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Studies have shown that the footprint of a single eddy covariance (EC) system may not yield representative measurements of the turbulent fluxes at the field scale for sparse vegetated surfaces, whereas scintillometry, due to its larger footprint, may be more suitable for this purpose. However, the latter approach strongly relies on the Monin-Obukhov similarity theory (MOST) that strictly applies in the inertial sub-layer only. This work aims at experimentally confirm the reliability of displaced-beam laser scintillometer (DBLS) measurements over an olive orchard against two EC systems during summer and autumn months of 2007 through 2009. It was found that the DBLS underestimated both the momentum and sensible heat fluxes by 15 to 20% when established retrieval procedures were applied. A new method to determine the sensible heat flux from the DBLS based on the addition of a single-height wind speed measurement was tested, yielding estimates that compare well with the EC observations, with discrepancies in sensible heat fluxes of about 30 to 40 W m(-2).

Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using surface energy balance (SEB) and soil-water balance models. Both modelling approaches use remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation whereas the soil-water balance model uses only VIS-NIR data to detect the spatial variability of crop parameters. Considering that the study area is characterized by typical spatially sparse Mediterranean vegetation, i.e. olive, citrus and vineyards, alternating bare soil and canopy, we focused the attention on the main conceptual differences between one-source and two-sources energy balance models. Two different models have been tested: the widely used one-source SEBAL model, where soil and vegetation are considered as the sole source (mostly appropriate in the case of uniform vegetation coverage) and the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared vs. the outputs of the agro-hydrological SWAP model, which was applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. Remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. Actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference to be used for energy balance models accuracy assessment. Airborne hyperspectral data acquired during a NERC (Natural Environment Research Council, UK) campaign in 2005 have been used. The results of this investigation seem to prove a slightly better agreement between SWAP and TSEB for some fields of the study area. Further investigations are programmed in order to confirm these indications.

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection) are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI) spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa and other continents with geostationary satellite coverage.

A remote sensing-based approach to estimate actual evapotranspiration (ET) was tested in an area covered by olive trees and characterized by Mediterranean climate. The methodology is a modified version of the standard FAO-56 dual crop coefficient procedure, in which the crop potential transpiration, T p, is obtained by directly applying the Penman-Monteith (PM) equation with actual canopy characteristics (i.e., leaf area index, albedo and canopy height) derived from optical remote sensing data. Due to the minimum requirement of in-situ ancillary inputs, the methodology is suitable also for applications on large areas where the use of tabled crop coefficient values become problematic, due to the need of corrections for specific crop parameters, i.e., percentage of ground cover, crop height, phenological cycles, etc. The methodology was applied using seven airborne remote sensing images acquired during spring-autumn 2008. The estimates based on PM approach always outperforms the ones obtained using simple crop coefficient constant values. Additionally, the comparison of simulated daily evapotranspiration and transpiration with the values observed by eddy correlation and sap flow techniques, respectively, shows a substantial agreement during both dry and wet days with an accuracy in the order of 0.5 and 0.3 mm d−1, respectively. The obtained results suggest the capability of the proposed approach to correctly partition evaporation and transpiration components during both the irrigation season and rainy period also under conditions of significant reduction of actual ET from the potential one.

