Next Article in Journal
High Sensitivity Refractometer Based on Reflective Smf-Small Diameter No Core Fiber Structure
Previous Article in Journal
Root System Water Consumption Pattern Identification on Time Series Data
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1411; doi:10.3390/s17061411

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs

1
Departamento de Ciencias de la Computación e Inteligencia Artificial, Universidad del País Vasco UPV/EHU, 20018 Donostia-San Sebastián, Spain
2
Centro Universitario de los Valles, Carretera Guadalajara - Ameca Km. 45.5, CP 46600 Ameca, Jalisco, México
3
Centro de Investigación en Matemáticas, Jalisco SN, Col. Valenciana, CP 36240, Guanajuato, México
*
Author to whom correspondence should be addressed.
Academic Editor: Felipe Gonzalez Toro
Received: 31 March 2017 / Revised: 6 June 2017 / Accepted: 9 June 2017 / Published: 16 June 2017
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [33352 KB, uploaded 16 June 2017]   |  

Abstract

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow. View Full-Text
Keywords: UAV; data mining; computer vision; geomatics; agave monitoring UAV; data mining; computer vision; geomatics; agave monitoring
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Calvario, G.; Sierra, B.; Alarcón, T.E.; Hernandez, C.; Dalmau, O. A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs. Sensors 2017, 17, 1411.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top