This data set contains satellite-derived information on geomorphic river mobility for ten catchments in the Philippines. We applied the locational probability approach to map the proportion of time that a river channel occupies a particular location. We quantified satellite-derived locational probabilities for 600 km2 of riverbed. The information is useful for predicting and developing resilience to river-related hazards in dynamic landscapes. We provide example Google Earth Engine (GEE) and MATLAB codes to replicate satellite-derived locational probability analyses, and provide outputs for each catchment. Data sets include: (1) example GEE codes to run satellite imagery analyses; (2) example MATLAB codes and data to generate locational probabilities; (3) example MATLAB codes and data to produce longitudinal analyses; and, (4) processed locational probability outputs for the ten catchments. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312. Full details about this dataset can be found at https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d

The shapefiles contain the classification and locations of each river style determined by the authors. The data were used to characterise the river styles in Bislak River, Philippines. Shapefiles were clipped to the catchment boundary from different national government agencies to produce different thematic maps. Catchment properties such as land use (from the National Mapping and Resource Information Authority (NAMRIA)), geology (from the Mines and Geosciences Bureau), fault (from Philippine Institute of Volcanology and Seismology, rainfall isohyets, slope map, and the digital elevation model (also from NAMRIA) were used for regional and catchment analysis. The data only covers the whole Bislak catchment, Philippines. The CSV contains data used for the stream power analysis where stream power is a factor of slope and discharge. Full details about this dataset can be found at https://doi.org/10.5285/31ae71aa-74a9-466b-9a3a-25d2b1a9406e