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Remote Sens. 2014, 6(3), 2239-2254; doi:10.3390/rs6032239

Estimating Canopy Characteristics of Inner Mongolia’s Grasslands from Field Spectrometry

1
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
2
Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, USA
3
Chinese Academy of Meteorological Sciences, Beijing 100081, China
4
International Center for Ecology, Meteorology and Environment, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
*
Author to whom correspondence should be addressed.
Received: 2 January 2014 / Revised: 26 February 2014 / Accepted: 3 March 2014 / Published: 12 March 2014
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Abstract

This study was designed to estimate the canopy biophysical characteristics of semi-arid grassland ecosystems by using in situ field spectrometry measurements to identify important spectral information for predictions at broader spatial scales. Spectral vegetation indices (VIs), reflectance spectra, continuum removal spectra, and the amplitude of the red edge peak (drre) based on 61 well-replicated field measurements across a large area in Inner Mongolia were used to develop empirical models for estimating four key canopy biophysical features: percent green coverage (PGC), canopy height (H), green aboveground biomass (GBM), and total aboveground biomass (TBM). The results showed that NDVI, EVI, NDSVI, and LSWI were useful for estimating canopy biophysical features, with NDSVI being the most significant variable. The PGC was accurately estimated with spectral reflectance at 441 nm and 2220 nm (R2 = 0.71), while the maximum depth of band (Dc), absorption area (Darea) in the red domain and drre were selected for estimating TBM and GBM (R2 = 0.51 and 0.44). Among the four canopy features, PGC received the highest confidence from all of the models (R2 = 0.81), while H was the most difficult to estimate (R2 = 0.49). Finally, the degree of disturbances and ecosystem types appeared to be a significant variable for model development. View Full-Text
Keywords: continuum removal spectra; hyperspectral field spectroscopy; reflectance spectra; vegetation indices; vegetation biophysical characteristics continuum removal spectra; hyperspectral field spectroscopy; reflectance spectra; vegetation indices; vegetation biophysical characteristics
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Zhang, F.; John, R.; Zhou, G.; Shao, C.; Chen, J. Estimating Canopy Characteristics of Inner Mongolia’s Grasslands from Field Spectrometry. Remote Sens. 2014, 6, 2239-2254.

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