400 research outputs found
Remote Sensing Monitoring of Land Surface Temperature (LST)
This book is a collection of recent developments, methodologies, calibration and validation techniques, and applications of thermal remote sensing data and derived products from UAV-based, aerial, and satellite remote sensing. A set of 15 papers written by a total of 70 authors was selected for this book. The published papers cover a wide range of topics, which can be classified in five groups: algorithms, calibration and validation techniques, improvements in long-term consistency in satellite LST, downscaling of LST, and LST applications and land surface emissivity research
Earth observation-based operational estimation of soil moisture and evapotranspiration for agricultural crops in support of sustainable water management
Global information on the spatio-temporal variation of parameters driving the Earthâs terrestrial water and energy cycles, such as evapotranspiration (ET) rates and surface soil moisture (SSM), is of key significance. The water and energy cycles underpin global food and water security and need to be fully understood as the climate changes. In the last few decades, Earth Observation (EO) technology has played an increasingly important role in determining both ET and SSM. This paper reviews the state of the art in the use specifically of operational EO of both ET and SSM estimates. We discuss the key technical and operational considerations to derive accurate estimates of those parameters from space. The review suggests significant progress has been made in the recent years in retrieving ET and SSM operationally; yet, further work is required to optimize parameter accuracy and to improve the operational capability of services developed using EO data. Emerging applications on which ET/SSM operational products may be included in the context specifically in relation to agriculture are also highlighted; the operational use of those operational products in such applications remains to be seen
A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data
An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements
Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products
This study assesses the accuracy of estimating daily grass reference evapotranspiration (PM-ETo) using daily
shortwave radiation (Rs) and reference evapotranspiration (ETREF) products provided by the Meteosat Second
Generation (MSG) geostationary satellite delivered by the Satellite Applications Facility on Land Surface Analysis
(LSA-SAF) framework. The accuracy of using reanalysis ERA5 shortwave radiation data (Rs ERA5) provided by the
European Center for Medium-Range Weather Forecasts (ECMWF) is also evaluated. The assessments were performed
using observed weather variables at 37 weather stations distributed across continental Portugal, where
climate conditions range from semi-arid to humid, and 12 weather stations located in Azores islands, characterized
by humid, windy and often cloudy conditions. This studyâs use of data from a variety of climate
conditions contributed to a unique and innovative assessment of the usability of LSA-SAF and ERA5 products for
ETo estimation. The first assessment focused on comparing LSA-SAF estimates of Rs (Rs LSA-SAF) against ground
stations (Rs ground). The results showed a good matching between the two Rs data sets for continental Portugal but
a tendency for Rs LSA-SAF to under-estimate Rs ground in the cloudy islands of Azores. ETo values computed using
Rs LSA-SAF data and observed temperature, humidity and wind speed (ETo LSA-SAF) were then compared with PMETo
estimates with ground-based data, which were used as benchmark; input data of temperature and humidity
needed for PM-ETo were quality checked for surface aridity effects. It was observed that ETo LSA-SAF is strongly
correlated with PM-ETo (R2 > 0.97) for most locations in continental Portugal, with regression coefficient of a
linear regression forced to the origin ranging between 0.95 and 1.05, mean root mean square error (RMSE)
of 0.13 mm d 1, and Nash and Sutcliff efficiency of modeling (EF) above 0.95. For most Azores locations,
ETo LSA-SAF over-estimated PM-ETo. This is likely a consequence of the high spatio-temporal heterogeneity of
weather conditions that occur in these oceanic islands together with the different footprints of satellite (averaged
over the pixel) and station observations. Reanalysis ERA5 shortwave radiation data presented similar behavior to
the LSA-SAF products, however with slightly lower accuracy. The daily LSA-SAF ETREF product (ETREF LSA-SAF)
was assessed and results have shown a good accuracy of this product, with acceptable RMSE and high EF values,
for continental Portugal but a low accuracy for the Azores islands. A simplified bias correction approach
was shown to improve both ETo derived from the LSA-SAF products, namely for Azores stations, which seem
to be representative of smaller areas. The use of the FAO-PM temperature approach (PMT) was also assessed
using the Rs LSA-SAF and Rs ERA5 data, which showed a superiority of the LSA-SAF product for ETo estimations
(ETo PMT LSA-SAF). No significant differences (p < 0.05) were observed in terms of the median value of the RMSE
when adopting ETo PMT and ETREF LSA-SAF. Differently, results showed that using the Rs LSA-SAF in the PMT
approach (ETo PMT LSA-SAF) produces significantly better RMSE results than ETo PMT and ETREF LSA-SAF. Overall, the
performed assessment allows concluding that the use of Rs LSA-SAF, and to a lesser extent the use of the
Rs ERA5, highly improves the accuracy of computation of ETo when Rs observations are not available, including
when only temperature data are accessible. The use of the ETREF LSA-SAF product is a good alternative when observed weather data are not availableinfo:eu-repo/semantics/publishedVersio
Estimation of hourly land surface heat fluxes over the Tibetan Plateau by the combined use of geostationary and polar-orbiting satellites
Estimation of land surface heat fluxes is important for
energy and water cycle studies, especially on the Tibetan Plateau (TP),
where the topography is unique and the landâatmosphere interactions are
strong. The land surface heating conditions also directly influence the
movement of atmospheric circulation. However, high-temporal-resolution
information on the plateau-scale land surface heat fluxes has been lacking for a
long time, which significantly limits the understanding of diurnal
variations in landâatmosphere interactions. Based on geostationary and polar-orbiting satellite data, the surface energy balance system (SEBS) was used
in this paper to derive hourly land surface heat fluxes at a spatial
resolution of 10 km. Six stations scattered throughout the TP and equipped
for flux tower measurements were used to perform a cross-validation. The
results showed good agreement between the derived fluxes and in situ
measurements through 3738 validation samples. The root-mean-square errors
(RMSEs) for net radiation flux, sensible heat flux, latent heat flux and
soil heat flux were 76.63, 60.29, 71.03 and
37.5 W mâ2, respectively; the derived results were also found to be
superior to the Global Land Data Assimilation System (GLDAS) flux products
(with RMSEs for the surface energy balance components of 114.32,
67.77, 75.6 and 40.05 W mâ2, respectively). The
diurnal and seasonal cycles of the land surface energy balance components
were clearly identified, and their spatial distribution was found to be
consistent with the heterogeneous land surface conditions and the general
hydrometeorological conditions of the TP.</p
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