38ef54df-3915-e0cf-e063-3050940ab7c7 English dataset British Geological Survey +44 115 936 3100 Environmental Science Centre, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk pointOfContact 2026-04-29 UK GEMINI 2.3 http://data.bgs.ac.uk/id/dataHolding/13608432 WGS 84 (EPSG::4326) Landslide polygons in Kahramanmaras province, Turkey (2022-2023) 2025-06-11 creation http://data.bgs.ac.uk/id/dataHolding/13608432 The Kahramanmaras landslide inventory shapefile contains polygons representing landslide areas in Kahramanmaras province, Turkey up to July 2023. It provides valuable data for analysing the spatial distributions, size, and characteristics of pre- and co-seismic landslides in this region. Enquiries British Geological Survey 0115 936 3143 0115 936 3276 Environmental Science Centre, Nicker Hill, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk distributor Enquiries British Geological Survey 0115 936 3143 0115 936 3276 Environmental Science Centre, Nicker Hill, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk distributor Enquiries British Geological Survey 0115 936 3143 0115 936 3276 Environmental Science Centre, Nicker Hill, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk originator Enquiries British Geological Survey 0115 936 3143 0115 936 3276 Environmental Science Centre, Nicker Hill, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk originator Enquiries British Geological Survey United Kingdom not available distributor Enquiries British Geological Survey United Kingdom not available pointOfContact notApplicable https://resources.bgs.ac.uk/images/geonetworkThumbs/38ef54df-3915-e0cf-e063-3050940ab7c7.png Geology GEMET - INSPIRE themes, version 1.0 2008-06-01 publication data.gov.uk (non-INSPIRE) Citable Data NGDC Deposited Data dataCentre NERC_DDC otherRestrictions licenceOGL Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]" otherRestrictions The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused. Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]" vector English geoscientificInformation 35.7800 39.6100 35.9700 38.7100 2022 2023 ESRI Shapefile 1994 Enquiries British Geological Survey 0115 936 3143 0115 936 3276 Environmental Science Centre, Nicker Hill, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk distributor Enquiries British Geological Survey 0115 936 3143 0115 936 3276 Environmental Science Centre, Nicker Hill, Keyworth NOTTINGHAM NOTTINGHAMSHIRE NG12 5GG United Kingdom enquiries@bgs.ac.uk distributor Enquiries British Geological Survey United Kingdom not available distributor https://webapps.bgs.ac.uk/services/ngdc/accessions/index.html#item188804 WWW:DOWNLOAD-1.0-http--download Data download https://doi.org/10.5285/d751a1c8-1f07-4f6d-98ca-3b5f86a8d1fd WWW:LINK-1.0-http--related Citation Information - Digital Object Identifier (DOI) Novellino, A., Leeming, K., Gonzalez Alvarez, I., Chahel, R. (2025). Landslide polygons in Kahramanmaras province, Turkey (2022-2023). NERC EDS National Geoscience Data Centre. (Dataset). https://doi.org/10.5285/d751a1c8-1f07-4f6d-98ca-3b5f86a8d1fd information dataset dataset INSPIRE Implementing rules laying down technical arrangements for the interoperability and harmonisation of Geology 2011 publication See the referenced specification false Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 publication See http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:323:0011:0102:EN:PDF false The inventory has been generated using satellite images, terrain information, and labelled examples of landslides to train a convolutional neural network (U-Net), for the purpose of adding previously undocumented and new landslides to inventories. This model segments the input images and highlights the pixels it labels as landslides. We have trained the model with two types of movements (slides and flows) under different triggers (earthquakes and rainfall), so that the model is exposed to a variety of training data. The model has been trained and tested on Sentinel-2 images at 10m resolution, so user should consider that landslides with size in the order of <0.01 km2 might be too small to be detected or can be falsely classified as landslides. Also, the model has been trained mainly on two specific types of movements – slides and flows – so other types of events (falls, topples) might be not reported. The Türkiye dataset was not used during the training process; these landslides represent out-of-sample results.