scholarly journals An original interpretation of the wet edge of the surface temperature–albedo space to estimate crop evapotranspiration (SEB-1S), and its validation over an irrigated area in northwestern Mexico

2013 ◽  
Vol 17 (9) ◽  
pp. 3623-3637 ◽  
Author(s):  
O. Merlin
Keyword(s):  
Linear Regression ◽  
Surface Temperature ◽  
Thermal Emission ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Available Energy ◽  
Irrigated Area ◽  
Green Vegetation ◽  
Northwestern Mexico ◽  
T Values

Abstract. The space defined by the pair surface temperature (T) and surface albedo (α), and the space defined by the pair T and fractional green vegetation cover (fvg) have been extensively used to estimate evaporative fraction (EF) from solar/thermal remote sensing data. In both space-based approaches, evapotranspiration (ET) is estimated as remotely sensed EF times the available energy. For a given data point in the T-α space or in the T-fvg space, EF is derived as the ratio of the distance separating the point from the line identified as the dry edge to the distance separating the dry edge and the line identified as the wet edge. The dry and wet edges are classically defined as the upper and lower limit of the spaces, respectively. When investigating side by side the T-α and the T-fvg spaces, one observes that the range covered by T values on the (classically determined) wet edge is different for both spaces. In addition, when extending the wet and dry lines of the T-α space, both lines cross at α ≈ 0.4 although the wet and dry edges of the T-fvg space never cross for 0 &amp;leq; fvg < 1. In this paper, a new ET (EF) model (SEB-1S) is derived by revisiting the classical physical interpretation of the T-α space to make its wet edge consistent with that of the T-fvg space. SEB-1S is tested over a 16 km by 10 km irrigated area in northwestern Mexico during the 2007–2008 agricultural season. The classical T-α space-based model is implemented as benchmark to evaluate the performance of SEB-1S. Input data are composed of ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) thermal infrared, Formosat-2 shortwave, and station-based meteorological data. The fluxes simulated by SEB-1S and the classical T-α space-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The ET simulated by SEB-1S is significantly more accurate and robust than that predicted by the classical T-α space-based model. The correlation coefficient and slope of the linear regression between simulated and observed ET is improved from 0.82 to 0.93, and from 0.63 to 0.90, respectively. Moreover, constraining the wet edge using air temperature data improves the slope of the linear regression between simulated and observed ET.

scholarly journals An original interpretation of the surface temperature-albedo space to estimate crop evapotranspiration (SEB-1S)

2013 ◽  
Vol 10 (5) ◽  
pp. 6277-6319
Author(s):  
O. Merlin
Keyword(s):  
Linear Regression ◽  
Surface Temperature ◽  
Thermal Emission ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Optical Remote Sensing ◽  
Available Energy ◽  
Green Vegetation ◽  
Northwestern Mexico ◽  
T Values

Abstract. The space defined by the pair surface temperature (T) and surface albedo (α), and the space defined by the pair T and fractional green vegetation cover (fvg) have been extensively used to estimate evaporative fraction (EF) from optical remote sensing data. In both space-based approaches, evapotranspiration (ET) is estimated as remotely sensed EF times the available energy. For a given data point in the T − α space or in the T − fvg space, EF is derived as the ratio of the distance separating the point from the line identified as the dry edge to the distance separating the dry edge and the line identified as the wet edge. The dry and wet edges are classically defined as the upper and lower limit of the spaces, respectively. When side-by-side investigating the T − α and the T − fvg spaces, one observes that the range covered by T values on the (classically determined) wet edge is different for both spaces. In addition, when extending the wet and dry lines of the T − α space, both lines cross at α ≈ 0.4 although the wet and dry edges of the T − fvg space never cross for 0 ≤ fvg < 1. In this paper, a new ET (EF) model (SEB-1S) is derived by revisiting the classical physical interpretation of the T − α space to make its wet edge consistent with that of the T − fvg space. SEB-1S is tested over a 16 km by 10 km irrigated area in northwestern Mexico during the 2007–2008 agricultural season. The classical T − α space-based model is implemented as benchmark to evaluate the performance of SEB-1S. Input data are composed of ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) thermal infrared, Formosat-2 shortwave, and station-based meteorological data. The fluxes simulated by SEB-1S and the classical T − α space-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The ET simulated by SEB-1S is significantly more accurate and robust than that predicted by the classical T − α space-based model. The correlation coefficient and slope of the linear regression between simulated and observed ET is improved from 0.82 to 0.93, and from 0.63 to 0.90, respectively. Moreover, constraining the wet edge using air temperature data improves the slope of the linear regression between simulated and observed ET.

scholarly journals Spatial Evaluation of Soil Moisture (SM), Land Surface Temperature (LST), and LST-Derived SM Indexes Dynamics during SMAPVEX12

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1247 ◽  
Author(s):  
Hao Sun ◽  
Baichi Zhou ◽  
Hongxing Liu
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Surface Radiation ◽  
Spatial Correlations ◽  
Application Potential ◽  
Decoupling Effect

