Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds

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© 2017 Elsevier Inc.Satellite measurements of surface water offer promise for understanding wetland habitat availability at broad spatial and temporal scales; reliable habitat is crucial for the persistence of migratory shorebirds that depend on wetland networks. We analyzed water extent dynamics within wetland habitats at a globally important shorebird stopover site for a 1983–2015 Landsat time series, and evaluated the effect of climate on water extent. A range of methods can detect open water from imagery, including supervised classification approaches and thresholds for spectral bands and indices. Thresholds provide a time advantage; however, there is no universally superior index, nor single best threshold for all instances. We used random forest to model the presence or absence of water from > 6200 reference pixels, and derived an optimal water probability threshold for our study area using receiver operating characteristic curves. An optimized mid-infrared (1.5–1.7 μm) threshold identified open water in the Sacramento Valley of California at 30-m resolution with an average of 90% producer's accuracy, comparable to approaches that require more intensive user input. SLC-off Landsat 7 imagery was integrated by applying a customized interpolation that mapped water in missing data gaps with 99% user's accuracy. On average we detected open water on ~ 26000 ha (~ 3% of the study area) in early April at the peak of shorebird migration, while water extent increased five-fold after the migration rush. Over the last three decades, late March water extent declined by ~ 1300 ha per year, primarily due to changes in the extent and timing of agricultural flood-irrigation. Water within shorebird habitats was significantly associated with an index of water availability at the peak of migration. Our approach can be used to optimize thresholds for time series analysis and near-real-time mapping in other regions, and requires only marginally more time than generating a confusion matrix.






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Schaffer-Smith, Danica, Jennifer J Swenson, Blake Barbaree and Matthew E Reiter (2017). Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds. Remote Sensing of Environment, 193. pp. 180–192. 10.1016/j.rse.2017.02.016 Retrieved from

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Jennifer J. Swenson

Adjunct Professor in the Division of Environmental Science and Policy

Swenson's research tracks changes in terrestrial Earth's living surface at the landscape to region scale with remote sensing and geospatial analysis. Her interest include: how patterns and canopy structure are effected by drought, afforestation, and deforestation, patterns and climate shifts of ecosystem biodiversity, and providing access to practitioners to remotely sensed data and analysis. Prior to her 15 years in Duke's Nicholas School of the Environment, she held positions in NGOs (NatureServe in DC, EcoCiencia in Quito, Ecuador), as well as in the US Federal Government (US Forest Service-Oregon, National Park Service-Colorado). Her research has been supported by NASA, NSF, USDA and other institutions.

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