Satellite-derived geomorphic river mobility for ten catchments in the Philippines, 1988-2019
Cite this dataset as:
Boothroyd, R.J.; Williams, R.D.; Hoey, T.B.; Brierley, G.J.; Tolentino, P.L.M.; Guardian, E.L.; Reyes, J.C.M.; Sabillo, C.J.; Quick, L.; Perez, J.E.G.; David, C.P.C. (2025). Satellite-derived geomorphic river mobility for ten catchments in the Philippines, 1988-2019. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d
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This dataset is available under the terms of the Open Government Licence 
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https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d
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.
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.
Publication date: 2025-04-04
View numbers valid from 04 April 2025 Download numbers valid from 04 April 2025 (information prior to this was not collected)
Formats
TIFF, .txt, Shapefile
Spatial information
Study area
Spatial representation types
Raster
Vector
Vector
Spatial reference system
WGS 84 / UTM zone 51N
Temporal information
Temporal extent
1988-01-01 to 2019-12-31
Provenance & quality
We calculated locational probabilities from multi-temporal Landsat imagery. We processed a 32-year record of Landsat satellite imagery between 1988-2019 into two-year time-windows and classified active channels as including both wetted channels and unvegetated alluvial deposits; analogous to the bankfull channel extent. Having quality checked and manually edited the binary active channel outputs, we calculated per-pixel locational probabilities to indicate the spatial dynamics of geomorphic river mobility.
QA was completed by visually checking the active channel extents against available imagery. The position of classified active river channels were in good visual agreement with satellite and aerial imagery (e.g. Landsat and Google Earth imagery).
The data set is fully described in the supporting documentation and the methods section of Boothroyd et al., (2025).
QA was completed by visually checking the active channel extents against available imagery. The position of classified active river channels were in good visual agreement with satellite and aerial imagery (e.g. Landsat and Google Earth imagery).
The data set is fully described in the supporting documentation and the methods section of Boothroyd et al., (2025).
Licensing and constraints
This dataset is available under the terms of the Open Government Licence
Cite this dataset as:
Boothroyd, R.J.; Williams, R.D.; Hoey, T.B.; Brierley, G.J.; Tolentino, P.L.M.; Guardian, E.L.; Reyes, J.C.M.; Sabillo, C.J.; Quick, L.; Perez, J.E.G.; David, C.P.C. (2025). Satellite-derived geomorphic river mobility for ten catchments in the Philippines, 1988-2019. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d
Citations
Boothroyd, R.J., Williams, R.D., Hoey, T.B. et al. Big data show idiosyncratic patterns and rates of geomorphic river mobility. Nat Commun 16, 3263 (2025). https://doi.org/10.1038/s41467-025-58427-9
Supplemental information
Boothroyd, R. J., Williams, R. D., Hoey, T. B., Brierley, G. J., Tolentino, P. L. M., Guardian, E. L., Reyes, J. C. M. O., Sabillo, C. J., Quick, L., Perez, J. E. G and David, C. P. C. (2025). Big data show idiosyncratic patterns and rates of geomorphic river mobility. Nature Communications
Correspondence/contact details
Authors
https://orcid.org/0000-0001-9742-4229
Guardian, E.L.
University of the Philippines Diliman
Reyes, J.C.M.
University of the Philippines Diliman
Sabillo, C.J.
University of the Philippines Diliman
Perez, J.E.G.
University of Vienna
David, C.P.C.
University of the Philippines Diliman
Other contacts
Rights holder
University of Glasgow
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Additional metadata
Keywords
Funding
Natural Environment Research Council Award: NE/S003312/1
Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD)
Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD)
Last updated
28 April 2025 12:16