Even though microbial imagery had constantly benefited upon technical developments, the analysis of microbial images did not record the same progress. However, analytical tools had been developed in conjunction with remote sensing imagery, and are available for other fields of study as well. When importing such approaches, it is necessary to understand their detailed functioning in order to envisage eventual problems and improve the correctness and

Le projet de recherche ADAM a été une coopération scientifique entre la France et la Roumanie dédiée ŕ l’Assimilation de Données spatiales par Agro-Modélisation, dont le promoteur et commanditaire a été le Centre National d’Études Spatiales. Le papier présente les principales approches utilisées et les résultats novateurs obtenus dans ADAM : constitution de la première base de données de télédétection de référence, production

The chlorophyll meter (CM) has been commonly used for in-season nitrogen (N) management of corn (Zea mays L.). Nevertheless, it has limited potential for site-specific N management in large fields due to difficulties in using it to generate N status maps. The objective of this study was to determine how well CM readings can be estimated using aerial hyperspectral and simulated multi-spectral remote sensing images at different corn growth stages.

The ADAM project (Assimilation of Spatial Data within Agriculture Models) was aiming at the development and evaluation of methods capable of exploiting high revisit frequency and high spatial satellite observations. The intensive experimental campaign conducted in 2000– 2001 over wheat crops yielded a unique database where frequent satellite observations at high spatial resolution in the solar and microwave domains were made concurrently to ground