Right whales unfortunately were named because they were considered the “right” whales to hunt. These slow moving, docile whales tend to stick close to coastlines and high blubber content made them ideal targets for whale hunters. During the height of whale hunting in the early 20th century, tens of thousands of right whales were harvested. In 1937, with the number of right whales estimated to be numbered in the low 300s, a moratorium on hunting was declared although illegal hunting continued for decades. While the right whale population has increased since the abatement of right whale hunting, populations are estimated to be less than 15% of pre whaling numbers. Pre-whaling populations estimate of the right whale are estimated to be 55,000–70,000 while current population estimates are about 7,500.
Because of the docile nature of the right whales, mortality from boat collisions and entanglement in fishing lines continues to threaten the survivability of the right whales. Peter Fretwell of the Mapping and Geographic Information Centre, British Antarctic Survey, has discovered that the shallow water preferring right whales can easily be viewed on satellite imagery, making them an ideal case study for tracking via remote sensing. In a paper cowritten with Iain J. Staniland and Jaume Forcada of the Ecosystems Department at the British Antarctic Survey and published in the journal PLOS One, Fretwell proposed a method of using Very High Resolution (VHR) satellite imagery to identify and count Southern right whales (Eubalaena australis) in their breeding grounds near Golfo Nuevo, Península Valdés in Argentina.
Research area in Golfo Nuevo used for the remote sensing study.
The paper, entitled, “Whales from Space: Counting Southern Right Whales by Satellite” used a September 2012 WorldView2 satellite image covering a 70 square mile area surrounding Golfo Nuevo. The image has a maximum resolution of 50 cm in the panchromatic and 2 m in its eight colour spectral bands and also contains a a water penetrating coastal band in the far-blue part of the spectrum that allowed the researchers to locate whales below the surface of the water.
In order to automate the detection of whales in the satellite imagery, the researchers used“ENVI5 image processing software and ArcGIS automatic detection of whale-like features in the water column was tested using maximum likelihood supervised classification, unsupervised classification (isoData and k-means) and thresholding of specific bands.”
From the abstract:
Using an image covering 113 km2, we identified 55 probable whales and 23 other features that are possibly whales, with a further 13 objects that are only detected by the coastal band … This is the first successful study using satellite imagery to count whales; a pragmatic, transferable method using this rapidly advancing technology that has major implications for future surveys of cetacean populations.
A selection of 20 comparable false colour image chips (bands 1-8-5) of probable whales found by the automated analysis.
Several of the images could be interpreted as whale pairs, or as a mother and calf, others may be displaying behaviour such as tail slapping, rolling or blowing. On several images there is a strong return at one end of the feature which is mostly likely the calluses on the whales head. Reprinted under a CC BY license with permission from British Antarctic Survey and DigitalGlobe.
The authors concluded that “We have shown that the use of current satellite imagery can be used to identify individual whales both at, and just below, the surface. The methods described here readily lend themselves to the calculation of population abundance estimates and suggest that behavioural patterns could also be elucidated. The automation of the methods means that counts can be carried out more quickly and efficiently than using traditional methods.” As opposed to the time intensive and expensive method of using boat expeditions or airplane flyovers to visually count whales, the authors propose that this method of counting whales via remote sensing will allow for more frequent whales count which should lead to a more accurate population estimates. The authors also anticipate that future improvements to the resolution of satellite imagery will allow for increased accuracy in identifying and counting whales.
Fretwell PT, Staniland IJ, Forcada J (2014) Whales from Space: Counting Southern Right Whales by Satellite. PLoS ONE 9(2): e88655. doi:10.1371/journal.pone.0088655