A5002972103- Remote Sensing and LiDAR Applications
- 3D Surveying and Cultural Heritage
- Forest ecology and management
- Geochemistry and Geologic Mapping
- Soil Geostatistics and Mapping
- Infrastructure Maintenance and Monitoring
- Remote Sensing in Agriculture
- Mineral Processing and Grinding
- Optical measurement and interference techniques
- Air Quality and Health Impacts
- Forest Ecology and Biodiversity Studies
- Landslides and related hazards
- 3D Shape Modeling and Analysis
- Air Quality Monitoring and Forecasting
- Spectroscopy and Chemometric Analyses
- Plant Water Relations and Carbon Dynamics
- Building Energy and Comfort Optimization
- Land Use and Ecosystem Services
- Neural Networks and Applications
- Advanced Statistical Methods and Models
- Mining Techniques and Economics
- Automated Road and Building Extraction
- Fuzzy Systems and Optimization
- Leaf Properties and Growth Measurement
- Advanced Vision and Imaging
Universidad de Oviedo
2015-2024
Universidade de Vigo
2005-2024
Universidad de León
2010-2011
Centro Universitario de la Defensa
2011
Florida International University
2003
The geometrical accuracy of georeferenced digital surface models (DTM) obtained from images captured by micro-UAVs and processed using structure motion (SfM) photogrammetry depends on several factors, including flight design, camera quality, calibration, SfM algorithms georeferencing strategy. This paper focusses the critical role number location ground control points (GCP) used during stage. A challenging case study involving an area 1200+ ha, 100+ GCP 2500+ photos was used. Three thousand,...
This study presents a comparison between the use of wearable laser scanning (WLS) and terrestrial (TLS) devices for automatic tree detection with an estimation two dendrometric variables: diameter at breast height (DBH) total (TH). Operative processes data collection forest inventory are described in detail. The approach used is based on clustering points belonging to each individual tree, isolation trunks, iterative fitting circles DBH calculation computation TH tree. TLS WLS point clouds...
Detecting and modeling urban furniture are of particular interest for management the development autonomous driving systems. This paper presents a novel method detecting classifying vertical objects trees from unstructured three-dimensional mobile laser scanner (MLS) or terrestrial (TLS) point cloud data. The includes an automatic initial segmentation to remove parts original that not objects, by means geometric index based on features cloud. Vertical object detection is carried out through...
Abstract Accurate and efficient forest inventories are essential for effective management conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed precise 3D measurements forested areas. Several algorithms methods have been developed in last years to automatically derive tree metrics from such terrestrial/ground-based point clouds. However, few attempts made make these automatic accessible wider audiences by producing software...
Mobile laser scanning (MLS) is a modern and powerful technology capable of obtaining massive point clouds objects in short period time. Although this nowadays being widely applied urban cartography 3D city modelling, it has some drawbacks that need to be avoided order strengthen it. One the most important shortcomings MLS data concerned with fact provides an unstructured dataset whose processing very time-consuming. Consequently, there growing interest developing algorithms for automatic...
Accurate forest inventories are crucial for sustainable management, but processing ground-based LiDAR and photogrammetric point clouds remains complex inaccessible to many users. 3DFin addresses this gap as a fully automated, open-source software extracting key tree metrics—tree height, diameter at breast height (DBH), location—from Terrestrial Laser Scanning (TLS), Mobile (MLS), photogrammetry-derived clouds. Unlike existing tools, is designed complete ease of use,...
Concentrations of certain chemical elements in plants need to be controlled ensure good crop quality and yield. However, laboratory analyses are usually time-consuming expensive. Although indirect methods based on leaf reflectance both faster less expensive, most indexes that only take into account wavelengths fail full advantage the entire curve depicted by modern hyperspectral sensors. This paper applies two functional prediction models, i.e., linear regression nonparametric methods,...