Vol. 13, Special Issue 1: 34th EARSeL Symposium, 30-35, 2014

Wetland Leaf Area Index modelling with field and satellite hyperspectral data
Tomasz Berezowski, and Jaroslaw Chormański

Leaf Area Index (LAI) is an important variable in environmental processes modelling. Already several approaches were proposed to model wetlands LAI with remote sensing data. However, none of these methods was based on upscaling the field spectral reflectance measurements, which is a matter of this paper. In this study, we used combined measurements of spectral reflectance (350-2500 nm) and LAI to establish a regression model of LAI. The spectral reflectance was resampled to the spectral resolution of a satellite hyperspectral sensor (CHRIS-PROBA) beforehand and then used to calculate NDVI-based spectral indices. From the set of spectral indices the one with the strongest correlation with LAI was chosen for the regression. Finally, the regression was applied to the CHRIS satellite images and the results were analysed within the scope of different wetland communities of the study area. The results show that the optimal regression model gives statistically different LAI values for the majority of different ground truth plant communities, rivers and urban areas.

View Full Text (pdf file, 2.4 MB) previous page
DOI: 10.12760/02-2014-1-06

Submitted: 3 Feb 2014
Revised: 17 July 2014
Accepted: 17 July 2014
Published: 30 July 2014
Responsible editor: Bogdan Zagajewski

Berezowski T & J Chormański, 2014. Wetland Leaf Area Index modelling with field and satellite hyperspectral data. EARSeL eProceedings, 13(S1): 30-35

EARSeL European Association of Remote Sensing Laboratories, Strasbourg, France


BIS Library and Information System, Carl von Ossietzky University of Oldenburg


Indexed in Scopus

DOAJ logo

Directory of Open Access Journals


Opening access to research

Creative Commons License

ISSN 1729-3782