Articles | Volume 15, issue 6
https://doi.org/10.5194/essd-15-2465-2023
© Author(s) 2023. 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-15-2465-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Jun 2023
Data description paper |
| 14 Jun 2023
| 14 Jun 2023
Digital soil mapping of lithium in Australia
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
Budiman Minasny
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
Alex McBratney
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
Patrice de Caritat
Geoscience Australia, Canberra, ACT 2601, Australia
John Wilford
Geoscience Australia, Canberra, ACT 2601, Australia
Related authors
Wartini Ng, Budiman Minasny, Wanderson de Sousa Mendes, and José Alexandre Melo Demattê
SOIL, 6, 565–578, https://doi.org/10.5194/soil-6-565-2020, https://doi.org/10.5194/soil-6-565-2020, 2020
Short summary
Short summary
The number of samples utilised to create predictive models affected model performance. This research compares the number of samples needed by a deep learning model to outperform the traditional machine learning models using visible near-infrared spectroscopy data for soil properties predictions. The deep learning model was found to outperform machine learning models when the sample size was above 2000.
Patrice de Caritat, Anthony Dosseto, and Florian Dux
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-352, https://doi.org/10.5194/essd-2024-352, 2024
Preprint under review for ESSD
Short summary
Short summary
This new, extensive dataset from southwestern Australia contributes considerable new data and knowledge to Australia’s strontium isotope coverage. The data are discussed in terms of the lithology and age of the source lithologies. This dataset will reduce northern-hemisphere bias in future global strontium isotope models. Other potential applications of the new data include mineralisation, hydrology, food tracing, dust provenancing, and historic migrations of people and animals.
Marliana Tri Widyastuti, Budiman Minasny, José Padarian, Federico Maggi, Matt Aitkenhead, Amélie Beucher, John Connolly, Dian Fiantis, Darren Kidd, Yuxin Ma, Fraser Macfarlane, Ciaran Robb, Rudiyanto, Budi Indra Setiawan, and Muh Taufik
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-333, https://doi.org/10.5194/essd-2024-333, 2024
Preprint under review for ESSD
Short summary
Short summary
PEATGRIDS, the first dataset containing maps of global peat thickness and carbon stock at 1 km resolution. The dataset has been publicly available at Zenodo to support further analyses and modelling of peatlands across the globe. This work employed the random forest machine learning model to provide spatially explicit peat carbon stock at pixel basis.
Claudia Hird, Morgane M. G. Perron, Thomas M. Holmes, Scott Meyerink, Christopher Nielsen, Ashley T. Townsend, Patrice de Caritat, Michal Strzelec, and Andrew R. Bowie
Aerosol Research Discuss., https://doi.org/10.5194/ar-2024-21, https://doi.org/10.5194/ar-2024-21, 2024
Preprint under review for AR
Short summary
Short summary
Dust deposition flux was investigated in lutruwita/Tasmania, Australia, between 2016 and 2021. Results show that the use of direct measurement of aluminium, iron, thorium and titanium in aerosols to estimate average dust deposition fluxes limits biases associated with using single elements. Observations of dust deposition fluxes in the Southern Hemisphere are critical to validate model outputs and better understand the seasonal and interannual impacts of dust deposition on biogeochemical cycles.
Marliana Tri Widyastuti, José Padarian, Budiman Minasny, Mathew Webb, Muh Taufik, and Darren Kidd
EGUsphere, https://doi.org/10.5194/egusphere-2024-2253, https://doi.org/10.5194/egusphere-2024-2253, 2024
Short summary
Short summary
This work aims to predict soil water content across a large region at fine spatial and temporal resolution (80 m grids, daily) to support agricultural management. It covers modelling assessment to predict multilevel soil moisture spatially via deep learning method. We address the challenge of mapping soil moisture at field scale resolution for Tasmania and perform the optimal model for near-real-time monitoring. This contributes to the deep learning method's applicability in soil science.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
Short summary
Short summary
Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Frisa Irawan Ginting, Rudiyanto Rudiyanto, Fatchurahman, Ramisah Mohd Shah, Norhidayah Che Soh, Sunny Goh Eng Giap, Dian Fiantis, Budi Indra Setiawan, Sam Schiller, Aaron Davitt, and Budiman Minasny
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-90, https://doi.org/10.5194/essd-2024-90, 2024
Preprint withdrawn
Short summary
Short summary
This study is the first to map rice cropping intensity and the harvested area across Southeast Asia at a spatial resolution of 10 m (SEA-Rice-Ci10). We have developed a geospatial inventory of paddy rice parcels and rice cropping intensity by integrating Sentinel-1 and 2 time-series data in a framework called LUCK-PALM, based on local phenological expert interpretation. According to our best knowledge, it is the finest-resolution and most accurate database of paddy rice in Southeast Asia.
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.
