Abstract
Degradation of streams and associated riparian habitat across the Missouri River Headwaters Basin has motivated several stream restoration projects across the watershed. Many of these projects install a series of beaver dam analogues (BDAs) to aggrade incised streams, elevate local water tables, and create natural surface water storage by reconnecting streams with their floodplains. Satellite imagery can provide a spatially continuous mechanism to monitor the effects of these in-stream structures on stream surface area. However, remote sensing-based approaches to map narrow (e.g., <5 m wide) linear features such as streams have been under-developed relative to efforts to map other types of aquatic systems, such as wetlands or lakes. We mapped pre- and post-restoration (one to three years post-restoration) stream surface area and riparian greenness at four stream restoration sites using Worldview-2 and 3 images as well as a QuickBird-2 image. We found that panchromatic brightness and eCognition-based outputs (0.5 m resolution) provided high-accuracy maps of stream surface area (overall accuracy ranged from 91% to 99%) for streams as narrow as 1.5 m wide. Using image pairs, we were able to document increases in stream surface area immediately upstream of BDAs as well as increases in stream surface area along the restoration reach at Robb Creek, Alkali Creek and Long Creek (South). Although Long Creek (North) did not show a net increase in stream surface area along the restoration reach, we did observe an increase in riparian greenness, suggesting increased water retention adjacent to the stream. As high-resolution imagery becomes more widely collected and available, improvements in our ability to provide spatially continuous monitoring of stream systems can effectively complement more traditional field-based and gage-based datasets to inform watershed management.
Highlights
Sensed imagery has been widely applied to characterize variability in surface-water extent across space and time [1,2]
We found separating the influence of weather relative to the influence of human-induced change challenging in the riparian areas
We found that utilizing bands unique to Worldview-2 and 3 in an eCognition framework can produce accurate results and minimal errors of commission down to a stream width of approximately 1.5 m
Summary
Sensed imagery has been widely applied to characterize variability in surface-water extent across space and time [1,2]. The spatial resolution (≥30 m) of commonly used sources of imagery (e.g., Landsat, MODIS, AVHRR), has limited our ability to remotely monitor river systems, except for large rivers (e.g., >40 m wide) [3] or rivers under flood conditions [4,5,6,7]. Riverscape units including the active channel have primarily been mapped by digitizing very high-resolution multispectral satellite imagery or aerial imagery [19,20,21] or by applying geographical object-based image analysis (GEOBIA) methods [11,22,23]. A GEOBIA approach segments an image into homogenous objects prior to object classification Such an approach can help account for the greater within-class spectral variability that can occur with high-resolution imagery, relative to moderate-resolution imagery [18]. Efforts to remotely monitor narrow, linear water features, such as rivers and streams, have lagged behind efforts to remotely monitor lakes and wetlands [24,25]
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