Articles | Volume 16, issue 10
https://doi.org/10.5194/essd-16-4817-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-4817-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Oct 2024
Data description paper |
| 24 Oct 2024
| 24 Oct 2024
A globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images
Chengyong Fang
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, 610059 Chengdu, China
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, 610059 Chengdu, China
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, 610059 Chengdu, China
Lorenzo Nava
Machine Intelligence and Slope Stability Laboratory, Department of Geosciences, University of Padua, 35129 Padua, Italy
Hao Zhong
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, 610059 Chengdu, China
College of Information Science and Technology, Chengdu University of Technology, 610059 Chengdu, China
Xiujun Dong
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, 610059 Chengdu, China
Jixiao Qi
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, 610059 Chengdu, China
Filippo Catani
Machine Intelligence and Slope Stability Laboratory, Department of Geosciences, University of Padua, 35129 Padua, Italy
Related authors
Lorenzo Nava, Alessandro Novellino, Chengyong Fang, Kushanav Bhuyan, Kathryn Leeming, Itahisa Gonzalez Alvarez, Claire Dashwood, Sophie Doward, Rahul Chahel, Emma McAllister, Sansar Raj Meena, and Filippo Catani
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-146, https://doi.org/10.5194/nhess-2024-146, 2024
Preprint under review for NHESS
Short summary
Short summary
On April 2, 2024, a Mw 7.4 earthquake hit Taiwan’s eastern coast, causing extensive landslides and damage. We used automated methods combining Earth Observation (EO) data with Artificial Intelligence (AI) to quickly inventory the landslides. This approach identified 7,090 landslides over 75 km2 within 3 hours of acquiring the EO imagery. The study highlights AI’s role in improving landslide detection and understanding earthquake-landslide interactions for better hazard mitigation.
Lorenzo Nava, Alessandro Novellino, Chengyong Fang, Kushanav Bhuyan, Kathryn Leeming, Itahisa Gonzalez Alvarez, Claire Dashwood, Sophie Doward, Rahul Chahel, Emma McAllister, Sansar Raj Meena, and Filippo Catani
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-146, https://doi.org/10.5194/nhess-2024-146, 2024
Preprint under review for NHESS
Short summary
Short summary
On April 2, 2024, a Mw 7.4 earthquake hit Taiwan’s eastern coast, causing extensive landslides and damage. We used automated methods combining Earth Observation (EO) data with Artificial Intelligence (AI) to quickly inventory the landslides. This approach identified 7,090 landslides over 75 km2 within 3 hours of acquiring the EO imagery. The study highlights AI’s role in improving landslide detection and understanding earthquake-landslide interactions for better hazard mitigation.
Isabelle Utley, Tristram Hales, Ekbal Hussain, and Xuanmei Fan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2277, https://doi.org/10.5194/egusphere-2024-2277, 2024
Short summary
Short summary
We analysed debris flows in Sichuan, China, using satellite data and simulations to assess check dam efficacy. Our study found whilst check dams can mitigate smaller flows, they may increase exposure to extreme events, with up to 40 % of structures in some areas affected. Urban development and reliance on check dams can create a false sense of security, raising exposure during large debris flows and highlights the need for risk management and infrastructure planning in hazard-prone areas.
Jingjuan Li, John D. Jansen, Xuanmei Fan, Zhiyong Ding, Shugang Kang, and Marco Lovati
Earth Surf. Dynam., 12, 953–971, https://doi.org/10.5194/esurf-12-953-2024, https://doi.org/10.5194/esurf-12-953-2024, 2024
Short summary
Short summary
In this study, we investigated the geomorphology, sedimentology, and chronology of Tuanjie (seven terraces) and Taiping (three terraces) terraces in Diexi, eastern Tibetan Plateau. Results highlight that two damming and three outburst events occurred in the area during the late Pleistocene, and the outburst floods have been a major factor in the formation of tectonically active mountainous river terraces. Tectonic activity and climatic changes play a minor role.
Sansar Raj Meena, Lorenzo Nava, Kushanav Bhuyan, Silvia Puliero, Lucas Pedrosa Soares, Helen Cristina Dias, Mario Floris, and Filippo Catani
Earth Syst. Sci. Data, 15, 3283–3298, https://doi.org/10.5194/essd-15-3283-2023, https://doi.org/10.5194/essd-15-3283-2023, 2023
Short summary
Short summary
Landslides occur often across the world, with the potential to cause significant damage. Although a substantial amount of research has been conducted on the mapping of landslides using remote-sensing data, gaps and uncertainties remain when developing models to be operational at the global scale. To address this issue, we present the High-Resolution Global landslide Detector Database (HR-GLDD) for landslide mapping with landslide instances from 10 different physiographical regions globally.
Xiangyang Dou, Xuanmei Fan, Ali P. Yunus, Junlin Xiong, Ran Tang, Xin Wang, and Qiang Xu
EGUsphere, https://doi.org/10.5194/egusphere-2022-586, https://doi.org/10.5194/egusphere-2022-586, 2022
Preprint withdrawn
Short summary
Short summary
This study created a multi-temporal inventory of glacial lake from 1990 to 2019 throughout the Tibetan Plateau . In here, we demonstrated the quantity and size of glacier lakes have grown by 3285 and 258.82 sq km, respectively. The distribution of glacial lakes across the 17 mountains of TP is uneven, and the pace of area change varies per subregion. Most glacial lakes are distributed in the elevation range of 4400–5400 m above sea level, with an obvious expansion tendency in recent decades.
Chengbin Zou, Paul Carling, Zetao Feng, Daniel Parsons, and Xuanmei Fan
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-119, https://doi.org/10.5194/tc-2022-119, 2022
Manuscript not accepted for further review
Short summary
Short summary
Climate change is causing mountain lakes behind glacier barriers to drain through ice tunnels as catastrophe floods, threatening people and infrastructure downstream. Understanding of how process works can mitigate the impacts by providing advanced warnings. A laboratory study of ice tunnel development improved understanding of how floods evolve. The principles of ice tunnel development were defined numerically and can be used to better model natural floods leading to improved prediction.
Sansar Raj Meena, Silvia Puliero, Kushanav Bhuyan, Mario Floris, and Filippo Catani
Nat. Hazards Earth Syst. Sci., 22, 1395–1417, https://doi.org/10.5194/nhess-22-1395-2022, https://doi.org/10.5194/nhess-22-1395-2022, 2022
Short summary
Short summary
The study investigated the importance of the conditioning factors in predicting landslide occurrences using the mentioned models. In this paper, we evaluated the importance of the conditioning factors (features) in the overall prediction capabilities of the statistical and machine learning algorithms.
Xiangyang Dou, Xuanmei Fan, Ali P. Yunus, Junlin Xiong, Ran Tang, Xin Wang, and Qiang Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-354, https://doi.org/10.5194/essd-2021-354, 2021
Revised manuscript not accepted
Short summary
Short summary
Due to global warming, the glaciers in the Tibetan Plateau (TP) undergoes rapid melting, leading to an increase in the number of glacial lakes and lake areas. However, these changes are not homogenous throughout TP. Here, we present the 30 years (1990–2019) record of glacial lakes inventory of TP using archived Landsat images. We showed that the number and area of glacial lakes increased by 3285 and 258.82 km2 in the last three decades in TP.
Oliver R. Francis, Tristram C. Hales, Daniel E. J. Hobley, Xuanmei Fan, Alexander J. Horton, Gianvito Scaringi, and Runqiu Huang
Earth Surf. Dynam., 8, 579–593, https://doi.org/10.5194/esurf-8-579-2020, https://doi.org/10.5194/esurf-8-579-2020, 2020
Short summary
Short summary
Large earthquakes can build mountains by uplifting bedrock, but they also erode them by triggering large volumes of coseismic landsliding. Using a zero-dimensional numerical model, we identify that the storage of sediment produced by earthquakes can affect surface uplift and exhumation rates across the mountain range. However, the storage also reduces the time span at which the impact of the earthquake can be measured, preventing the recognition of single earthquakes in many long-term records.