Mercedes Román Dobarco, Alexandre M. J-C. Wadoux, Brendan Malone, Budiman Minasny, Alex B. McBratney, and Ross Searle
Biogeosciences, 20, 1559–1586, https://doi.org/10.5194/bg-20-1559-2023, https://doi.org/10.5194/bg-20-1559-2023, 2023
Short summary
Short summary
Soil organic carbon (SOC) is of a heterogeneous nature and varies in chemistry, stabilisation mechanisms, and persistence in soil. In this study we mapped the stocks of SOC fractions with different characteristics and turnover rates (presumably PyOC >= MAOC > POC) across Australia, combining spectroscopy and digital soil mapping. The SOC stocks (0–30 cm) were estimated as 13 Pg MAOC, 2 Pg POC, and 5 Pg PyOC.
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.
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.
José Padarian, Budiman Minasny, Alex B. McBratney, and Pete Smith
SOIL Discuss., https://doi.org/10.5194/soil-2021-73, https://doi.org/10.5194/soil-2021-73, 2021
Manuscript not accepted for further review
Short summary
Short summary
Soil organic carbon sequestration is considered an attractive technology to partially mitigate climate change. Here, we show how the SOC storage potential varies globally. The estimated additional SOC storage potential in the topsoil of global croplands (29–67 Pg C) equates to only 2 to 5 years of emissions offsetting and 32 % of agriculture's 92 Pg historical carbon debt. Since SOC is temperature-dependent, this potential is likely to reduce by 18 % by 2040 due to climate change.
Edward J. Jones, Patrick Filippi, Rémi Wittig, Mario Fajardo, Vanessa Pino, and Alex B. McBratney
SOIL, 7, 33–46, https://doi.org/10.5194/soil-7-33-2021, https://doi.org/10.5194/soil-7-33-2021, 2021
Short summary
Short summary
Soil physical health is integral to maintaining functional agro-ecosystems. A novel method of assessing soil physical condition using a smartphone app has been developed – SLAKES. In this study the SLAKES app was used to investigate aggregate stability in a mixed agricultural landscape. Cropping areas were found to have significantly poorer physical health than similar soils under pasture. Results were mapped across the landscape to identify problem areas and pinpoint remediation efforts.
Wartini Ng, Budiman Minasny, Wanderson de Sousa Mendes, and José Alexandre Melo Demattê
SOIL, 6, 565–578, https://doi.org/10.5194/soil-6-565-2020, https://doi.org/10.5194/soil-6-565-2020, 2020
Short summary
Short summary
The number of samples utilised to create predictive models affected model performance. This research compares the number of samples needed by a deep learning model to outperform the traditional machine learning models using visible near-infrared spectroscopy data for soil properties predictions. The deep learning model was found to outperform machine learning models when the sample size was above 2000.
José Padarian, Alex B. McBratney, and Budiman Minasny
SOIL, 6, 389–397, https://doi.org/10.5194/soil-6-389-2020, https://doi.org/10.5194/soil-6-389-2020, 2020
Short summary
Short summary
In this paper we introduce the use of game theory to interpret a digital soil mapping (DSM) model to understand the contribution of environmental factors to the prediction of soil organic carbon (SOC) in Chile. The analysis corroborated that the SOC model is capturing sensible relationships between SOC and climatic and topographical factors. We were able to represent them spatially (map) addressing the limitations of the current interpretation of models in DSM.
Yosra Ellili-Bargaoui, Brendan Philip Malone, Didier Michot, Budiman Minasny, Sébastien Vincent, Christian Walter, and Blandine Lemercier
SOIL, 6, 371–388, https://doi.org/10.5194/soil-6-371-2020, https://doi.org/10.5194/soil-6-371-2020, 2020
Sanjeewani Nimalka Somarathna Pallegedara Dewage, Budiman Minasny, and Brendan Malone
SOIL, 6, 359–369, https://doi.org/10.5194/soil-6-359-2020, https://doi.org/10.5194/soil-6-359-2020, 2020
Short summary
Short summary
Most soil management activities are implemented at farm scale, yet digital soil maps are commonly available at regional/national scales. This study proposes Bayesian area-to-point kriging to downscale regional-/national-scale soil property maps to farm scale. A regional soil carbon map with a resolution of 100 m (block support) was disaggregated to 10 m (point support) information for a farm in northern NSW, Australia. Results are presented with the uncertainty of the downscaling process.
José Padarian and Alex B. McBratney
SOIL, 6, 89–94, https://doi.org/10.5194/soil-6-89-2020, https://doi.org/10.5194/soil-6-89-2020, 2020
Short summary
Short summary
Data sharing and collaboration are critical to solving large-scale problems. The prevailing soil data-sharing model is of a centralized nature and, consequently, results in the participants ceding control and governance over their data to the lead party. Here we explore the use of a distributed ledger (blockchain) to solve the aforementioned issues. We also describe the potential use case of developing a global soil spectral library between multiple, international institutions.
