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A multispectral multiplatform based change detection tool for vegetation disturbance on Irish peatlands

O'Connell, Jerome orcid logoORCID: 0000-0002-4782-1549, Connolly, John orcid logoORCID: 0000-0002-2897-9711 and Holden, Nicholas M. orcid logoORCID: 0000-0002-0452-4632 (2011) A multispectral multiplatform based change detection tool for vegetation disturbance on Irish peatlands. In: SPIE Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 19-22 Sept 2011, Prague, Czech Republic.

In this study satellite data from five different multispectral sensors were used in a change detection study of vegetation disturbance on an Irish active raised bog. Radiometric normalisation was performed using Temporally Invariant Clusters (TIC) and cross calibration applied using linear regression of radiometrically stable ground-based targets. Erdas Imagine’s Spatial Modeller was used to create a change detection model using pixel-to-pixel based subtraction with a Standard Deviation (SD) threshold. The effectiveness of the cross calibration process was shown with the aid of Kolmogorov Smirnov sample tests which showed a reduced D value between master and slave cumulative distribution curves after cross calibration. The spatial accuracy of various SD threshold levels was assessed, with 1.5 SD producing 0.19% error when compared to actual ground truth boundary data of change. An error matrix of change/ no change verified 1.5 SD as the optimum threshold for change detection, with user, producer, overall and kappa values all above 95%. Vegetation disturbance in the study was predominantly attributed to turf cutting on the boundaries of the bog. However in May 2008 a large burn event occurred on the northeastern side of the bog which removed all surface vegetation, equating to an area of 36ha (or 7.85% of total area).
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Geography; change detection; multi-platform; multispectral; multi-temporal; EVI2; peatlands
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Humanities and Social Science > School of History and Geography
Published in: Neale, Christopher M. U., Maltese, Antonino and Richte, Katja, (eds.) Proceedings, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII. 8174. SPIE.
Official URL:http://dx.doi.org/10.1117/12.898562
Copyright Information:© 2011 SPIE
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:23581
Deposited On:18 Jul 2019 15:14 by Thomas Murtagh . Last Modified 18 Jul 2019 15:14

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