Articles | Volume 18, issue 1
https://doi.org/10.5194/nhess-18-185-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-18-185-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2018
Research article |
| 16 Jan 2018
| 16 Jan 2018
Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes
Jack G. Williams
CORRESPONDING AUTHOR
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Nick J. Rosser
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Mark E. Kincey
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Jessica Benjamin
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Katie J. Oven
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Alexander L. Densmore
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
David G. Milledge
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Tom R. Robinson
Institute of Hazard, Risk and Resilience and Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Colm A. Jordan
British Geological Survey, Natural Environment Research Council, Environmental Science Centre, Keyworth, Nottingham, NG12 5GG, UK
Tom A. Dijkstra
British Geological Survey, Natural Environment Research Council, Environmental Science Centre, Keyworth, Nottingham, NG12 5GG, UK
School of Architecture, Building and Civil Engineering, Loughborough University, Ashby Road, Loughborough, LE11 3TU, UK
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Cited
47 citations as recorded by crossref.
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- Use of scenario ensembles for deriving seismic risk T. Robinson et al. 10.1073/pnas.1807433115
- A new strategy to map landslides with a generalized convolutional neural network N. Prakash et al. 10.1038/s41598-021-89015-8
- Rapid Mapping of Landslides on SAR Data by Attention U-Net L. Nava et al. 10.3390/rs14061449
- Fast Mapping of Large-Scale Landslides in Sentinel-1 SAR Images Using SPAUNet X. Shi et al. 10.1109/JSTARS.2023.3310153
- From ground motion simulations to landslide occurrence prediction A. Dahal et al. 10.1016/j.geomorph.2023.108898
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- Accurate landslide identification by multisource data fusion analysis with improved feature extraction backbone network Y. Jin et al. 10.1080/19475705.2022.2116357
- The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia D. Kirschbaum et al. 10.3389/feart.2019.00197
- Geomorphological and hydrological controls on sediment export in earthquake-affected catchments in the Nepal Himalaya E. Graf et al. 10.5194/esurf-12-135-2024
- Improving Landslide Detection on SAR Data Through Deep Learning L. Nava et al. 10.1109/LGRS.2021.3127073
- Automatic detection of earthquake triggered landslides using Sentinel-1 SAR imagery based on deep learning L. Chen et al. 10.1080/17538947.2024.2393261
- A New Method for Large-Scale Landslide Classification from Satellite Radar K. Burrows et al. 10.3390/rs11030237
- Changing significance of landslide Hazard and risk after the 2015 Mw 7.8 Gorkha, Nepal Earthquake N. Rosser et al. 10.1016/j.pdisas.2021.100159
- Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti P. Amatya et al. 10.1007/s11069-023-06096-6
- Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal P. Amatya et al. 10.3390/rs11192284
- Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions G. Giardina et al. 10.1007/s10518-023-01716-9
- The influence of the physical environment on self-recovery after disasters in Nepal and the Philippines S. Sargeant et al. 10.1016/j.ijdrr.2020.101673
- Preface: Estimating and predicting natural hazards and vulnerabilities in the Himalayan region W. Schwanghart et al. 10.5194/nhess-24-3291-2024
- Synergic use of Sentinel-1 and Sentinel-2 data for automatic detection of earthquake-triggered landscape changes: A case study of the 2016 Kaikoura earthquake (Mw 7.8), New Zealand J. Jelének & V. Kopačková-Strnadová 10.1016/j.rse.2021.112634
- Co‐seismic landslides in the Sikkim Himalaya during the 2011 Sikkim Earthquake: Lesson learned from the past and inference for the future M. Joshi 10.1002/gj.4416
- The dynamic threat from landslides following large continental earthquakes K. Arrell et al. 10.1371/journal.pone.0308444
- Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding K. Burrows et al. 10.5194/nhess-22-2637-2022
- Landslides triggered by the 2015 Mw 6.0 Sabah (Malaysia) earthquake: inventory and ESI-07 intensity assignment M. Ferrario 10.5194/nhess-22-3527-2022
- Assessing the Accuracy of ALOS/PALSAR-2 and Sentinel-1 Radar Images in Estimating the Land Subsidence of Coastal Areas: A Case Study in Alexandria City, Egypt N. Darwish et al. 10.3390/rs13091838
- A closer look at factors governing landslide recovery time in post-seismic periods H. Tanyaş et al. 10.1016/j.geomorph.2021.107912