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 6, 35–52, https://doi.org/10.5194/soil-6-35-2020, https://doi.org/10.5194/soil-6-35-2020, 2020
Short summary
Short summary
The application of machine learning (ML) has shown an accelerated adoption in soil sciences. It is a difficult task to manually review all papers on the application of ML. This paper aims to provide a review of the application of ML aided by topic modelling in order to find patterns in a large collection of publications. The objective is to gain insight into the applications and to discuss research gaps. We found 12 main topics and that ML methods usually perform better than traditional ones.
Alexandre M. J.-C. Wadoux, José Padarian, and Budiman Minasny
SOIL, 5, 107–119, https://doi.org/10.5194/soil-5-107-2019, https://doi.org/10.5194/soil-5-107-2019, 2019
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 5, 79–89, https://doi.org/10.5194/soil-5-79-2019, https://doi.org/10.5194/soil-5-79-2019, 2019
Short summary
Short summary
Digital soil mapping has been widely used as a cost-effective method for generating soil maps. DSM models are usually calibrated using point observations and rarely incorporate contextual information of the landscape. Here, we use convolutional neural networks to incorporate spatial context. We used as input a 3-D stack of covariate images to simultaneously predict organic carbon content at multiple depths. In this study, our model reduced the error by 30 % compared with conventional techniques.
Edward J. Jones and Alex B. McBratney
SOIL Discuss., https://doi.org/10.5194/soil-2018-12, https://doi.org/10.5194/soil-2018-12, 2018
Revised manuscript has not been submitted
Short summary
Short summary
Variable soil moisture content is one of the main factors limiting field application of visible near-infrared spectroscopy. External parameter orthogonalisation of soil spectra was found to conserve intrinsic soil information under variable moisture conditions. k-means clustering of treated spectra yielded similar classifications under in situ, field moist (laboratory) and air-dried condition. Homogeneous spectral response zones were identified that corresponded with field observed horizons.
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 globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images
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
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.
Chengyong Fang, Xuanmei Fan, Xin Wang, Lorenzo Nava, Hao Zhong, Xiujun Dong, Jixiao Qi, and Filippo Catani
Earth Syst. Sci. Data, 16, 4817–4842, https://doi.org/10.5194/essd-16-4817-2024, https://doi.org/10.5194/essd-16-4817-2024, 2024
Short summary
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.
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.
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
Alhumimidi, M. S., Aboud, E., Alqahtani, F., Al-Battahien, A., Saud, R., Alqahtani, H. H., Aljuhani, N., Alyousif, M. M., and Alyousef, K. A.: Gamma-ray spectrometric survey for mineral exploration at Baljurashi area, Saudi Arabia, Journal of Radiation Research and Applied Sciences, 14, 82–90, https://doi.org/10.1080/16878507.2020.1856600, 2021.
Anderson, M. A., Bertsch, P. M., and Miller, W. P.: The distribution of lithium in selected soils and surface waters of the southeastern USA, Appl. Geochem., 3, 205–212, 1988.
Antezana Lopez, F. P., Zhou, G., Paye Vargas, L., Jing, G., Oscori Marca, M. E., Villalobos Quispe, M., Antonio Ticona, E., Mollericona Tonconi, N. M., and Orozco Apaza, E.: Lithium quantification based on random forest with multi-source geoinformation in Coipasa salt flats, Bolivia, Int. J. Appl. Earth Obs., 117, 103184, https://doi.org/10.1016/j.jag.2023.103184, 2023.
Aral, H. and Vecchio-Sadus, A.: Toxicity of lithium to humans and the environment – a literature review, Ecotoxicol. Environ. Safe., 70, 349–356, https://doi.org/10.1016/j.ecoenv.2008.02.026, 2008.
Bellon-Maurel, V., Fernandez-Ahumada, E., Palagos, B., Roger, J. M., and McBratney, A.: Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy, Trac-Trend. Anal. Chem., 29, 1073–1081, https://doi.org/10.1016/j.trac.2010.05.006, 2010.
Benedikt, S.: Using Tellus stream sediment geochemistry to fingerprint regional geology and mineralisation systems in Southeast Ireland, Irish J. Earth Sci., 36, 45–61, https://doi.org/10.3318/ijes.2018.36.45, 2018.
Benson, T. R., Coble, M. A., Rytuba, J. J., and Mahood, G. A.: Lithium enrichment in intracontinental rhyolite magmas leads to Li deposits in caldera basins, Nat. Commun., 8, 270, https://doi.org/10.1038/s41467-017-00234-y, 2017.
Bishop, T. F. A., McBratney, A. B., and Laslett, G. M.: Modelling soil attribute depth functions with equal-area quadratic smoothing splines, Geoderma, 91, 27–45, https://doi.org/10.1016/S0016-7061(99)00003-8, 1999.
Cardoso-Fernandes, J., Lima, A., and Teodoro, A.: Potential of Sentinel-2 data in the detection of Lithium (Li)-bearing pegmatites: a study case, SPIE Remote Sensing, Berlin, Germany, https://doi.org/10.1117/12.2326285, 2018.
