Publicaciones en colaboración con investigadores/as de Swansea University (12)

2023

  1. 3D Point Cloud Semantic Segmentation Through Functional Data Analysis

    Journal of Agricultural, Biological, and Environmental Statistics

  2. Optimal bucking of stems from terrestrial laser scanning data to maximize forest value

    Scandinavian Journal of Forest Research, Vol. 38, Núm. 3, pp. 174-188

2022

  1. AI applications in forest monitoring need remote sensing benchmark datasets

    Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

  2. Automatic Assessment of Individual Stem Shape Parameters in Forest Stands from TLS Point Clouds: Application in Pinus pinaster

    Forests, Vol. 13, Núm. 3

  3. Supporting proactive planning for climate change adaptation and conservation using an attributed road-river structure dataset

    Journal of Environmental Management, Vol. 321

2021

  1. A distance correlation approach for optimum multiscale selection in 3d point cloud classification

    Mathematics, Vol. 9, Núm. 12

  2. An algorithm for the automatic parametrization of wood volume equations from Terrestrial Laser Scanning point clouds: application in Pinus pinaster

    GIScience and Remote Sensing, Vol. 58, Núm. 7, pp. 1130-1150

  3. Influence of the Number and Spatial Distribution of Ground Control Points in the Accuracy of UAV-SfM DEMs: An Approach Based on Generalized Additive Models

    IEEE Transactions on Geoscience and Remote Sensing, Vol. 59, Núm. 12, pp. 10618-10627

2020

  1. Assessing canopy responses to thinnings for sweet chestnut coppice with time-series vegetation indices derived from Landsat-8 and Sentinel-2 imagery

    Remote Sensing, Vol. 12, Núm. 18

  2. Automatic delineation of forest patches in highly fragmented landscapes using coloured point clouds

    Forests, Vol. 11, Núm. 2

  3. Estimating fuel loads and structural characteristics of shrub communities by using terrestrial laser scanning

    Remote Sensing, Vol. 12, Núm. 22, pp. 1-21

2019

  1. Structure from Motion Photogrammetry in Forestry: a Review

    Current Forestry Reports, Vol. 5, Núm. 3, pp. 155-168