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  • The earthquake-induced landslide (EIL) probability calculated with the EIL Forecast Tool V2.1 (version 2.1), using Peak Ground Acceleration (PGA) on Soil Class B for the 500 year mean return period. The EIL probability has been calculated at 32 m resolution, and then aggregated to 256 m and 512 m using the maximum option, for better display at smaller scales. The grid covers the areas with probabilities in the upper quartile. The quartiles were derived using an EIL probability grid developed without the earthquake PGA variable included in the model. The upper quartile is defined by probabilities greater than 0.000926. The PGA input (earthquake shaking data) used in the EIL Forecast Tool V2.1 has been obtained from the GNS Science's National Seismic Hazard Model (NSHM, 2010). The common V2.1 tool inputs (static data) have been derived from the NZ 8m Digital Elevation Model (LINZ, 2012) and the 1:1 250 000 Geological Map of New Zealand (2nd edition, 2018). For more details about the EIL Forecast tool V2.1 see Massey, C.I.; Lukovic, B. 2023 Earthquake-induced landslide forecast tool for New Zealand: Version 2.1. Lower Hutt, N.Z.: GNS Science. GNS Science report 2023/04.; https://doi.org/10.21420/1ZXA-AB51 and Massey, C.I.; Lukovic, B.; Huso, R.; Buxton, R.; Potter, S.H. 2021 Earthquake-induced landslide forecast tool for New Zealand: version 2.0. Lower Hutt, N.Z.: GNS Science. GNS Science report 2018/08. 77 p.; https://doi.org/10.21420/G2TP9V. Earthquake-induced landscape dynamics (EILD) is an MBIE Endeavour programme led by GNS Science in association with experts from leading landslide research institutions in New Zealand and a suite of international experts. One of the programme aims is to quantify landslide activation thresholds and forecast landslide severity at different magnitudes of ground shaking, by studying landslides caused by the 2016 Kaikōura earthquake. It also seeks to develop a framework and tools to allow people to manage the risk to life, property and infrastructure from future earthquake-induced landslides, both in Aotearoa New Zealand and internationally.

  • The earthquake-induced landslide (EIL) probability calculated with the EIL Forecast Tool V2.1 (version 2.1), using Peak Ground Acceleration (PGA) on Soil Class B for the 250 year mean return period. The EIL probability has been calculated at 32 m resolution, and then aggregated to 256 m and 512 m, for better display at smaller scales. The grid covers the areas with probabilities in the upper quartile. The quartiles were derived using an EIL probability grid developed without the earthquake PGA variable included in the model. The upper quartile is defined by probabilities greater than 0.000926. The PGA input (earthquake shaking data) used in the EIL Forecast Tool V2.1 has been obtained from the GNS Science's National Seismic Hazard Model (NSHM, 2010). The common V2.1 tool inputs (static data) have been derived from the NZ 8m Digital Elevation Model (LINZ, 2012) and the 1:1 250 000 Geological Map of New Zealand (2nd edition, 2018). For more details about the EIL Forecast tool V2.1 see Massey, C.I.; Lukovic, B. 2023 Earthquake-induced landslide forecast tool for New Zealand: Version 2.1. Lower Hutt, N.Z.: GNS Science. GNS Science report 2023/04.; https://doi.org/10.21420/1ZXA-AB51 and Massey, C.I.; Lukovic, B.; Huso, R.; Buxton, R.; Potter, S.H. 2021 Earthquake-induced landslide forecast tool for New Zealand: version 2.0. Lower Hutt, N.Z.: GNS Science. GNS Science report 2018/08. 77 p.; https://doi.org/10.21420/G2TP9V. Earthquake-induced landscape dynamics (EILD) is an MBIE Endeavour programme led by GNS Science in association with experts from leading landslide research institutions in New Zealand and a suite of international experts. One of the programme aims is to quantify landslide activation thresholds and forecast landslide severity at different magnitudes of ground shaking, by studying landslides caused by the 2016 Kaikōura earthquake. It also seeks to develop a framework and tools to allow people to manage the risk to life, property and infrastructure from future earthquake-induced landslides, both in Aotearoa New Zealand and internationally.