Cardoso-Fernandes, J., Teodoro, A. C., and Lima, A.: Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites, Int. J. Appl. Earth Obs., 76, 10–25, https://doi.org/10.1016/j.jag.2018.11.001, 2019.
Cardoso-Fernandes, J., Teodoro, A. C., Lima, A., and Roda-Robles, E.: Semi-Automatization of Support Vector Machines to Map Lithium (Li) Bearing Pegmatites, Remote Sens.-Basel, 12, 2319, https://doi.org/10.3390/rs12142319, 2020.
Cardoso-Fernandes, J., Lima, J., Lima, A., Roda-Robles, E., Kohler, M., Schaefer, S., Barth, A., Knobloch, A., Goncalves, M. A., Goncalves, F., and Teodoro, A. C.: Stream sediment analysis for Lithium (Li) exploration in the Douro region (Portugal): A comparative study of the spatial interpolation and catchment basin approaches, J. Geochem. Explor., 236, 106978, https://doi.org/10.1016/j.gexplo.2022.106978, 2022.
Carranza, E. J. M.: Handbook of Exploration and Environmental Geochemistry, Elsevier Science B. V., 189–247, https://doi.org/10.1016/S1874-2734(09)70011-7, 2008.
Carranza, E. J. M.: Geocomputation of mineral exploration targets, Comput. Geosci., 37, 1907–1916, https://doi.org/10.1016/j.cageo.2011.11.009, 2011.
Champion, D.: Australian Resource Reviews: Lithium 2018, Geoscience Australia, Canberra [data set], https://doi.org/10.11636/9781925848281, 2019.
Crósta, A. P., De Souza Filho, C. R., Azevedo, F., and Brodie, C.: Targeting key alteration minerals in epithermal deposits in Patagonia, Argentina, using ASTER imagery and principal component analysis, Int. J. Remote Sens., 24, 4233–4240, https://doi.org/10.1080/0143116031000152291, 2010.
de Caritat, P.: The National Geochemical Survey of Australia: review and impact, Geochemistry: Exploration, Environment, Analysis, 22, https://doi.org/10.1144/geochem2022-032, 2022.
de Caritat, P. and Cooper, M.: National Geochemical Survey of Australia: Data Quality Assessment, Record 2011/021, https://pid.geoscience.gov.au/dataset/ga/71971 (last access: 11 January 2023), 2011a.
de Caritat, P. and Cooper, M.: National Geochemical Survey of Australia: The Geochemical Atlas of Australia. Record 2011/020, Geoscience Australia [data set], https://doi.org/10.11636/Record.2011.020, 2011b.
de Caritat, P. and Cooper, M.: A continental-scale geochemical atlas for resource exploration and environmental management: the National Geochemical Survey of Australia, Geochem.-Explor. Env. A., 16, 3–13, https://doi.org/10.1144/geochem2014-322, 2015.
de Caritat, P. and Reimann, C.: Comparing results from two continental geochemical surveys to world soil composition and deriving Predicted Empirical Global Soil (PEGS2) reference values, Earth Planet. Sc. Lett., 319–320, 269–276, https://doi.org/10.1016/j.epsl.2011.12.033, 2012.
de Caritat, P. and Troitzsch, U.: Towards a Regolith Mineralogy Map of the Australian Continent – A Feasibility Study in the Darling-Curnamona-Delamerian Region. Record 2021/35, https://doi.org/10.11636/Record.2021.035, 2021.
de Caritat, P., Cooper, M., Lech, M., McPherson, A., and Thun, C.: National Geochemical Survey of Australia: Sample Preparation Manual, Record 2009/08, http://pid.geoscience.gov.au/dataset/ga/68657 (last access: 11 January 2023), 2009.
de Caritat, P., Cooper, M., Pappas, W., Thun, C., and Webber, E.: National Geochemical Survey of Australia: Analytical Methods Manual, Record 2010/15, http://pid.geoscience.gov.au/dataset/ga/70369 (last access: 11 January 2023), 2010.
de Caritat, P., Bastrakov, E., Walker, A. T., and McInnes, B. I. A.: The Heavy Mineral Map of Australia Project. Data Release 2. The Barkly Isa Georgetown Region, https://doi.org/10.11636/Record.2022.043, 2022a.
de Caritat, P., McInnes, B., Walker, A., Bastrakov, E., Rowins, S., and Prent, A.: The Heavy Mineral Map of Australia: Vision and Pilot Project, 12, 961, https://doi.org/10.3390/min12080961, 2022b.
de Caritat, P., Walker, A. T., Bastrakov, E., and McInnes, B. I. A.: The Heavy Mineral Map of Australia Project – Data Release 1: The Darling-Curnamona-Delamerian Region, https://doi.org/10.11636/Record.2022.031, 2022c.
