World's Best Scientists 2026 revealed!
Francisca López-Granados

Francisca López-Granados

D-Index & Metrics

Plant Science and Agronomy

D-Index
46
Citations
9152
World Ranking
2666
National Ranking
108

Francisca López-Granados publication distribution in Plant Science and Agronomy in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Plant Science and Agronomy in 2026. The highlighted bar marks where Francisca López-Granados sits on this spectrum.

36–40 publications: 2 scientists 41–45 publications: 7 scientists 46–50 publications: 40 scientists 51–55 publications: 58 scientists 56–60 publications: 60 scientists 61–65 publications: 107 scientists 66–70 publications: 130 scientists 71–75 publications: 153 scientists 76–80 publications: 191 scientists 81–85 publications: 199 scientists 86–90 publications: 206 scientists 91–95 publications: 218 scientists 96–100 publications: 226 scientists 101–105 publications: 227 scientists 106–110 publications: 247 scientists 111–115 publications: 255 scientists 116–120 publications: 253 scientists 121–125 publications: 233 scientists 126–130 publications: 219 scientists 131–135 publications: 201 scientists 136–140 publications: 194 scientists 141–145 publications: 176 scientists 146–150 publications: 157 scientists 151–155 publications: 147 scientists 156–160 publications: 151 scientists 161–165 publications: 159 scientists 166–170 publications: 137 scientists 171–175 publications: 128 scientists 176–180 publications: 126 scientists 181–185 publications: 98 scientists 186–190 publications: 114 scientists 191–195 publications: 100 scientists 196–200 publications: 90 scientists 201–205 publications: 71 scientists 206–210 publications: 98 scientists 211–215 publications: 70 scientists 216–220 publications: 86 scientists 221–225 publications: 61 scientists 226–230 publications: 58 scientists 231–235 publications: 53 scientists 236–240 publications: 64 scientists 241–245 publications: 39 scientists 246–250 publications: 46 scientists 251–255 publications: 51 scientists 256–260 publications: 36 scientists 261–265 publications: 44 scientists 266–270 publications: 35 scientists 271–275 publications: 30 scientists 276–280 publications: 33 scientists 281–285 publications: 35 scientists 286–290 publications: 36 scientists 291–295 publications: 26 scientists 296–300 publications: 26 scientists 301–305 publications: 31 scientists 306–310 publications: 30 scientists 311–315 publications: 21 scientists 316–320 publications: 29 scientists 321–325 publications: 14 scientists 326–330 publications: 15 scientists 331–335 publications: 15 scientists 336–340 publications: 17 scientists 341–345 publications: 15 scientists 346–350 publications: 12 scientists 351–355 publications: 17 scientists 356–360 publications: 18 scientists 361–365 publications: 12 scientists 366–370 publications: 11 scientists 371–375 publications: 6 scientists 376–380 publications: 6 scientists 381–385 publications: 11 scientists 386–390 publications: 9 scientists 391–395 publications: 10 scientists 396–400 publications: 8 scientists 401–405 publications: 4 scientists 406–410 publications: 9 scientists 411–415 publications: 11 scientists 416–420 publications: 4 scientists 421–425 publications: 7 scientists 426–430 publications: 4 scientists 431–435 publications: 3 scientists 436–440 publications: 5 scientists 441–445 publications: 8 scientists 446–450 publications: 6 scientists 451–455 publications: 7 scientists 456–460 publications: 5 scientists 461–465 publications: 6 scientists 466 publications: 2 scientists 467+ publications: 99 scientists
36 publications 467+

This scientist: 108 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 467 publications or more.

Francisca López-Granados D-index placement in Plant Science and Agronomy in 2026

The chart shows the D-index (discipline H-index) distribution of Plant Science and Agronomy scientists ranked by Research.com in 2026. The highlighted bar marks where Francisca López-Granados sits on this spectrum.