  • The earthquake-induced landslide (EIL) probability calculated with the EIL Forecast Tool V2.1 (version 2.1). The PGA input (earthquake shaking data) used in the EIL Forecast Tool V2.1 has been obtained from the GNS Science's National Seismic Hazard Model (NSHM, 2010). The common V2.1 tool inputs (static data) have been derived from the NZ 8m Digital Elevation Model (LINZ, 2012) and the 1:1 250 000 Geological Map of New Zealand (2nd edition, 2018). For more details about the EIL Forecast tool V2.1 see Massey, C.I.; Lukovic, B. 2023 Earthquake-induced landslide forecast tool for New Zealand: Version 2.1. Lower Hutt, N.Z.: GNS Science. GNS Science report 2023/04.; https://doi.org/10.21420/1ZXA-AB51 and Massey, C.I.; Lukovic, B.; Huso, R.; Buxton, R.; Potter, S.H. 2021 Earthquake-induced landslide forecast tool for New Zealand: version 2.0. Lower Hutt, N.Z.: GNS Science. GNS Science report 2018/08. 77 p.; https://doi.org/10.21420/G2TP9V. Earthquake-induced landscape dynamics (EILD) is an MBIE Endeavour programme led by GNS Science in association with experts from leading landslide research institutions in New Zealand and a suite of international experts. One of the programme aims is to quantify landslide activation thresholds and forecast landslide severity at different magnitudes of ground shaking, by studying landslides caused by the 2016 Kaikōura earthquake. It also seeks to develop a framework and tools to allow people to manage the risk to life, property and infrastructure from future earthquake-induced landslides, both in Aotearoa New Zealand and internationally.

  • The earthquake-induced landslide (EIL) probability calculated with the EIL Forecast Tool V2.1 (version 2.1), using Peak Ground Acceleration (PGA) on Soil Class B for the 1000 year mean return period. The EIL probability has been calculated at 32 m resolution, and then aggregated to 256 m and 512 m, for better display at smaller scales. The grid covers the areas with probabilities in the upper quartile. The quartiles were derived using an EIL probability grid developed without the earthquake PGA variable included in the model. The upper quartile is defined by probabilities greater than 0.000926. The PGA input (earthquake shaking data) used in the EIL Forecast Tool V2.1 has been obtained from the GNS Science's National Seismic Hazard Model (NSHM, 2010). The common V2.1 tool inputs (static data) have been derived from the NZ 8m Digital Elevation Model (LINZ, 2012) and the 1:1 250 000 Geological Map of New Zealand (2nd edition, 2018). For more details about the EIL Forecast tool V2.1 see Massey, C.I.; Lukovic, B. 2023 Earthquake-induced landslide forecast tool for New Zealand: Version 2.1. Lower Hutt, N.Z.: GNS Science. GNS Science report 2023/04.; https://doi.org/10.21420/1ZXA-AB51 and Massey, C.I.; Lukovic, B.; Huso, R.; Buxton, R.; Potter, S.H. 2021 Earthquake-induced landslide forecast tool for New Zealand: version 2.0. Lower Hutt, N.Z.: GNS Science. GNS Science report 2018/08. 77 p.; https://doi.org/10.21420/G2TP9V. Earthquake-induced landscape dynamics (EILD) is an MBIE Endeavour programme led by GNS Science in association with experts from leading landslide research institutions in New Zealand and a suite of international experts. One of the programme aims is to quantify landslide activation thresholds and forecast landslide severity at different magnitudes of ground shaking, by studying landslides caused by the 2016 Kaikōura earthquake. It also seeks to develop a framework and tools to allow people to manage the risk to life, property and infrastructure from future earthquake-induced landslides, both in Aotearoa New Zealand and internationally.

