Remote Sensing for Precision Agriculture and Weed Science

Departament of Crop Protection
Major research lines of “Remote Sensing for Precision Agriculture and Weed Science” Group are centered on the optimization of agrochemical applications by using site-specific strategies.

Main current research activities are focused on the following objectives:

  • To detect and map weeds and other agronomic variables in herbaceous and woody crops by using remote sensing techniques and imagery from high resolution satellite and unmanned aerial vehicles (UAV).
  • To design, develop and evaluate OBIA (Objects-Based-Image-Analysis) procedures for geospatial analysis, image feature extraction, segmentation, tree geometry and vegetation classification in crops using digital cameras and multispectral sensors.
  • To improve the workflows for image processing by developing Geostatistics algorithms and specific software “add-on”- “plug-in” for precision agriculture approaches as well as for an accurate georeferenciation / co-registration and classification of cropping systems.

Def_Since1999

TEAM

Francisca López-Granados

Research ScientistHead of group
flgranados@ias.csic.es

José Manuel Peña-Barragán

Tenured Scientist

Currently at the Institute of Agricultural Sciences (ICA-CSIC)
jmpena@ica.csic.es
Ana Isabel de Castro Megías

Ana Isabel de Castro-Megías

Postdoctoral Researcher

anadecastro@ias.csic.es

Jorge Torres-Sánchez

Postdoctoral Researcherjtorres@ias.csic.es
Francisco Manuel Jiménez Brenes

Francisco Manuel Jiménez-Brenes

Postdoctoral Researcher

fmjimenez@ias.csic.es

F. J. Mesas-Carrascosa, A. I. De Castro, J. Torres-Sánchez, P. Triviño-Tarradas, F. M. Jiménez Brenes, A. García-Ferrer & F. López-Granados. 2020. Classification of 3D point clouds using color vegetation indices for precision viticulture and digitizing applications. Remote Sensing, 12(2), 317. https://doi.org/10.3390/rs12020317.

A. I. De Castro, J. M. Peña, J. Torres-Sánchez, F. M. Jiménez-Brenes, F. Valencia-Gredilla, J. Recasens & F. López-Granados. 2020. Mapping Cynodon dactylon infesting cover crops with an automatic decision tree-OBIA procedure and UAV imagery for precision viticulture. Remote Sensing, 12(1), 56. https://doi.org/10.3390/rs12010056.

F. López-Granados, J. Torres-Sánchez, F. M. Jiménez-Brenes, O. Arquero, M. Lovera & A. I. De Castro. 2019. An efficient RGB-UAV-based platform for field almond tree phenotyping: 3-D architecture and flowering traits. Plant Methods, 15, 160. https://doi.org/10.1186/s13007-019-0547-0.

A. I. De Castro, P. Rallo, Mª. P. Suárez, J. Torres-Sánchez, L. Casanova, F. M. Jiménez-Brenes, A. Morales-Sillero, R. Jiménez & F. López-Granados. 2019. High-throughput system for the early quantification of major architectural traits in olive breeding trials using UAV images and OBIA techniques. Front. Plant Sci. 10:1472. doi: 10.3389/fpls.2019.01472.

F. M. Jiménez-Brenes, F. López-Granados, J. Torres-Sánchez, J. M. Peña, P. Ramírez, I. L. Castillejo González & A. I. De Castro. 2019. Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management. PloS ONE, 14(6): e0218132. https://doi.org/10.1371/journal.pone.0218132.

M. Jurado-Expósito, A. I. de Castro, J. Torres-Sánchez, F. M. Jiménez-Brenes & F. López-Granados. 2019. Papaver rhoeas L. mapping with cokriging using UAV imagery. Precision Agriculture, 20: 1045-1067. https://doi.org/10.1007/s11119-019-09635-z.

I. L. Castillejo-González, A. I. De Castro, M. Jurado-Expósito, J. M. Peña, A. García-Ferrer & F. López-Granados. 2019. Assessment of the persistence of Avena sterilis L. patches in wheat fields for site-specific sustainable management. Agronomy, 9(1), 30. https://doi.org/10.3390/agronomy9010030.

J. Torres-Sánchez, A. I. de Castro, J. M. Peña, F. M. Jiménez-Brenes, O. Arquero, M. Lovera & F. López-Granados. 2018. Mapping the 3D structure of almond trees using UAV acquired photogrammetric point clouds and object-based image analysis. Biosystems Engineering, 176: 172-184. https://doi.org/10.1016/j.biosystemseng.2018.10.018.

J. Torres-Sánchez, F. López-Granados, I. Borra-Serrano & J. M. Peña. 2018. Assessing UAV-collected image overlap influence on computation time and digital surface model accuracy in olive orchards. Precision Agriculture, 19(1): 115-133. https://doi.org/10.1007/s11119-017-9502-0.

C. Fernández‐Quintanilla, J. M. Peña, D. Andújar, J. Dorado, A. Ribeiro & F. López‐Granados. 2018. Is the current state of the art of weed monitoring suitable for site‐specific weed management in arable crops?. Weed Research, 58: 259-272. doi:10.1111/wre.12307.

A. I. de Castro, F. M. Jiménez-Brenes, J. Torres-Sánchez, J. M. Peña, I. Borra-Serrano & F. López-Granados. 2018. 3-D characterization of vineyards using a novel UAV imagery-based OBIA procedure for precision viticulture applications. Remote Sensing, 10(4), 584. https://doi.org/10.3390/rs10040584.

A. I. de Castro, J. Torres-Sánchez, J. M. Peña, F. M. Jiménez-Brenes, O. Csillik & F. López-Granados. 2018. An automatic random forest-OBIA algorithm for early weed mapping between and within crop rows using UAV imagery. Remote Sensing, 10(2), 285. https://doi.org/10.3390/rs10020285.

P. González-de-Santos, A. Ribeiro, C. Fernández-Quintanilla, F. López-Granados, M. Brandstoetter, S. Tomic, S. Pedrazzi, A. Peruzzi, G. Pajares, G. Kaplanis, M. Pérez-Ruiz, C. Valero, J. del Cerro, M. Vieri, G. Rabatel & B. Debilde. 2017. Fleets of robots for environmentally-safe pest control in agriculture. Precision Agriculture. doi:10.1007/s11119-016-9476-3.

F. López-Granados, J. Torres-Sánchez, A.I. de Castro, A. Serrano-Pérez, F.J. Mesas-Carrascosa & J.M. Peña. 2016. Object-based early monitoring of a grass weed in a grass crop using high resolution UAV imagery. Agronomy for Sustainable Development, 36(4): paper 67. doi:10.1007/s13593-016-0405-7.

No Comments

Post a Comment

Time limit is exhausted. Please reload CAPTCHA.