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Temporary Dataset Download: Gully erosion in the EU

Dataset Access Expires on

25-January-2026

Notifications

  • The data provided has been prepared for use by internal research activities in the Joint Research Centre (JRC) Ispra.
  • The data are the result of JRC research activities and are primarily made available for further research. The JRC does not accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The JRC agrees to provide the data free of charge but is not bound to justify the content and values contained in the databases.
  • The permission to use the data specified above is granted on condition that, under NO CIRCUMSTANCES are these data passed to third parties. They can be used for any purpose, including commercial gain.
  • The user agrees to:
       a) Make proper reference to the source of the data when disseminating the results to which this agreement relates;
       b) Participate in the verification of the data (e.g. by noting and reporting any errors or omissions discovered to the JRC).



 

 

Data Download:

LUCAS2022_original.CSV. (411,845 KB) (comma-separated values format). This data format consists of 399,591 records that represents the locations of the LUCAS 2022 observations. The data is composed of 307 fields (columns) representing the 265 landscape elements included in the survey. Acronyms and data explanations are provided in the supporting file LUCAS-2022-record-descriptor.ods (22 KB).

LUCAS2022_with_gully_channels.shp (2,998 KB) (shapefile format). This point geometry vector data model consists of 3,116 records representing the LUCAS2022 locations where gullies were detected. The vector data model includes the following fields: LUCAS code (POINT_ID), countries (POINT_NUTS), coordinates (POINT_LAT and POINT_LONG), altitude (POINT_ALTI) survey date (SURVEY_DAT), type of observation (SURVEY_OBS), land cover (SURVEY_LC1), land use (SURVEY_LU1), presence or absence of gullies (SURVEY_GUL), type of observed gully (SURVEY_G_1), direction of the gully from the LUCAS point (SURVEY_G_2), mean length in meters (SURVEY_G_3), mean width in meters (SURVEY_G_4), mean depth in meters (SURVEY_G_5)

LUCAS2022_gully_channel_locations.shp (2,593 KB) (shapefile format). This point geometry vector data model consists of 3,116 locations found to be affected by gully erosion channels. The main difference with the ‘LUCAS2022_point_with_gullies’ vector data model lies in the fact that the points reported in this data do not reflect the LUCAS locations, but the locations where the actual gullies were found to be located. The vector data model includes the following fields: LUCAS code (POINT_ID), countries (POINT_NUTS), survey date (SURVEY_DAT), type of observation (SURVEY_OBS), land cover (SURVEY_LC1), type of observed gully (SURVEY_G_1), mean width in meters (SURVEY_G_4), and mean depth in meters (SURVEY_G_5).

Europe_RF_gully_probability_map.tif (597,201 KB) (GeoTIFF format). This data represent the probabilistic spatial interpolations of gully occurrence from the RF classifier model in the EU and the UK. The map is provided as a percent probability layer in integer format.

Random_cross-check.shp (237 KB) (shapefile format). This point geometry vector data model consists of 4,500 randomly selected locations (~1% of the LUCAS 2022 records) for which the presence or absence of gullies has been determined via a further on-screen visual assessment of Google Earth™ imagery. There is only one field (i.e., Code) in this vector data model, and its values can be 0 (no gully) or 1 (yes gully).

LUCAS2022_cross-check.shp (106 KB) (shapefile format). This point geometry vector data model comprises of 2,500 LUCAS 2022’s locations revisited through on-screen visual assessment of Google Earth™ imagery to gain statistical indication of the error of omission (potential false negatives).

GE-LUCAS v1.1 aerial photo inventory.PDF (47,293 KB) (text format). A library of aerial photos of all the 3,116 LUCAS 2022 locations in which gullies were observed in the in situ or remote observations.

LUCAS ground photo archive (5,670,000 KB) (JPG format). The ground photo archive includes 8,488 out of approximately 15,580 total LUCAS cover photos (five per LUCAS location). The discrepancy between the number of photos collected and the total is due to the unavailability of some photos in the Eurostat repository. This may be attributable to privacy concerns or other formal constraints. As the photos is a huge file, you can download it here

 

Borrelli, P.,  Matthews, F., Alewell, C., Kaffas, K., Poesen, J., Saggau, P.,  Prăvălie, R., Vanmaercke, M., Panagos, P.  2025.  A hybrid in situ and on-screen survey to monitor gully erosion across the European Union. Nature Scientific Data 12, 755

Joint Research Centre - European Soil Data Centre (ESDAC)
ID 123595
Date - Time Sun, 01/11/2026 - 10:23
Name of User Janis Donis
Organization Silava
Type of Organization Research Organization
-- Other
E-mail janis.donis@silava.lv
Purpose test soil erosion risk in forest
Notes

When making reference to the ESDAC

  • Panagos, P., Van Liedekerke, M., Borrelli, P., Köninger, J., Ballabio, C., Orgiazzi, A., Lugato, E., Liakos, L., Hervas, J., Jones, A.  Montanarella, L. 2022. European Soil Data Centre 2.0: Soil data and knowledge in support of the EU policies. European Journal of Soil Science, 73(6), e13315. DOI: 10.1111/ejss.13315
  • Panagos P., Van Liedekerke M., Jones A., Montanarella L., “European Soil Data Centre: Response to European policy support and public data requirements”; (2012) Land Use Policy, 29 (2), pp. 329-338. doi:10.1016/j.landusepol.2011.07.003
  • European Soil Data Centre (ESDAC), esdac.jrc.ec.europa.eu, European Commission, Joint Research Centre