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Article

Analysis of the Scaling Effects in the Area-Averaged Fraction of Vegetation Cover Retrieved Using an NDVI-Isoline-Based Linear Mixture Model

by 1,2,†, 2 and 1,*
1
Department of Information Science and Technology, Aichi Prefectural University, 1522-3 Ibara, Nagakute, Aichi 480-1198, Japan
2
Department of Natural Resources and Environmental Management, University of Hawaii at Manoa, 1910 East West Road, Sherman 101, Honolulu, HI 96822, USA
*
Author to whom correspondence should be addressed.
Current address: Department of Natural Resources and Environmental Management, University of Hawaii at Manoa, 1910 East West Road, Sherman 101, Honolulu, HI 96822, USA.
Remote Sens. 2012, 4(7), 2156-2180; https://doi.org/10.3390/rs4072156
Received: 16 May 2012 / Revised: 11 July 2012 / Accepted: 11 July 2012 / Published: 18 July 2012
The spectral unmixing of a linear mixture model (LMM) with Normalized Difference Vegetation Index (NDVI) constraints was performed to estimate the fraction of vegetation cover (FVC) over the earth’s surface in an effort to facilitate long-term surface vegetation monitoring using a set of environmental satellites. Although the integrated use of multiple sensors improves the spatial and temporal quality of the data sets, area-averaged FVC values obtained using an LMM-based algorithm suffer from systematic biases caused by differences in the spatial resolutions of the sensors, known as scaling effects. The objective of this study is to investigate the scaling effects in area-averaged FVC values using analytical approaches by focusing on the monotonic behavior of the scaling effects as a function of the spatial resolution. The analysis was conducted based on a resolution transformation model introduced recently by the authors in the accompanying paper (Obata et al., 2012). The maximum value of the scaling effects present in FVC values was derived analytically and validated numerically. A series of derivations identified the error bounds (inherent uncertainties) of the averaged FVC values caused by the scaling effect. The results indicate a fundamental difference between the NDVI and the retrieved FVC from NDVI, which should be noted for accuracy improvement of long-term observation datasets. View Full-Text
Keywords: fraction of vegetation cover; scaling effect; monotonicity; NDVI; resolution transformation model fraction of vegetation cover; scaling effect; monotonicity; NDVI; resolution transformation model
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MDPI and ACS Style

Obata, K.; Miura, T.; Yoshioka, H. Analysis of the Scaling Effects in the Area-Averaged Fraction of Vegetation Cover Retrieved Using an NDVI-Isoline-Based Linear Mixture Model. Remote Sens. 2012, 4, 2156-2180. https://doi.org/10.3390/rs4072156

AMA Style

Obata K, Miura T, Yoshioka H. Analysis of the Scaling Effects in the Area-Averaged Fraction of Vegetation Cover Retrieved Using an NDVI-Isoline-Based Linear Mixture Model. Remote Sensing. 2012; 4(7):2156-2180. https://doi.org/10.3390/rs4072156

Chicago/Turabian Style

Obata, Kenta, Tomoaki Miura, and Hiroki Yoshioka. 2012. "Analysis of the Scaling Effects in the Area-Averaged Fraction of Vegetation Cover Retrieved Using an NDVI-Isoline-Based Linear Mixture Model" Remote Sensing 4, no. 7: 2156-2180. https://doi.org/10.3390/rs4072156

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