Linear transformation to minimize the effects of variability in understory to estimate percent tree canopy cover using RapidEye data

Ozdemir I.

GISCIENCE & REMOTE SENSING, vol.51, no.3, pp.288-300, 2014 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 51 Issue: 3
  • Publication Date: 2014
  • Doi Number: 10.1080/15481603.2014.912876
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.288-300


Variability in understory structure is an important problem in estimating tree canopy cover (TCC) with satellite imagery. Differences between understory structure due to the composition and configuration of herbaceous/shrub species often produce different vegetation index values despite these areas having the same TCC. This study offers a linear transformation approach to minimizing the influence of variability in the understory to accurately estimate percent TCC from RapidEye satellite data. TCC was modeled as a function of the Normalized Difference Vegetation Index (NDVI), Normalized Difference Red-Edge Index (NDRE), adjusted (linear transformed) NDVI (NDVIadj), and adjusted NDRE (NDREadj) using simple linear regression. The coefficient of determination of validation (R-vld(2)) of the models using NDVI, NDRE, NDVIadj, and NDREadj as explanatory variables were, respectively, 0.50 (RMSEvld = 9.64%), 0.38 (RMSEvld = 10.7%), 0.78 (RMSEvld = 6.61%), and 0.73 (RMSEvld = 7.23%). These results showed that the linear transformation used for standardizing the vegetation index values of understory was an effective approach for estimating TCC.