scholarly journals Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations

2016 ◽  
Vol 8 (7) ◽  
pp. 587 ◽  
Author(s):  
Miriam Pablos ◽  
José Martínez-Fernández ◽  
María Piles ◽  
Nilda Sánchez ◽  
Mercè Vall-llossera ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Observations ◽  
Temperature Dynamics ◽  
Multi Temporal

scholarly journals VALIDATION AND UPSCALING OF SOIL MOISTURE SATELLITE PRODUCTS IN ROMANIA

2016 ◽  
Vol XLI-B2 ◽  
pp. 313-317 ◽  
Author(s):  
I. Sandric ◽  
A. Diamandi ◽  
N. Oana ◽  
D. Saizu ◽  
C. Vasile ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Soil Texture ◽  
Soil Type ◽  
Land Surface ◽  
Vegetation Type ◽  
In Situ Measurements ◽  
Wide Range

The study presents the validation of SMOS soil moisture satellite products for Romania. The validation was performed with in-situ measurements spatially distributed over the country and with in-situ measurements concentrated in on small area. For country level a number of 20 stations from the national meteorological observations network in Romania were selected. These stations have in-situ measurements for soil moisture in the first 5 cm of the soil surface. The stations are more or less distributed in one pixel of SMOS, but it has the advantage that covers almost all the country with a wide range of environmental conditions. Additionally 10 mobile soil moisture measurements stations were acquired and installed. These are spatially concentrated in one SMOS pixel in order to have a more detailed validation against the soil type, soil texture, land surface temperature and vegetation type inside one pixel. The results were compared and analyzed for each day, week, season, soil type, and soil texture and vegetation type. Minimum, maximum, mean and standard deviation were extracted and analyzed for each validation criteria and a hierarchy of those were performed. An upscaling method based on the relations between soil moisture, land surface temperature and vegetation indices was tested and implemented. The study was financed by the Romanian Space Agency within the framework of ASSIMO project <a href="http://assimo.meteoromania.ro"target="_blank">http://assimo.meteoromania.ro</a>.

Downscaling of L-Band microwave using Sentinel-3 land surface temperature

2020 ◽  
Author(s):  
Ahmad Al Bitar ◽  
Nitu Ojha ◽  
Chiara Corbari ◽  
Olivier Merlin ◽  
Yann Kerr ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Combined Use ◽  
Combining Data ◽  
Global Coverage ◽  
L Band ◽  
Comparative Results

<p><strong>Downscaling of L-Band microwave using Sentinel-3 land surface temperature</strong></p><p>A large number of agricultural and water management applications require sub-kilometric frequent revisit surface Soil Moisture (SM) observations. L-band passive radiometer acquisitions are especially suited for soil moisture retrieval since they are less susceptible to attenuation by vegetation than active methods and are less sensitive to surface roughness than C or X – bands. However, while providing a 3 days global coverage for ascending and descending orbits with the currently available missions (SMOS/SMAP) the spatial resolution of the space-borne L-band radiometers is of ~40 km. Downscaling technics have been extensively used to increase the resolution of the SM products by combining data from optical (Merlin et al. 2012) and SAR sensors (Tomer et al. 2015). Here, we use land surface temperature data from the Sentinel-3 sensors to disaggregate the SMOS SM product into the DISPATCH algorithm. DISPATCH is based on the link between the evaporative efficiency and the SM (Merlin et al. 2010). The exercices is applied over Italy and compared to in-situ SM observations and model outputs over two sites in Northern and southrn Italy (Chiese and Capitanata). The algorithm is run using  MODIS and the Sentinel-3 data for a comparative results. The potential of the combined use of Sentienl-3/MODIS and SMOS/SMAP is also investigate. The current study extends the application of an existing algorithm to new operational data from the Copernicus programe while accessing the advantages and ceavates. </p>

scholarly journals VALIDATION AND UPSCALING OF SOIL MOISTURE SATELLITE PRODUCTS IN ROMANIA

2016 ◽  
Vol XLI-B2 ◽  
pp. 313-317
Author(s):  
I. Sandric ◽  
A. Diamandi ◽  
N. Oana ◽  
D. Saizu ◽  
C. Vasile ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Soil Texture ◽  
Soil Type ◽  
Land Surface ◽  
Vegetation Type ◽  
In Situ Measurements ◽  
Wide Range