Correct estimation of crop actual transpiration plays a key-role in precision irrigation scheduling, since crop growth and yield are associated to the water passing through the crop. Objective of the work was to assess how the combined use of micro-meteorological techniques (eddy covariance, EC) and physiological measurements (sap flow, SF) allows a better comprehension of the processes involving in the Soil–Plant–Atmosphere continuum. To this aim, an experimental dataset of actual evapotranspiration, plant transpiration, and soil water content measurements was collected in an olive orchard during the midseason phenological period of 2009 and 2010. It was demonstrated that the joint use of EC and SF techniques is effective to evaluate the components of actual evapotranspiration in an olive orchard characterized by sparse vegetation and a significant fraction of exposed bare soil. The availability of simultaneous soil water content measurements allowed to estimate the crop coefficients and to assess a simple crop water stress index, depending on actual transpiration that can be evaluated even in the absence of direct measurements of actual transpiration. The crop coefficients experimentally determined resulted very similar to those previously evaluated; in particular, in the absence of water stress, a seasonal average value of about 0.65 was obtained for the “single” crop coefficient, whereas values of a 0.34 and 0.41 were observed under limited water availability in the root zone. The comparison between the values of crop water stress index evaluated during the investigated periods evidenced systematically lower values (less crop water stress) in the first year compared to the second, according to the general trend of soil waters content in the root zone. Further researches are however necessary to extent the experimental dataset to periods characterized by values of soil evaporation higher than those observed, in order to verify the crop coefficients even under different conditions than those investigated.

Reference evapotranspiration (ET 0 ) is widely used for irrigation scheduling, to promote an efficient use of water resources for a sustainable agro-ecosystem productivity, as well as to manage water quality and to face other environmental concerns. As suggested by ASCE-EWRI and FAO, standard Penman–Monteith methods are generally applied for an accurate estimation of ET 0 from hourly to daily scale. In absence of detailed meteorological information several simplified equations, using a limited number of variables, have been proposed as alternative. In this paper, the performance of different reference evapotranspiration methods, at hourly (Penman–Monteith, Pristley–Taylor, Makkink and Turc) and daily scale (Penman–Monteith, Blaney and Criddle, Hargreaves, Pristley–Taylor, Makkink and Turc), was evaluated against scintillometer measurements collected during six month in 2005 in an experimental plot maintained under “reference” conditions (alfalfa crop). The daily values of ET 0 obtained with the examined methodologies were then used as input in the FAO-56 agro-hydrological model, in order to evaluate, for an olive grove in a Mediterranean environment, the impact on simulated actual evapotranspiration. The experiment was carried out in South-West Sicily, in an area where olive groves are the major crop. The comparison between estimated and measured fluxes confirmed that FAO-56 Penman–Monteith (PM) standardized equation is characterized by the lowest mean bias error (−0.15 mm d −1 and 0.06 mm d −1 using daily or hourly data, respectively). Additionally, the analysis also highlighted that the Pristley–Taylor equation can be considered a valid alternative for an accurate estimation of ET 0 (mean bias error of 0.35 mm d −1 and 0.43 mm d −1 using daily or hourly data, respectively). The application of the FAO-56 water balance model on the investigated olive grove evidenced that the best estimations of actual evapotranspiration are obtained when the Pristley–Taylor ET 0 data are used as input, confirming that this approach can be considered a valid alternative to the standard Penman–Monteith.

Summary An operational use of the actual evapotranspiration assessed by remote sensing approaches requires the integration of instantaneous fluxes to daily values. This is commonly achieved under the hypotheses of daytime self-preservation of evaporative fraction and negligible daily ground heat flux. The aim of this study is to evaluate the effect of these assumptions on estimate daily evapotranspiration over a full phenological cycle, including phases characterized by significant changes both in net radiation and vegetation cover. To assess the reliability of these hypotheses, the observations made by a flux tower, installed within a homogeneous field of cereal located in the valley part of the Imera Meridionale basin, were analyzed. Additionally, the widely-known SEBAL (Surface Energy Balance Algorithm for Land) model was applied on the same study area by means of four MODIS (MODerate-resolution Imaging Spectroradiometer) images selected across a three-rainfall events period in March–April 2007 with the aim to analyze the consistency of its estimates in an operational study case under different conditions of water availability. The analysis of in situ data highlights errors on 24-h evapotranspiration characterized by an average value of 20% due to daily soil heat flux neglecting; whereas, the hypothesis of evaporative fraction self-preservation causes an average error equal to −16%. Moreover, the analysis of the observations suggests that a compensation effect of the errors related to each hypothesis occurs in most cases (56%), and this makes suitable the approach for practical daily integration purposes. The application of the SEBAL model at basin scale shows a good capability to detect the increase of the actual 24-h evapotranspiration under the tested hypotheses, also in the case of instantaneous evaporative fraction and daily net radiation not derived form in situ observations.

