2024-03-28T11:05:15Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1649562020-05-27T13:50:27Zcom_10261_74com_10261_6col_10261_453
DIGITAL.CSIC
author
Peña Barragán, José Manuel
author
Torres-Sánchez, Jorge
author
Castro, Ana Isabel de
author
López Granados, Francisca
2018-05-22T06:45:10Z
2018-05-22T06:45:10Z
2016-06
7th International Weed Science Congress (2016)
http://hdl.handle.net/10261/164956
The application of site-specifi c weed management (SSWM) practices requires that the weeds
be previously located in the crop fi eld, e.g., by generating a weed map. Until now, obtaining
these weed maps early in the growing season, which is the moment recommended in many
crops for an optimal weed management treatment, has been a great challenge because
of the reduced size of the weed and crop plants and their spectral similarity at an early
phenological stage. This challenge has been overcome by the combined use of aerial images
collected with an Unmanned Aerial Vehicles (UAV) and application of object-based image
analysis (OBIA) techniques. This abstract describes the full protocol developed in the last
four years by our research group with that objective. The investigation was conducted over
several parcels of three herbaceous (wheat, corn and sunfl ower) and three woody (olive,
poplar and grape) crops. The main phases of this protocol involved: 1) confi guration and use
of the UAV and sensors for image acquisition, 2) determining the fi nest fl ight confi guration
(UAV altitude, image spatial and spectral resolutions, fl ight length, etc.) for each type of crop,
with particular attention to crop evolution (multi-temporal study), 3) optimizing the process
of image mosaicing and geo-referencing in order to generate a unique ortho-mosaiced
image that completely covers the fi elds of study, and 4) development of customised and
robust OBIA procedures for weed mapping and crop assessment in order to optimize cropweed
management operations adapted to diff erent scenarios. Our results demonstrated
that weed emergences could be discriminated with accuracy higher than 90% if image
resolutions are correctly selected for each type of crop and scenario, although an agreement
with fl ight length and UAV battery duration is needed in order to optimize the full procedure.
eng
closedAccess
Site-specific weed management (SSWM)
Unmanned aerial vehicle
Object-based image analysis
Herbaceous row crops
Woody crops
The full protocol for early-season weed mapping with UAV technology
comunicación de congreso
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
URL
https://digital.csic.es/bitstream/10261/164956/1/accesoRestringido.pdf
File
MD5
42637ae8545636bc41605c1740a9a84e
15753
application/pdf
accesoRestringido.pdf