A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

Author

David Lagomasino 1,2,†,* ,  Temilola Fatoyinbo 2,†

,  SeungKuk Lee 2,†

,Emanuelle Feliciano 2,†

,  Carl Trettin 3

 and   Marc Simard 4

1 Universities Space Research Association/GESTAR, 7178 Columbia Gateway Dr., Columbia, MD 21046, USA

2 NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

3 US Department of Agriculture, Forest Service, Cordesville, SC 29434, USA

4 Jet Propulsion Laboratory, Pasadena, CA 91109, USA

† These authors contributed equally to this work.

* Author to whom correspondence should be addressed. 

Academic Editors: Lars T. Waser, Nicolas Baghdadi and Prasad S. Thenkabail

Received: 21 January 2016 / Revised: 5 April 2016 / Accepted: 6 April 2016 / Published: 14 April 2016

Abstract 

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

Keywords: canopy height; DSM; biomass; Africa; H100; blue carbon; TDX; VHR; MRV

This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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