The study presents the validation of SMOS soil moisture satellite products for Romania. The validation was performed with in-situ measurements spatially distributed over the country and with in-situ measurements concentrated in on small area. For country level a number of 20 stations from the national meteorological observations network in Romania were selected. These stations have in-situ measurements for soil moisture in the first 5 cm of the soil surface. The stations are more or less distributed in one pixel of SMOS, but it has the advantage that covers almost all the country with a wide range of environmental conditions. Additionally 10 mobile soil moisture measurements stations were acquired and installed. These are spatially concentrated in one SMOS pixel in order to have a more detailed validation against the soil type, soil texture, land surface temperature and vegetation type inside one pixel. The results were compared and analyzed for each day, week, season, soil type, and soil texture and vegetation type. Minimum, maximum, mean and standard deviation were extracted and analyzed for each validation criteria and a hierarchy of those were performed. An upscaling method based on the relations between soil moisture, land surface temperature and vegetation indices was tested and implemented. The study was financed by the Romanian Space Agency within the framework of ASSIMO project <a href="http://assimo.meteoromania.ro"target="_blank">http://assimo.meteoromania.ro</a>.

Plot-scale retrieval of land surface temperature and emissivity estimation

2021 ◽  
Author(s):  
Gitanjali Thakur ◽  
Stan Schymanski ◽  
Kaniska Mallick ◽  
Ivonne Trebs
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Longwave Radiation ◽  
Landscape Scale ◽  
The Earth ◽  
Downwelling Longwave Radiation

&lt;p&gt;The surface energy balance (SEB) is defined as the balance between incoming energy from the sun and outgoing energy from the Earth&amp;#8217;s surface. All components of the SEB depend on land surface temperature (LST). Therefore, LST is an important state variable that controls the energy and water exchange between the Earth&amp;#8217;s surface and the atmosphere. LST can be estimated radiometrically, based on the infrared radiance emanating from the surface. At the landscape scale, LST is derived from thermal radiation measured using&amp;#160; satellites.&amp;#160; At the plot scale, eddy covariance flux towers commonly record downwelling and upwelling longwave radiation, which can be inverted to retrieve LST&amp;#160; using the grey body equation :&lt;br&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; R&lt;sub&gt;lup&lt;/sub&gt; = &amp;#949;&amp;#963; T&lt;sub&gt;s&lt;/sub&gt;&lt;sup&gt;4&lt;/sup&gt; + (1 &amp;#8722; &amp;#949;) R&lt;sub&gt; ldw&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; &lt;/sub&gt;(1)&lt;br&gt;where R&lt;sub&gt;lup&lt;/sub&gt; is the upwelling longwave radiation, R&lt;sub&gt;ldw&lt;/sub&gt; is the downwelling longwave radiation, &amp;#949; is the surface emissivity, &lt;em&gt;T&lt;sub&gt;s&lt;/sub&gt;&amp;#160; &lt;/em&gt;is the surface temperature and &amp;#963;&amp;#160; is the Stefan-Boltzmann constant. The first term is the temperature-dependent part, while the second represents reflected longwave radiation. Since in the past downwelling longwave radiation was not measured routinely using flux towers, it is an established practice to only use upwelling longwave radiation for the retrieval of plot-scale LST, essentially neglecting the reflected part and shortening Eq. 1 to:&lt;br&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; R&lt;sub&gt;lup&lt;/sub&gt; = &amp;#949;&amp;#963; T&lt;sub&gt;s&lt;/sub&gt;&lt;sup&gt;4 &lt;/sup&gt;&amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160;&amp;#160; (2)&lt;br&gt;Despite&amp;#160; widespread availability of downwelling longwave radiation measurements, it is still common to use the short equation (Eq. 2) for in-situ LST retrieval. This prompts the question if ignoring the downwelling longwave radiation introduces a bias in LST estimations from tower measurements. Another associated question is how to obtain the correct &amp;#949; needed for in-situ LST retrievals using tower-based measurements.&lt;br&gt;The current work addresses these two important science questions using observed fluxes at eddy covariance towers for different land cover types. Additionally, uncertainty in retrieved LST and emissivity due to uncertainty in input fluxes was quantified using SOBOL-based uncertainty analysis (SALib). Using landscape-scale emissivity obtained from satellite data (MODIS), we found that the LST&amp;#160; obtained using the complete equation (Eq. 1) is 0.5 to 1.5 K lower than the short equation (Eq. 2). Also, plot-scale emissivity was estimated using observed sensible heat flux and surface-air temperature differences. Plot-scale emissivity obtained using the complete equation was generally between 0.8 to 0.98 while the short equation gave values between 0.9 to 0.98, for all land cover types. Despite additional input data for the complete equation, the uncertainty in plot-scale LST was not greater than if the short equation was used. Landscape-scale daytime LST obtained from satellite data (MODIS TERRA) were strongly correlated with our plot-scale estimates, but on average higher by 0.5 to 9 K, regardless of the equation used. However, for most sites, the correspondence between MODIS TERRA LST and retrieved plot-scale LST estimates increased significantly if plot-scale emissivity was used instead of the landscape-scale emissivity obtained from satellite data.&lt;/p&gt;

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