Semi-automatic and manual shallow landslide inventories of two extreme rainfall events.

<p>This dataset contains the polygons of automatic ( PL) and manually (ML)&nbsp;&nbsp;based shallow landslides related to two extreme rainfall events. In KML format, the dataset can be visualized on GIS software or&nbsp;&nbsp;Google Earth.</p><p>With more details, it is possible to find:</p><ul><li>AOI_2016: The study area of the extreme rainfall of November 2016,&nbsp; Tanerello and Arroscia Valleys NW Italy.</li><li>The&nbsp; 2016_PL:&nbsp; The inventory of potential shallow landslides semi-automatically&nbsp;&nbsp;mapped on the base of Sentinel-2 images&nbsp;&nbsp;related to extreme rainfall events that hit NW Italy in November 2016</li><li>The&nbsp; 2016_ML:&nbsp; The inventory of shallow landslides manually mapped on high-resolution images of Google Earth, related to extreme rainfall events that hit NW Italy in November 2016</li><li>AOI_2019_large: The study area of the extreme rainfall of October&nbsp;2019&nbsp;&nbsp;NW Italy.</li><li>AOI_2019: The testing&nbsp;area of the extreme rainfall of October&nbsp;2019,&nbsp;Gavi Area&nbsp;NW Italy.</li><li>The&nbsp; 2019_PL_all: The inventory of potential shallow landslides semi-automatically&nbsp;&nbsp;mapped on the base of Sentinel-2 images&nbsp;&nbsp;related to extreme rainfall events that hit NW Italy in October 2019 (whole Study&nbsp;area)</li><li>The&nbsp; 2019_PL:&nbsp; The inventory of potential shallow landslides semi-automatically&nbsp;&nbsp;mapped on the base of Sentinel-2 images&nbsp;&nbsp;related to extreme rainfall events that hit NW Italy in October 2019 (Gavi test area)</li><li>The&nbsp; 2019_ML: The inventory of shallow landslides manually mapped on high-resolution images of Google Earth, related to extreme rainfall events that hit NW Italy in October 2019</li></ul><p>GEE_Script: A list of codes used in Google Earth Engine to produce NDVI time series or averaged NDVI on some sample studied areas are reported in the attached PDF.&nbsp; The code may be pasted and copied to the Google Earth Engine console.&nbsp;</p><p>The codes (if an account on &nbsp;Google Earth Engine is active) may be reached directly from the following URLs:&nbsp;</p><p><strong>Script 1. </strong>NDVI time series of some sampled areas to select the best pair of images for the PL creation (Tanarello and Arroscia Valley and GAVI AOIs; Fig. 16 of the paper). Link to GEE: <a href="https://code.earthengine.google.com/998af951fcb74519589bf8e722bb30b0?noload=true">https://code.earthengine.google.com/998af951fcb74519589bf8e722bb30b0?noload=true</a></p><p><strong>Script 2.</strong> sampled NDVI time series from different intersection cases for the Tanarello and Arroscia Valley study area (2016&nbsp; Event). Link to&nbsp; GEE: <a href="https://code.earthengine.google.com/b622cb64f90771ced78ef73bad9cc50f?noload=true">https://code.earthengine.google.com/b622cb64f90771ced78ef73bad9cc50f?noload=true</a></p><p><strong>Script 3.&nbsp;</strong>Sampled NDVI time series from different land-use cases for the Gavi study area (2019&nbsp; Event). Link to&nbsp; GEE: <a href="https://code.earthengine.google.com/f686c60b78a3dee0b2a2c94a259ccff2?noload=true">https://code.earthengine.google.com/f686c60b78a3dee0b2a2c94a259ccff2?noload=true</a></p><p><strong>Script 4.</strong> Multi-temporal-averaged NDVIvar &nbsp;&nbsp; Link to GEE Script: &nbsp;<a href="https://code.earthengine.google.com/bfc2e570bb675372c4c482eef682be4a?noload=true">https://code.earthengine.google.com/bfc2e570bb675372c4c482eef682be4a?noload=true</a>&nbsp;for the whole Gavi study area (2019 flood) and&nbsp; &nbsp;<a href="https://code.earthengine.google.com/89e1c0a1361860cd407b7e6ab8bb95de?noload=true">https://code.earthengine.google.com/a3390b262cef1b5f42837c88d8791b5b?noload=true</a>&nbsp;for the entire Arroscia-Tanarello study area</p><p>The full description of the methodology can be found in the paper of&nbsp; Notti et al., 2023</p><p>Notti, D., Cignetti, M., Godone, D., and Giordan, D.: Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine, Nat. Hazards Earth Syst. Sci., 23, 2625–2648, <a href="https://doi.org/10.5194/nhess-23-2625-2023">https://doi.org/10.5194/nhess-23-2625-2023</a>, 2023</p>