Remote Sensing Applications and Decision Support

Estimating woody above-ground biomass in an arid zone of central Australia using Landsat imagery

[+] Author Affiliations
Zhihui Wang

Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Sciences, Beijing 100094, China

Graduate University of Chinese Academy of Sciences, Beijing 100039, China

Gary N. Bastin

CSIRO Ecosystem Sciences, PO Box 2111, Alice Springs, Northern Territory 0871, Australia

Liangyun Liu, Dailiang Peng

Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Sciences, Beijing 100094, China

Peter A. Caccetta

CSIRO Division of Mathematics, Informatics and Statistics, Private Bag 5, Wembley, Western Australia 6913, Australia

J. Appl. Remote Sens. 9(1), 096036 (Jun 25, 2015). doi:10.1117/1.JRS.9.096036
History: Received December 4, 2014; Accepted May 27, 2015
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Abstract.  Woody cover was found to be an easily measurable and significant variable for estimating woody above-ground biomass (AGB) based on in situ measurements in an arid zone of central Australia. In addition, the potential of woody cover to estimate woody AGB based on Landsat imagery was further tested. Linear spectral mixture analysis (LSMA) using multitemporal endmembers was employed to estimate the woody cover for Landsat imagery and the LSMA method was tested for different Landsat images under various drought conditions. The results show that the accuracy of the woody cover estimation increased as the accumulated rainfall prior to the image acquisition date decreased. Woody AGB across the study area was finally retrieved using the combination of plot-level woody AGB model and woody cover derived from dry-period Landsat images closest to the acquisition time of the field data, with an root mean square error of 0.798t/ha. It is concluded that woody cover is able to replace tree basal area to estimate woody AGB at plot-level scale, and it is much more suitable for estimating woody AGB than the normalized difference vegetation index-AGB model for this arid zone covered with low-cover shrubs; however, woody AGB estimated using the proposed method is underestimated for some areas.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Topics

Landsat

Citation

Zhihui Wang ; Gary N. Bastin ; Liangyun Liu ; Peter A. Caccetta and Dailiang Peng
"Estimating woody above-ground biomass in an arid zone of central Australia using Landsat imagery", J. Appl. Remote Sens. 9(1), 096036 (Jun 25, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096036


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