Giovanni Forzieri, Matteo Pecchi, Marco Girardello, Achille Mauri, Marcus Klaus, Christo Nikolov, Marius Rüetschi, Barry Gardiner, Julián Tomaštík, David Small, Constantin Nistor, Donatas Jonikavicius, Jonathan Spinoni, Luc Feyen, Francesca Giannetti, Rinaldo Comino, Alessandro Wolynski, Francesco Pirotti, Fabio Maistrelli, Ionut Savulescu, Stéphanie Wurpillot-Lucas, Stefan Karlsson, Karolina Zieba-Kulawik, Paulina Strejczek-Jazwinska, Martin Mokroš, Stefan Franz, Lukas Krejci, Ionel Haidu, Mats Nilsson, Piotr Wezyk, Filippo Catani, Yi-Ying Chen, Sebastiaan Luyssaert, Gherardo Chirici, Alessandro Cescatti, and Pieter S. A. Beck
Earth Syst. Sci. Data, 12, 257–276, https://doi.org/10.5194/essd-12-257-2020, https://doi.org/10.5194/essd-12-257-2020, 2020
Short summary
Short summary
Strong winds may uproot and break trees and represent a risk for forests. Despite the importance of this natural disturbance and possible intensification in view of climate change, spatial information about wind-related impacts is currently missing on a pan-European scale. We present a new database of wind disturbances in European forests comprised of more than 80 000 records over the period 2000–2018. Our database is a unique spatial source for the study of forest disturbances at large scales.
Xuanmei Fan, Gianvito Scaringi, Guillem Domènech, Fan Yang, Xiaojun Guo, Lanxin Dai, Chaoyang He, Qiang Xu, and Runqiu Huang
Earth Syst. Sci. Data, 11, 35–55, https://doi.org/10.5194/essd-11-35-2019, https://doi.org/10.5194/essd-11-35-2019, 2019
Short summary
Short summary
Large earthquakes cause major disturbances to mountain landscapes. They trigger many landslides that can form deposits of debris on steep slopes and channels. Rainfall can remobilise these deposits and generate large and destructive flow-like landslides and floods. We release two datasets that track a decade of landsliding following the 2008 7.9 magnitude Wenchuan earthquake in China. These data are useful for quantifying the role of major earthquakes in shaping mountain landscapes.
Teresa Salvatici, Veronica Tofani, Guglielmo Rossi, Michele D'Ambrosio, Carlo Tacconi Stefanelli, Elena Benedetta Masi, Ascanio Rosi, Veronica Pazzi, Pietro Vannocci, Miriana Petrolo, Filippo Catani, Sara Ratto, Hervè Stevenin, and Nicola Casagli
Nat. Hazards Earth Syst. Sci., 18, 1919–1935, https://doi.org/10.5194/nhess-18-1919-2018, https://doi.org/10.5194/nhess-18-1919-2018, 2018
Short summary
Short summary
In this paper, we present the application of the physically based HIRESSS model (High Resolution Stability Simulator) to forecast the occurrence of shallow landslides in a portion of the Aosta Valley region (Italy). An in-depth study of the geotechnical and hydrological properties of the hillslopes controlling shallow landslides formation was conducted, in order to generate an input map of parameters. The main aim of this study is to set up a regional landslide early warning system.
Xuanmei Fan, Qiang Xu, and Gianvito Scaringi
Nat. Hazards Earth Syst. Sci., 18, 397–403, https://doi.org/10.5194/nhess-18-397-2018, https://doi.org/10.5194/nhess-18-397-2018, 2018
Short summary
Short summary
The long-term effect of strong earthquakes on geological hazards in mountainous areas is an underestimated issue, but the integrated use of field monitoring, remote sensing, and real-time predictive modelling can help to set up effective early warning systems, provide timely alarms, optimize rescue operations, and perform more accurate secondary hazard assessments. With this paper we wish to stimulate an open discussion on post-seismic slope stability and its implications for policy makers.
Weiwei Zhan, Xuanmei Fan, Runqiu Huang, Xiangjun Pei, Qiang Xu, and Weile Li
Nat. Hazards Earth Syst. Sci., 17, 833–844, https://doi.org/10.5194/nhess-17-833-2017, https://doi.org/10.5194/nhess-17-833-2017, 2017
Short summary
Short summary
Channelized rock avalanches are a type of rock slope failures with massive flow-like movements of fragmented rock, which are potentially dangerous due to their strong mobility. This study built an empirical prediction model of travel distance using the Wenchuan earthquake dataset. The results suggest that the movement was dominated by the landslide volume, total relief and channel gradient. The model was tested by a separate dataset and proved to be useful in other regions as well.
Qiang Xu, Dalei Peng, Weile Li, Xiujun Dong, Wei Hu, Minggao Tang, and Fangzhou Liu
Nat. Hazards Earth Syst. Sci., 17, 277–290, https://doi.org/10.5194/nhess-17-277-2017, https://doi.org/10.5194/nhess-17-277-2017, 2017
Short summary
Short summary
The article aims at presenting the first-hand dataset and results from the field investigation, laboratory test, and numerical analysis for the flowslide
that occurred on 20 December 2015 in Shenzhen, China: a devastating event causing significant human and property losses. The article concluded that the
landfill stagnated groundwater flow and resulted in high water pressure due to the absence of a drainage system, with both disposal rate and amount
exceeding the maximum design capacity.
D. Lagomarsino, S. Segoni, A. Rosi, G. Rossi, A. Battistini, F. Catani, and N. Casagli
Nat. Hazards Earth Syst. Sci., 15, 2413–2423, https://doi.org/10.5194/nhess-15-2413-2015, https://doi.org/10.5194/nhess-15-2413-2015, 2015
S. Segoni, A. Battistini, G. Rossi, A. Rosi, D. Lagomarsino, F. Catani, S. Moretti, and N. Casagli
Nat. Hazards Earth Syst. Sci., 15, 853–861, https://doi.org/10.5194/nhess-15-853-2015, https://doi.org/10.5194/nhess-15-853-2015, 2015
Short summary
Short summary
We monitor and forecast (with lead times up to 48h) regional-scale landslide hazard with an early warning system (EWS) implemented on a user-friendly WebGIS interface.
The EWS detects the most critical rainfall conditions using a mosaic of 25 site-specific thresholds. Moreover, when the rainfall paths recorded by the instruments are compared with the thresholds, the thresholds are shifted in the time axis and adjusted to all possible starting times until the most hazardous scenario is found.
