| dc.creator |
Ozdemir, Ibrahim |
|
| dc.date |
2013-12-31T22:00:00Z |
|
| dc.date.accessioned |
2020-10-06T09:29:42Z |
|
| dc.date.available |
2020-10-06T09:29:42Z |
|
| dc.identifier |
1d8de630-9793-4954-97a7-0986afd4be28 |
|
| dc.identifier |
10.1080/15481603.2014.912876 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/1d8de630-9793-4954-97a7-0986afd4be28/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/54836 |
|
| dc.description |
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. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Linear transformation to minimize the effects of variability in understory to estimate percent tree canopy cover using RapidEye data |
|
| dc.type |
info:eu-repo/semantics/article |
|