de Vos, W., Tarvainen, T., Salminen, R., Reeder, S., Vivo, B. D., Demetriades, A., Pirc, S., Batista, M. J., Marsina, K., Ottesen, R. T., O'Connor, P., Bidovec, M., Lima, A., Siewers, U., Smith, B., Taylor, H., Shaw, R., Salpeteur, I., Gregorauskienė, V., Halamić, J., Slaninka, I., Lax, K., Gravesen, P., Birke, M., Breward, N., Ander, E. L., Jordan, G., Ďuriš, M., Klein, P., Locutura, J., Bel-lan, A., Pasieczna, A., Lis, J., Mazreku, A., Gilucis, A., Heitzmann, P., Klaver, G. T., and Petersell, V.: Geochemical atlas of Europe. Part 2, Interpretation of geochemical maps, additional tables, figures, maps, and related publications, ISBN 951-690-960-4, 2006.
Dickson, B. L. and Scott, K. M.: Interpretation of aerial gamma-ray surveys – adding the geochemical factors, AGSO Journal of Australian Geology and Geophysics, 17, 187–200, 1997.
Dickson, B. L., Fraser, S. J., and Kinsey-Henderson, A.: Interpreting aerial gamma-ray surveys utilising geomorphological and weathering models, J. Geochem. Explor., 57, 75–88, https://doi.org/10.1016/S0375-6742(96)00017-9, 1996.
Ducart, D. F., Silva, A. M., Toledo, C. L. B., and de Assis, L. M.: Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajas Mineral Province, Brazil, Braz. J. Geol., 46, 331–349, https://doi.org/10.1590/2317-4889201620160023, 2016.
ESRI: ArcGIS Desktop: Release 10.8, Environmental Systems Research Institute, https://www.esri.com/ (last access: 15 March 2022), 2019.
Gallant, J. and Austin, J.: Slope derived from 1′′ SRTM DEM-S. v4, CSIRO [data set], https://doi.org/10.4225/08/5689DA774564A, 2012a.
Gallant, J. and Austin, J.: Topographic Wetness Index derived from 1′′ SRTM DEM-H. v2, CSIRO [data set], https://doi.org/10.4225/08/57590B59A4A08, 2012b.
Gallant, J., Wilson, N., Dowling, T., Read, A., and Inskeep, C.: SRTM-derived 1 Second Digital Elevation Models Version 1.0. Record 1, Geoscience Australia, https://pid.geoscience.gov.au/dataset/ga/72759 (last access: 11 January 2023), 2011.
Gluyas, A.: Explorer makes significant Lithium discovery in North Queensland,
https://www.australianmining.com.au/news/
explorer-makes-significant-lithium-discovery-in-north-queensland/
(last access: 14 March 2022), 2019.
Gopp, N. V., Savenkov, O. A., Nechaeva, T. V., and Smirnova, N. V.: The Use of NDVI in Digital Mapping of the Content of Available Lithium in the Arable Horizon of Soils in Southwestern Siberia, Izv. Atmos. Ocean. Phys+., 54, 1152–1157, https://doi.org/10.1134/S0001433818090165, 2018.
Graedel, T. E., Barr, R., Chandler, C., Chase, T., Choi, J., Christoffersen, L., Friedlander, E., Henly, C., Jun, C., Nassar, N. T., Schechner, D., Warren, S., Yang, M. Y., and Zhu, C.: Methodology of metal criticality determination, Environ. Sci. Technol., 46, 1063–1070, https://doi.org/10.1021/es203534z, 2012.
Grosjean, C., Miranda, P. H., Perrin, M., and Poggi, P.: Assessment of world lithium resources and consequences of their geographic distribution on the expected development of the electric vehicle industry, Renew. Sust. Energ. Rev., 16, 1735–1744, https://doi.org/10.1016/j.rser.2011.11.023, 2012.
Harris, J. R., Ayer, J., Naghizadeh, M., Smith, R., Snyder, D., Behnia, P., Parsa, M., Sherlock, R., and Trivedi, M.: A study of faults in the Superior province of Ontario and Quebec using the random forest machine learning algorithm: Spatial relationship to gold mines, Ore Geol. Rev., 157, 105403, https://doi.org/10.1016/j.oregeorev.2023.105403, 2023.
Harwood, T.: 9 s climatology for continental Australia 1976–2005: BIOCLIM variable suite. v1, Data Access Portal [data set], https://doi.org/10.25919/5dce30cad79a8, 2019.
Hijmans, R. J.: raster: Geographic Data Analysis and Modeling, R package version 3.5-2, CRAN [code], https://CRAN.R-project.org/package=raster (last access: 8 December 2022), 2021.
Hughes, A.: Australian Operating Mines Map 2019, Geoscience Australia, Canberra [data set], http://pid.geoscience.gov.au/dataset/ga/133033 (last access: 11 January 2023), 2020.
Isbell, R.: Australian Soil Classification, CSIRO Publishing, Melbourne, Victoria, 192 pp., https://doi.org/10.1071/9781486314782, 2021.
