Dr. Manuel Arbelo Profile

Dr. Manuel Arbelo

Professor at Univ de La Laguna

SPIE Involvement:

Author

Area of Expertise:

Remote Sensing

Publications (9)

Proceedings Article | 21 October 2019 Paper

Identification of plant species of interest for beekeeping in a volcanic landscape

Francesca Marchetti, Manuel Arbelo, Yeray Brito, Andrea Alonso, Gloria Piso, Enrique Casas

Proceedings Volume 11149, 111491Q (2019) https://doi.org/10.1117/12.2537013

KEYWORDS: Principal component analysis, Hyperspectral imaging, Unmanned aerial vehicles, Vegetation, Spatial resolution, Cartography, Cameras, Image processing

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Proceedings Article | 2 November 2017 Paper

Multitemporal WorldView satellites imagery for mapping chestnut trees

F. Marchetti, M. Arbelo, J. Moreno-Ruíz, P. Hernández-Leal, A. Alonso-Benito

Proceedings Volume 10421, 104211Q (2017) https://doi.org/10.1117/12.2278655

KEYWORDS: Satellite imaging, Earth observing sensors, Satellites, Infrared sensors, Sensors, Cartography, Vegetation, Agriculture, Spatial resolution

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Proceedings Article | 25 October 2016 Paper

Satellite image based methods for fuels maps updating

Alfonso Alonso-Benito, Pedro Hernandez-Leal, Manuel Arbelo, Alejandro Gonzalez-Calvo, Jose Moreno-Ruiz, Jose Garcia-Lazaro

Proceedings Volume 9998, 999821 (2016) https://doi.org/10.1117/12.2241990

KEYWORDS: Satellites, Satellite imaging, Earth observing sensors, Electroluminescence, Landsat, Remote sensing, Sensors, Spatial resolution, Image sensors, Image classification

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Proceedings Article | 25 October 2016 Paper

Mapping species distribution of Canarian Monteverde forest by field spectroradiometry and satellite imagery

Antonio Martín-Luis, Manuel Arbelo, Pedro Hernández-Leal, Manuel Arbelo-Bayó

Proceedings Volume 9998, 99981M (2016) https://doi.org/10.1117/12.2241993

KEYWORDS: Ecosystems, Vegetation, Sensors, Satellite imaging, Earth observing sensors, Satellites, Radiometry, Remote sensing, Spatial resolution, Lanthanum

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Proceedings Article | 25 October 2016 Paper

Mapping species distribution of Canarian Monteverde forest by field spectroradiometry and satellite imagery

Antonio Martín-Luis, Manuel Arbelo, Pedro Hernández-Leal, Manuel Arbelo-Bayó

Proceedings Volume 9998, 99981M (2016) https://doi.org/10.1117/12.2241993

KEYWORDS: Ecosystems, Vegetation, Sensors, Satellite imaging, Earth observing sensors, Satellites, Radiometry, Remote sensing, Spatial resolution, Lanthanum

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Proceedings Article | 1 November 2012 Paper

Atmospheric correction models for high resolution WorldView-2 multispectral imagery: a case study in Canary Islands, Spain

J. Martin, F. Eugenio, J. Marcello, A. Medina, Juan A. Bermejo, M. Arbelo

Proceedings Volume 8534, 85340O (2012) https://doi.org/10.1117/12.974564

KEYWORDS: Atmospheric modeling, Atmospheric corrections, Reflectivity, Satellites, Sensors, Atmospheric monitoring, Image resolution, Remote sensing, Environmental monitoring, Atmospheric sensing

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The emergence of high-resolution satellites with new spectral channels and the ability to change its viewing angle has highlighted the importance of modeling the atmospheric effects. So, atmospheric correction serves a critical role in the processing of remotely sensed image data, particularly with respect to identification of pixel content. Efficient and accurate realization of images in units of reflectance, rather than radiance, has proven to be a crucial point in the pre-processing of images in remote sensing applications, acquired under a variety of measurement conditions. However, reflectance of the objects recorded by satellite sensors is generally affected by atmospheric absorption and scattering, sensor-targetillumination geometry, and sensor calibration. These normally result in distortion of the actual reflectance of the objects that subsequently affects the extraction of information from images. The use of atmospheric models has significantly improved the results of the corrections. In this study we have proceeded to make the atmospheric correction of the eight multispectral bands of high resolution WorldView-2 satellite by three different atmospherics models (COST, DOS, 6S) defining the geometry of the satellite observation, viewing angle and setting the weather conditions more suited for the acquired images of the study area (Granadilla, Canary Islands). For this purpose, the reflectance obtained by COST, DOS and 6S atmospheric correction techniques are compared with the Top of Atmosphere (TOA) reflectance. Specifically, the 6S atmospheric correction model, based on radiative transfer theory, provides patterns which describe properly atmospheric conditions in this specific study area for monitoring turbid coastal environments. To check the proper functioning of the atmospheric correction comparison was performed between ground-based measurements and corresponding obtained by the eight multispectral satellite channels through the 6S atmospheric model, with similar date, weather and lighting conditions.

Proceedings Article | 26 February 2004 Paper

Effects of geographic distribution of data used to derive satellite SST algorithms

Luis Arvelo-Valencia, Manuel Arbelo, Pedro Hernandez-Leal

Proceedings Volume 5233, (2004) https://doi.org/10.1117/12.514198

KEYWORDS: Satellites, Algorithm development, Databases, Infrared radiation, Radiometry, Statistical analysis, In situ metrology, Error analysis, Lanthanum, Space operations

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Proceedings Article | 15 December 1995 Paper

Comparison of total water vapor content obtained from TOVS-NOAA with radiosoundings data in Canary Islands zone

M. Arbelo, F. Exposito, Felix Herrera

Proceedings Volume 2582, (1995) https://doi.org/10.1117/12.228548

KEYWORDS: Infrared radiation, Satellites, Atmospheric physics, Radiometry, Meteorology, Humidity, Atmospheric sensing, Temperature metrology, Remote sensing, Physics

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Proceedings Article | 15 December 1995 Paper

Remote sensing of aerosols optical depth in Saharan dust episodes for the Canary Islands

F. Exposito, J. Diaz, M. Arbelo, Felix Herrera, Juan Perez, A. Diaz

Proceedings Volume 2582, (1995) https://doi.org/10.1117/12.228550

KEYWORDS: Aerosols, Satellites, Atmospheric particles, Ocean optics, Particles, Remote sensing, Scattering, Atmospheric optics, Channel projecting optics, Signal detection

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Showing 5 of 9 publications

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