Scientists use satellites to track whales

Scientists are using a new high-resolution satellite technology to track whales, count their numbers and estimate their population size.
Using Very High Resolution (VHR) satellite imagery, alongside image processing software, researchers were able to automatically detect and count whales breeding in part of the Golfo Nuevo, Peninsula Valdes in Argentina.
The new method could revolutionise how whale population size is estimated, researchers said.
Marine mammals are extremely difficult to count on a large scale and traditional methods, such as counting from platforms or land, can be costly and inefficient.
"This is a proof of concept study that proves whales can be identified and counted by satellite. Whale populations have always been difficult to assess; traditional means of counting them are localised, expensive and lack accuracy," said lead author Peter Fretwell from the British Antarctic Survey (BAS).

"The ability to count whales automatically, over large areas in a cost effective way will be of great benefit to conservation efforts for this and potentially other whale species," said Fretwell.

Previously, satellites have provided limited success in counting whales but their accuracy has improved in recent years.
The BAS team used a single WorldView2 satellite image of a bay where southern right whales gather to calve and mate.
Driven to near extinction, these whales have made a limited recovery following the end of whaling, researchers said.
In recent years, however, many deaths have been seen on their nursery grounds at Peninsula Valdes. Their population size is now unknown but with this sharp increase in calf mortality, estimates are needed.

The enclosed bays in this region contain calm, shallow waters which increase the chance of spotting the whales from space.
Three main criteria were used to identify whales: objects visible in the image should be the right size and shape; they should be in the right place (where whales would be expected to be) and there should be no (or few) other types of objects that could be mistaken as whales, said researchers.
Whales in the image were manually identified and counted, finding 55 probable whales, 23 possible whales and 13 sub-surface features. Several automated methods where then tested against these numbers.

A "thresholding" of the Coastal Band of the WorldView2 image gave the greatest accuracy. This part of the image uses light from the far blue end of the spectrum which penetrates the water column deeper and allows us to see more whales.
This technique found 89 per cent of probable whales identified in the manual count.
The finding appears in the journal PLoS ONE.