Jaireth, S., Bastrakov, E. N., Wilford, J., English, P., Magee, J., Clarke, J., de Caritat, P., Mernagh, T. P., McPherson, A., and Thomas, M.: Map of Salt Lake Systems Prospective for Lithium Deposits, Geoscience Australia, Canberra, http://pid.geoscience.gov.au/dataset/ga/75878 (last access: 11 January 2023), 2013.
Jenny, H.: Factors of Soil Formation: A System of Quantitative Pedology, McGraw-Hill, New York, NY, ISBN 0486681289, 1941.
Johnson, A. K.: Regolith and associated mineral systems of the Eucla Basin, South Australia, Department of Geology and Geophysics, Adelaide University, https://hdl.handle.net/2440/95312 (last access: 8 May 2022), 2015.
Jooshaki, M., Nad, A., and Michaux, S.: A Systematic Review on the Application of Machine Learning in Exploiting Mineralogical Data in Mining and Mineral Industry, Minerals, 11, 816, https://doi.org/10.3390/min11080816, 2021.
Kabata-Pendias, A.: Biogeochemistry of Lithium, Proc. Int. Symp. Lithium in the Trophic Chain Soil-Plant-Animal-Man, 13–14 September 1995, Warsaw, 9–15, 1995.
Kabata-Pendias, A.: Trace elements in soils and plants, 4th edn., CRC press, ISBN 042919112X, 2010.
Kashin, V. K.: Lithium in Soils and Plants of Western Transbaikalia, Eurasian Soil Sci+., 52, 359–369, https://doi.org/10.1134/S1064229319040094, 2019.
Khorram, S., Koch, F. H., van der Wiele, C. F., and Nelson, S. A. C.: Remote Sensing, Springer, New York, ISBN 9781461431039, 2012.
Köhler, M., Hanelli, D., Schaefer, S., Barth, A., Knobloch, A., Hielscher, P., Cardoso-Fernandes, J., Lima, A., and Teodoro, A. C.: Lithium Potential Mapping Using Artificial Neural Networks: A Case Study from Central Portugal, Minerals-Basel, 11, 1046, https://doi.org/10.3390/min11101046, 2021.
Kuhn, M.: Classification and Regression Training, R package version 6.0-93, https://CRAN.R-project.org/package=caret (last access: 8 December 2022), 2022.
Kuhn, M. and Quinlan, R.: Cubist: Rule- And Instance-Based Regression
Modeling, R package version 0.3.0, https://CRAN.R-project.org/package=Cubist, (last access: 8 December 2022), 2021.
Lau, I., Bateman, R., Beattie, E., de Caritat, P., Thomas, M., Ong, C., Laukamp, C., Caccetta, M., Wang, R., and Cudahy, T.: National Geochemical Survey of Australia reflectance spectroscopy measurements. v4, CSIRO, Data Collection, https://doi.org/10.25919/5cdba18939c29, 2016.
Lin, L. I.: A concordance correlation coefficient to evaluate reproducibility, Biometrics, 45, 255–268, https://doi.org/10.2307/2532051, 1989.
Liu, H., Wang, X., Zhang, B., Wang, W., Han, Z., Chi, Q., Zhou, J., Nie, L., Xu, S., Yao, W., Liu, D., Liu, Q., and Liu, J.: Concentration and distribution of lithium in catchment sediments of China: Conclusions from the China Geochemical Baselines project, J. Geochem. Explor., 215, 106540, https://doi.org/10.1016/j.gexplo.2020.106540, 2020.
London, D. and Burt, D. M.: Chemical-Models for Lithium Aluminosilicate Stabilities in Pegmatites and Granites, Am. Mineral., 67, 494–509, 1982.
Luecke, W.: Soil Geochemistry above a Lithium Pegmatite Dyke at Aclare, Southeast Ireland, Irish J. Earth Sci., 6, 205–211, 1984.
Main, P. T. and Champion, D. C.: Levelling of multi-generational
and spatially isolated geochemical surveys, J. Geochem. Explor.,
240, 107028, https://doi.org/10.1016/j.gexplo.2022.107028, 2022.
Main, P. T., Bastrakov, E. N., Wygralak, A. S., and Khan, M.: Northern Australia Geochemical Survey: Data Release 2 – Total (coarse fraction), Aqua Regia (coarse and fine fraction), and Fire Assay (coarse and fine fraction) element contents, Geoscience Australia, Canberra [data set], https://doi.org/10.11636/Record.2019.002, 2019.
Malone, B. and Searle, R.: Updating the Australian digital soil texture mapping (Part 2), Soil Res., 59, 435–451, https://doi.org/10.1071/sr20284, 2021.
Malone, B. P., McBratney, A. B., Minasny, B., and Laslett, G. M.: Mapping continuous depth functions of soil carbon storage and available water capacity, Geoderma, 154, 138–152, https://doi.org/10.1016/j.geoderma.2009.10.007, 2009.
