-resolution seafloor maps from NGU, Bekkby and her colleagues are also working on developing new models to map nature types. Their hope is that they can use NGU’s shallow-marine geological maps together with data on the physical environment, such as temperature, salinity, wave exposure, and light, to model the different nature types along the coast.
Big potential for drones

Two rooms to the left from Bekkby’s office at NIVA, sits Hancke. He pictures a bright future for drone mapping, which will be a lot more efficient and cost-saving than today’s mapping methods. Drone mapping also provides continuous observations along the shores, instead of single data points that need to be extrapolated, like now. In the future, Hancke also wants to use drones for taking underwater photos from the air, not only photos of the exposed intertidal. Cameras that are adapted for underwater photos are not yet on the market, but NIVA has developed their own special equipment for this purpose.

– Further, drone pictures can be used to monitor the expansion of introduced species, like the pacific oyster. We are also working towards use of drones for quantification of plastics and marine litter in the coastal oceans and along the shores, and are developing automated image analysis routines, Hancke finishes.
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Contacts and sources:     .
Norwegian Institute for Water Research (NIVA)

Citation:   Bekkby, Trine, mfl. (2018): Pilotprosjekt – Kartlegging av marin natur i Møre og Romsdal. Årsrapport 2017. NIVA-rapport 6404

Møre og Romsdal fylkeskommune. 2012. Mørekysten er EU-pilot
[online]. Available from https://mrfylke.no/Nyheiter/Moerekysten-er-EU-pilot.    .