Combining multisensor images and social network data to assess the area flooded by a hurricane event.

In this study, multisensor remote sensing datasets were used to characterize the land use and land covers (LULC) flooded by Hurricane Willa which made landfall on October 24, 2018. The landscape characterization was done using an unsupervised K-means algorithm of a cloud-free Sentinel-2 MultiSpectral Instrument (MSI) image, acquired during the dry season before Hurricane Willa. A flood map was derived using the histogram thresholding technique over a Synthetic Aperture Radar (SAR) Sentinel-1 C-band and combined with a flood map derived from a Sentinel-2 MSI image.

Effects of land use changes on the ecosystem service values of coastal wetlands.

Changes in the coastal landscape of Southern Sinaloa (Mexico), between 2000 and 2010, were analyzed to relate spatial variations in wetlands extent with the provision and economic value of the ecosystem services (ES). Remote sensing techniques applied to Landsat TM imagery were used to evaluate land use/land cover changes while the value transfer method was used to assess the value of ES by land cover category. Five wetland types and other four land covers were found as representative of the coastal landscape.

Assessment of runoff response to landscape changes in the San Pedro subbasin (Nayarit, Mexico) using remote sensing data and GIS.

Results on runoff estimates as a response to land-use and land-cover changes are presented. We used remote sensing and GIS techniques with rainfall time-series data, spatial ancillary information, and the curve-number method (NRCS-CN) to assess the runoff response in the San Pedro subbasin. Thematic maps with eight land-cover classes derived from satellite imagery classification (1973, 1990, and 2000) and hydrologic soil-group maps were used as the input for the runoff calculation.