Summary A coupled energy/hydrologic model was applied to simulate the exchange of energy and water in the soil–plant-atmosphere system (SPA). The model, which uses a “two-source” approach to estimate the energy fluxes, and the “force-restore” approach to represent the water balance, was validated by means of evapotranspiration measurements collected via scintillometry and soil moisture measurements collected via time domain reflectometry (TDR) in a Sicilian olive grove. The comparison between measured and estimated fluxes values at an hourly scale showed good agreement. Additional comparisons on a daily timescale confirmed the model’s applicability for quantifying crop water requirements. Also in terms of daily evapotranspiration and soil water content values, the obtained results confirmed the model’s applicability for those practical applications aiming to quantify the crop water requirement. Moreover, further studies should be conducted to test the feasibility of using this model for long term simulations over a broad range of conditions.

Two regionalized models for the distributed estimation of daily reference evapotranspiration, the temperature-based Hargreaves (HE) and the radiation-based Makkink (MK) equations, are applied in Southern Italy during the years 2007 and 2008. Spatially distributed meteorological inputs, such as air temperature and incoming solar radiation, were derived from geostatistical interpolation of ground data and from the Land Surface Analysis Satellite Application Facility (LSA-SAF) surface radiation product, respectively. Comparison of the latter with 83,394 daily measurements provided by 128 weather stations shows a not negligible seasonal error in daily solar radiation that is corrected by means of a periodic equation. A preliminary local calibration of the MK coefficient highlights its strong dependency on the interactions between moist winds from the Atlantic Ocean and orographic obstructions, leading to two western and eastern subzones. Hence, a regionalization of the MK-adjusted coefficient was performed following a procedure similar to the one already used by the authors in a previous work for the HE coefficient. Application of both regionalized models and their comparison with Penman-Monteith estimates derived from the same stations leads to average whole-year absolute errors of approximately 0.5 mm d-1, further showing the great potential of the MK method in terms of informative content and less dependence on the site density of a ground-based monitoring network. Overall, discussing pros and cons of both regionalized models, it is shown that their integrated use in southern Italy is possible and advisable.

Application of FAO-56 methodology for the assessment of reference evapotranspiration, ET 0 , is challenging in areas of the world with sparse meteorological network stations. For this reason alternative procedures using remotely observed data have been proposed in the literature. In this work, a simplified version of the Makkink approach [J. Inst. Wat. Eng. 11: 277–288, 1957] was tested in a typical Mediterranean environment (Sicily, Italy). The implemented Makkink approach (MAK) uses remotely estimated solar radiation derived from Meteosat Second Generation (MSG) satellite data and in situ observations of air temperature to assess ET 0 at daily time scale. Alternatively, taking advantage of well-defined relationships that exist between seasonality, elevation and air temperature, a deterministic procedure for estimating air temperature inputs used in the MAK approach (named RS) was also tested. This approach allows the assessment of daily ET 0 without the need of auxiliary air temperature ground observations. A comparison between the FAO-56 and MAK approaches was performed for 45 sites in Sicily over the period 2007–2010. Assuming FA0-56 as the benchmark, the average accuracy of the MAK methodology was 0.4 mm d −1 , with a relative error of 12%. Similar to other applications of the same procedure, the MAK approach showed a slightly underestimation of ET 0 high values; however, an average regression slope of 0.96 (and negligible intercept) suggests a satisfactory agreement with the FAO-56 modeled values. Air temperature observations acquired during 2002–2006 were used to calibrate the deterministic relation between air temperature, seasonality (as a function of the DOY) and orography (as a function of elevation). For the period 2007–2010, the RS approach performs similarly to MAK, with an average difference of less than 0.05 mm d −1 . Analysis of monthly, seasonal and yearly ET 0 maps shows a slight decrease in RS performance during June and July; nevertheless, the differences between MAK and RS approaches are negligible at all analyzed temporal scales.