S. Segoni, A. Rosi, G. Rossi, F. Catani, and N. Casagli
Nat. Hazards Earth Syst. Sci., 14, 2637–2648, https://doi.org/10.5194/nhess-14-2637-2014, https://doi.org/10.5194/nhess-14-2637-2014, 2014
F. Catani, D. Lagomarsino, S. Segoni, and V. Tofani
Nat. Hazards Earth Syst. Sci., 13, 2815–2831, https://doi.org/10.5194/nhess-13-2815-2013, https://doi.org/10.5194/nhess-13-2815-2013, 2013
P. Mercogliano, S. Segoni, G. Rossi, B. Sikorsky, V. Tofani, P. Schiano, F. Catani, and N. Casagli
Nat. Hazards Earth Syst. Sci., 13, 771–777, https://doi.org/10.5194/nhess-13-771-2013, https://doi.org/10.5194/nhess-13-771-2013, 2013
G. Martelloni, S. Segoni, D. Lagomarsino, R. Fanti, and F. Catani
Hydrol. Earth Syst. Sci., 17, 1229–1240, https://doi.org/10.5194/hess-17-1229-2013, https://doi.org/10.5194/hess-17-1229-2013, 2013
V. Tofani, S. Segoni, A. Agostini, F. Catani, and N. Casagli
Nat. Hazards Earth Syst. Sci., 13, 299–309, https://doi.org/10.5194/nhess-13-299-2013, https://doi.org/10.5194/nhess-13-299-2013, 2013
G. Rossi, F. Catani, L. Leoni, S. Segoni, and V. Tofani
Nat. Hazards Earth Syst. Sci., 13, 151–166, https://doi.org/10.5194/nhess-13-151-2013, https://doi.org/10.5194/nhess-13-151-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Geology and geochemistry
Integration by design: driving mineral system knowledge using multi-modal, collocated, scale-consistent characterisation
MUDA: dynamic geophysical and geochemical MUltiparametric DAtabase
A field-based thickness measurement dataset of fallout pyroclastic deposits in the peri-volcanic areas of Campania (Italy): statistical combination of different predictions for spatial estimation of thickness
The China Active Faults Database (CAFD) and its web system
A regolith lead isoscape of Australia
High-resolution digital outcrop model of the faults, fractures, and stratigraphy of the Agardhfjellet Formation cap rock shales at Konusdalen West, central Spitsbergen
High-resolution digital elevation models and orthomosaics generated from historical aerial photographs (since the 1960s) of the Bale Mountains in Ethiopia
A global zircon U–Th–Pb geochronological database
Subsurface geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy)
The secret life of garnets: a comprehensive, standardized dataset of garnet geochemical analyses integrating localities and petrogenesis
HR-GLDD: a globally distributed dataset using generalized deep learning (DL) for rapid landslide mapping on high-resolution (HR) satellite imagery
IESDB – the Iberian Evaporite Structure Database
Spectral Library of European Pegmatites, Pegmatite Minerals and Pegmatite Host-Rocks – the GREENPEG project database
The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy
Digital soil mapping of lithium in Australia
A multi-dimensional dataset of Ordovician to Silurian graptolite specimens for virtual examination, global correlation, and shale gas exploration
A strontium isoscape of northern Australia
Valgarður: a database of the petrophysical, mineralogical, and chemical properties of Icelandic rocks
A geodatabase of historical landslide events occurring in the highly urbanized volcanic area of Campi Flegrei, Italy
Pan-Arctic soil element bioavailability estimations
Geomorphological landslide inventory map of the Daunia Apennines, southern Italy
A novel specimen-based mid-Paleozoic dataset of antiarch placoderms (the most basal jawed vertebrates)
A database of radiogenic Sr–Nd isotopes at the “three poles”
MOdern River archivEs of Particulate Organic Carbon: MOREPOC
The Active Faults of Eurasia Database (AFEAD): the ontology and design behind the continental-scale dataset
A strontium isoscape of inland southeastern Australia
A new digital lithological map of Italy at the 1:100 000 scale for geomechanical modelling
Retrogressive thaw slumps along the Qinghai–Tibet Engineering Corridor: a comprehensive inventory and their distribution characteristics
OCTOPUS database (v.2)
A national landslide inventory for Denmark
James R. Austin, Michael Gazley, Renee Birchall, Ben Patterson, Jessica Stromberg, Morgan Willams, Andreas Björk, Monica Le Gras, Tina D. Shelton, Courteney Dhnaram, Vladimir Lisitsin, Tobias Schlegel, Helen McFarlane, and John Walshe
Earth Syst. Sci. Data, 16, 5027–5067, https://doi.org/10.5194/essd-16-5027-2024, https://doi.org/10.5194/essd-16-5027-2024, 2024
Short summary
Short summary
Cloncurry METAL shifts the big-data paradigm in mineral exploration by developing a quantitative, fully integrated, multi-modal, scale-consistent methodology for mineral system characterisation. The data comprise collocated petrophysical–mineralogical–geochemical–structural–metasomatic characterisation of 23 deposits from a highly complex mineral system. This approach enables translation of the mineral system processes into physics, providing a framework for smarter geophysics-based exploration.
Marco Massa, Andrea Luca Rizzo, Davide Scafidi, Elisa Ferrari, Sara Lovati, Lucia Luzi, and MUDA working group
Earth Syst. Sci. Data, 16, 4843–4867, https://doi.org/10.5194/essd-16-4843-2024, https://doi.org/10.5194/essd-16-4843-2024, 2024
Short summary
Short summary
MUDA (geophysical and geochemical MUltiparametric DAtabase) is a new infrastructure of the National Institute of Geophysics and Volcanology serving geophysical and geochemical multiparametric data. MUDA collects information from different sensors, such as seismometers, accelerometers, hydrogeochemical sensors, meteorological stations and sensors for the flux of carbon dioxide and radon gas, with the aim of making correlations between seismic phenomena and variations in environmental parameters.
Pooria Ebrahimi, Fabio Matano, Vincenzo Amato, Raffaele Mattera, and Germana Scepi
Earth Syst. Sci. Data, 16, 4161–4188, https://doi.org/10.5194/essd-16-4161-2024, https://doi.org/10.5194/essd-16-4161-2024, 2024
Short summary
Short summary
Fallout pyroclastic deposits cover hillslopes after explosive volcanic eruptions and strongly influence landscape evolution, hydrology, erosion, and slope stability processes. Accurate mapping of the spatial-thickness variations of these fallout pyroclastic deposits over large hillslope areas remains a knowledge gap. We attempt to bridge this gap by applying statistical techniques to a field-based thickness measurement dataset of fallout pyroclastic deposits.
Xiyan Wu, Xiwei Xu, Guihua Yu, Junjie Ren, Xiaoping Yang, Guihua Chen, Chong Xu, Keping Du, Xiongnan Huang, Haibo Yang, Kang Li, and Haijian Hao
Earth Syst. Sci. Data, 16, 3391–3417, https://doi.org/10.5194/essd-16-3391-2024, https://doi.org/10.5194/essd-16-3391-2024, 2024
Short summary
Short summary
This study presents a national-scale database (1:4000 000) of active faults in China and its adjacent regions in tandem with an associated web-based query system. This database integrates regional-scale studies and surveys conducted over the past 2 decades (at reference scales from 1:250 000 to 1:50 000). Our system hosts this nation-scale database accessible through a Web Geographic Information System (GIS) application.
Candan U. Desem, Patrice de Caritat, Jon Woodhead, Roland Maas, and Graham Carr
Earth Syst. Sci. Data, 16, 1383–1393, https://doi.org/10.5194/essd-16-1383-2024, https://doi.org/10.5194/essd-16-1383-2024, 2024
Short summary
Short summary
Lead (Pb) isotopes form a potent tracer in studies of provenance, mineral exploration and environmental remediation. Previously, however, Pb isotope analysis has rarely been deployed at a continental scale. Here we present a new regolith Pb isotope dataset for Australia, which includes 1119 large catchments encompassing 5.6 × 106 km2 or close to ~75 % of the continent. Isoscape maps have been produced for use in diverse fields of study.
Peter Betlem, Thomas Birchall, Gareth Lord, Simon Oldfield, Lise Nakken, Kei Ogata, and Kim Senger
Earth Syst. Sci. Data, 16, 985–1006, https://doi.org/10.5194/essd-16-985-2024, https://doi.org/10.5194/essd-16-985-2024, 2024
Short summary
Short summary
We present the digitalisation (i.e. textured outcrop and terrain models) of the Agardhfjellet Fm. cliffs exposed in Konusdalen West, Svalbard, which forms the seal of a carbon capture site in Longyearbyen, where several boreholes cover the exposed interval. Outcrop data feature centimetre-scale accuracies and a maximum resolution of 8 mm and have been correlated with the boreholes through structural–stratigraphic annotations that form the basis of various numerical modelling scenarios.