McBratney, A. B., Santos, M. L. M., and Minasny, B.: On digital soil mapping, Geoderma, 117, 3–52, https://doi.org/10.1016/S0016-7061(03)00223-4, 2003.
Merian, E. and Clarkson, T. W.: Metals and their compounds in the
environment, VCH, Weinheim, ISBN 0895735628, 1991.
Mernagh, T. P., Bastrakov, E. N., Clarke, J. D. A., de Caritat, P., English, P. M., Howard, F. J. F., Jaireth, S., Magee, J. W., McPherson, A. A., Roach, I. C., Schroder, I. F., Thomas, M., and Wilford, J. R.: A review of Australian salt lakes and assessment of their potential for strategic resources, Geoscience Australia, Canberra, http://pid.geoscience.gov.au/dataset/ga/76454 (last access: 11 January 2023), 2013.
Mernagh, T. P., Bastrakov, E. N., Jaireth, S., de Caritat, P., English, P. M., and Clarke, J. D. A.: A review of Australian salt lakes and associated mineral systems, Aust. J. Earth Sci., 63, 131–157, https://doi.org/10.1080/08120099.2016.1149517, 2016.
Mudd, G. M., Werner, T. T., Weng, Z.-H., Yellishetty, M., Yuan, Y., McAlpine, S. R. B., Skirrow, R., and Czarnota, K.: Critical Minerals in Australia: A Review of Opportunities and Research Needs, Record 2018/51, Geoscience Australia, Canberra [data set], https://doi.org/10.11636/Record.2018.051, 2018.
Négrel, P., Ladenberger, A., Reimann, C., Birke, M., Demetriades, A., and Sadeghi, M.: GEMAS: Geochemical background and mineral potential of emerging tech-critical elements in Europe revealed from low-sampling density geochemical mapping, Appl. Geochem., 111, 104425, https://doi.org/10.1016/j.apgeochem.2019.104425, 2019.
Ng, W., Minasny, B., McBratney, A., de Caritat, P., and Wilford, J.: Predicted aqua regia-extractable lithium concentration in Australia, Zenodo [data set], https://doi.org/10.5281/zenodo.7895482, 2023.
Porwal, A., Das, R. D., Chaudhary, B., Gonzalez-Alvarez, I., and Kreuzer, O.: Fuzzy inference systems for prospectivity modeling of mineral systems and a case-study for prospectivity mapping of surficial Uranium in Yeelirrie Area, Western Australia, Ore Geol. Rev., 71, 839–852, https://doi.org/10.1016/j.oregeorev.2014.10.016, 2015.
Poudjom Djomani, Y., Minty, B. R. S., Hutchens, M., and Lane, R. J. L.: Total Magnetic Intensity (TMI) Grid of Australia 2019 – seventh edition – 80 m cell size, Geoscience Australia, Canberra [data set], https://doi.org/10.26186/5e9cf3f2c0f1d, 2019.
Pour, A. B. and Hashim, M.: Hydrothermal alteration mapping from Landsat-8 data, Sar Cheshmeh copper mining district, south-eastern Islamic Republic of Iran, Journal of Taibah University for Science, 9, 155–166, https://doi.org/10.1016/j.jtusci.2014.11.008, 2015.
Quinlan, J. R.: C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers Inc., San Mateo, California, ISBN 9781558602380, 1993.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, https://www.R-project.org (last access: 15 March 2022), 2021.
Reimann, C. and de Caritat, P.: Establishing geochemical background variation and threshold values for 59 elements in Australian surface soil, Sci. Total Environ., 578, 633–648, https://doi.org/10.1016/j.scitotenv.2016.11.010, 2017.
Reimann, C., Birke, M., Demetriades, A., Filzmoser, P., and O'Connor, P.: Chemistry of Europe's Agricultural Soils – Part A: methodology and interpretation of the GEMAS dataset, Schweizerbarth, Stuttgart, 9783510968466, 2014.
Roberts, D., Wilford, J., and Ghattas, O.: Exposed soil and mineral map of the Australian continent revealing the land at its barest, Nat. Commun., 10, 5297, https://doi.org/10.1038/s41467-019-13276-1, 2019.
Robinson, B. H., Yalamanchali, R., Reiser, R., and Dickinson, N. M.: Lithium as an emerging environmental contaminant: Mobility in the soil-plant system, Chemosphere, 197, 1–6, https://doi.org/10.1016/j.chemosphere.2018.01.012, 2018.
Roshanravan, B., Kreuzer, O. P., Buckingham, A., Keykhay-Hosseinpoor, M., and Keys, E.: Mineral potential modelling of orogenic gold systems in the granites-tanami Orogen, Northern Territory, Australia: A multi-technique approach, Ore Geol. Rev., 152, 105224, https://doi.org/10.1016/j.oregeorev.2022.105224, 2023.