  • The earthquake-induced landslide (EIL) probability calculated with the EIL Forecast Tool V2.1 (version 2.1), using Peak Ground Acceleration (PGA) on Soil Class B for the 100 year mean return period. The EIL probability has been calculated at 32 m resolution, and then aggregated to 256 m and 512 m using the maximum option, for better display at smaller scales. The grid covers the areas with probabilities in the upper quartile. The quartiles were derived using an EIL probability grid developed without the earthquake PGA variable included in the model. The upper quartile is defined by probabilities greater than 0.000926. The PGA input (earthquake shaking data) used in the EIL Forecast Tool V2.1 has been obtained from the GNS Science's National Seismic Hazard Model (NSHM, 2010). The common V2.1 tool inputs (static data) have been derived from the NZ 8m Digital Elevation Model (LINZ, 2012) and the 1:1 250 000 Geological Map of New Zealand (2nd edition, 2018). For more details about the EIL Forecast tool V2.1 see Massey, C.I.; Lukovic, B. 2023 Earthquake-induced landslide forecast tool for New Zealand: Version 2.1. Lower Hutt, N.Z.: GNS Science. GNS Science report 2023/04.; https://doi.org/10.21420/1ZXA-AB51 and Massey, C.I.; Lukovic, B.; Huso, R.; Buxton, R.; Potter, S.H. 2021 Earthquake-induced landslide forecast tool for New Zealand: version 2.0. Lower Hutt, N.Z.: GNS Science. GNS Science report 2018/08. 77 p.; https://doi.org/10.21420/G2TP9V. Earthquake-induced landscape dynamics (EILD) is an MBIE Endeavour programme led by GNS Science in association with experts from leading landslide research institutions in New Zealand and a suite of international experts. One of the programme aims is to quantify landslide activation thresholds and forecast landslide severity at different magnitudes of ground shaking, by studying landslides caused by the 2016 Kaikōura earthquake. It also seeks to develop a framework and tools to allow people to manage the risk to life, property and infrastructure from future earthquake-induced landslides, both in Aotearoa New Zealand and internationally.

  • The dataset comprises the centroids of the landslide source areas and is extracted from the 2016 Kaikōura Landslide Inventory (Version 2). Landslides were triggered by the 2016 Kaikōura earthquake and were captured using post-earthquake 0.3 m ground resolution orthorectified air photographs and digital surface models derived from them, alongside digital elevation models derived from post-earthquake airborne Light Detection And Ranging (LiDAR) surveys and other pre‐ and post‐Kaikōura earthquake imagery and LiDAR data. Landslide polygons were manually digitized directly into a Geographic Information System. An inventory of 29,519 coseismic landslides inferred to have been triggered by the 14 November 2016 Kaikōura earthquake and associated aftershocks, collected for the research purposes. This is version 2 of the landslide inventory. The inventory can be downloaded from DesignSafe: https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2765/#details-6410851737832919531-242ac118-0001-012 Cite dataset as: Massey, C. Townsend, D. Rosser, B. Morgenstern, R. Jones, K. Lukovic, B. Davidson, J. (2021) "Version 2.0 of the landslide inventory for the Mw 7.8 14 November 2016, Kaikōura Earthquake." DesignSafe-CI. https://doi.org/10.17603/ds2-1ftv-hm22

  • The dataset comprises the 2016 Kaikōura Landslide Inventory (Version 3). Landslides were triggered by the 2016 Kaikōura earthquake and were captured using post-earthquake Light Detection And Ranging (LiDAR) surveys, 0.3 m ground resolution orthorectified air photography and derived digital surface models. Landslide polygons were manually digitized into a Geographic Information System. The inventory contains 31,594 landslide source area polygons and 26,559 debris trail polygons. The mapped coseismic landslides are inferred to have been triggered by the 14 November 2016 Kaikōura earthquake and associated aftershocks, collected for the research purposes. This is version 3 of the landslide inventory. Cite data as: Jones, K., Massey, C. Townsend, D. Rosser, B. Morgenstern, R., Lukovic, B., Davidson, J., Lyndsell, B., Singeisen, C., Tamsen, D., Carey, J., Villeneuve, M., Mason, D., Wolter, A., Gasston, C., (2022). Version 3.0 of the landslide inventory for the Mw 7.8 14 November 2016, Kaikōura Earthquake [Data set]. GNS Science. https://doi.org/10.21420/WX2X-H603