Mohammed Ahmed Muhammed, Binyam Tesfaw Hailu, Georg Miehe, Luise Wraase, Thomas Nauss, and Dirk Zeuss
Earth Syst. Sci. Data, 15, 5535–5552, https://doi.org/10.5194/essd-15-5535-2023, https://doi.org/10.5194/essd-15-5535-2023, 2023
Short summary
Short summary
We processed the only available and oldest historical aerial photographs for the Bale Mountains, Ethiopia. We used structure-from-motion multi-view stereo photogrammetry to generate the first high-resolution DEMs and orthomosaics for 1967 and 1984 at larger spatial extents (5730 km2) and at high spatial resolutions (0.84 m and 0.98 m, respectively). Our datasets will help the scientific community address questions related to the Bale Mountains and afro-alpine ecosystems.
Yujing Wu, Xianjun Fang, and Jianqing Ji
Earth Syst. Sci. Data, 15, 5171–5181, https://doi.org/10.5194/essd-15-5171-2023, https://doi.org/10.5194/essd-15-5171-2023, 2023
Short summary
Short summary
We introduce a zircon U‒Th‒Pb chronological database of the global continental crust. This database provides comprehensive research materials for Earth system science in deep time and space due to its large amount of data (~2 million records), long time span (4.4 billion years), global sampling range, comprehensive zircon samples, and various dating instruments.
Michele Livani, Lorenzo Petracchini, Christoforos Benetatos, Francesco Marzano, Andrea Billi, Eugenio Carminati, Carlo Doglioni, Patrizio Petricca, Roberta Maffucci, Giulia Codegone, Vera Rocca, Francesca Verga, and Ilaria Antoncecchi
Earth Syst. Sci. Data, 15, 4261–4293, https://doi.org/10.5194/essd-15-4261-2023, https://doi.org/10.5194/essd-15-4261-2023, 2023
Short summary
Short summary
This paper presents subsurface geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy). We collected and digitized data from 160 deep wells (including geophysical logs), 61 geological cross-sections, and 10 isobath maps. Furthermore, after a data accuracy analysis, we generated a simplified 3D geological model with several gridded surfaces separating units with different lithological properties. All data are available in delimited text files in ASCII format.
Kristen Chiama, Morgan Gabor, Isabella Lupini, Randolph Rutledge, Julia Ann Nord, Shuang Zhang, Asmaa Boujibar, Emma S. Bullock, Michael J. Walter, Kerstin Lehnert, Frank Spear, Shaunna M. Morrison, and Robert M. Hazen
Earth Syst. Sci. Data, 15, 4235–4259, https://doi.org/10.5194/essd-15-4235-2023, https://doi.org/10.5194/essd-15-4235-2023, 2023
Short summary
Short summary
We compiled 95 650 garnet sample analyses from a variety of sources, ranging from large data repositories to peer-reviewed literature. Garnets are commonly used as indicators of geological formation environments and are an ideal subject for the creation of an extensive dataset incorporating composition, localities, formation, age, temperature, pressure, and geochemistry. This dataset is available in the Evolutionary System of Mineralogy Database and paves the way for future geochemical studies.
Sansar Raj Meena, Lorenzo Nava, Kushanav Bhuyan, Silvia Puliero, Lucas Pedrosa Soares, Helen Cristina Dias, Mario Floris, and Filippo Catani
Earth Syst. Sci. Data, 15, 3283–3298, https://doi.org/10.5194/essd-15-3283-2023, https://doi.org/10.5194/essd-15-3283-2023, 2023
Short summary
Short summary
Landslides occur often across the world, with the potential to cause significant damage. Although a substantial amount of research has been conducted on the mapping of landslides using remote-sensing data, gaps and uncertainties remain when developing models to be operational at the global scale. To address this issue, we present the High-Resolution Global landslide Detector Database (HR-GLDD) for landslide mapping with landslide instances from 10 different physiographical regions globally.
Eloi González-Esvertit, Juan Alcalde, and Enrique Gomez-Rivas
Earth Syst. Sci. Data, 15, 3131–3145, https://doi.org/10.5194/essd-15-3131-2023, https://doi.org/10.5194/essd-15-3131-2023, 2023
Short summary
Short summary
Evaporites are, scientifically and economically, key rocks due to their unique geological features and value for industrial purposes. To compile and normalise the vast amount of information of evaporite structures in the Iberian Peninsula, we present the IESDB – the first comprehensive database of evaporite structures and their surrounding rocks in Spain and Portugal. The IESDB is free to use, open access, and can be accessed and downloaded through the interactive IESDB webpage.
Joana Cardoso-Fernandes, Douglas Santos, Cátia Rodrigues de Almeida, Alexandre Lima, Ana C. Teodoro, and GREENPEG project team
Earth Syst. Sci. Data, 15, 3111–3129, https://doi.org/10.5194/essd-15-3111-2023, https://doi.org/10.5194/essd-15-3111-2023, 2023
Short summary
Short summary
GREENPEG aims to develop tools for pegmatite exploration and to enhance European databases, adding new data on pegmatite properties, such as the spectral signature. Samples comprise pegmatites and wall rocks from Austria, Ireland, Norway, Portugal, and Spain. A detailed description of the spectral database is presented as well as reflectance spectra, photographs, and absorption features. Its European scale comprises pegmatites with distinct characteristics, providing a reference for exploration.
Silvia Peruccacci, Stefano Luigi Gariano, Massimo Melillo, Monica Solimano, Fausto Guzzetti, and Maria Teresa Brunetti
Earth Syst. Sci. Data, 15, 2863–2877, https://doi.org/10.5194/essd-15-2863-2023, https://doi.org/10.5194/essd-15-2863-2023, 2023
Short summary
Short summary
ITALICA (ITAlian rainfall-induced LandslIdes CAtalogue) is the largest catalogue of rainfall-induced landslides accurately located in space and time available in Italy. ITALICA currently lists 6312 landslides that occurred between January 1996 and December 2021. The information was collected using strict objective and homogeneous criteria. The high spatial and temporal accuracy makes the catalogue suitable for reliably defining the rainfall conditions capable of triggering future landslides.
Wartini Ng, Budiman Minasny, Alex McBratney, Patrice de Caritat, and John Wilford
Earth Syst. Sci. Data, 15, 2465–2482, https://doi.org/10.5194/essd-15-2465-2023, https://doi.org/10.5194/essd-15-2465-2023, 2023
Short summary
Short summary
With a higher demand for lithium (Li), a better understanding of its concentration and spatial distribution is important to delineate potential anomalous areas. This study uses a framework that combines data from recent geochemical surveys and relevant environmental factors to predict and map Li content across Australia. The map shows high Li concentration around existing mines and other potentially anomalous Li areas. The same mapping principles can potentially be applied to other elements.
Hong-He Xu, Zhi-Bin Niu, Yan-Sen Chen, Xuan Ma, Xiao-Jing Tong, Yi-Tong Sun, Xiao-Yan Dong, Dan-Ni Fan, Shuang-Shuang Song, Yan-Yan Zhu, Ning Yang, and Qing Xia
Earth Syst. Sci. Data, 15, 2213–2221, https://doi.org/10.5194/essd-15-2213-2023, https://doi.org/10.5194/essd-15-2213-2023, 2023
Short summary
Short summary
A multi-dimensional and integrated dataset of fossil specimens is described. The dataset potentially contributes to a range of scientific activities and provides easy access to and virtual examination of fossil specimens in a convenient and low-cost way. It will greatly benefit paleontology in research, teaching, and science communication.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 15, 1655–1673, https://doi.org/10.5194/essd-15-1655-2023, https://doi.org/10.5194/essd-15-1655-2023, 2023
Short summary
Short summary
This new, extensive (~1.5×106 km2) dataset from northern Australia contributes considerable new information on Australia's strontium (Sr) isotope coverage. The data are discussed in terms of lithology and age of the source areas. This dataset will reduce Northern Hemisphere bias in future global Sr isotope models. Other potential applications of the new data include mineral exploration, hydrology, food tracing, dust provenancing, and examining historic migrations of people and animals.