- Plotting earthquake emergency maps based on audience theory J. Xu et al. 10.1016/j.ijdrr.2020.101554
- Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories R. Emberson et al. 10.5194/nhess-22-1129-2022
- A novel network for semantic segmentation of landslide areas in remote sensing images with multi-branch and multi-scale fusion K. Wang et al. 10.1016/j.asoc.2024.111542
- Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine A. Handwerger et al. 10.5194/nhess-22-753-2022
- Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika-Kivu Rift region O. Dewitte et al. 10.1007/s10346-020-01452-0
- Integrating empirical models and satellite radar can improve landslide detection for emergency response K. Burrows et al. 10.5194/nhess-21-2993-2021
- Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation P. Caporossi et al. 10.3390/ijgi7090372
- Assessing sustainable development prospects through remote sensing: A review R. Avtar et al. 10.1016/j.rsase.2020.100402
- The Fate of Sediment After a Large Earthquake O. Francis et al. 10.1029/2021JF006352
- Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future A. Mondini et al. 10.1016/j.earscirev.2021.103574
- Working with communities on disaster risk research: Reflections from cross-disciplinary practice R. Few et al. 10.1016/j.ijdrr.2022.102815
- Automated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mapping D. Milledge et al. 10.5194/nhess-22-481-2022
- Combination of optical images and SAR images for detecting landslide scars, using a classification and regression tree S. Phakdimek et al. 10.1080/01431161.2023.2224096
- Modelling post‐earthquake cascading hazards: Changing patterns of landslide runout following the 2015 Gorkha earthquake, Nepal M. Kincey et al. 10.1002/esp.5501
- Sentinel-1 SAR Amplitude Imagery for Rapid Landslide Detection A. Mondini et al. 10.3390/rs11070760
- UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products C. Watson et al. 10.3390/drones3010018
- Rapid post-earthquake modelling of coseismic landslide intensity and distribution for emergency response decision support T. Robinson et al. 10.5194/nhess-17-1521-2017
- Scenario ensemble modelling of possible future earthquake impacts in Bhutan T. Robinson 10.1007/s11069-020-04138-x
- The Spatial and Temporal Influence of Cloud Cover on Satellite-Based Emergency Mapping of Earthquake Disasters T. Robinson et al. 10.1038/s41598-019-49008-0
- Landslides in the glaciated mountains of the Cordillera Blanca, Peru—types, spatial distribution, and conditioning factors J. Klimeš et al. 10.1007/s10346-024-02387-6
43 citations as recorded by crossref.
- Simple rules to minimise exposure to coseismic landslide hazard D. Milledge et al. 10.5194/nhess-19-837-2019
- Role of landslides on the volume balance of the Nepal 2015 earthquake sequence A. Valagussa et al. 10.1038/s41598-021-83037-y
- Use of scenario ensembles for deriving seismic risk T. Robinson et al. 10.1073/pnas.1807433115
- A new strategy to map landslides with a generalized convolutional neural network N. Prakash et al. 10.1038/s41598-021-89015-8
- Rapid Mapping of Landslides on SAR Data by Attention U-Net L. Nava et al. 10.3390/rs14061449
- Fast Mapping of Large-Scale Landslides in Sentinel-1 SAR Images Using SPAUNet X. Shi et al. 10.1109/JSTARS.2023.3310153
- From ground motion simulations to landslide occurrence prediction A. Dahal et al. 10.1016/j.geomorph.2023.108898
- A systematic exploration of satellite radar coherence methods for rapid landslide detection K. Burrows et al. 10.5194/nhess-20-3197-2020
- Accurate landslide identification by multisource data fusion analysis with improved feature extraction backbone network Y. Jin et al. 10.1080/19475705.2022.2116357
- The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia D. Kirschbaum et al. 10.3389/feart.2019.00197
- Geomorphological and hydrological controls on sediment export in earthquake-affected catchments in the Nepal Himalaya E. Graf et al. 10.5194/esurf-12-135-2024
- Improving Landslide Detection on SAR Data Through Deep Learning L. Nava et al. 10.1109/LGRS.2021.3127073
- Automatic detection of earthquake triggered landslides using Sentinel-1 SAR imagery based on deep learning L. Chen et al. 10.1080/17538947.2024.2393261
- A New Method for Large-Scale Landslide Classification from Satellite Radar K. Burrows et al. 10.3390/rs11030237
- Changing significance of landslide Hazard and risk after the 2015 Mw 7.8 Gorkha, Nepal Earthquake N. Rosser et al. 10.1016/j.pdisas.2021.100159
- Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti P. Amatya et al. 10.1007/s11069-023-06096-6
- Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal P. Amatya et al. 10.3390/rs11192284
- Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions G. Giardina et al. 10.1007/s10518-023-01716-9
- The influence of the physical environment on self-recovery after disasters in Nepal and the Philippines S. Sargeant et al. 10.1016/j.ijdrr.2020.101673
- Preface: Estimating and predicting natural hazards and vulnerabilities in the Himalayan region W. Schwanghart et al. 10.5194/nhess-24-3291-2024
- Synergic use of Sentinel-1 and Sentinel-2 data for automatic detection of earthquake-triggered landscape changes: A case study of the 2016 Kaikoura earthquake (Mw 7.8), New Zealand J. Jelének & V. Kopačková-Strnadová 10.1016/j.rse.2021.112634
- Co‐seismic landslides in the Sikkim Himalaya during the 2011 Sikkim Earthquake: Lesson learned from the past and inference for the future M. Joshi 10.1002/gj.4416
- The dynamic threat from landslides following large continental earthquakes K. Arrell et al. 10.1371/journal.pone.0308444
- Using Sentinel-1 radar amplitude time series to constrain the timings of individual landslides: a step towards understanding the controls on monsoon-triggered landsliding K. Burrows et al. 10.5194/nhess-22-2637-2022
- Landslides triggered by the 2015 Mw 6.0 Sabah (Malaysia) earthquake: inventory and ESI-07 intensity assignment M. Ferrario 10.5194/nhess-22-3527-2022
- Assessing the Accuracy of ALOS/PALSAR-2 and Sentinel-1 Radar Images in Estimating the Land Subsidence of Coastal Areas: A Case Study in Alexandria City, Egypt N. Darwish et al. 10.3390/rs13091838
- A closer look at factors governing landslide recovery time in post-seismic periods H. Tanyaş et al. 10.1016/j.geomorph.2021.107912
- Plotting earthquake emergency maps based on audience theory J. Xu et al. 10.1016/j.ijdrr.2020.101554
- Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories R. Emberson et al. 10.5194/nhess-22-1129-2022
- A novel network for semantic segmentation of landslide areas in remote sensing images with multi-branch and multi-scale fusion K. Wang et al. 10.1016/j.asoc.2024.111542
- Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine A. Handwerger et al. 10.5194/nhess-22-753-2022
- Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika-Kivu Rift region O. Dewitte et al. 10.1007/s10346-020-01452-0
- Integrating empirical models and satellite radar can improve landslide detection for emergency response K. Burrows et al. 10.5194/nhess-21-2993-2021
- Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation P. Caporossi et al. 10.3390/ijgi7090372
- Assessing sustainable development prospects through remote sensing: A review R. Avtar et al. 10.1016/j.rsase.2020.100402
- The Fate of Sediment After a Large Earthquake O. Francis et al. 10.1029/2021JF006352
- Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future A. Mondini et al. 10.1016/j.earscirev.2021.103574
- Working with communities on disaster risk research: Reflections from cross-disciplinary practice R. Few et al. 10.1016/j.ijdrr.2022.102815
- Automated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mapping D. Milledge et al. 10.5194/nhess-22-481-2022
- Combination of optical images and SAR images for detecting landslide scars, using a classification and regression tree S. Phakdimek et al. 10.1080/01431161.2023.2224096
- Modelling post‐earthquake cascading hazards: Changing patterns of landslide runout following the 2015 Gorkha earthquake, Nepal M. Kincey et al. 10.1002/esp.5501
- Sentinel-1 SAR Amplitude Imagery for Rapid Landslide Detection A. Mondini et al. 10.3390/rs11070760
- UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products C. Watson et al. 10.3390/drones3010018
4 citations as recorded by crossref.
- Rapid post-earthquake modelling of coseismic landslide intensity and distribution for emergency response decision support T. Robinson et al. 10.5194/nhess-17-1521-2017
- Scenario ensemble modelling of possible future earthquake impacts in Bhutan T. Robinson 10.1007/s11069-020-04138-x
- The Spatial and Temporal Influence of Cloud Cover on Satellite-Based Emergency Mapping of Earthquake Disasters T. Robinson et al. 10.1038/s41598-019-49008-0
- Landslides in the glaciated mountains of the Cordillera Blanca, Peru—types, spatial distribution, and conditioning factors J. Klimeš et al. 10.1007/s10346-024-02387-6
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Short summary
There is currently no protocol for rapid humanitarian-facing landslide assessment and no published recognition of what is possible and useful to compile immediately after a triggering event. Drawing on the 2015 Gorkha earthquake (Nepal), we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated.
There is currently no protocol for rapid humanitarian-facing landslide assessment and no...
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