DocumentCode :
576723
Title :
Forest mapping and monitoring in Tasmania using multi-temporal Landsat and ALOS-PALSAR data
Author :
Lehmann, E.A. ; Zhou, Z. -S ; Caccetta, P. ; Milne, A. ; Mitchell, A. ; Lowell, K. ; Held, A.
Author_Institution :
Div. of Math., Inf. & Stat., Commonwealth Sci. & Ind. Res. Organ. (CSIRO), Perth, WA, Australia
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6431
Lastpage :
6434
Abstract :
Developing a large-scale forest monitoring system able to take advantage of the complementary nature of optical and radar remote sensing data presents a number of technical and conceptual challenges. This paper investigates the issue of sensor interoperability in a time series of Landsat and ALOS-PALSAR data for purposes related to forest mapping and monitoring. The proposed approach relies on the processing methods developed in the frame of an existing and operational Landsat-based forest monitoring system. These methods are here applied to a PALSAR dataset within a bioregion of north-eastern Tasmania, Australia. Particular attention is given to the selection of training data in an attempt to generate results comparable to those obtained with the original Landsat-only time series, thereby allowing for a relevant assessment of interoperability. Results are presented in the form of forest maps and areal forest estimates. Despite similar gross amounts of forest extents, these results highlight differences in the forest (and change) classifications produced using different sensors. Combinations of sensors should therefore be carefully considered in light of what is required of the monitoring system.
Keywords :
forestry; geophysical image processing; image classification; radar imaging; remote sensing by radar; synthetic aperture radar; vegetation mapping; ALOS-PALSAR data; Australia; Landsat time series; Landsat-based forest monitoring system; PALSAR dataset; areal forest estimation; forest mapping; interoperability assessment method; large-scale forest monitoring system; multitemporal Landsat data; north-eastern Tasmania bioregion; optical remote sensing data; radar remote sensing data; Biomedical optical imaging; Earth; Noise measurement; Optical sensors; Remote sensing; Satellites; Time series analysis; Forest mapping; interoperability; multi-sensor; multi-temporal; remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352731
Filename :
6352731
Link To Document :
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