30 D-Index: 200 scientists 31 D-Index: 236 scientists 32 D-Index: 253 scientists 33 D-Index: 283 scientists 34 D-Index: 288 scientists 35 D-Index: 240 scientists 36 D-Index: 246 scientists 37 D-Index: 243 scientists 38 D-Index: 247 scientists 39 D-Index: 229 scientists 40 D-Index: 232 scientists 41 D-Index: 230 scientists 42 D-Index: 228 scientists 43 D-Index: 219 scientists 44 D-Index: 193 scientists 45 D-Index: 164 scientists 46 D-Index: 158 scientists 47 D-Index: 143 scientists 48 D-Index: 131 scientists 49 D-Index: 127 scientists 50 D-Index: 122 scientists 51 D-Index: 122 scientists 52 D-Index: 110 scientists 53 D-Index: 102 scientists 54 D-Index: 98 scientists 55 D-Index: 79 scientists 56 D-Index: 85 scientists 57 D-Index: 88 scientists 58 D-Index: 91 scientists 59 D-Index: 62 scientists 60 D-Index: 61 scientists 61 D-Index: 59 scientists 62 D-Index: 54 scientists 63 D-Index: 61 scientists 64 D-Index: 59 scientists 65 D-Index: 58 scientists 66 D-Index: 41 scientists 67 D-Index: 49 scientists 68 D-Index: 39 scientists 69 D-Index: 32 scientists 70 D-Index: 40 scientists 71 D-Index: 47 scientists 72 D-Index: 38 scientists 73 D-Index: 28 scientists 74 D-Index: 29 scientists 75 D-Index: 28 scientists 76 D-Index: 22 scientists 77 D-Index: 21 scientists 78 D-Index: 25 scientists 79 D-Index: 26 scientists 80 D-Index: 19 scientists 81 D-Index: 16 scientists 82 D-Index: 12 scientists 83 D-Index: 16 scientists 84 D-Index: 14 scientists 85 D-Index: 11 scientists 86 D-Index: 17 scientists 87 D-Index: 13 scientists 88 D-Index: 10 scientists 89 D-Index: 12 scientists 90 D-Index: 18 scientists 91 D-Index: 16 scientists 92 D-Index: 16 scientists 93 D-Index: 17 scientists 94 D-Index: 12 scientists 95 D-Index: 8 scientists 96 D-Index: 9 scientists 97 D-Index: 9 scientists 98 D-Index: 11 scientists 99 D-Index: 12 scientists 100 D-Index: 5 scientists 101 D-Index: 8 scientists 102 D-Index: 4 scientists 103 D-Index: 11 scientists 104 D-Index: 5 scientists 105 D-Index: 9 scientists 106 D-Index: 7 scientists 107 D-Index: 4 scientists 108 D-Index: 8 scientists 109+ D-Index: 99 scientists
30 D-Index 109+

This scientist: 46 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 109 D-Index or more.

Overview

What is she best known for?

The fields of study she is best known for:

  • Agronomy
  • Artificial intelligence
  • Statistics

Her primary scientific interests are in Remote sensing, Precision agriculture, Weed control, Multispectral image and Weed. Her Remote sensing research is multidisciplinary, incorporating perspectives in Mean squared error, Pixel, Early season and Vegetation. Her work on Image resolution expands to the thematically related Precision agriculture.

Her Weed control research incorporates themes from Weed detection and Environmental resource management. Her Multispectral image study combines topics from a wide range of disciplines, such as Image processing, Classifier, Segmentation and Normalized Difference Vegetation Index. Her Weed study necessitates a more in-depth grasp of Agronomy.

Her most cited work include:

  • Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV (219 citations)
  • Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images. (213 citations)
  • Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management. (189 citations)

What are the main themes of her work throughout her whole career to date?

Remote sensing, Precision agriculture, Weed, Agronomy and Weed control are her primary areas of study. Her biological study spans a wide range of topics, including Image resolution, Pixel and Vegetation. Her Precision agriculture study integrates concerns from other disciplines, such as Tree, Statistics and Support vector machine, Artificial intelligence.

Her work in Weed addresses subjects such as Spatial distribution, which are connected to disciplines such as Geostatistics. Her research in Weed control intersects with topics in Agroforestry and Image acquisition. Her Multispectral image research incorporates elements of Hyperspectral imaging and Satellite imagery.

She most often published in these fields:

  • Remote sensing (36.63%)
  • Precision agriculture (36.63%)
  • Weed (33.66%)

What were the highlights of her more recent work (between 2017-2021)?

  • Photogrammetry (8.91%)
  • Remote sensing (36.63%)
  • Precision agriculture (36.63%)

In recent papers she was focusing on the following fields of study:

Francisca López-Granados spends much of her time researching Photogrammetry, Remote sensing, Precision agriculture, Weed and Tree. As part of her studies on Remote sensing, Francisca López-Granados often connects relevant subjects like Vegetation. In her study, Vine and Contextual image classification is inextricably linked to Crop, which falls within the broad field of Precision agriculture.

Much of her study explores Weed relationship to Weed control. Francisca López-Granados interconnects Mean squared error, Statistics and Agricultural engineering in the investigation of issues within Tree. Her Agronomy research integrates issues from Artificial neural network and Weed detection.

Between 2017 and 2021, her most popular works were:

  • An Automatic Random Forest-OBIA Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery (92 citations)
  • 3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications (48 citations)
  • Assessing UAV-collected image overlap influence on computation time and digital surface model accuracy in olive orchards (46 citations)

In her most recent research, the most cited papers focused on:

  • Agronomy
  • Artificial intelligence
  • Botany

Her main research concerns Remote sensing, Photogrammetry, Precision agriculture, Weed control and Weed. Spatial analysis and RGB color model is closely connected to Tree in her research, which is encompassed under the umbrella topic of Remote sensing. Her research integrates issues of Mean squared error and Similarity in her study of Photogrammetry.

