applied to Plant Science

Maize extraction from UAS imagery-based point clouds 

LiDAR data in Forestry

Individual maize skeletonization by UAS

Root phenotyping by X-Ray

Soybean heights by Structure from Motion

         Terrestrial image-based modeling 

3D forestry mapping from UAS imagenery

Berry characterization by low-cost scanner


Civil Engineering with a PhD entitled 'Close-Range Photogrammetry applied to Agroforestry Engineering' from the Department of Cartographic and Land Engineering, University of Salamanca (SP, 2016). Postdoctoral studies from Delft University of Technology (The Netherlands) in the department of Geosciences and Remote Sensing (2015-2018). Active member from TIDOP research group (Geomatic Technologies for the 3D digitization and modelling of complex objects) (SP). Research staff member at Purdue University for the Institute for Plant Science, College of Agriculture (IN, USA). Currently, distinguished researcher at the University of Salamanca (SP).

Her research interests to date have been focused primarily on close-range hyperspectral photogrammetry and LiDAR by alternative platforms and specifically in computer vision and deep learning analysis by multi-sensor data fusion applied to plant science.

Keywords: Photogrammetry, Artificial Intelligence, Laser Scanning, 3D Modeling, Plant Science.

3D Rendering

3D Rendering, Image Processing and Data Fusion

Software development

  Software development to specific solutions

Design and Drafting

Design and Drafting of I+D Projects


  • From Forests to 3D Digital Models: training new generations on 3D geodata surveying and analysis (3DForTrain). The International Society for Photogrammetry and Remote Sensing Education and Capacity Building Initiative. 
  • SIMFOREST: Digital Twin to simulate Forest Dynamics due to disturbances driven by Climate Change (Fires, Invasive Plants and Diseases). Provincial Council of Ávila (SP).
  • XTRACT: A Sustainable Ecosystem for the Innovative Resource Recovery and Complex Ore Extraction. HORIZON. 2022 (UE)
  • CHAMELEON: a holistic approach to sustainable, digital EU Agriculture, Forestry, Livestock and Rural Development based on Reconfigurable Aerial Enablers and edge Artificial Intelligence-on-Demand Systems. 2022 (UE)

  • TREEADS: A holistic Fire Management Ecosystem for Prevention, Detection and Restoration of Environmental Disasters. 2022 (UE)
  • Experiments for corn breeding in the Controlled Environment Phenotyping Facility. 2021 (Bayer, USA).
  • Machine Learning-based digital innovations for in-field phenotyping. 2021 (Bayer, USA)
  • Innovations in Close and Proximal Sensing data processing pipelines to Crop Phenotyping. 2020 (USA)
  • Development of Analytical Tools for Drone-based Canopy Phenotyping in Crop Breeding. 2018 (USA)
  • Physical testing and modelling - Masonry structures. 2017 (The Netherlands)

  • Smart Irrigation from Soil Moisture Forecast using Satellite and Hydro-meteorological Modelling. 2016 (The Netherlands)
  • Managing Crop Water Saving with Enterprise Services. 2016 (The Netherlands)
  • A High-volume Fusion and Analysis Platform for Geospatial Point Clouds, Coverages and Volumetric Data Sets. 2015 (UE)
  • Radiative Transfer Models in Agronomic Scenarios by Hyperspectral Imaging. 2014 (Spain)
  • Augmented reality to Social and Emotional Learning for people with Intellectual Disability. 2014 (Ireland)
  • Energetic 3D Modeling for Smart Cities. 2013 (Spain)
Monica Herrero-Huerta, Unversity of Salamanca ( SP)
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