TY - JOUR

T1 - Unmanned aerial vehicles for biodiversity-friendly agricultural landscapes

T2 - A systematic review

AU - Librán-Embid, Felipe Miguel

AU - Klaus, Felix

AU - Tscharntke, Teja

AU - Grass, Ingo

N1 - Funding information: This research was supported by the German Research Association (DFG) Research Training Group 1644 “Scaling Problems in Statistics”, grant no. 152112243 . We thank two anonymous reviewers and the editor for the valuable comments that improved the manuscript. Our gratitude goes also to Emmeline Topp, Kevin Li and Carolina Ocampo Ariza for proofreading the manuscript.

PY - 2020/8/25

Y1 - 2020/8/25

N2 - The development of biodiversity-friendly agricultural landscapes is of major importance to meet the sustainable development challenges of our time. The emergence of unmanned aerial vehicles (UAVs), i.e. drones, has opened a new set of research and management opportunities to achieve this goal. On the one hand, this review summarizes UAV applications in agricultural landscapes, focusing on biodiversity conservation and agricultural land monitoring, based on a systematic review of the literature that resulted in 550 studies. Additionally, the review proposes how to integrate UAV research in these fields and point to new potential applications that may contribute to biodiversity-friendly agricultural landscapes. UAV-based imagery can be used to identify and monitor plants, floral resources and animals, facilitating the detection of quality habitats with high prediction power. Through vegetation indices derived from their sensors, UAVs can estimate biomass, monitor crop plant health and stress, detect pest or pathogen infestations, monitor soil fertility and target patches of high weed or invasive plant pressure, allowing precise management practices and reduced agrochemical input. Thereby, UAVs are helping to design biodiversity-friendly agricultural landscapes and to mitigate yield-biodiversity trade-offs. In conclusion, UAV applications have become a major means of biodiversity conservation and biodiversity-friendly management in agriculture, while latest developments, such as the miniaturization and decreasing costs of hyperspectral sensors, promise many new applications for the future.

AB - The development of biodiversity-friendly agricultural landscapes is of major importance to meet the sustainable development challenges of our time. The emergence of unmanned aerial vehicles (UAVs), i.e. drones, has opened a new set of research and management opportunities to achieve this goal. On the one hand, this review summarizes UAV applications in agricultural landscapes, focusing on biodiversity conservation and agricultural land monitoring, based on a systematic review of the literature that resulted in 550 studies. Additionally, the review proposes how to integrate UAV research in these fields and point to new potential applications that may contribute to biodiversity-friendly agricultural landscapes. UAV-based imagery can be used to identify and monitor plants, floral resources and animals, facilitating the detection of quality habitats with high prediction power. Through vegetation indices derived from their sensors, UAVs can estimate biomass, monitor crop plant health and stress, detect pest or pathogen infestations, monitor soil fertility and target patches of high weed or invasive plant pressure, allowing precise management practices and reduced agrochemical input. Thereby, UAVs are helping to design biodiversity-friendly agricultural landscapes and to mitigate yield-biodiversity trade-offs. In conclusion, UAV applications have become a major means of biodiversity conservation and biodiversity-friendly management in agriculture, while latest developments, such as the miniaturization and decreasing costs of hyperspectral sensors, promise many new applications for the future.

KW - Drones

KW - Precision agriculture

KW - Smart farming

KW - UAV

KW - Unmanned aerial systems (UAS)

KW - Vegetation monitoring

KW - Yield-biodiversity trade-offs

UR - http://www.scopus.com/inward/record.url?scp=85084704549&partnerID=8YFLogxK

U2 - 10.1016/j.scitotenv.2020.139204

DO - 10.1016/j.scitotenv.2020.139204

M3 - Article

VL - 732

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

M1 - 139204

ER -