Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles
The development of lightweight sensors compatible with mini unmanned aerial vehicles (UAVs) has expanded the agronomical applications of remote sensing. Of particular interest in this paper are thermal sensors based on lightweight microbolometer technology. These are mainly used to assess crop water...
| Main Authors: | , , , , , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
MDPI
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/7317 |
| _version_ | 1789406368627687424 |
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| author | Mesas Carrascosa, Francisco Javier Pérez Porras, Fernando Meroño de Larriva, José Emilio Mena Frau, Carlos Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio Jesús García Ferrer, Alfonso |
| author_facet | Mesas Carrascosa, Francisco Javier Pérez Porras, Fernando Meroño de Larriva, José Emilio Mena Frau, Carlos Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio Jesús García Ferrer, Alfonso |
| author_sort | Mesas Carrascosa, Francisco Javier |
| collection | DSpace |
| description | The development of lightweight sensors compatible with mini unmanned aerial vehicles (UAVs) has expanded the agronomical applications of remote sensing. Of particular interest in this paper are thermal sensors based on lightweight microbolometer technology. These are mainly used to assess crop water stress with thermal images where an accuracy greater than 1 °C is necessary. However, these sensors lack precise temperature control, resulting in thermal drift during image acquisition that requires correction. Currently, there are several strategies to manage thermal drift effect. However, these strategies reduce useful flight time over crops due to the additional in-flight calibration operations. This study presents a drift correction methodology for microbolometer sensors based on redundant information from multiple overlapping images. An empirical study was performed in an orchard of high-density hedgerow olive trees with flights at different times of the day. Six mathematical drift correction models were developed and assessed to explain and correct drift effect on thermal images. Using the proposed methodology, the resulting thermally corrected orthomosaics yielded a rate of error lower than 1° C compared to those where no drift correction was applied. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-7317 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-73172023-04-12T19:29:22Z Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles Mesas Carrascosa, Francisco Javier Pérez Porras, Fernando Meroño de Larriva, José Emilio Mena Frau, Carlos Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio Jesús García Ferrer, Alfonso UAV uncooled thermal sensor precision agriculture thermal orthomosaic The development of lightweight sensors compatible with mini unmanned aerial vehicles (UAVs) has expanded the agronomical applications of remote sensing. Of particular interest in this paper are thermal sensors based on lightweight microbolometer technology. These are mainly used to assess crop water stress with thermal images where an accuracy greater than 1 °C is necessary. However, these sensors lack precise temperature control, resulting in thermal drift during image acquisition that requires correction. Currently, there are several strategies to manage thermal drift effect. However, these strategies reduce useful flight time over crops due to the additional in-flight calibration operations. This study presents a drift correction methodology for microbolometer sensors based on redundant information from multiple overlapping images. An empirical study was performed in an orchard of high-density hedgerow olive trees with flights at different times of the day. Six mathematical drift correction models were developed and assessed to explain and correct drift effect on thermal images. Using the proposed methodology, the resulting thermally corrected orthomosaics yielded a rate of error lower than 1° C compared to those where no drift correction was applied. 2020-01-16T08:00:35Z 2020-01-16T08:00:35Z 2018-04-17 info:eu-repo/semantics/article 2072-4292 http://hdl.handle.net/10835/7317 en https://www.mdpi.com/2072-4292/10/4/615 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | UAV uncooled thermal sensor precision agriculture thermal orthomosaic Mesas Carrascosa, Francisco Javier Pérez Porras, Fernando Meroño de Larriva, José Emilio Mena Frau, Carlos Agüera Vega, Francisco Carvajal Ramírez, Fernando Martínez Carricondo, Patricio Jesús García Ferrer, Alfonso Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles |
| title | Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles |
| title_full | Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles |
| title_fullStr | Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles |
| title_full_unstemmed | Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles |
| title_short | Drift Correction of Lightweight Microbolometer Thermal Sensors On-Board Unmanned Aerial Vehicles |
| title_sort | drift correction of lightweight microbolometer thermal sensors on-board unmanned aerial vehicles |
| topic | UAV uncooled thermal sensor precision agriculture thermal orthomosaic |
| url | http://hdl.handle.net/10835/7317 |
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