Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

This research estimated the surface water fraction from MODIS 16-day 500 m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500 m reference dataset on surface water fraction by spatially aggregating 30 m binary water masks derived from the C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30 m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2 = 0.91, RMSE = 11.05%, MAE = 7.67%). Our approach is promising for monitoring surface water fraction at high frequency time intervals over much larger regions provided that training data are collected across the spatial domain for which the model will be applied.

Identifier
DOI https://doi.org/10.17026/dans-zf9-4882
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-hp-t8bc
Related Identifier https://doi.org/10.1016/j.jag.2017.11.007
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:100995
Provenance
Creator Li, L
Publisher Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente
Contributor Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente
Publication Year 2018
Rights info:eu-repo/semantics/openAccess; DANS License; https://dans.knaw.nl/en/about/organisation-and-policy/legal-information/DANSLicence.pdf
OpenAccess true
Representation
Language English
Resource Type Dataset
Format Excel; .csv
Discipline Other
Spatial Coverage Spain