Her Precision agriculture study frequently draws connections to adjacent fields such as Crop. Her Weed control study incorporates themes from Agroforestry, Segmentation and Arable land. Her work deals with themes such as Image resolution, Classifier, Algorithm, Random forest and Crop management, which intersect with Weed.

Best Publications

  • Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV

    J. Torres-Sánchez;J.M. Peña;A.I. de Castro;F. López-Granados

  • Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

    José Manuel Peña;Jorge Torres-Sánchez;Ana Isabel de Castro;Maggi Kelly

  • Weed detection for site-specific weed management: mapping and real-time approaches

    F López-Granados

  • Configuration and Specifications of an Unmanned Aerial Vehicle (UAV) for Early Site Specific Weed Management

    Jorge Torres-Sánchez;Francisca López-Granados;Ana Isabel De Castro;José Manuel Peña-Barragán

  • Spatial variability of agricultural soil parameters in southern Spain

    Francisca López-Granados;Montserrat Jurado-Expósito;Silvia Atenciano;Alfonso García-Ferrer

  • Object- and pixel-based analysis for mapping crops and their agro-environmental associated measures using QuickBird imagery

    Isabel Luisa Castillejo-González;Francisca López-Granados;Alfonso García-Ferrer;José Manuel Peña-Barragán

  • An automatic object-based method for optimal thresholding in UAV images

    J. Torres-Sánchez;F. López-Granados;J.M. Peña

  • Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat

    D. Gómez-Candón;A. I. De Castro;F. López-Granados

  • An Automatic Random Forest-OBIA Algorithm for Early Weed Mapping between and within Crop Rows Using UAV Imagery

    Ana I. de Castro;Jorge Torres-Sánchez;José M. Peña;Francisco Manuel Jiménez-Brenes

  • High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology

    Jorge Torres-Sánchez;Francisca López-Granados;Nicolás Serrano;Octavio Arquero

  • Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution.

    José M. Peña;Jorge Torres-Sánchez;Angélica Serrano-Pérez;Ana I. de Castro

  • Fleets of robots for environmentally-safe pest control in agriculture

    Pablo Gonzalez-de-Santos;Angela Ribeiro;Cesar Fernandez-Quintanilla;Francisca Lopez-Granados

  • Object-Based Image Classification of Summer Crops with Machine Learning Methods

    José M. Peña;Pedro Antonio Gutiérrez;César Hervás-Martínez;Johan Six

  • A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method

    M. Pérez-Ortiz;J.M. Peña;P.A. Gutiérrez;J. Torres-Sánchez

  • Early season weed mapping in sunflower using UAV technology: variability of herbicide treatment maps against weed thresholds

    Francisca López-Granados;Jorge Torres-Sánchez;Angélica Serrano-Pérez;Ana I. de Castro

  • Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery

    María Pérez-Ortiz;José Manuel Peña;Pedro Antonio Gutiérrez;Jorge Torres-Sánchez

  • Using geostatistical and remote sensing approaches for mapping soil properties

    F. López-Granados;M. Jurado-Expósito;J.M. Peña-Barragán;L. García-Torres

  • Assessing Optimal Flight Parameters for Generating Accurate Multispectral Orthomosaicks by UAV to Support Site-Specific Crop Management

    Francisco-Javier Mesas-Carrascosa;Jorge Torres-Sánchez;Inmaculada Clavero-Rumbao;Alfonso García-Ferrer

  • Is the current state of the art of weed monitoring suitable for site-specific weed management in arable crops?

    C. Fernández‐Quintanilla;J. M. Peña;Dionisio Andújar;J. Dorado

  • Assessing UAV-collected image overlap influence on computation time and digital surface model accuracy in olive orchards

    Jorge Torres-Sánchez;Francisca López-Granados;Irene Borra-Serrano;José Manuel Peña

Frequent Co-Authors

César Hervás-Martínez
César Hervás-Martínez University of Córdoba
Pedro Antonio Gutiérrez
Pedro Antonio Gutiérrez University of Córdoba
Maggi Kelly
Maggi Kelly University of California, Berkeley
Johan Six
Johan Six ETH Zurich
Gonzalo Pajares
Gonzalo Pajares Complutense University of Madrid
Amparo Alonso-Betanzos
Amparo Alonso-Betanzos University of A Coruña
Angela Ribeiro
Angela Ribeiro Spanish National Research Council

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Best Scientists Citing Francisca López-Granados

Trending Scientists

Recently Published Articles