Salminen, R., Batista, M. J., Bidovec, M., Demetriades, A., Vivo, B. D., Vos, W. D., Ďuriš, M., Gilucis, A., Gregorauskienë, V., Halamiă, J., Heitzmann, P., Lima, A., Jordan, G., Klaver, G., Klein, P., Lis, J. z., Locutura, J., Marsina, K., Mazreku, A., O'Connor, P., Olsson, S. Å., Ottesen, R. T., Petersell, V., Plant, J. A., Reeder, S., Salpeteur, I., Sandström, H., Siewers, U., Steenfelt, A., and Tarvainen, T.: Geochemical Atlas of Europe. Part 1 – Background information, methodology and maps, ISBN 9516909132, 2006.
Searle, R.: Australian Soil Classification Map. Version 1.0.0, Terrestrial Ecosystem Research Network [data set], https://doi.org/10.25901/edyr-wg85, 2021.
Senior, A., Britt, A. F., Summerfield, D., Hughes, A., Hitchman, A., Cross, A., Sexton, M., Pheeney, J., Teh, M., Hill, J., and Cooper, M.: Australia's Identified Mineral Resources 2021, Geoscience Australia, Canberra, https://doi.org/10.11636/1327-1466.2021, 2022.
Sitando, O. and Crouse, P. L.: Processing of a Zimbabwean petalite to obtain lithium carbonate, Int. J. Miner. Process., 102, 45–50, https://doi.org/10.1016/j.minpro.2011.09.014, 2012.
Smith, D. B., Solano, F., Woodruff, L. G., Cannon, W. F., and Ellefsen, K. J.: Geochemical and mineralogical maps, with interpretation, for soils of the conterminous United States, Reston, VA, Report 2017–5118, https://doi.org/10.3133/sir20175118, 2019.
SSSA: Soil Science Society of America Glossary, https://www.soils.org/publications/soils-glossary, last access: 7 September 2022.
Starkey, H. C.: The Role of Clays in Fixing Lithium, Report 1278F, https://doi.org/10.3133/b1278F, 1982.
Teng, F. Z., McDonough, W. F., Rudnick, R. L., Dalpe, C., Tomascak, P. B., Chappell, B. W., and Gao, S.: Lithium isotopic composition and concentration of the upper continental crust, Geochim. Cosmochim. Ac., 68, 4167–4178, https://doi.org/10.1016/j.gca.2004.03.031, 2004.
TERN: TERN Landscape Covariates 90m, Terrestrial Ecosystem
Research Network [data set], https://esoil.io/TERNLandscapes/Public/Products/TERN/Covariates/Mosaics/90m/ (last access: 10 March 2022), 2019.
Vieceli, N., Nogueira, C. A., Pereira, M. F. C., Durão, F. O., Guimarães, C., and Margarido, F.: Recovery of lithium carbonate by acid digestion and hydrometallurgical processing from mechanically activated lepidolite, Hydrometallurgy, 175, 1–10, https://doi.org/10.1016/j.hydromet.2017.10.022, 2018.
Wilford, J.: A weathering intensity index for the Australian continent using airborne gamma-ray spectrometry and digital terrain analysis, Geoderma, 183, 124–142, https://doi.org/10.1016/j.geoderma.2010.12.022, 2012.
Wilford, J. and Roberts, D.: Landsat 30+ Barest Earth, Geoscience Australia, Canberra [data set], http://pid.geoscience.gov.au/dataset/ga/131897 (last access: 11 January 2023), 2019.
Wilford, J., Worrall, L., and Minty, B.: Radiometric map of Australia provides new insights into uranium prospectivity, Ausgeo News, 95, 1–4, 2009.
Wilford, J., de Caritat, P., and Bui, E.: Modelling the abundance of soil calcium carbonate across Australia using geochemical survey data and environmental predictors, Geoderma, 259, 81–92, https://doi.org/10.1016/j.geoderma.2015.05.003, 2015.
Wilford, J. R. and Kroll, A.: Complete Radiometric Grid of Australia (Radmap) v4 2019 with modelled infill, Geoscience Australia, Canberra [data set], http://pid.geoscience.gov.au/dataset/ga/144413 (last access: 11 January 2023), 2020.
Wilford, J. R., Bierwirth, P. N., and Craig, M. A.: Application of airborne gamma-ray spectrometry in soil/regolith mapping and applied geomorphology, AGSO Journal of Australian Geology and Geophysics, 17, 201–216, 1997.
Wilson, J. and Gallant, J.: Primary topographic attributes, in: Terrain Analysis: Principles and Applications, edited by: Wilson, J. P., and Gallant, J. C., John Wiley & Sons, 51–85, ISBN 0471321885, 2000.
Zuo, R. G.: Geodata Science-Based Mineral Prospectivity Mapping: A Review, Natural Resour. Res., 29, 3415–3424, https://doi.org/10.1007/s11053-020-09700-9, 2020.
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.
With a higher demand for lithium (Li), a better understanding of its concentration and spatial...
Altmetrics
Final-revised paper
Preprint