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Use of radar remote sensing (RADARSAT) to map winter wetland habitat for shorebirds in an agricultural landscape

Environmental Management

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Abstract

Many of todays agricultural landscapes once held vast amounts of wetland habitat for waterbirds and other wildlife. Successful restoration of these landscapes relies on access to accurate maps of the wetlands that remain. We used C-band (5.6-cm-wavelength), HH-polarized radar remote sensing (RADARSAT) at a 38A? incidence angle (8-m resolution) to map the distribution of winter shorebird (Charadriiformes) habitat on agricultural lands in the Willamette Valley of western Oregon. We acquired imagery on three dates (10 December 1999, 27 January 2000, and 15 March 2000) and simultaneously collected ground reference data to classify radar signatures and evaluate map accuracy of four habitat classes: (1) wet with 50% vegetation (considered optimal shorebird habitat), (2) wet with > 50% vegetation, (3) dry with 50% vegetation, and (4) dry with > 50% vegetation. Overall accuracy varied from 45 to 60% among the three images, but the accuracy of focal class 1 was greater, ranging from 72 to 80%. Class 4 coverage was stable and dominated maps (40% of mapped study area) for all three dates, while coverage of class 3 decreased slightly throughout the study period. Among wet classes, class 1 was most abundant (about 30% coverage) in December and January, decreasing in March to approximately 15%. Conversely, class 2 increased dramatically from January to March, likely due to transition from class 1 as vegetation grew. This approach was successful in detecting optimal habitat for shorebirds on agricultural lands. For modest classification schemes, radar remote sensing is a valuable option for wetland mapping in areas where cloud cover is persistent.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Use of radar remote sensing (RADARSAT) to map winter wetland habitat for shorebirds in an agricultural landscape
Series title:
Environmental Management
Volume
33
Issue:
5
Year Published:
2004
Language:
English
Contributing office(s):
Forest and Rangeland Ecosystem Science Center
Description:
p. 750-763
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Environmental Management
First page:
750
Last page:
763
Number of Pages:
14