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A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs
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 a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492524/ https://www.ncbi.nlm.nih.gov/pubmed/28621740 http://dx.doi.org/10.3390/s17061411 |
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author | Calvario, Gabriela Sierra, Basilio Alarcón, Teresa E. Hernandez, Carmen Dalmau, Oscar |
author_facet | Calvario, Gabriela Sierra, Basilio Alarcón, Teresa E. Hernandez, Carmen Dalmau, Oscar |
author_sort | Calvario, Gabriela |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5492524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54925242017-07-03 A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs Calvario, Gabriela Sierra, Basilio Alarcón, Teresa E. Hernandez, Carmen Dalmau, Oscar Sensors (Basel) Article 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. MDPI 2017-06-16 /pmc/articles/PMC5492524/ /pubmed/28621740 http://dx.doi.org/10.3390/s17061411 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Calvario, Gabriela Sierra, Basilio Alarcón, Teresa E. Hernandez, Carmen Dalmau, Oscar A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs |
title | A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs |
title_full | A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs |
title_fullStr | A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs |
title_full_unstemmed | A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs |
title_short | A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs |
title_sort | multi-disciplinary approach to remote sensing through low-cost uavs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492524/ https://www.ncbi.nlm.nih.gov/pubmed/28621740 http://dx.doi.org/10.3390/s17061411 |
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