Estimation of evapotranspiration (ET) in Sicilian vineyard is an emerging issue since these agricultural systems are more and more converted from rainfed to irrigated conditions, with significant impacts on the management of the scarce water resources of the region. The choice of the most appropriate methodology for assessing water use in these systems is still an issue of debating, due to the complexity of canopy and root systems and for their high spatial fragmentation. In vineyards, quality and quantity of the final product are dependent on the controlled stress conditions to be set trough irrigation. This paper reports an application of the well-known Penman-Monteith approach, applied in a distributed way, using high resolution remote sensing data to map the potential evapotranspiration (ET p ). In 2008 a series of airborne multispectral images were acquired on "Tenute Rapitala", a wine farm located in the northwest of Sicily. Five airborne remote sensing scenes were collected using a SKY ARROW 351 650 TC/TCNS aircraft, at a height of about 1000 m a.g.l.. The acquisitions were performed encompassing a whole phenological period, period between June and September 2008 (approximately every three weeks). The platform had on board a multi-spectral camera with 3 spectral bands at green (G, 530-570 nm), red (R, 650-690 nm) and near infrared (NIR, 767-832 nm) wavelengths, and a thermal camera with a broad band in the range 7.5-13 µm. The nominal pixel resolution was approximately 0.7 m for VIS/NIR acquisitions, and 1.7 m for the thermal-IR data. Field data were acquired simultaneously to airborne acquisitions. These data include spectral reflectances in VIS-NIR-SWIR (shortwave infrared), leaf area index (LAI), soil moisture at different depths (both in row and below plants). Moreover, meteo variables were measured by a standard weather station whereas fluxes were measured by means of an Eddy correlation tower located within the field. The VIS-NIR bands were atmospherically corrected and calibrated in order to calculate albedo, NDVI and LAI, which represented the distributed inputs of the Penman-Monteith algorithm. Moreover a sensitivity analysis has been carried out on input parameters (such as albedo). A sensitivity analysis was carried out to highlight the variability of outputs (such as ET p ) on the accuracy in the parameters assessment obtainable using high spatial resolution airborne images. Scale effects have been also investigated by means of an artificial degradation of images spatial resolution. Finally the relationship between stress factor evaluated as the ratio between actual and reference ET and pre-dawn leaf water potential has been also investigated.

In the last years, modeling of surface processes - such as water, energy and carbon budgets, as well as vegetation growth- seems to be focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a core role due to the cross-cutting impact of this novel source of spatially distributed information on all these research areas. However, several applications - such as drought monitoring, yield forecasting and crop management - require spatially detailed products at sub-field scales, which can be obtained only with support of adequately fine resolution remote sensing data (< 100 m). In particular, observations in the visible to the near infrared (VIS/NIR) spectral region can be used to derive biophysical and biochemical properties of the vegetation (i.e., leaf area index and leaf chlorophyll). Complementarily, the thermal infrared (TIR) signal provides valuable information about land surface temperature, which in turn represents an accurate proxy indicator of the subsurface moisture status by means of surface energy budget analysis. Additionally, the strong link between crop water stress and stomatal closure allows inference of crop carbon assimilation using the same tools. In this work, an integrated approach is proposed to model both carbon and water budgets at field scale by means of a joint use of a thermal-based Two Source Energy Budget (TSEB) model and an analytical, Light-Use-Efficiency (LUE) based model of canopy resistance. This suite of models allows integration of information retrieved by both fine and coarse resolution satellites by means of a data fusion procedure. A set of Landsat and MODIS images are used to investigate the suitability of this approach, and the modeled fluxes are compared with observations made by several flux towers in terms of both water and carbon fluxes.

