• Reduce text

    Reduce text
  • Restore text size

    Restore text size
  • Increase the text

    Increase the text
  • Print

Processionary pine moths. © INRA, Jean-Claude Martin

Using Google Street View to localise pest insects

For the first time, INRA scientists have used the freely downloadable Google Street View (GSV) database to map the geographical distribution of an increasingly common invasive pest insect, the pine processionary moth.  The scientists estimated that this on-line database would provide a good representation of the presence of this species.  Their findings, published in PLOS ONE on 9 October 2013, open the way to the simplified and inexpensive acquisition of data that are essential when studying invasive or expanding species.

Updated on 11/18/2013
Published on 10/10/2013

Mapping of the geographical distribution of species is crucial to monitor the evolution of those that are invasive or native and expanding.  However, it is sometimes difficult to access the necessary data from the literature, and it is expensive to collect them in the field.  This is an even more problematic issue because the distribution of some species is evolving under the effects of climate change.  For this reason, the INRA research team focused on using Google Street View (GSV) in order to determine how far this new technology would enable the reliable collection of data on the geographical distribution of particular species.

The pine processionary moth is an insect whose larvae eat the needles of different species of pine and cedar.  The larvae weave their winter nests of white silk, particularly in trees along public roadsides.  This feature renders the use of GSV very interesting, because this system provides access to panoramic views of these roads, and is able to identify numerous details.

The researchers determined a large sampling area covering about 47,000 km² in the Centre region of France, which they then divided into 183 16x16 km cells.  The team then noted the presence or absence of nests within each cell.  The data were collected by direct observation in the field and via GSV.  By comparing these findings, they were able to determine that GSV was a good indicator of the values measured in the field, offering reliability of around 90% at this resolution.

These results offer important prospects for the simplification and less expensive acquisition of data to study the presence of invasive organisms and changes to their geographical distribution.  Although it is not possible to apply such observations to all species, many organisms could undoubtedly be studied in this way, including pest insects or pathogens associated with common trees whose symptoms can be identified by means of roadside sampling (for example, the horse chestnut leaf miner or ash dieback).

Scientific contact(s):

Press Relations:
INRA News Office (33 0(1) 42 75 91 86)
Associated Division(s):
Forest, Grassland and Freshwater Ecology
Associated Centre(s):


Jérôme Rousselet, Charles-Edouard Imbert, Anissa Dekri, Jacques Garcia, Francis Goussard, Bruno Vincent, Olivier Denux, Christelle Robinet, Franck Dorkeld, Alain Roques, Jean-Pierre Rossi. Assessing species distribution using Google street view: a pilot study with the Pine Processionary Moth. PLOS ONE, 9 October 2013. DOI: http://dx.plos.org/10.1371/journal.pone.0074918