Samuel W. Scott, Léa Lévy, Cari Covell, Hjalti Franzson, Benoit Gibert, Ágúst Valfells, Juliet Newson, Julia Frolova, Egill Júlíusson, and María Sigríður Guðjónsdóttir
Earth Syst. Sci. Data, 15, 1165–1195, https://doi.org/10.5194/essd-15-1165-2023, https://doi.org/10.5194/essd-15-1165-2023, 2023
Short summary
Short summary
Rock properties such as porosity and permeability play an important role in many geological processes. The Valgarður database is a compilation of petrophysical, geochemical, and mineralogical observations on more than 1000 Icelandic rock samples. In addition to helping constrain numerical models and geophysical inversions, these data can be used to better understand the interrelationship between lithology, hydrothermal alteration, and petrophysical properties.
Giuseppe Esposito and Fabio Matano
Earth Syst. Sci. Data, 15, 1133–1149, https://doi.org/10.5194/essd-15-1133-2023, https://doi.org/10.5194/essd-15-1133-2023, 2023
Short summary
Short summary
In the highly urbanized volcanic area of Campi Flegrei (southern Italy), more than 500 000 people are exposed to multi-hazard conditions, including landslides. In the 1828–2017 time span, more than 2000 mass movements affected the volcanic slopes, concentrated mostly along the coastal sector. Rapid rock failures and flow-like landslides are frequent in the whole area. Besides their relevant role in modeling the landscape of Campi Flegrei, these processes also pose a societal risk.
Peter Stimmler, Mathias Goeckede, Bo Elberling, Susan Natali, Peter Kuhry, Nia Perron, Fabrice Lacroix, Gustaf Hugelius, Oliver Sonnentag, Jens Strauss, Christina Minions, Michael Sommer, and Jörg Schaller
Earth Syst. Sci. Data, 15, 1059–1075, https://doi.org/10.5194/essd-15-1059-2023, https://doi.org/10.5194/essd-15-1059-2023, 2023
Short summary
Short summary
Arctic soils store large amounts of carbon and nutrients. The availability of nutrients, such as silicon, calcium, iron, aluminum, phosphorus, and amorphous silica, is crucial to understand future carbon fluxes in the Arctic. Here, we provide, for the first time, a unique dataset of the availability of the abovementioned nutrients for the different soil layers, including the currently frozen permafrost layer. We relate these data to several geographical and geological parameters.
Francesca Ardizzone, Francesco Bucci, Mauro Cardinali, Federica Fiorucci, Luca Pisano, Michele Santangelo, and Veronica Zumpano
Earth Syst. Sci. Data, 15, 753–767, https://doi.org/10.5194/essd-15-753-2023, https://doi.org/10.5194/essd-15-753-2023, 2023
Short summary
Short summary
This paper presents a new geomorphological landslide inventory map for the Daunia Apennines, southern Italy. It was produced through the interpretation of two sets of stereoscopic aerial photographs, taken in 1954/55 and 2003, and targeted field checks. The inventory contains 17 437 landslides classified according to relative age, type of movement, and estimated depth. The dataset consists of a digital archive publicly available at https://doi.org/10.1594/PANGAEA.942427.
Zhaohui Pan, Zhibin Niu, Zumin Xian, and Min Zhu
Earth Syst. Sci. Data, 15, 41–51, https://doi.org/10.5194/essd-15-41-2023, https://doi.org/10.5194/essd-15-41-2023, 2023
Short summary
Short summary
Antiarch placoderms, the most basal jawed vertebrates, have the potential to enlighten the origin of the last common ancestor of jawed vertebrates during the Paleozoic. This dataset, which was extracted manually from 142 published papers or books from 1939 to 2021, consists of 60 genera of 6025 specimens from the Ludfordian to the Famennian, covering all antiarch lineages. We transferred the unstructured data from the literature to structured data for further detailed research.
Zhiheng Du, Jiao Yang, Lei Wang, Ninglian Wang, Anders Svensson, Zhen Zhang, Xiangyu Ma, Yaping Liu, Shimeng Wang, Jianzhong Xu, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5349–5365, https://doi.org/10.5194/essd-14-5349-2022, https://doi.org/10.5194/essd-14-5349-2022, 2022
Short summary
Short summary
A dataset of the radiogenic strontium and neodymium isotopic compositions from the three poles (the third pole, the Arctic, and Antarctica) were integrated to obtain new findings. The dataset enables us to map the standardized locations in the three poles, while the use of sorting criteria related to the sample type permits us to trace the dust sources and sinks. The purpose of this dataset is to try to determine the variable transport pathways of dust at three poles.
Yutian Ke, Damien Calmels, Julien Bouchez, and Cécile Quantin
Earth Syst. Sci. Data, 14, 4743–4755, https://doi.org/10.5194/essd-14-4743-2022, https://doi.org/10.5194/essd-14-4743-2022, 2022
Short summary
Short summary
In this paper, we introduce the largest and most comprehensive database for riverine particulate organic carbon carried by suspended particulate matter in Earth's fluvial systems: 3546 data entries for suspended particulate matter with detailed geochemical parameters are included, and special attention goes to the elemental and isotopic carbon compositions to better understand riverine particulate organic carbon and its role in the carbon cycle from regional to global scales.
Egor Zelenin, Dmitry Bachmanov, Sofya Garipova, Vladimir Trifonov, and Andrey Kozhurin
Earth Syst. Sci. Data, 14, 4489–4503, https://doi.org/10.5194/essd-14-4489-2022, https://doi.org/10.5194/essd-14-4489-2022, 2022
Short summary
Short summary
Active faults are faults in the Earth's crust that could experience a possible future slip. A slip at the fault would cause an earthquake; thus, this draws particular attention to active faults in tectonic studies and seismic hazard assessment. We present the Active Faults of Eurasia Database (AFEAD): a high-detail continental-scale geodatabase comprising ~48 000 faults. The location, name, slip characteristics, and a reference to source publications are provided for database entries.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data, 14, 4271–4286, https://doi.org/10.5194/essd-14-4271-2022, https://doi.org/10.5194/essd-14-4271-2022, 2022
Short summary
Short summary
Strontium isotopes are useful in geological, environmental, archaeological, and forensic research to constrain or identify the source of materials such as minerals, artefacts, or foodstuffs. A new dataset, contributing significant new data and knowledge to Australia’s strontium isotope coverage, is presented from an area of over 500 000 km2 of inland southeastern Australia. Various source areas for the sediments are recognized, and both fluvial and aeolian transport processes identified.
Francesco Bucci, Michele Santangelo, Lorenzo Fongo, Massimiliano Alvioli, Mauro Cardinali, Laura Melelli, and Ivan Marchesini
Earth Syst. Sci. Data, 14, 4129–4151, https://doi.org/10.5194/essd-14-4129-2022, https://doi.org/10.5194/essd-14-4129-2022, 2022
Short summary
Short summary
The paper describes a new lithological map of Italy at a scale of 1 : 100 000 obtained from classification of a digital database following compositional and geomechanical criteria. The map represents the national distribution of the lithological classes at high resolution. The outcomes of this study can be relevant for a wide range of applications, including statistical and physically based modelling of slope stability assessment and other geoenvironmental studies.
