|
Titel |
Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception |
VerfasserIn |
H. H. Bulcock, G. P. W. Jewitt |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1027-5606
|
Digitales Dokument |
URL |
Erschienen |
In: Hydrology and Earth System Sciences ; 14, no. 2 ; Nr. 14, no. 2 (2010-02-25), S.383-392 |
Datensatznummer |
250012191
|
Publikation (Nr.) |
copernicus.org/hess-14-383-2010.pdf |
|
|
|
Zusammenfassung |
The establishment of commercial forestry plantations in natural grassland
vegetation, results in increased transpiration and interception which in
turn, results in a streamflow reduction. Methods to quantify this impact
typically require LAI as an input into the various equations and process
models that are applied. The use of remote sensing technology as a tool to
estimate leaf area index (LAI) for use in estimating canopy interception is
described in this paper. Remote sensing provides a potential solution to
effectively monitor the spatial and temporal variability of LAI. This is
illustrated using Hyperion hyperspectral imagery and three vegetation
indices, namely the normalized difference vegetation index (NDVI), soil
adjusted vegetation index (SAVI) and Vogelmann index 1 to estimate LAI in a
catchment afforested with Eucalyptus, Pinus and Acacia genera in the KwaZulu-Natal midlands of South
Africa. Of the three vegetation indices used in this study, it was found
that the Vogelmann index 1 was the most robust index with an R2 and
root mean square error (RMSE) values of 0.7 and 0.3 respectively. However,
both NDVI and SAVI could be used to estimate the LAI of 12 year old Pinus patula
accurately. If the interception component is to be quantified independently,
estimates of maximum storage capacity and canopy interception are required.
Thus, the spatial distribution of LAI in the catchment is used to estimate
maximum canopy storage capacity in the study area. |
|
|
Teil von |
|
|
|
|
|
|