Next Article in Journal
Multi-Sensor As-Built Models of Complex Industrial Architectures
Next Article in Special Issue
Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data
Previous Article in Journal
Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring
Previous Article in Special Issue
Object-Based Canopy Gap Segmentation and Classification: Quantifying the Pros and Cons of Integrating Optical and LiDAR Data
 
Search for Articles:
Title / Keyword
Author / Affiliation
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
Journals
Remote Sensing
Volume 7
Issue 12
10.3390/rs71215830
remotesensing-logo
Submit to this Journal Review for this Journal Edit a Special Issue
► Article Menu

Article Menu

share announcement question_answer thumb_up
...
textsms
...
Article

Estimation of Alpine Forest Structural Variables from Imaging Spectrometer Data

by
Parviz Fatehi
*,
Alexander Damm
,
Michael E. Schaepman
and
Mathias Kneubühler
Remote Sensing Laboratories (RSL), University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editors: Sangram Ganguly, Compton Tucker, Randolph H. Wynne and Prasad S. Thenkabail
Remote Sens. 2015, 7(12), 16315-16338; https://doi.org/10.3390/rs71215830
Received: 7 October 2015 / Revised: 23 November 2015 / Accepted: 27 November 2015 / Published: 3 December 2015
(This article belongs to the Special Issue Remote Sensing of Vegetation Structure and Dynamics)
View Full-Text Download PDF
Browse Figures

Abstract

Spatial information of forest structural variables is crucial for sustainable forest management planning, forest monitoring, and the assessment of forest ecosystem productivity. We investigate a complex alpine forest ecosystem located in the Swiss National Park (SNP) and apply empirical models to retrieve the structural variables canopy closure, basal area, and timber volume at plot scale. We used imaging spectrometer (IS) data from the Airborne Prism EXperiment (APEX) in combination with in-situ measurements of forest structural variables to develop empirical models. These models are based on simple and stepwise multiple regressions, while all potential two narrow-band combinations of the Simple Ratio (SR), the Normalized Difference Vegetation Index (NDVI), the perpendicular vegetation index (PVI), the second soil-adjusted vegetation index (SAVI2), and band depth indices were tested. The accuracy of the estimated structural attributes was evaluated using a leave-one-out cross-validation technique. Using stepwise multiple regression models, we obtained a moderate to good accuracy when estimating canopy closure (R2 = 0.81, rRMSE = 10%), basal area (R2 = 0.68, rRMSE = 20%), and timber volume (R2 = 0.73, rRMSE = 22%). We discuss the reliability of empirical approaches for estimates of canopy structural parameters considering the causality of light interaction and surface information. View Full-Text
Keywords: forest structural variables; imaging spectrometer data; empirical approach; narrow-band vegetation indices; band depth indices; APEX; Swiss National Park forest structural variables; imaging spectrometer data; empirical approach; narrow-band vegetation indices; band depth indices; APEX; Swiss National Park
►▼ Show Figures

Graphical abstract

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

Supplementary Materials

SciFeed

Share and Cite

MDPI and ACS Style

Fatehi, P.; Damm, A.; Schaepman, M.E.; Kneubühler, M. Estimation of Alpine Forest Structural Variables from Imaging Spectrometer Data. Remote Sens. 2015, 7, 16315-16338. https://doi.org/10.3390/rs71215830

AMA Style

Fatehi P, Damm A, Schaepman ME, Kneubühler M. Estimation of Alpine Forest Structural Variables from Imaging Spectrometer Data. Remote Sensing. 2015; 7(12):16315-16338. https://doi.org/10.3390/rs71215830

Chicago/Turabian Style

Fatehi, Parviz, Alexander Damm, Michael E. Schaepman, and Mathias Kneubühler. 2015. "Estimation of Alpine Forest Structural Variables from Imaging Spectrometer Data" Remote Sensing 7, no. 12: 16315-16338. https://doi.org/10.3390/rs71215830

Find Other Styles

Article Metrics

Article Access Map by Country/Region

1
Back to TopTop