Zhuoxuan Xia, Lingcao Huang, Chengyan Fan, Shichao Jia, Zhanjun Lin, Lin Liu, Jing Luo, Fujun Niu, and Tingjun Zhang
Earth Syst. Sci. Data, 14, 3875–3887, https://doi.org/10.5194/essd-14-3875-2022, https://doi.org/10.5194/essd-14-3875-2022, 2022
Short summary
Short summary
Retrogressive thaw slumps are slope failures resulting from abrupt permafrost thaw, and are widely distributed along the Qinghai–Tibet Engineering Corridor. The potential damage to infrastructure and carbon emission of thaw slumps motivated us to obtain an inventory of thaw slumps. We used a semi-automatic method to map 875 thaw slumps, filling the knowledge gap of thaw slump locations and providing key benchmarks for analysing the distribution features and quantifying spatio-temporal changes.
Alexandru T. Codilean, Henry Munack, Wanchese M. Saktura, Tim J. Cohen, Zenobia Jacobs, Sean Ulm, Paul P. Hesse, Jakob Heyman, Katharina J. Peters, Alan N. Williams, Rosaria B. K. Saktura, Xue Rui, Kai Chishiro-Dennelly, and Adhish Panta
Earth Syst. Sci. Data, 14, 3695–3713, https://doi.org/10.5194/essd-14-3695-2022, https://doi.org/10.5194/essd-14-3695-2022, 2022
Short summary
Short summary
OCTOPUS v.2 is a web-enabled database that allows users to visualise, query, and download cosmogenic radionuclide, luminescence, and radiocarbon ages and denudation rates associated with erosional landscapes, Quaternary depositional landforms, and archaeological records, along with ancillary geospatial data layers. OCTOPUS v.2 hosts five major data collections. Supporting data are comprehensive and include bibliographic, contextual, and sample-preparation- and measurement-related information.
Gregor Luetzenburg, Kristian Svennevig, Anders A. Bjørk, Marie Keiding, and Aart Kroon
Earth Syst. Sci. Data, 14, 3157–3165, https://doi.org/10.5194/essd-14-3157-2022, https://doi.org/10.5194/essd-14-3157-2022, 2022
Short summary
Short summary
We produced the first landslide inventory for Denmark. Over 3200 landslides were mapped using a high-resolution elevation model and orthophotos. We implemented an independent validation into our mapping and found an overall level of completeness of 87 %. The national inventory represents a range of landslide sizes covering all regions that were covered by glacial ice during the last glacial period. This inventory will be used for investigating landslide causes and for natural hazard mitigation.
Cited articles
Alpert, L.: Rainfall maps of Hispaniola, B. Am. Meteorol. Soc., 23, 423–431, 1942.
Basofi, A., Fariza, A., and Dzulkarnain, M. R.: Landslides susceptibility mapping using fuzzy logic: A case study in Ponorogo, East Java, Indonesia, in: Proceedings of the 2016 International Conference on Data and Software Engineering (ICoDSE), Malang, Indonesia, pp. 1–7, https://doi.org/10.1109/ICODSE.2016.7936156, 2016.
Bhuyan, K., Rana, K., Ferrer, J. V., Cotton, F., Ozturk, U., Catani, F., and Malik, N.: Landslide topology uncovers failure movements, Nat. Commun., 15, 2633, https://doi.org/10.1038/s41467-024-46741-7, 2024.
Bhuyan, K., Tanyaş, H., Nava, L., Puliero, S., Meena, S. R., Floris, M., Van Westen, C., and Catani, F.: Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data, Sci. Rep., 13, 162, https://doi.org/10.1038/s41467-024-46741-7, 2023.
Brardinoni, F., Slaymaker, O., and Hassan, M. A.: Landslide inventory in a rugged forested watershed: a comparison between air-photo and field survey data, Geomorphology, 54, 179–196, 2003.
Burrows, K., Walters, R. J., Milledge, D., Spaans, K., and Densmore, A. L.: A new method for large-scale landslide classification from satellite radar, Remote Sens.-Basel, 11, 237, https://doi.org/10.3390/rs11030237, 2019.
Calais, E., Symithe, S., Monfret, T., Delouis, B., Lomax, A., Courboulex, F., Ampuero, J. P., Lara, P. E., Bletery, Q., Cheze, J., Peix, F., Deschamps, A., de Lepinay, B., Raimbault, B., Jolivet, R., Paul, S., St Fleur, S., Boisson, D., Fukushima, Y., Duputel, Z., Xu, L., and Meng, L.: Citizen seismology helps decipher the 2021 Haiti earthquake, Science, 376, 283–287, https://doi.org/10.1126/science.abn1045, 2022.
Cao, H., Wang, Y., Chen, J., Jiang, D., Zhang, X., Tian, Q., and Wang, M.: Swin-unet: Unet-like pure transformer for medical image segmentation, in: Proceedings of the European Conference on Computer Vision (ECCV 2022 Workshops), Tel Aviv, Israel, 23–28 October 2022, pp. 9, https://doi.org/10.1007/978-3-031-25066-8_9, 2022.
Casagli, N., Intrieri, E., Tofani, V., Gigli, G., and Raspini, F.: Landslide detection, monitoring and prediction with remote-sensing techniques, Nat. Rev. Earth Environ., 4, 51–64, 2023.
Chau, K. T., Sze, Y., Fung, M., Wong, W., Fong, E., and Chan, L.: Landslide hazard analysis for Hong Kong using landslide inventory and GIS, Comput. Geosci., 30, 429–443, 2004.
Chen, B., Xu, B., Zhu, Z., Yuan, C., Suen, H. P., Guo, J., Xu, N., Li, W., Zhao, Y., and Yang, J.: Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017, Sci. Bull., 64, 3, https://doi.org/10.1016/j.scib.2019.03.002, 2019.
Chen, D., Yuan, R., Wang, P., Tian, Y., Hu, G., An, J., and Ma, S.: Preliminary study on the development characteristics and formation mechanism of the Zhongchuan Town liquefaction landslide-mudflow-blockage disaster chain induced by the 2023 Jishishan Earthquake in Gansu Province, Landslides, 21, 2467–2480, https://doi.org/10.1007/s10346-024-02307-8, 2024.
Chen, L. C., Zhu, Y., Papandreou, G., Schroff, F., and Adam, H.: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation, in: Proceedings of the European Conference on Computer Vision (ECCV 2018), Munich, Germany, 8–14 September 2018, pp. 49, https://doi.org/10.1007/978-3-030-01234-2_49, 2018.
Chicco, D. and Jurman, G.: The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation, BMC Genomics, 21, 6, https://doi.org/10.1186/s12864-019-6413-7, 2020.
Cigna, F., Osmanoğlu, B., Cabral-Cano, E., Dixon, T. H., Ávila-Olivera, J. A., Garduño-Monroy, V. H., DeMets, C., and Wdowinski, S.: Monitoring land subsidence and its induced geological hazard with Synthetic Aperture Radar Interferometry: A case study in Morelia, Mexico, Remote Sens. Environ., 117, 146–161, 2012.
Cigna, F., Tapete, D., and Lee, K.: Geological hazards in the UNESCO World Heritage sites of the UK: From the global to the local scale perspective, Earth-Sci. Rev., 176, 166–194, 2018.
Coe, J. A., Ellis, W. L., Godt, J. W., Savage, W. Z., Savage, J. E., Michael, J., Kibler, J. D., Powers, P. S., Lidke, D. J., and Debray, S.: Seasonal movement of the Slumgullion landslide determined from Global Positioning System surveys and field instrumentation, July 1998–March 2002, Eng. Geol., 68, 67–101, 2003.
Dai, L., Fan, X., Wang, X., Fang, C., Zou, C., Tang, X., Wei, Z., Xia, M., Wang, D., and Xu, Q.: Coseismic landslides triggered by the 2022 Luding Ms6. 8 earthquake, China, Landslides, 20, 1277–1292, 2023.
De Boer, P.-T., Kroese, D. P., Mannor, S., and Rubinstein, R. Y.: A tutorial on the cross-entropy method, Ann. Oper. Res., 134, 19–67, 2005.
Diakogiannis, F. I., Waldner, F., Caccetta, P., and Wu, C.: ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data, ISPRS J. Photogramm. Remote, 162, 94–114, 2020.
