Emanuelle Feliciano

Emanuelle Feliciano

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Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 April 2016 in Remote Sensing
Verified
Journal Article
Open access
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DLDavid Lagomasino
David Lagomasino
TFTemilola Fatoyinbo
Temilola Fatoyinbo
SLSeung Kuk Lee
Seung Kuk Lee
EFEmanuelle Feliciano
Emanuelle Feliciano
CTCarl Trettin
Carl Trettin
MSMarc Simard
Marc Simard
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.

12 June 2018 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Verified
Journal Article
Closed access
SLSeung Kuk Lee
Seung Kuk Lee
TFTemilola Fatoyinbo
Temilola Fatoyinbo
DLDavid Lagomasino
David Lagomasino
EFEmanuelle Feliciano
Emanuelle Feliciano
CTCarl Trettin
Carl Trettin
We generated a large-scale mangrove forest height map using multiple TanDEM-X (TDX) interferometric synthetic aperture radar (InSAR) acquisitions with various spatial baselines in order to improve the height estimation accuracy across a wide range of forest heights. The forest height inversion using InSAR data is strongly dependent upon the vertical wavenumber (i.e., perpendicular baseline). First, we investigated the role of the vertical wavenumber in forest height inversion from InSAR data using the sensitivity of the interferometric (volume) coherence to forest height. We used corrected but lower resolution and accuracy Shuttle Radar Topography Mission (SRTM) mangrove height maps as a priori information over Akanda and Pongara National Parks in Gabon to estimate lower and upper boundaries of the vertical wavenumber over test sites from the measured coherence-to-height sensitivity. Only TDX acquisitions within the boundaries of the vertical wavenumber were selected and combined for multibaseline mangrove height inversion. Mangrove forest height was obtained with multibaseline TDX acquisitions and was validated against the reference height derived from field measurement data providing improvements in multibaseline inversion over existing height estimates (i.e., SRTM height) and single-baseline inversions (multibaseline inversion: $r^{2}= {\text{0.98}}$, root mean square error (RMSE) of 2.73 m; SRTM height: $r^{2}= {\text{0.86}}$, ${\text{RMSE}}= {\text{7.21}}$ m; single-baseline inversions: $r^{2}= {\text{0.08}}{\hbox{-}} {\text{0.97}}$, ${\text{RMSE}}= {\text{3.86}}$–11.10 m). As a result, to accurately estimate forest heights over a wide range (3–60 m), multibaseline InSAR acquisitions (at least three different baselines) are needed to exclude biases associated with the vertical wavenumber in forest height inversion.