Space
Accurate Whale Watching From Space Via Satellites: BAS
Benita Matilda
First Posted: Feb 13, 2014 08:50 AM EST
Scientists at British Antarctic Survey demonstrated how novel satellite technology can be used to estimate whale population.
A new method highlighted by the British Antarctica Survey reveals how Very High Resolution (VHR) satellite imagery clubbed with image processing software can be used to automatically detect and count the number of whales breeding in regions of Golfo Nuevo, Peninsula Valdes in Argentina.
It is extremely challenging and difficult to keep a count of the whales on a large scale. The scientists believe that this new technology will help in revolutionising the manner in which whale population size is estimated. This can be replaced with the traditional methods that include counting the marine species from land, which is not just a costly, but also inefficient.
The lead author for this finding is Peter Fretwell, British Antarctic Survey.
"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 localized, expensive and lack accuracy. 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," says Fretwell.
Over the recent years, satellites have improved in their accuracy of counting whales. This time, scientists from BAS used a single WorldView2 satellite image of a bay where southern right whales crowd to calve and mate.
End of whaling has helped these whales recover, but researchers have found that there has been an alarming rise in the number of dead whales washed on the nursery grounds of Peninsula Valdes. Currently, the population size of these whales remains unknown.
The shallow water of the bays increases the chances of spotting the whales from space. The team basically relied on three main aspects: 'Objects visible in the image should be the right size and shape' , 'present in the right place where whales are expected to be' and ' no other object should be seen and mistaken as whales'.
The whales in the image were later manually identified and counted. They spotted 55 probable whales and 23 possible whales and 13 sub surface features. In order to test these numbers several automated methods were adopted. The greatest accuracy was achieved from WorldView2 image of the Costal Band. In this image, the light from the blue end of the spectrum enters the great depths of the water and allows the crew members to spot more whales. With this technique, the team found 89 percent probable whales identified in the manual count. Unlike the previous technique, this is a semi-automated technique that requires the user to spot the best threshold.
They plan to launch WorldView3 this year that will allow high quality imagery and will help in differentiating mother and calf pairs.
This was funded by the UK's Natural Environment Research Council (NERC).
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First Posted: Feb 13, 2014 08:50 AM EST
Scientists at British Antarctic Survey demonstrated how novel satellite technology can be used to estimate whale population.
A new method highlighted by the British Antarctica Survey reveals how Very High Resolution (VHR) satellite imagery clubbed with image processing software can be used to automatically detect and count the number of whales breeding in regions of Golfo Nuevo, Peninsula Valdes in Argentina.
It is extremely challenging and difficult to keep a count of the whales on a large scale. The scientists believe that this new technology will help in revolutionising the manner in which whale population size is estimated. This can be replaced with the traditional methods that include counting the marine species from land, which is not just a costly, but also inefficient.
The lead author for this finding is Peter Fretwell, British Antarctic Survey.
"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 localized, expensive and lack accuracy. 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," says Fretwell.
Over the recent years, satellites have improved in their accuracy of counting whales. This time, scientists from BAS used a single WorldView2 satellite image of a bay where southern right whales crowd to calve and mate.
End of whaling has helped these whales recover, but researchers have found that there has been an alarming rise in the number of dead whales washed on the nursery grounds of Peninsula Valdes. Currently, the population size of these whales remains unknown.
The shallow water of the bays increases the chances of spotting the whales from space. The team basically relied on three main aspects: 'Objects visible in the image should be the right size and shape' , 'present in the right place where whales are expected to be' and ' no other object should be seen and mistaken as whales'.
The whales in the image were later manually identified and counted. They spotted 55 probable whales and 23 possible whales and 13 sub surface features. In order to test these numbers several automated methods were adopted. The greatest accuracy was achieved from WorldView2 image of the Costal Band. In this image, the light from the blue end of the spectrum enters the great depths of the water and allows the crew members to spot more whales. With this technique, the team found 89 percent probable whales identified in the manual count. Unlike the previous technique, this is a semi-automated technique that requires the user to spot the best threshold.
They plan to launch WorldView3 this year that will allow high quality imagery and will help in differentiating mother and calf pairs.
This was funded by the UK's Natural Environment Research Council (NERC).
See Now: NASA's Juno Spacecraft's Rendezvous With Jupiter's Mammoth Cyclone