Fan, X., Scaringi, G., Xu, Q., Zhan, W., Dai, L., Li, Y., Pei, X., Yang, Q., and Huang, R.: Coseismic landslides triggered by the 8th August 2017 M s 7.0 Jiuzhaigou earthquake (Sichuan, China): factors controlling their spatial distribution and implications for the seismogenic blind fault identification, Landslides, 15, 967–983, 2018.
Fang, C.: GDCLD: A globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images (the code), Zenodo [code], https://doi.org/10.5281/zenodo.13956757, 2024.
Fang, C., Fan, X., Zhong, H., Lombardo, L., Tanyas, H., and Wang, X.: A Novel historical landslide detection approach based on LiDAR and lightweight attention U-Net, Remote Sens.-Basel, 14, 4357, https://doi.org/10.3390/rs14174357, 2022.
Fang, C., Fan, X., and Wang, X.: GDCLD: A globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images, Zenodo [data set], https://doi.org/10.5281/zenodo.13612636, 2024.
Fiorucci, F., Cardinali, M., Carlà, R., Rossi, M., Mondini, A., Santurri, L., Ardizzone, F., and Guzzetti, F.: Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images, Geomorphology, 129, 59–70, 2011.
Fiorucci, F., Ardizzone, F., Mondini, A. C., Viero, A., and Guzzetti, F.: Visual interpretation of stereoscopic NDVI satellite images to map rainfall-induced landslides, Landslides, 16, 165–174, 2019.
Gao, H., Yin, Y., Li, B., Gao, Y., Zhang, T., Liu, X., and Wan, J.: Geomorphic evolution of the Sedongpu Basin after catastrophic ice and rock avalanches triggered by the 2017 Ms 6.9 Milin earthquake in the Yarlung Zangbo River area, China, Landslides, 1–15, 2023.
Gao, J. and Maro, J.: Topographic controls on evolution of shallow landslides in pastoral Wairarapa, New Zealand, 1979–2003, Geomorphology, 114, 373–381, 2010.
Ghorbanzadeh, O., Xu, Y., Zhao, H., Wang, J., Zhong, Y., Zhao, D., Zang, Q., Wang, S., Zhang, F., and Shi, Y.: The outcome of the 2022 landslide4sense competition: Advanced landslide detection from multisource satellite imagery, IEEE J. Sel. Top. Appl. Earth Obs., 15, 9927–9942, 2022.
Gorum, T., Fan, X., van Westen, C. J., Huang, R. Q., Xu, Q., Tang, C., and Wang, G.: Distribution pattern of earthquake-induced landslides triggered by the 12 May 2008 Wenchuan earthquake, Geomorphology, 133, 152–167, 2011.
Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., and Chang, K.-T.: Landslide inventory maps: New tools for an old problem, Earth-Sci. Rev., 112, 42–66, 2012.
Harp, E. L., Jibson, R. W., and Schmitt, R. G.: Map of landslides triggered by the January 12, 2010, Haiti earthquake, Reston, VA, Report 3353, USGeological Survey Scientific Investigations Map, https://doi.org/10.3133/sim3353, 2016.
He, K., Zhang, X., Ren, S., and Sun, J.: Deep Residual Learning for Image Recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 27 June–2 July 2016, pp. 770–778, https://doi.org/10.1109/CVPR.2016.90, 2016.
Hu, K., Zhang, X., You, Y., Hu, X., Liu, W., and Li, Y.: Landslides and dammed lakes triggered by the 2017 Ms 6.9 Milin earthquake in the Tsangpo gorge, Landslides, 16, 993–1001, 2019.
Huang, R. and Fan, X.: The landslide story, Nat. Geosci., 6, 325–326, 2013.
Huang, R., Pei, X., Fan, X., Zhang, W., Li, S., and Li, B.: The characteristics and failure mechanism of the largest landslide triggered by the Wenchuan earthquake, May 12, 2008, China, Landslides, 9, 131–142, 2012.
Huang, Y., Xu, C., Zhang, X., Xue, C., and Wang, S.: An Updated Database and Spatial Distribution of Landslides Triggered by the Milin, Tibet Mw 6.4 Earthquake of 18 November 2017, J. Earth Sci., 32, 1069–1078, 2021.
Hungr, O., Leroueil, S., and Picarelli, L.: The Varnes classification of landslide types, an update, Landslides, 11, 167–194, 2014.
Ji, S., Yu, D., Shen, C., Li, W., and Xu, Q.: Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks, Landslides, 17, 1337-1352, 2020.
Li, Z., Shi, W., Lu, P., Yan, L., Wang, Q., and Miao, Z.: Landslide mapping from aerial photographs using change detection-based Markov random field, Remote Sens. Environ., 187, 76–90, 2016.
Li, Z., Shi, A., Li, X., Dou, J., Li, S., Chen, T., and Chen, T.: Deep learning-based landslide recognition incorporating deformation characteristics, Remote Sens.-Basel, 16, 992, https://doi.org/10.3390/rs16060992, 2024.
Liu, J., Huang, X., Song, G., Li, H., and Liu, Y.: Uninet: Unified architecture search with convolution, transformer, and MLP, in: Proceedings of the European Conference on Computer Vision (ECCV), Tel Aviv, Israel, 23–28 October 2022, pp. 33–49, https://doi.org/10.1007/978-3-031-19803-8_3, 2022.
Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., and Guo, B.: Swin transformer: Hierarchical vision transformer using shifted windows, in: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC, Canada, 9–16 October 2021, pp. 9992–10002, https://doi.org/10.1109/ICCV48922.2021.00986, 2021.
Loshchilov, I. and Hutter, F.: Decoupled weight decay regularization, arXiv [preprint], arXiv:1711.05101, https://doi.org/10.48550/arXiv.1711.05101, 2017.
Lu, P., Qin, Y., Li, Z., Mondini, A. C., and Casagli, N.: Landslide mapping from multi-sensor data through improved change detection-based Markov random field, Remote Sens. Environ., 231, 111235, https://doi.org/10.1016/j.rse.2019.111235, 2019.
Luppino, L. T., Hansen, M. A., Kampffmeyer, M., Bianchi, F. M., Moser, G., Jenssen, R., and Anfinsen, S. N.: Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images, IEEE Trans. Neural Netw. Learn. Syst., 35, 60–72, https://doi.org/10.1109/TNNLS.2022.3172183, 2022.
Ma, Y., Yu, D., Wu, T., and Wang, H.: PaddlePaddle: An open-source deep learning platform from industrial practice, Front. Data Comput., 1, 105-115, 2019.
Marc, O. and Hovius, N.: Amalgamation in landslide maps: effects and automatic detection, Nat. Hazards Earth Syst. Sci., 15, 723–733, https://doi.org/10.5194/nhess-15-723-2015, 2015.
Meena, S. R., Ghorbanzadeh, O., van Westen, C. J., Nachappa, T. G., Blaschke, T., Singh, R. P., and Sarkar, R.: Rapid mapping of landslides in the Western Ghats (India) triggered by 2018 extreme monsoon rainfall using a deep learning approach, Landslides, 18, 1937–1950, 2021.
Meena, S. R., Nava, L., Bhuyan, K., Puliero, S., Soares, L. P., Dias, H. C., Floris, M., and Catani, F.: HR-GLDD: a globally distributed dataset using generalized deep learning (DL) for rapid landslide mapping on high-resolution (HR) satellite imagery, Earth Syst. Sci. Data, 15, 3283–3298, https://doi.org/10.5194/essd-15-3283-2023, 2023.
Metternicht, G., Hurni, L., and Gogu, R.: Remote sensing of landslides: An analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments, Remote Sens. Environ., 98, 284–303, 2005.
