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Open AccessArticle

Identification of Woodland Vernal Pools with Seasonal Change PALSAR Data for Habitat Conservation

Michigan Tech Research Institute, Michigan Technological University, 3600 Green Ct. Suite 100, Ann Arbor, MI 48105, USA
Michigan Natural Features Inventory, Michigan State University Extension, P.O. Box 13036, Lansing, MI 48901, USA
Author to whom correspondence should be addressed.
Academic Editors: Javier Bustamante, Alfredo R. Huete, Patricia Kandus, Ricardo Díaz-Delgado, Josef Kellndorfer and Prasad S. Thenkabail
Remote Sens. 2016, 8(6), 490;
Received: 2 March 2016 / Revised: 20 May 2016 / Accepted: 2 June 2016 / Published: 10 June 2016
(This article belongs to the Special Issue What can Remote Sensing Do for the Conservation of Wetlands?)
Woodland vernal pools are important, small, cryptic, ephemeral wetland ecosystems that are vulnerable to a changing climate and anthropogenic influences. To conserve woodland vernal pools for the state of Michigan USA, vernal pool detection and mapping methods were sought that would be efficient, cost-effective, repeatable and accurate. Satellite-based L-band radar data from the high (10 m) resolution Japanese ALOS PALSAR sensor were evaluated for suitability in vernal pool detection beneath forest canopies. In a two phase study, potential vernal pool (PVP) detection was first assessed with unsupervised PALSAR (LHH) two season change detection (spring when flooded—summer when dry) and validated with 268, 1 ha field-sampled test cells. This resulted in low false negatives (14%–22%), overall map accuracy of 48% to 62% and high commission error (66%). These results make this blind two-season PALSAR approach for cryptic PVP detection of use for locating areas of high vernal pool likelihood. In a second phase of the research, PALSAR was integrated with 10 m USGS DEM derivatives in a machine learning classifier, which greatly improved overall PVP map accuracies (91% to 93%). This supervised approach with PALSAR was found to produce better mapping results than using LiDAR intensity or C-band SAR data in a fusion with the USGS DEM-derivatives. View Full-Text
Keywords: synthetic aperture radar; DEM; vernal pools; LiDAR synthetic aperture radar; DEM; vernal pools; LiDAR
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Bourgeau-Chavez, L.L.; Lee, Y.M.; Battaglia, M.; Endres, S.L.; Laubach, Z.M.; Scarbrough, K. Identification of Woodland Vernal Pools with Seasonal Change PALSAR Data for Habitat Conservation. Remote Sens. 2016, 8, 490.

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