Downscaling microwave soil moisture (SM) with optical/thermal remote sensing data has considerable application potential. Spatial correlations between SM and land surface temperature (LST) or LST-derived SM indexes (SMIs) are vital to the current optical/thermal and microwave fusion downscaling methods. In this study, the spatial correlations were evaluated at the same spatial scale using SMAPVEX12 SM data and MODIS day/night LST products. LST-derived SMIs was calculated using NLDAS-2 gridded meteorological data with conventional trapezoid and two-stage trapezoid models. Results indicated that (1) SM agrees better with daytime LST than the nighttime or the day-night differential LST; (2) the daytime LSTs on Aqua and Terra present very similar spatial agreement with SM and they have very similar performances as downscaling factors in simulating SM; (3) decoupling effect among SM, LST, and LST-derived SMIs occurs not only in very wet but also in very dry condition; and (4) the decoupling effect degrades the performance of LST as a downscaling factor. The future downscaling algorithms should consider net surface radiation and soil type to tackle the decoupling effect.

Estimation of Missing GPS Precipitable Water Vapor Data by Zenith Wet Delay and Meteorological Data

2014 ◽  
Vol 931-932 ◽  
pp. 703-708
Author(s):  
Prawit Uang-Aree ◽  
Sununtha Kingpaiboon ◽  
Kulyakorn Khuanmar
Keyword(s):  
Water Vapor ◽  
Linear Regression ◽  
Vapor Pressure ◽  
Surface Temperature ◽  
Meteorological Data ◽  
Water Vapor Pressure ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Dew Point ◽  
Zenith Wet Delay

This article presents a statistical correlation between GPS precipitable water vapor and meteorological data, i.e., surface temperature, air pressure, relative humidity, dew point temperature, and water vapor pressure by using linear regression. The data, recorded over a 4-year period, was used as an estimation of missing GPS precipitable water vapor data from discontinuous recordings. A multiple linear regression equation showed a correlation among zenith wet delay (ZWD), water vapor pressure (e) and surface temperature (T) was ZWD(e,T) = 17.4952e-0.8281T-93.164, with a coefficient of determination (R2) of 0.725, a mean absolute error of 8.71 mm, a root mean square error of 10.39 mm, and a mean absolute percentage error of 18.63%. The equation obtained can be used to estimate GPS precipitable water vapor data which is missing from recordings due to accident or technological error.

scholarly journals Evaluation of a complementary based model for mapping land surface evapotranspiration

2012 ◽  
Vol 9 (3) ◽  
pp. 3029-3062 ◽  
Author(s):  
Z. Sun ◽  
Q. Wang ◽  
Z. Ouyang ◽  
Y. Yang
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Thermal Emission ◽  
Remote Sensing Data ◽  
Dew Point ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Parameterization Method ◽  
A Site

Abstract. A modified Priestley-Taylor (P-T) equation was proposed by Venturini et al. (2008) to map actual evapotranspiration (ET) based solely on satellite remote sensing data, involving a parameter based on a scaled temperature between dew point temperature and surface temperature. In this study, however, theoretical analyses and field experimental evidence show that it is hard to obtain this scaled temperature using dew point temperature and surface temperature. This study also presents a new parameterization method using air temperature, surface temperature, and surface temperature of a reference dry surface. The actual ET estimates obtained by means of our proposed parameterization method are validated at a site scale, and a case study is conducted to map actual ET from Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) images using our proposed method. Results of ground-based validation and a case study of mapping ET using ASTER images indicate that the improvement on the modified P-T equation proposed by Venturini et al. (2008) can contribute to generating reliable actual ET.

scholarly journals Topoclimate Mapping Using Landsat ETM+ Thermal Data: Wolin Island, Poland

2021 ◽  
Vol 13 (14) ◽  
pp. 2712
Author(s):  
Marta Ciazela ◽  
Jakub Ciazela
Keyword(s):  
Land Surface ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Animal Husbandry ◽  
Boundary Layer Processes ◽  
Lowland Area ◽  
Agricultural Areas ◽  
Glacial Landforms ◽  
Climatic Pattern

Variations in climatic pattern due to boundary layer processes at the topoclimatic scale are critical for ecosystems and human activity, including agriculture, fruit harvesting, and animal husbandry. Here, a new method for topoclimate mapping based on land surface temperature (LST) computed from the brightness temperature of Landsat ETM+ thermal bands (band6) is presented. The study was conducted in a coastal lowland area with glacial landforms (Wolin Island). The method presented is universal for various areas, and is based on freely available remote sensing data. The topoclimatic typology obtained was compared to the classical one based on meteorological data. It was proven to show a good sensitivity to changes in topoclimatic conditions (demonstrated by changes in LST distribution) even in flat, agricultural areas with only small variations in topography. The technique will hopefully prove to be a convenient and relatively fast tool that can improve the topoclimatic classification of other regions. It could be applied by local authorities and farmer associations for optimizing agricultural production.

scholarly journals Experimental Determination of the Heat Transfer Coefficient of Real Cooled Geometry Using Linear Regression Method