Agricultural water requirement in arid and semi-arid environments represents an important fraction of the total water consumption, suggesting the need of appropriate water management practices to sparingly use the resource. Furthermore the quality and quantity of some crops products, such as grape, is improved under a controlled amount of water stress. The latter is related, on a side to actual evapotranspiration (ET) through water demand, on the other side to plant water content through leaf water potential. Residual energy balance approaches based on remote sensing allow to estimate the spatial distribution of daily actual ET at plant scale, representing an useful tool to detect its spatial variability across different cultivars and even within each parcel. Moreover, the connection between actual ET and leaf water potential is still not well assessed, especially under water stress conditions, even if farmers use leaf water potential to plan irrigation. However residual energy balance methods are based on the hypothesis that storage terms are negligible, at least during the remote sensor overpass. Indeed, energy balance approaches estimate daily actual ET from the instantaneous value at the overpass time using a daily integration method. The paper first verifies this latter assumption using field data acquired by a flux tower on a whole phenological period. Then, the actual ET values measured by eddy covariance tower were analyzed together with water potential measured using a Scholander chamber; the analysis highlights that, under water stress conditions, daily actual ET is inversely linearly related with water potential. These results suggest the possibility to use remote sensing-based ET as support for irrigation management at plot scale.

During last two decades the increasing availability of remotely sensed acquisitions in the thermal infrared part of the spectrum has encouraged hydrologist community to develop models and methodologies based on these kind of data. The aim of this paper is to compare three methods developed to assess the actual evapotranspiration spatial distribution by means of remote sensing data. The comparison was focused on the differences between the "single" (SEBAL) and "two" source (TSEB) surface energy balance approaches and the S-SEBI semi-empirical method. The first assumes a semiempirical internal calibration for the sensible heat flux assessment; the second uses a physically based approach in order to assess separately the soil and vegetation fluxes. Finally, the last one is based on the correlation between albedo and surface temperature for evaporative fraction estimations. The models were applied using 7 high resolution images, collected by an airborne platform between June and October 2008, approximately every 3 weeks. The acquired data include multi-spectral images (red, green and near infrared) and thermal infrared images for surface temperature estimation. The study area, located in the south-west cost of Sicily (Italy), is characterised by the presence of typical Mediterranean cultivations: olive, vineyard and citrus. Due to irrigation supplies and rainfall events, the water availability for the crops varies in time and this allowed to perform the comparison in a wide range of the modelled variables. Additionally, the availability of high spatial resolution images allowed the testing of the models performances at field scale despite the high vegetation fragmentation of the study area. The comparison of models performance highlights a good agreements of model estimations, analyzed by means of MAD (Mean Absolute Differences) and MAPD (Mean Absolute Percent Differences) indices, especially in terms of study area averaged fluxes. The analysis in correspondence of various crop fields highlights higher differences for low vegetation coverage and for scarce water availability.

The rate at which the net radiation is transferred to the soil as ground heat flux varies with surface characteristics. Surface energy balance algorithms use empirical relationships taking into account the effects of the canopy cover to insulate the soil through vegetation indexes, the soil capacity to absorb incoming net radiation via the albedo, and the surface temperature promoting the energy transfer. However empirical relationships are often dependent on local conditions, such as the soil humidity and vegetation type. Ground heat flux assumes a minimum value in case of full canopy cover and a maximum value for dry bare soil. Aim of the present research is the critical analysis of some ground heat flux equations on a homogeneous field of cereal using measured data acquired between February and May 2008. The study period covers almost a full phenological cycle, including phases characterised by a significant change in both reflected radiation and vegetation cover. The dataset begins with the emergence phase, in November, within which shoots emerge from the ground and finishes with the flowering phase, in May, when tiny white stems begin to come-out; moreover the dataset includes a bare soil period (from September up to November). The daily evapotranspiration is calculated in energy balance models under the hypotheses of negligible daily ground heat flux and constant daily evaporative fraction. Actually micrometeorological data show that daily average ground heat flux is not null but characterised by an increasing or decreasing transient. As a consequence, it is particular important to assess the effects of neglecting the daily ground heat flux on daily evapotranspiration estimation.

Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using Surface Energy Balance and Agro-Hydrological models. Both modelling approaches require remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation. To this end two different schemes have been tested: the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately, and the widely used one-source SEBAL model, where soil and vegetation are considered as a sole source. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared with the results of the Agro-Hydrological model SWAP, applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. In this latter model, remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. In the comparison presented here, actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference. Considering that the study area is characterized by typical Mediterranean sparse vegetation, i.e. olive, citrus and vineyards, we focused the attention on the main conceptual differences between SEBAL and TSEB. Airborne hyperspectral data acquired during a NERC campaign in 2005 have been used. The results of the investigation evidenced that the remote sensing two-sources approach used in TSEB model describes turbulent and radiative surface fluxes in a more realistic way than the one-source approach.

An alternative way to map the actual evapotranspiration (ET) spatial distribution at daily scale is the application of residual surface energy balance models to satellite images that are characterised by high temporal frequency and moderate spatial resolution, like those acquired by the MODIS sensors on board of TERRA and AQUA platforms. Within this research the well-known SEBAL model has been applied on an area located in the southern part of Sicily (Imera Meridionale catchment) using four images acquired between the 27th of March and the 11th of April 2007. The catchment extends for about 2000 km2 and includes both mountains and hill areas: the first are located in the northern part (the Madonie Mountains), while the latter characterise the southern area. The altitude ranges between 0 and 1900 m a.s.l., with an average altitude of 500 m a.s.l.. In order to validate the outputs of the energy balance model, a flux tower has been installed within a homogeneous field of cereal located in the valley part of the basin (close to Licata town within the Quignones Farm), characterised by semi-arid conditions. The selected images have been acquired before and after a three-rainfall events period (5 mm during the night between the 2nd and the 3rd of April, 17 mm on the 3rd evening, 8 mm on the 4th thoroughly all the day). The study area is mostly cultivated with cereals that, during the study period, were characterised by flag and bolting phenological phases. In the first, the leaf at the stem apex assumes a flag shape, while during the latter, the terminal part of the stem a barrel shape enlargement containing the ear appears. The study aim is the evaluation of the energy partition between sensible and latent heat fluxes, due to the increased water availability in a period characterised by a significant vegetation growth. The comparison between model results and flux tower measurements shows that both the latent heat flux and the other energy balance components are modelled with high accuracy. Moreover, the model well represents the variation in time of energy partition, which increases from 0.5 up to 0.65 in terms of evaporative fraction (Λ). Therefore a greater percent of energy is used to evapotranspiration after the rainfall events.

Daily high spatial resolution assessment of actual evapotranspiration is essential for water management and crop water requirement estimation under stress conditions. The application of energy balance models usually requires satellite observations of radiometric surface temperat ure with high geometrical and temporal resolutions. By now, however, high spatial resolution (~ 100 m) is available with low time fre quency (approximately every two weeks); at the opposite daily acquisition are characterised by poor spatial resolution. The analysis of vegetation index (VI) and land surface temperature (LST) spatial relationship, shows in substance a scale invariant behaviour [1] ; this consideration allows the application of spatial sharpening algorithms of thermal data, by means of a combination of high spatial resolution data in VIS/NIR range with high temporal acquisition on TIR. In this paper, a sharpening algorithm was applied using the thermal bands of MODIS ( MOderate resolution Imaging Spectroradiometer ) and vegetation indices derived by ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer ) sensor; the choice of this sensors is justified by the simultaneous acquisition time. The results of this sharpening process was firstly compared against LST estimation (at the same spatial resolution) by means of the ASTER simultaneous data; then the derived high spatial resolution LST distribution was used in order to investigate the effect of the disaggregation on the outputs of surface energy balance models. The above described application was performed on a Sicilian study area. Keywords: land surface temperature, disaggregation, actual ev apotranspiration, surface energy balance models.