Near-surface remote sensing applications for a robust, climate-smart measurement, monitoring, and information system (MMIS)

  • Benjamin R.K. Runkle
  • , Mallory Barnes
  • , Matt Dannenberg
  • , John A. Gamon
  • , Troy Magney
  • , Zoe Pierrat
  • , Charles D. Southwick
  • , Christopher Still
  • , William Woodgate

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

To reduce its greenhouse gas (GHG) impact, the United States government plans GHG Measurement, Monitoring, and Information System (MMIS) activities to better quantify GHG sources and sinks in natural, forested, and agricultural ecosystems. The national strategy discusses several areas where a robust MMIS can be strengthened by near-surface remote sensing (RS) technology—i.e. non-contact measurement of electromagnetic signals by sensors mounted near the ground, on towers, or on drones. Here, we outline specific applications of near-surface RS for an MMIS, using tools presently available and offering guidance on improvements needed for an expansion of their applications. Near-surface RS can help quantify carbon stocks by assessing vegetation structure and function, and it can inform cross-scale understanding of ecosystem carbon processes and properties. The integration of near-surface RS tools into an MMIS will overcome some limitations and uncertainties of current carbon cycle accounting methods and carbon project implementation. Development of robust, standardized near-surface RS systems can be accomplished through transdisciplinary partnerships among government agencies, academics, land managers, and the private sector. The result will hasten achievement of MMIS objectives of improved bottom-up and top-down GHG estimation and improved accessibility and standardization of GHG data and measurements.

Original languageEnglish
Article number2465361
JournalCarbon Management
Volume16
Issue number1
DOIs
StatePublished - 2025

Keywords

  • carbon cycle science
  • landscape monitoring
  • LiDAR
  • management
  • policy
  • Proximal or near-surface remote sensing
  • solar-induced chlorophyll fluorescence

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