Research Highlights We make a review of agronomical variables and plant traits that can be estimated from remote sensing  We describe different methodological approaches to retrieve them  We discuss how these variables are employed by different stakeholders for specific applications We conclude with an overview of caveats and future challenges

No abstract

Hydrology and crop water management require daily values of evapotranspiration ET at different time-space scale. Sun synchronous optical remote sensing, which allows for the assessment of ET with high to moderate spatial resolution, provides instantaneous estimates during satellites overpass. Then, usual solutions consist of extrapolating instantaneous to daily values by assuming that evaporative fraction EF is constant throughout the day, providing that daily available energy AE is known. The current study aims at deriving daily ET values from ASTER derived instantaneous estimates, over an olive orchard in a semi-arid region of Moroccan. It has been shown that EF is almost constant under dry conditions, but it depicts a pronounced concave up shape under wet conditions. A new heuristic parameterization is then proposed, which is based on the combination of routine daily meteorological data for characterizing atmospheric dependence, and on optical remote sensing based estimates of instantaneous EF values to take into account the dependence on soil and vegetation conditions. Using the same type of approach, a similar parameterization is next developed for AE. The validation of both approaches shows good performances. The overall method is finally applied to ASTER data. Though performances are reasonably good, their moderate reduction is ascribed to errors on remotely sensed variables. Future works will focus on method portability since its empirical formulation does not account for the direct stomatal response to water availability, as well as on application over different surface and climate conditions. ª

The temporal frequency of the thermal data provided by current spaceborne high-resolution imagery systems is inadequate for agricultural applications.As an alternative to the lack of high-resolution observations, kilometric thermal data can be disaggregated using a green (photosynthetically active) veg- . The approach is also tested using the MODIS data re-sampled at 2 km resolution. Aggregation reduces errors in MODIS data and consequently increases the disaggregation accuracy.

No abstract

No abstract

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Evaporation from heterogeneous and sparse canopies is often represented by multi-source models that take the form of electrical analogues based upon resistance networks. The chosen representation de facto imposes a specific form on the composition of elementary fluxes and resistances. The two-and three-source representations are discussed in relation to previous work where some ambiguities arise. Using the two-layer model (Shuttleworth and Wallace, Q J R Meteorol Soc 111: [839][840][841][842][843][844][845][846][847][848][849][850][851][852][853][854][855] 1985) and the clumped (three-source) model (Brenner and Incoll, Agric For Meteorol 84:187-205, 1997) as a basis, it is shown that the stomatal characteristics of the foliage (amphistomatous or hypostomatous) generate different formulations. New generic and more concise equations, valid in both configurations, are derived. The differences between the patch and layer approaches are outlined and the consequences they have on the composition and formulation of component fluxes are specified. Then, the issue of calculating the effective resistances of the single-layer model from multi-source representations is addressed. Finally, a sensitivity analysis is carried out to illustrate the significance of the new formulations. Keywords Big leaf model · Effective parameters · Evaporation · Heterogeneous and sparse vegetation · Multi-layer models List of SymbolsA Available energy of the whole crop (W m −2 ) A f Available energy of the foliage (W m −2 ) A s Available energy of the substrate (W m −2 ) A vs Available energy of the vegetated soil (W m −2 ) A bs Available energy of the bare soil (W m −2 ) R n Net radiation of the whole crop (W m −2 ) G Soil heat flux (W m −2 ) 123 244 J. P. Lhomme et al. H Sensible heat flux from the complete canopy (W m −2 ) λE Latent heat flux from the complete canopy (W m −2 ) H i Component heat flux (i = f, s, vs, bs) (W m −2 ) λE i Component latent heat flux (i = f, s, vs, bs) (W m −2 ) D a Vapour pressure deficit at reference height (Pa) D m Vapour pressure deficit at canopy source height (Pa) T a Air temperature at reference height ( • C) T m Air temperature at canopy source height ( • C) T i Surface temperature of component i (i = f, s, vs, bs) ( • C) u a Wind speed at reference height (m s −1 ) e a Vapour pressure at reference height (Pa) e m Vapour pressure at canopy source height (Pa) e * (T ) Saturated vapour pressure at temperature T (Pa) c p Specific heat of air at constant pressure (J kg −1 K −1 ) ρ Air density (kg m −3 ) γ Psychrometric constant (Pa K −1 ) Slope of the saturated vapour pressure curve (Pa K −1 ) Canopy Structural Characteristics d Canopy displacement height (m) F Fractional cover of foliage (dimensionless) LAI Leaf area index (m 2 m −2 ) n Parameter with value of 1 for amphistomatous and 2 for hypostomatous foliage z r Reference height (m) z h Mean canopy height (m) z m Mean canopy source height (Canopy aerodynamic roughness length (m) Component Resistances r a Aerodynamic resistance between the source height an...