Olivier Marloie

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Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface(More)
Water monitoring at the scale of a small agricultural region is a key point to insure a good crop development particularly in South-Eastern France, where extreme climatic conditions result in long dry periods in spring and summer with very sparse precipitation events, corresponding to a crucial period of crop development. Remote sensing with the increasing(More)
The impact of using non-coincident radiosoundings to remove atmosphere effect from thermal radiances is analyzed here. We considered 27 Landsat-7 ETM+ images acquired over a Mediterranean agricultural region, benefiting from nearby radiosoundings launched almost 2 hours later, and from the availability of a network of ground stations deployed over different(More)
The influence of temperature on the dielectric permittivity of soil is the result of counteracting effect that depends on the soil's composition and mineralogy. In this paper, laboratory experiments showed that for a given water content, the soil dielectric permittivity was linearly related to the temperature, with a slope (α) that varied between samples(More)
Among MODIS products (freely available to the scientific community from 2001), albedo data (MCD43B3) are 16 days composites at 1km spatial resolution, widely used for various applications in climate models, but which still remains difficult to validate. The objective of this study is to propose a method to validate these products with high spatial and(More)
This study provides the first assessment of the Noah and Noah-GEM (photosynthesis-based Gas exchange Evapotranspiration Model) land surface model using observations from the Avignon, France CarboEurope agricultural site during 2006 and 2007. Noah and Noah-GEM are integrated within a Land Data Assimilation System (LDAS) framework. The LDAS fields of soil(More)