Dr. José González-Piqueras Profile

Dr. José González-Piqueras

Research Staff at IDR-UCLM

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Publications (6)

Proceedings Article | 21 October 2019 Presentation + Paper

Determining crop phenology for different varieties of barley and wheat on intensive plots using proximal remote sensing

J. González-Piqueras, F. Jara, H. López, J. Villodre, D. Hernández, A. Calera, R. López-Urrea, J. Sánchez

Proceedings Volume 11149, 111490H (2019) https://doi.org/10.1117/12.2533091

KEYWORDS: Agriculture, Remote sensing, Vegetation, Environmental management, Statistical analysis, Meteorology, Genetics, Humidity, Climatology, Sensors

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Crop phenology is a key parameter for precision farming and necessary in crop models for improving water and nutrients management in space and time. It has been traditionally determined at field, with observations of biophysical parameters in correspondence with different time-scales, but depending on plot size, it is not full representative of the variability inside it and of the variation between plots. Remote sensing techniques may increase the accessibility of high frequency spatialized data that in combination with meteorological information provide a tool for monitoring crops. Particularly, an important variety of sensors suited for agricultural applications on board of unmanned aerial systems, including spectral bands coherent with satellites and field radiometry, are being applied to describe within plot variability. With this purpose, an experiment along the year 2017 has been designed, to study the behavior of more than forty varieties of barley and wheat in an intensive experiment composed of 576 micro-plots of 1.4 × 10 m size. They have been monitored at field, registering the phenology in the BBCH scale and a complete set of soil and plant biophysical parameters in coincidence to sixteen multispectral very high-resolution images, using the number of days after sowing (NADS), the accumulated growing degree days (AGDD) and accumulated reference evapotranspiration (AcETo) as temporal scales, for studying the spatio-temporal distribution response of crop. The images were supplied with a parrot sequoia® multispectral camera, at a ground sample distance of 10 cm which allow to determine the variability into the micro-plots and obtaining representative results between them. The meteorological parameters were registered in a weather station close to the experimental area. The results show that the vegetation index in combination to the growing degree days scale or the accumulate reference evapotranspiration can set the emerging, flowering and maturity stages that are crucial inputs for management and crop models. AGDD and AcETo show a better-defined plateau between flag leave and early maturity. The ratio between the TNDVI along the reproductive phase (from BBCH = 55 to 89) and the growing cycle for barley show values of 0.31 ± 0.05 in NADS, 0.45 ± 0.03 in AGDD and 0.48 ± 0.03 in AcETo. For durum wheat the 0.32 ± 0.05 (NADS), 0.46 ± 0.03 (AGDD) and 0.49 ± 0.05 (AcETo). In case of bread wheat, the values are 0.27 ± 0.03 (NADS), 0.53 ± 0.06 (AGDD) and 0.54 ± 0.05 (AcETo). These results show that proximal remote sensing is very useful in intensive experiments as prospective techniques to explore new crop varieties that could be implanted in the experimental area and setting up the tools for satellite applications.

Proceedings Article | 27 June 2019 Paper

Ground LST measurements in the Barrax test site for the assessment of the SBAC atmospheric correction technique applied to Landsat 8-TIRS

Joan Galve, Juan Sánchez, Julio Villodre, José González-Piqueras, César Coll, Alfonso Calera

Proceedings Volume 11174, 1117411 (2019) https://doi.org/10.1117/12.2533444

KEYWORDS: Atmospheric corrections, Earth observing sensors, Landsat, Temperature metrology, Radiometry, Atmospheric modeling, Satellites, Sensors

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Proceedings Article | 27 June 2019 Paper

Downscaling MODIS land surface temperature to Sentinel-2 spatial resolution in the Barrax test site

Juan Sánchez, Joan Galve, José González-Piqueras, Ramón López-Urrea, Raquel Niclòs, Alfonso Calera

Proceedings Volume 11174, 1117410 (2019) https://doi.org/10.1117/12.2533442

KEYWORDS: Spatial resolution, MODIS, Earth observing sensors, Landsat, Radiometry, Thermography, Infrared radiation, Satellites, Agriculture

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Proceedings Article | 23 October 2012 Paper

Evapotranspiration monitoring in a vineyard using satellite-based thermal remote sensing

M. P. González-Dugo, J. González-Piqueras, I. Campos, A. Andréu, C. Balbontín, A. Calera

Proceedings Volume 8531, 85310N (2012) https://doi.org/10.1117/12.974731

KEYWORDS: Data modeling, Satellites, Radon, Temperature metrology, Vegetation, Performance modeling, Thermal remote sensing, Earth observing sensors, Heat flux, Landsat

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Proceedings Article | 24 February 2004 Paper

Estimation of crop coefficients by means of optimized vegetation indices for corn

Jose Gonzalez-Piqueras, Alfonso Calera, Maria Gilabert, Andres Cuesta, Fernando De la Cruz Tercero

Proceedings Volume 5232, (2004) https://doi.org/10.1117/12.511317

KEYWORDS: Vegetation, Near infrared, Reflectivity, Humidity, Remote sensing, Agriculture, Soil science, Meteorology, Thermodynamics, Physics

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Proceedings Article | 11 December 1998 Paper

Designing a generalized soil-adjusted vegetation index (GESAVI)

M. Gilabert, Jose Gonzalez Piqueras, Joan Garcia-Haro, J. Melia

Proceedings Volume 3499, (1998) https://doi.org/10.1117/12.332774

KEYWORDS: Vegetation, Reflectivity, Near infrared, Soil science, Data modeling, Remote sensing, Optical properties, Signal to noise ratio, Multiple scattering, Information operations

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Showing 5 of 6 publications

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