0000000000790775
AUTHOR
José Gomis-cebolla
showing 9 related works from this author
LST retrieval algorithm adapted to the Amazon evergreen forests using MODIS data
2018
Abstract Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Considering the importance of this biome and climate change projections, the monitoring of vegetation status of these rainforests becomes of significant importance. In this context vegetation temperature is presented as a key variable linked with plant physiology. In particular some studies showed the relationship between this variable and the CO2 absorption capacity and biomass loss of these tropical forests proving the potential use of vegetation temperature in the monitoring of the vegetation status. Nevertheless, the use of thermal remote sensing data over tropical forests still has so…
Sentinel 2 and 3 for Temperature Monitoring Over the Amazon
2018
In this work we present results of an early assessment of the performance of the Land Surface Temperature (LST) product retrieved from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellite (S3/SLSTR) over the Amazon basin. Results are validated from comparison of S3/SLSTR retrievals against in situ measurements of surface temperature collected over one instrumented site in the Peruvian Amazon. The validation exercise was performed on the standard S3/SLSTR Level-2 LST product as well as on a dedicated LST split-window algorithm with an explicit dependence on surface emissivity. Surface emissivity maps obtained from the high spatial resolution of S2/MSI are…
Episodios térmicos extremos analizados con productos MODIS durante el invierno boreal (2000-2016)
2016
<p>The beginning of the XXI century is characterized by the intensification of the existing global warming situation and for a series of drastic global meteorological events. Particularly, during the winter season a series of extreme temperature episodes affecting large areas of the northern hemisphere have been produced. In this paper, these episodes are studied by analyzing the thermal anomalies spatial distribution and temporal evolution in the period 2001-2016 from Land Surface Temperature (LST) products obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The study regions considered in this investigation are eight of the northern hemisphere. The result…
MODIS probabilistic cloud masking over the Amazonian evergreen tropical forests: a comparison of machine learning-based methods
2019
Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Satellite remote sensing is presented as a feasible means in order to monitor these forests. In particu...
Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests
2019
Abstract Evapotranspiration (ET) is considered a key variable in the understanding of the Amazonian tropical forests and their response to climate change. Remote-Sensing (RS) based evapotranspiration models are presented as a feasible means in order to provide accurate spatially-distributed ET estimates over this region. In this work, the performance of four commonly used ET RS models was evaluated over Amazonia using Moderate Resolution Imaging Spectroradiometer (MODIS) data. RS models included i) Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), ii) Penman-Monteith MODIS operative parametrization (PM-Mu), iii) Surface Energy Balance System (SEBS), and iv) Satellite Application Facility…
Using MSG-Seviri Data to Monitor the Planet in Near Real Time
2018
The SEVIRI (Spinning Enhanced Visible and Infra Red Imager) instrument onboard MSG (Meteosat Second Generation) satellite series provides valuable data for the observation of our planet. We describe here the processing chain implemented at the Global Change Unit of the University of Valencia to provide information such as vegetation index, temperatures of both land and sea, synthetic quicklooks for an easy interpretation of the data as well as fire hotspots. Vegetation index and temperature data are available for download from a dedicated portal updated every 3 hours with the most recent processed data. Additionally, a web page displays this information for a non scientific public in near r…
Vicarious Calibration of Landsat-8 Thermal Data Collections and its Influence on Split-Window Algorithm Validation
2018
Landsat 8 (L8) satellite was launched on February 11, 2013 with two thermal bands located in the atmospheric window between $10-12\ \mu \mathrm{m}$ . Continuous monitoring of the Thermal Infrared Sensor (TIRS) onboard of L8 was performed over two Spanish test sites – Barrax and Donana – in order to contribute to the quality of TIRS data. In this work, a Vicarious Calibration (VC) of the TIRS bands was performed between years 2013–2016 in order to assess the new Stray Light (SL) data correction. The results of VC show us that band 10 and 11 provide accurate results (bias near to zero, and precision around 0.8 K) which is an improvement – especially for band 11 – in comparison to preprocessed…
MODIS-Based Monthly LST Products over Amazonia under Different Cloud Mask Schemes
2016
One of the major problems in the monitoring of tropical rainforests using satellite imagery is their persistent cloud coverage. The use of daily observations derived from high temporal resolution sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS), could potentially help to mitigate this issue, increasing the number of clear-sky observations. However, the cloud contamination effect should be removed from these results in order to provide a reliable description of these forests. In this study the available MODIS Land Surface Temperature (LST) products have been reprocessed over the Amazon Basin (10 N–20 S, 80 W–45 W) by introducing different cloud masking schemes. The mont…
MODIS probabilistic cloud masking over the Amazonian evergreen tropical forests: a comparison of machine learning-based methods
2019
Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Satellite remote sensing is presented as a feasible means in order to monitor these forests. In particular, the Moderate Resolution Imaging Spectroradiometer (MODIS) is amongst major tools for studying this region. Nevertheless, MODIS operative surface variable retrieval was reported to be impacted by cloud contamination effects. A proper cloud masking is a major consideration in order to ensure accuracy when analysing Amazonian tropical forests current and future status. In the present study, the potential of supervised machine learning algorithms in order to overcome this issue is evaluated. In f…