To be fully operational for assisting decisions at global, national and local levels, environmental modelling require precise spatially referenced soil information as inputs. The current soil database that exist in the world are neither exhaustive nor precise enough for being used efficiently for this purpose. An alternative is the digital soil mapping (DSM) which can be defined as 'the creation and population of spatial soil information systems by numerical models inferring the spatial and temporal variations of soil types and soil properties from soil observation and knowledge and from related environmental variables'. To face the lack of soil data, The Digital Soil Mapping working group of IUSS recently proposed (www.globalsoilmap.net/) to make a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution (100 m). This new global soil map is expected to assist better decisions in a range of global issues like food production, climate change and environmental degradation. The submitted project is designed to initiate a French contribution to this global initiative. It aims to conduct a 'proof-of-concept' test of the proposed digital soil map in Tunisia. The innovative aspect of this French contribution is the extensive use of spatial spectroscopy as a new source of data that is expected to provide direct estimates of some soil surface key properties (carbon content, soil texture, calcium carbonate,…) that can considerably increase the accuracy of the Digital Soil Mapping outputs. The main study area of the proposed research project is centred around the Lebna catchment, in Tunisia. This 1200 km² area (36°52'N ; 10°52'E) constitutes a suitable proof of concept zone that may anticipate the digital soil mapping of the northern Africa and middle East area. The proposed scientific program is broken into three work packages and to three distinct scientific domains: soil property mapping by hyperspectral imagery (WP1), Digital Soil Mapping of soil properties (WP2) and Environmental Modelling using DSM outputs (WP3). The Workpackage 1 aims to predict all possible soil surface properties from hyperspectral imagery over large areas. It includes the elaboration of spectrotransfert functions for predicting simultaneously several soil properties from Visible and Near Infrared spectrum of soil. These spectro-transfert functions will then be adapted for the fine-scale soil properties mapping using airborne vis-NIR data, over bare soils. Finally, the case of mixed surface with soil but also vegetation and rock will be adressed following methods such as Independent Component Analysis for extracting soil spectrum from mixed surface spectrum. The Workpackage 2 aims to perform the digital soil mapping of surface and sub-surface soil properties from the hyperspectral imagery predictions made in the previous work package. Soil surface properties will be predicted by extending the hyperspectral imagery results obtained in the previous step to the areas that remain inaccessible because of a too large amount of perturbing components. This suppose to develop a specific conditional simulaion approach. Although hyperspectral imagery cannot directly estimate sub-surface soil properties we expect that using this new variable as input of DSM function together with relief indicators will greatly improve the prediction of these properties. This is the joint use of this two new set of spatial data that will be innovative here. The general objective of the work package 3 is to determine the added value of Digital Soil Mapping over currently available soil databases for the environmental modelling. We have selected for that two case studies of environmental modelling that have been already undertaken in previous research programs in Tunisia and that will be re-applied in this program: i) the Spatialized assessment of soil vulnerability to erosion and ii) the Mapping wheat yield in water limited situations. The consortium of the project include three French teams (LISAH, EMMAH and BioSP) three Tunisian teams and an Australian one. It covers all the competences required by the objective of the project.