Data for: A generalized area-based framework to quantify river mobility from remotely sensed imagery

Rivers are the primary conduits of water and sediment across Earth’s
surface. In recent decades, rivers have been increasingly impacted by
climate change and human activities. The availability of global-coverage
satellite imagery provides a powerful avenue to study river mobility and
quantify the impacts of these perturbations on global river behavior.
However, we lack remote sensing methods for quantifying river mobility
that can be generally applied across the diversity of river planforms
(e.g., meandering, braided) and fluvial processes (e.g., channel
migration, avulsion). Here, we upscale area-based methods from laboratory
flume experiments to build a generalized remote sensing framework for
quantifying river mobility. The framework utilizes binary channel-mask
time series to determine time- and area-integrated rates and scales of
river floodplain reworking and channel-thread reorganization. We apply the
framework to numerical models to demonstrate that these rates and scales
are sensitive to specific river processes (channel migration, channel-bend
cut-off, and avulsion). We then apply the framework to natural migrating
and avulsing rivers with meandering and braided planforms. Results show
that our area-based framework is an accurate method to quantify river
mobility at reach- to landscape-scales, and is largely insensitive to
spatial and temporal biases that can arise in traditional mobility
metrics. Our work provides a framework for investigating global controls
on river mobility, testing hypotheses about river response to
environmental gradients, and quantifying the timescales of terrestrial
organic carbon cycling.