@article{fdi:010077371,
  title = {{R}emote sensing of the terrestrial carbon cycle : a review of advances over 50 years},
  author = {{X}iao, {J}. {F}. and {C}hevallier, {F}. and {G}omez, {C}{\'e}cile and {G}uanter, {L}. and {H}icke, {J}. {A}. and {H}uete, {A}. {R}. and {I}chii, {K}. and {N}i, {W}. {J}. and {P}ang, {Y}. and {R}ahman, {A}. {F}. and {S}un, {G}. {Q}. and {Y}uan, {W}. {P}. and {Z}hang, {L}. and {Z}hang, {X}. {Y}.},
  editor = {},
  language = {{ENG}},
  abstract = {{Q}uantifying ecosystem carbon fluxes and stocks is essential for better understanding the global carbon cycle and improving projections of the carbon-climate feedbacks. {R}emote sensing has played a vital role in this endeavor during the last five decades by quantifying carbon fluxes and stocks. {T}he availability of satellite observations of the land surface since the 1970s, particularly the early 1980s, has made it feasible to quantify ecosystem carbon fluxes and stocks at regional to global scales. {H}ere we provide a review of the advances in remote sensing of the terrestrial carbon cycle from the early 1970s to present. {F}irst, we present an overview of the terrestrial carbon cycle and remote sensing of carbon fluxes and stocks. {R}emote sensing data acquired in a broad wavelength range (visible, infrared, and microwave) of the electromagnetic spectrum have been used to estimate carbon fluxes and/or stocks. {S}econd, we provide a historical overview of the key milestones in remote sensing of the terrestrial carbon cycle. {T}hird, we review the platforms/sensors, methods, findings, and challenges in remote sensing of carbon fluxes. {T}he remote sensing data and techniques used to quantify carbon fluxes include vegetation indices, light use efficiency models, terrestrial biosphere models, data-driven (or machine learning) approaches, solar-induced chlorophyll fluorescence ({SIF}), land surface temperature, and atmospheric inversions. {F}ourth, we review the platforms/sensors, methods, findings, and challenges in passive optical, microwave, and lidar remote sensing of biomass carbon stocks as well as remote sensing of soil organic carbon. {F}ifth, we review the progresses in remote sensing of disturbance impacts on the carbon cycle. {S}ixth, we also discuss the uncertainty and validation of the resulting carbon flux and stock estimates. {F}inally, we offer a forward-looking perspective and insights for future research and directions in remote sensing of the terrestrial carbon cycle. {R}emote sensing is anticipated to play an increasingly important role in carbon cycling studies in the future. {T}his comprehensive and insightful review on 50 years of remote sensing of the terrestrial carbon cycle is timely and valuable and can benefit scientists in various research communities (e.g., carbon cycle, remote sensing, climate change, ecology) and inform ecosystem and carbon management, carbon-climate projections, and climate policymaking.},
  keywords = {{C}arbon fluxes ; {C}arbon stocks ; {O}ptical remote sensing ; {M}icrowave remote sensing ; {L}idar ; {S}olar-induced chlorophyll fluorescence ; {C}arbon cycling ; {A}boveground biomass ; {D}isturbance ; {C}arbon-climate feedbacks},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {233},
  numero = {},
  pages = {art. 111383 [37 p.]},
  ISSN = {0034-4257},
  year = {2019},
  DOI = {10.1016/j.rse.2019.111383},
  URL = {https://www.documentation.ird.fr/hor/fdi:010077371},
}