Using drones to estimate crop damage by wild boar

Date: 12 December 2017

Introduction: A new drone based method, realised by Anneleen Rutten (UAntwerp), allows estimating crop damage in a fast, standardised and objective manner.

Growing populations of wild boar (Sus scrofa L.) have been causing more and more damage to agricultural land in Europe over the last decades, necessitating hundreds of thousands of Euros in compensation.

Anneleen Rutten, PhD student at University of Antwerp and the Research Institute for Nature and Forest (INBO), Brussels, will present the method at the conference ‘Ecology Across Borders’ in Ghent, Belgium, this week. She uses a standard commercial drone to take aerial photographs of damaged agricultural fields, which are analysed with an algorithm identifying damaged area.

Rising numbers of wild boar have been linked to higher crop damage, disease transmissions and car accidents in many European countries. In Flanders, wild boar has been extinct for almost 50 years, and only returned in 2006. Estimates from hunting bags show a growing population which is still expanding its range, from the Eastern province of Limburg towards the Centre (Antwerpen and Vlaams-Brabant).

Prominent conflicts
Landscape structure in Flanders changed in the years of absence of wild boar, resulting in a dense, mosaic-like pattern of agricultural, natural and urban areas. Thus, human-wildlife conflicts have been prominent in the last years.

“I want to get a first insight in the extent of agricultural damage by wild boars in Flanders because, in contrast to neighbouring regions and countries, damage is not monitored and it is not known what the financial extent of crop damage is for the agricultural sector” Anneleen Rutten says.

The method was developed to be affordable and easy to apply. “I connect my smartphone to the remote controller of my drone which allows me to see the camera visualisation of the drone. Damage is really clear on the camera: in maize fields, boars roll over the maize which makes that you have areas in a normally green covered maize field with holes in the coverage of broken stems. In grasslands, rooting causes a clear colour difference with grass because the soil is rooted up”, Rutten explains.

For each field, many individual photographs with 75 -85% overlap are taken. The high overlap allows combining the individual photographs in a single image corrected for the different perspectives and showing the entire field. The area of the field is then classified into damaged and undamaged parts using Object Based Image Analysis (OBIA). The algorithm reaches 93% of accuracy for maize fields, and 94% accuracy for grasslands.

Traditionally, crop damage is estimated by trained experts measuring the damaged area in the field. “Flying and taking photographs of damaged fields does not take as long as doing an assessment by ground visit which also makes it cost-effective” Rutten adds. Another advantage is that the method is standardised, which allows direct comparisons between different fields and over time.

Watch the movie on Youtube

drone wild boar

drone wild boar

drone wild boar

drone wild boar
A new drone based method, realised by Anneleen Rutten (UAntwerp), allows estimating crop damage in a fast, standardised and objective manner.