Mohan, A., Singh, A. K., Kumar, B., and Dwivedi, R.: Review on remote sensing methods for landslide detection using machine and deep learning, T. Emerg. Telecommun. T., 32, e3998, https://doi.org/10.1002/ett.3998, 2021.
Mondini, A. C., Guzzetti, F., Chang, K.-T., Monserrat, O., Martha, T. R., and Manconi, A.: Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future, Earth-Sci. Rev., 216, 103574, https://doi.org/10.1016/j.earscirev.2021.103574, 2021.
Nava, L., Monserrat, O., and Catani, F.: Improving landslide detection on SAR data through deep learning, IEEE Geosci. Remote Sens. Lett., 19, 1–5, 2021.
O'Shea, K. and Nash, R.: An introduction to convolutional neural networks, arXiv [preprint], arXiv:1511.08458, 2015.
Planet Team: Education and RESEARCH: Satellite imagery solutions, Planet [data set], https://www.planet.com/ (last access: 1 March 2024), 2019.
Poveda, E., Pedraza, P., Velandia, F., Mayorga, E., Plicka, V., Gallovič, F., and Zahradník, J.: 2019 Mw 6.0 Mesetas (Colombia) Earthquake Sequence: Insights From Integrating Seismic and Morphostructural Observations, Earth Space Sci., 9, e2022EA002465, https://doi.org/10.1029/2022EA002465, 2022.
Rezatofighi, H., Tsoi, N., Gwak, J., Sadeghian, A., Reid, I., and Savarese, S.: Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, 16–21 June 2019, pp. 658–666, https://doi.org/10.1109/CVPR.2019.00075, 2019.
Ronneberger, O., Fischer, P., and Brox, T.: U-net: Convolutional networks for biomedical image segmentation, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, 5–9 October 2015, Munich, Germany, Proceedings, Part III 18, 234–241, 2015.
Shao, X., Ma, S., and Xu, C.: Distribution and characteristics of shallow landslides triggered by the 2018 Mw 7.5 Palu earthquake, Indonesia, Landslides, 20, 157–175, 2023.
Soares, L. P., Dias, H. C., Garcia, G. P. B., and Grohmann, C. H.: Landslide segmentation with deep learning: Evaluating model generalization in rainfall-induced landslides in Brazil, Remote Sens.-Basel, 14, 2237, https://doi.org/10.3390/rs14092237, 2022.
Ss, V. C. and Shaji, E.: Landslide identification using machine learning techniques: Review, motivation, and future prospects, Earth Sci. Inform., 15, 2063–2090, 2022.
Tang, D., Ge, W., and Cao, X.: Stress triggering of the 2022 Lushan–Maerkang earthquake sequence by historical events and its implication for fault stress evolution in eastern Tibet, Front. Earth Sci., 11, 1105394, https://doi.org/10.3389/feart.2023.1105394, 2023.
Townsend, J. T.: Theoretical analysis of an alphabetic confusion matrix, Perception & Psychophysics, 9, 40–50, 1971.
Udin, W. S., Norazami, N. A. S., Sulaiman, N., Che Zaudin, N. A., Ma’ail, S., and Mohamad Nor, A. N.: UAV Based Multi-spectral Imaging System for Mapping Landslide Risk Area Along Jeli-Gerik Highway, Jeli, Kelantan, in: Proceedings of the 2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA), Penang, Malaysia, pp. 162–167, https://doi.org/10.1109/CSPA.2019.8695995, 2019.
Valagussa, A., Marc, O., Frattini, P., and Crosta, G. B.: Seismic and geological controls on earthquake-induced landslide size, Earth Planet. Sc. Lett., 506, 268–281, 2019.
Wang, F., Fan, X., Yunus, A. P., Siva Subramanian, S., Alonso-Rodriguez, A., Dai, L., Xu, Q., and Huang, R.: Coseismic landslides triggered by the 2018 Hokkaido, Japan (Mw 6.6), earthquake: spatial distribution, controlling factors, and possible failure mechanism, Landslides, 16, 1551–1566, 2019.
Wang, J., Sun, K., Cheng, T., Jiang, B., Deng, C., Zhao, Y., Liu, D., Mu, Y., Tan, M., and Wang, X.: Deep high-resolution representation learning for visual recognition, IEEE T. Pattern Anal., 43, 3349–3364, 2020.
Xiao, T., Liu, Y., Zhou, B., Jiang, Y., and Sun, J.: Unified Perceptual Parsing for Scene Understanding, in: Computer Vision – ECCV 2018, European Conference on Computer Vision, Munich, Germany, 8–14 September 2018, pp. 26, https://doi.org/10.1007/978-3-030-01228-1_26, 2018.
Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J. M., and Luo, P.: SegFormer: Simple and efficient design for semantic segmentation with transformers, Adv. Neur. In., 34, 12077–12090, 2021.
Xu, Y., Ouyang, C., Xu, Q., Wang, D., Zhao, B., and Luo, Y.: CAS Landslide Dataset: A Large-Scale and Multisensor Dataset for Deep Learning-Based Landslide Detection, Sci. Data, 11, 12, https://doi.org/10.1038/s41597-023-02847-z, 2024.
Yamagishi, H. and Yamazaki, F.: Landslides by the 2018 hokkaido iburi-tobu earthquake on september 6, Landslides, 15, 2521–2524, 2018.
Yang, Z., Dai, D., Zhang, Y., Zhang, X., and Liu, J.: Rupture process and aftershock mechanisms of the 2022 Luding M6.8 earthquake in Sichuan, China, Earthquake Science, 35, 1–2, 2022a.
Yang, Z., Xu, C., and Li, L.: Landslide detection based on ResU-net with transformer and CBAM embedded: two examples with geologically different environments, Remote Sens.-Basel, 14, 2885, https://doi.org/10.3390/rs14122885, 2022b.
Ye, C., Li, Y., Cui, P., Liang, L., Pirasteh, S., Marcato, J., Goncalves, W. N., and Li, J.: Landslide detection of hyperspectral remote sensing data based on deep learning with constrains, IEEE J. Sel. Top. Appl. Earth Obs., 12, 5047–5060, 2019.
Yi, Y., Zhang, Z., Zhang, W., Jia, H., and Zhang, J.: Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region, Catena, 195, 104851, https://doi.org/10.1016/j.catena.2020.104851, 2020.
Zhang, X., Yu, W., Pun, M.-O., and Shi, W.: Cross-domain landslide mapping from large-scale remote sensing images using prototype-guided domain-aware progressive representation learning, ISPRS J. Photogramm., 197, 1–17, 2023.
Zhao, B., Li, W., Su, L., Wang, Y., and Wu, H.: Insights into the landslides triggered by the 2022 Lushan Ms 6.1 earthquake: spatial distribution and controls, Remote Sens.-Basel, 14, 4365, https://doi.org/10.3390/rs14174365, 2022a.
Zhao, B., Wang, Y., Li, W., Lu, H., and Li, Z.: Evaluation of factors controlling the spatial and size distributions of landslides, 2021 Nippes earthquake, Haiti, Geomorphology, 415, 108419, https://doi.org/10.1016/j.geomorph.2022.108419, 2022b.
Zhong, C., Liu, Y., Gao, P., Chen, W., Li, H., Hou, Y., Nuremanguli, T., and Ma, H.: Landslide mapping with remote sensing: challenges and opportunities, Int. J. Remote Sens., 41, 1555–1581, 2020.
Short summary
In this study, we present the largest publicly available landslide dataset, Globally Distributed Coseismic Landslide Dataset (GDCLD), which includes multi-sensor high-resolution images from various locations around the world. We test GDCLD with seven advanced algorithms and show that it is effective in achieving reliable landslide mapping across different triggers and environments, with great potential in enhancing emergency response and disaster management.
In this study, we present the largest publicly available landslide dataset, Globally Distributed...
Altmetrics
Final-revised paper
Preprint