Research Topic

Spaceborne Active Sensors for Characterizing Canopy Structure

About this Research Topic

Given the recent launch of ICESat-2 (Ice, Cloud and Land Elevation Satellite) and GEDI (Global Ecosystem Dynamics Investigation) and upcoming radar missions such as NISAR (NASA-ISRO Synthetic Aperture Radar), active remote sensing from space provides opportunities for global scale characterization of vegetation canopy structure and biophysical parameters. A synergistic approach of integrating data from multiple sensors, including optical data such as Landsat, is of great interest to improve vegetation monitoring from space.

This Research Topic welcomes submissions related to active satellite remote sensing of the canopy structure. Topics covered by this Research Topic include, but are not limited to:
• Algorithms for data fusion with active and passive spaceborne sensors
• Methods of Scaling up from lidar coverage patterns to gridded products of canopy structure
• Software tools for processing lidar and radar data for vegetation studies
• Using ancillary datasets and field inventory to calibrate spaceborne estimates of vegetation canopy structure

Contributions should indicate explicitly the core observations exploited in the study, e.g. whether Lidar or radar, to facilitate channeling the study to the appropriate Frontiers section


Keywords: lidar, ICE-Sat-2, GEDI, NISAR, vegetation, canopy structure


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Given the recent launch of ICESat-2 (Ice, Cloud and Land Elevation Satellite) and GEDI (Global Ecosystem Dynamics Investigation) and upcoming radar missions such as NISAR (NASA-ISRO Synthetic Aperture Radar), active remote sensing from space provides opportunities for global scale characterization of vegetation canopy structure and biophysical parameters. A synergistic approach of integrating data from multiple sensors, including optical data such as Landsat, is of great interest to improve vegetation monitoring from space.

This Research Topic welcomes submissions related to active satellite remote sensing of the canopy structure. Topics covered by this Research Topic include, but are not limited to:
• Algorithms for data fusion with active and passive spaceborne sensors
• Methods of Scaling up from lidar coverage patterns to gridded products of canopy structure
• Software tools for processing lidar and radar data for vegetation studies
• Using ancillary datasets and field inventory to calibrate spaceborne estimates of vegetation canopy structure

Contributions should indicate explicitly the core observations exploited in the study, e.g. whether Lidar or radar, to facilitate channeling the study to the appropriate Frontiers section


Keywords: lidar, ICE-Sat-2, GEDI, NISAR, vegetation, canopy structure


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Topic Editors

Loading..

Submission Deadlines

20 July 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..

Topic Editors

Loading..

Submission Deadlines

20 July 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..