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 180
Author(s):  
Asif Ali ◽  
Lorenzo Cocchi ◽  
Alessio Picchi ◽  
Bruno Facchini
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Heat Transfer Coefficient ◽  
Linear Regression ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
External Surface ◽  
Internal Surface ◽  
Regression Method ◽  
Thermal Transient

The scope of this work was to develop a technique based on the regression method and apply it on a real cooled geometry for measuring its internal heat transfer distribution. The proposed methodology is based upon an already available literature approach. For implementation of the methodology, the geometry is initially heated to a known steady temperature, followed by thermal transient, induced by injection of ambient air to its internal cooling system. During the thermal transient, external surface temperature of the geometry is recorded with the help of infrared camera. Then, a numerical procedure based upon a series of transient finite element analyses of the geometry is applied by using the obtained experimental data. The total test duration is divided into time steps, during which the heat flux on the internal surface is iteratively updated to target the measured external surface temperature. The final procured heat flux and internal surface temperature data of each time step is used to find the convective heat transfer coefficient via linear regression. This methodology is successfully implemented on three geometries: a circular duct, a blade with U-bend internal channel, and a cooled high pressure vane of real engine, with the help of a test rig developed at the University of Florence, Italy. The results are compared with the ones retrieved with similar approach available in the open literature, and the pros and cons of both methodologies are discussed in detail for each geometry.

scholarly journals Shallow groundwater effect on land surface temperature and surface energy balance under bare soil conditions: modeling and description

2012 ◽  
Vol 16 (7) ◽  
pp. 1817-1831 ◽  
Author(s):  
F. Alkhaier ◽  
G. N. Flerchinger ◽  
Z. Su
Keyword(s):  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface ◽  
Shallow Groundwater ◽  
Bare Soil ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Soil Conditions ◽  
Potential Evaporation ◽  
Available Energy

Abstract. Understanding when and how groundwater affects surface temperature and energy fluxes is significant for utilizing remote sensing in groundwater studies and for integrating aquifers within land surface models. To investigate the shallow groundwater effect under bare soil conditions, we numerically exposed two soil profiles to identical metrological forcing. One of the profiles had shallow groundwater. The different responses that the two profiles manifested were inspected regarding soil moisture, temperature and energy balance at the land surface. The findings showed that the two profiles differed in three aspects: the absorbed and emitted amounts of energy, the portioning out of the available energy and the heat fluency in the soil. We concluded that due to their lower albedo, shallow groundwater areas reflect less shortwave radiation and consequently get a higher magnitude of net radiation. When potential evaporation demand is sufficiently high, a large portion of the energy received by these areas is consumed for evaporation. This increases the latent heat flux and reduces the energy that could have heated the soil. Consequently, lower magnitudes of both sensible and ground heat fluxes are caused to occur. The higher soil thermal conductivity in shallow groundwater areas facilitates heat transfer between the top soil and the subsurface, i.e. soil subsurface is more thermally connected to the atmosphere. For the reliability of remote sensors in detecting shallow groundwater effect, it was concluded that this effect can be sufficiently clear to be detected if at least one of the following conditions occurs: high potential evaporation and high contrast between day and night temperatures. Under these conditions, most day and night hours are suitable for shallow groundwater depth detection.

Early stress detection in grapevine – can remotely-sensed sun-induced chlorophyll fluorescence do the job?

2021 ◽  
Author(s):  
Georg Wohlfahrt ◽  
Albin Hammerle ◽  
Barbara Rainer ◽  
Florian Haas
Keyword(s):  
Chlorophyll Fluorescence ◽  
Vegetation Index ◽  
Near Infrared ◽  
Census Data ◽  
Meteorological Data ◽  
Vegetation Indices ◽  
Wavelength Region ◽  
Remote Sensing Data ◽  
Warning Signs ◽  
Mitigation Measures

&lt;p&gt;Ongoing changes in climate (both in the means and the extremes) are increasingly challenging grapevine production in the province of South Tyrol (Italy). Here we ask the question whether sun-induced chlorophyll fluorescence (SIF) observed remotely from space can detect early warning signs of stress in grapevine and thus help guide mitigation measures.&lt;/p&gt;&lt;p&gt;Chlorophyll fluorescence refers to light absorbed by chlorophyll molecules that is re-emitted in the red to far-red wavelength region. Previous research at leaf and canopy scale indicated that SIF correlates with the plant photosynthetic uptake of carbon dioxide as it competes for the same energy pool.&lt;/p&gt;&lt;p&gt;To address this question, we use time series of two down-scaled SIF products (GOME-2 and OCO-2, 2007/14-2018) as well as the original OCO-2 data (2014-2019). As a benchmark, we use several vegetation indices related to canopy greenness, as well as a novel near-infrared radiation-based vegetation index (2000-2019). Meteorological data fields are used to explore possible weather-related causes for observed deviations in remote sensing data. Regional DOC grapevine census data (2000-2019) are used as a reference for the analyses.&lt;/p&gt;

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