# Remote Sensing Data for Digital Soil Mapping in French Research--A Review
## 7 Main Progresses, Perspectives, and Prospects
### The Increasing Importance of RS Data in DSM
#### 7.2.2 Incorporation of RS Products as Covariates in DSM  
We have seen that RS products can be used as covariates in DSM models (see Section 4.2). This is primarily because many RS products not only reflect soil surface properties, but can provide spatiotemporal information about two categories of information that can be used in DSM. RS products can provide information on the controlling factors of soil formation and changes. This is particularly the case for vegetation indexes, which provide indirect information about SOC inputs to soils. Conversely, soil moisture and temperature products can provide indirect information on the mineralization rate of SOC. Land cover and changes in land cover are related to different soil outputs and inputs that can influence pH, C and N cycles, nutrients, and possible sources of contamination. Airborne gamma-ray spectroscopy can provide information on the soil depth, presence of peaks, soil weathering, and the nature and mineralogy of the parent material, or help better map clay content and/or mineralogy. The high-resolution DEMs derived from RS are essential to capture the different scales of soil processes and soil erosion/redistribution in the landscape at different scales. They are also very useful information for water redistribution and thus water regimes. One big challenge with the multiplication of RS imagery is to conduct the right selection of covariates to avoid overfitting and respect the parsimony and relevance principles in DSM. Several ways of selecting covariates have been proposed and cited in this review. We must keep in mind that among the criteria used for selecting covariates and/or aggregating them in synthetic ones, we should take into account not only parsimony and redundancy, but also their meanings in terms of soil science. Conversely, another big challenge of DSM and data-driven modeling is to use them as knowledge discovery tools that may reveal or help with the understanding of new soil processes at various scales. In other words, RS and DSM are not only tools that can extend the spatially statistical relationships established on a set of leaning variates; they should also be able to discover new soil processes. Although still underutilized, information on soil management practices at the field level is probably one of the most promising covariates with the development of hyperspectral sensors with high spatial and temporal resolution. Conceptualization, A.C.R.-d.-F. and D.A. ; methodology, A.C.R.-d.-F; data curation, A.C.R.-d.-F.; writing--original draft preparation, A.C.R.-d.-F; writing--review and editing, A.C.R.-d.-F., Q.C., N.B., S.C., G.S., J.G.M., V.L.M., D.U.-S., E.V., M.W., J.-P.W. and D.A. ; visualization, A.C.R.-d.-F.; supervision, D.A. and E.V. ; project administration, E.V. ; funding acquisition, E.V. All authors have read and agreed to the published version of the manuscript. **Funding:** This review was supported by the THEIA TOSCA of the CNES and the MELICERTES project (ANR-22-PEAE-0010) of the French National Research Agency (France2030 and national PEPR \"agroecologie et numerique\" programmes). This review was supported by the European Joint Programme Cofund on Agricultural Soil Management (EJP-SOIL grant number 862695) and was carried out in the framework of the STEROPES project of EJP-SOIL. [PERSON] has been awarded a scholarship grant (202206320054) by the Chinese Scholarship Council to pursue her studies in France as a PhD student. [PERSON] has received the support of a PhD scholarship from both INRAE (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement) and ADEME (Agence de la transition ecologique). **Data Availability Statement:** There is no data to share. This is a review paper. **Acknowledgments:** [PERSON] is the coordinator of the Centre d'Etudes Scientifiques Theia \"Cartographie Numerique des Sols\" supported by the CNES, France. [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] are members of this Centre d'Etudes Scientifiques Theia \"Cartographie Numerique des Sols\".