J. Martínez-Sánchez

ORCID: 0000-0003-0320-4191
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • 3D Surveying and Cultural Heritage
  • Remote Sensing and LiDAR Applications
  • Infrastructure Maintenance and Monitoring
  • Robotics and Sensor-Based Localization
  • Advanced Optical Sensing Technologies
  • Geophysical Methods and Applications
  • Structural Health Monitoring Techniques
  • Fire effects on ecosystems
  • Landslides and related hazards
  • Remote Sensing in Agriculture
  • Optical measurement and interference techniques
  • Thermography and Photoacoustic Techniques
  • Building Energy and Comfort Optimization
  • Image Processing and 3D Reconstruction
  • Forest ecology and management
  • Image and Object Detection Techniques
  • Autonomous Vehicle Technology and Safety
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Flood Risk Assessment and Management
  • Additive Manufacturing and 3D Printing Technologies
  • Traffic Prediction and Management Techniques
  • 3D Modeling in Geospatial Applications
  • Conservation Techniques and Studies
  • Plasma and Flow Control in Aerodynamics
  • Isotope Analysis in Ecology

Universidade de Vigo
2015-2024

University of Córdoba
2024

Mexican Institute of Petroleum
2023

Mexican Academy of Sciences
2023

Centro de Estudios Andaluces
2018

Universitat Politècnica de Catalunya
2013

Universidad de Valladolid
2007-2011

3D models of indoor environments are increasingly gaining importance due to the wide range applications which they can be subjected: from redesign and visualization monitoring simulation. These usually exist only for newly constructed buildings; therefore, development automatic approaches reconstructing indoors imagery and/or point clouds make process easier, faster cheaper. Among constructive elements defining a building interior, doors very common their detection useful either knowing...

10.3390/s150203491 article EN cc-by Sensors 2015-02-03

10.1016/j.isprsjprs.2016.11.011 article EN ISPRS Journal of Photogrammetry and Remote Sensing 2016-12-05

In the near future, communication between autonomous cars will produce a network of sensors that allow us to know state roads in real time. Lidar technology, upon which most are based, allows acquisition 3D geometric information environment. The objective this work is use point clouds acquired by Mobile Laser Scanning (MLS) segment main elements road environment (road surface, ditches, guardrails, fences, embankments, and borders) through PointNet. Previously, cloud was automatically divided...

10.3390/s19163466 article EN cc-by Sensors 2019-08-08

The optimization of forest management in roadsides is a necessary task terms wildfire prevention order to mitigate their effects. Forest fire risk assessment identifies high-risk locations, while providing decision-making support about vegetation for firefighting. In this study, nine relevant parameters: elevation, slope, aspect, road distance, settlement fuel model types, normalized difference index (NDVI), weather (FWI), and historical regimes, were considered as indicators the likelihood...

10.3390/rs12223705 article EN cc-by Remote Sensing 2020-11-11

Abstract This article proposes a method to semiautomatically extract the road axis through mobile LiDAR system, recent popular technology for transportation‐related applications, estimation and even enhance driver safety. In particular, approach developed has two components: (1) feature extraction from data model axis, (2) of horizontal alignment that meets requirements practice transportation authority. Given massive complex character captured by hierarchical (coarse‐to‐fine) robust...

10.1111/mice.12087 article EN Computer-Aided Civil and Infrastructure Engineering 2014-09-10

Macroalgae are a fundamental component of coastal ecosystems and play key role in shaping community structure functioning. currently threatened by diverse stressors, particularly climate change invasive species, but they do not all respond the same way to stressors. Effective methods collecting qualitative quantitative information essential enable better, more efficient management macroalgae. Acquisition high-resolution images, which macroalgae can be distinguished on basis their texture...

10.1080/01431161.2020.1842543 article EN International Journal of Remote Sensing 2020-12-20
Coming Soon ...