Title :
Extraction of forest parameters in a mire biotope using high-resolution digital surface models and airborne imagery
Author :
Waser, L.T. ; Ginzler, C. ; Kuechle, M. ; Thee, P. ; Baltsavias, E. ; Eisenbeiss, H.
Author_Institution :
Swiss Fed. Res. Inst. WSL, Birmensdorf
Abstract :
The objective of this paper is to spatially predict tree/shrub genera using generalized linear models (GLM), color- infrared (CIR) aerial images, ADS40 images, digital surface models (DSM)s and field samples. The present study was carried out in the framework of the Swiss Mire Protection Program, where extraction of forest parameters for description of present state of a mire ecosystem and as indicators for changes are of high importance. In a first step, high-quality DSMs were automatically generated from CIR aerial images for two test sites, both located in the Pre-alpine zone of Central Switzerland. In a second step, tree layers were then generated combining canopy height models derived from the DSMs and LiDAR DTM with a fuzzy classification of CIR aerial images. In a third step, on the basis of these tree layers, fractional tree/shrub covers were generated using explanatory variables derived from the DSMs and logistic regression models. Then tree genera were predicted for the pixel values (tree/shrub probability > 0.3) of the fractional covers using a multinomial regression model and additional spectral information as provided by Leica ADS40 data for one test site and CIR aerial images for the other test site. Overall, prediction of tree genera was less satisfactory when only using CIR aerial images. In contrary, up to six different tree genera were predicted with high accuracy using explanatory variables derived from ADS40 images. The study stresses the importance of high-resolution and high-quality DSMs and highlights the potential airborne remotes sensing data for ecological modeling purposes.
Keywords :
atmospheric boundary layer; feature extraction; fuzzy logic; geophysics computing; image classification; remote sensing; vegetation; ADS40 images; Central Switzerland; GLM; LiDAR DTM; Pre-alpine zone; Swiss Mire Protection Program; airborne remote sensing data; canopy height models; color-infrared aerial images; ecological modeling; forest parameters extraction; fractional tree-shrub cover; fuzzy classification; generalized linear models; high-resolution digital surface models; logistic regression model; mire biotope; mire ecosystem; multinomial regression model; Automatic testing; Classification tree analysis; Ecosystems; Infrared imaging; Laser radar; Logistics; Pixel; Predictive models; Protection; Regression tree analysis; CIR aerial images; Leica ADS40 image; LiDAR; Swiss Mire Protection Program; Tree genera; environmental modeling; forest classification; fractional tree/shrub cover; multi-image matching; stand composition;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4423036