@article{fdi:010088178,
  title = {{R}emote sensing data for digital soil mapping in {F}rench research : a review},
  author = {{R}icher-de-{F}orges, {A}. {C}. and {C}hen, {Q}. {Q}. and {B}aghdadi, {N}. and {C}hen, {S}. {C}. and {G}omez, {C}{\'e}cile and {J}acquemoud, {S}. and {M}artelet, {G}. and {M}ulder, {V}. {L}. and {U}rbina-{S}alazar, {D}. and {V}audour, {E}. and {W}eiss, {M}. and {W}igneron, {J}. {P}. and {A}rrouays, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}oils are at the crossroads of many existential issues that humanity is currently facing. {S}oils are a finite resource that is under threat, mainly due to human pressure. {T}here is an urgent need to map and monitor them at field, regional, and global scales in order to improve their management and prevent their degradation. {T}his remains a challenge due to the high and often complex spatial variability inherent to soils. {O}ver the last four decades, major research efforts in the field of pedometrics have led to the development of methods allowing to capture the complex nature of soils. {A}s a result, digital soil mapping ({DSM}) approaches have been developed for quantifying soils in space and time. {DSM} and monitoring have become operational thanks to the harmonization of soil databases, advances in spatial modeling and machine learning, and the increasing availability of spatiotemporal covariates, including the exponential increase in freely available remote sensing ({RS}) data. {T}he latter boosted research in {DSM}, allowing the mapping of soils at high resolution and assessing the changes through time. {W}e present a review of the main contributions and developments of {F}rench (inter)national research, which has a long history in both {RS} and {DSM}. {T}hanks to the {F}rench {SPOT} satellite constellation that started in the early 1980s, the {F}rench {RS} and soil research communities have pioneered {DSM} using remote sensing. {T}his review describes the data, tools, and methods using {RS} imagery to support the spatial predictions of a wide range of soil properties and discusses their pros and cons. {T}he review demonstrates that {RS} data are frequently used in soil mapping (i) by considering them as a substitute for analytical measurements, or (ii) by considering them as covariates related to the controlling factors of soil formation and evolution. {I}t further highlights the great potential of {RS} imagery to improve {DSM}, and provides an overview of the main challenges and prospects related to digital soil mapping and future sensors. {T}his opens up broad prospects for the use of {RS} for {DSM} and natural resource monitoring.},
  keywords = {remote sensing ; soil digital soil mapping ; scale ; sampling density ; resolution ; sensors ; wavelengths ; covariates ; review ; {FRANCE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {15},
  numero = {12},
  pages = {3070 [38 p.]},
  year = {2023},
  DOI = {10.3390/rs15123070},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088178},
}