Victor Maus | Publications

An open database on global coal and metal mine production

Jasansky, Simon, Lieber, Mirko, Giljum, Stefan, and Maus, Victor

Scientific Data 2023. 🔗 DOI Tweet

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While the extraction of natural resources has been well documented and analysed at the national level, production trends at the level of individual mines are more difficult to uncover, mainly due to poor availability of mining data with sub-national detail. In this paper, we contribute to filling this gap by presenting an open database on global coal and metal mine production on the level of individual mines. It is based on manually gathered information from more than 1900 freely available reports of mining companies, where every data point is linked to its source document, ensuring full transparency. The database covers 1171 individual mines and reports mine-level production for 80 different materials in the period 2000-2021. Furthermore, also data on mining coordinates, ownership, mineral reserves, mining waste, transportation of mining products, as well as mineral processing capacities (smelters and mineral refineries) and production is included.

An update on global mining land use

Maus, Victor, Giljum, Stefan, Silva, Dieison M., Gutschlhofer, Jakob, Rosa, Robson P., Luckeneder, Sebastian, Gass, Sidnei L. B., Lieber, Mirko, and McCallum, Ian

Scientific Data 2022. 📎 🔗 DOI Tweet

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The growing demand for minerals has pushed mining activities into new areas increasingly affecting biodiversity-rich natural biomes. Mapping the land use of the global mining sector is, therefore, a prerequisite for quantifying, understanding and mitigating adverse impacts caused by mineral extraction. This paper updates our previous work mapping mining sites worldwide. Using visual interpretation of Sentinel-2 images for 2019, we inspected more than 34,000 mining locations across the globe. The result is a global-scale dataset containing 44,929 polygon features covering 101,583 km2 of large-scale as well as artisanal and small-scale mining. The increase in coverage is substantial compared to the first version of the dataset, which included 21,060 polygons extending over 57,277 km2. The polygons cover open cuts, tailings dams, waste rock dumps, water ponds, processing plants, and other ground features related to the mining activities. The dataset is available for download from https://doi.org/10.1594/PANGAEA.942325and visualisation at www.fineprint.global/viewer.
A pantropical assessment of deforestation caused by industrial mining

Giljum, Stefan, Maus, Victor, Kuschnig, Nikolas, Luckeneder, Sebastian, Tost, Michael, Sonter, Laura J., and Bebbington, Anthony J.

PNAS 2022. DOI Tweet

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Growing demand for minerals continues to drive deforestation worldwide. Tropical forests are particularly vulnerable to the environmental impacts of mining and mineral processing. Many local- to regional-scale studies document extensive, long-lasting impacts of mining on biodiversity and ecosystem services. However, the full scope of deforestation induced by industrial mining across the tropics is yet unknown. Here, we present a biome-wide assessment to show where industrial mine expansion has caused the most deforestation from 2000 to 2019. We find that 3,264 km2 of forest was directly lost due to industrial mining, with 80% occurring in only four countries: Indonesia, Brazil, Ghana, and Suriname. Additionally, controlling for other nonmining determinants of deforestation, we find that mining caused indirect forest loss in two-thirds of the investigated countries. Our results illustrate significant yet unevenly distributed and often unmanaged impacts on these biodiverse ecosystems. Impact assessments and mitigation plans of industrial mining activities must address direct and indirect impacts to support conservation of the world’s tropical forests.

Surge in global metal mining threatens vulnerable ecosystems

Luckeneder, Sebastian, Giljum, Stefan, Schaffartzik, Anke, Maus, Victor, and Tost, Michael

Global Environmental Change 2021. 📎 🔗 DOI Tweet

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Mining activities induce profound changes to societies and the environment they inhabit. With global extraction of metal ores doubling over the past two decades, pressures related to mining have dramatically increased. In this paper, we explore where growing global metal extraction has particularly taken effect. Using fine-grain data, we investigate the spatial and temporal distribution of mining of nine metal ores (bauxite, copper, gold, iron, lead, manganese, nickel, silver and zinc) across approximately 3,000 sites of extraction worldwide between 2000 and 2019. To approach the related environmental implications, we intersect mining sites with terrestrial biomes, protected areas, and watersheds categorised by water availability. We find that 79% of global metal ore extraction in 2019 originated from five of the six most species-rich biomes, with mining volumes doubling since 2000 in tropical moist forest ecosystems. We also find that half of global metal ore extraction took place at 20 km or less from protected territories. Further, 90% of all considered extraction sites correspond to below-average relative water availability, with particularly copper and gold mining occurring in areas with significant water scarcity. Our study has far-reaching implications for future global and local policy and resource management responses to mitigate the negative effects of the expected expansion of metal mining.

A global-scale data set of mining areas

Maus, Victor, Giljum, Stefan, Gutschlhofer, Jakob, Silva, Dieison M., Gass, Sidnei L.B., Luckeneder, Sebastian, Lieber, Mirko, and McCallum, Ian

Scientific Data 2020. 📎 🔗 DOI Tweet

FABIO–The Construction of the Food and Agriculture Biomass Input-Output Model

Bruckner, Martin, Wood, Richard, Moran, Daniel, Kuschnig, Nikolas, Wieland, Hanspeter, Maus, Victor, and Börner, Jan

Environmental Science & Technology 2019. 📎 DOI Tweet
Sensitivity of global pasturelands to climate variation

Stanimirova, Radost, Arévalo, Paulo, Kaufmann, Robert K., Maus, Victor, Lesiv, Myroslava, Havlík, Petr, and Friedl, Mark A.

Earth’s Future 2019. 📎 DOI Tweet
dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R

Maus, Victor, Câmara, Gilberto, Appel, Marius, and Pebesma, Edzer

Journal of Statistical Software 2019. 📎 🔗 DOI Tweet
Quantifying the global cropland footprint of the European Union’s non-food bioeconomy

Bruckner, Martin, Häyhä, Tiina, Giljum, Stefan, Maus, Victor, Fischer, Günther, Tramberend, Sylvia, and Börner, Jan

Environmental Research Letters 2019. 📎 🔗 DOI Tweet

Monitoring Deforestation in Rainforests Using Satellite Data: A Pilot Study from Kalimantan, Indonesia

Hadi, , Krasovskii, Andrey, Maus, Victor, Yowargana, Ping, Pietsch, Stephan, and Rautiainen, Miina

Forests 2018. 📎 🔗 DOI Tweet

LACO-Wiki: A New Online Land Cover Validation Tool Demonstrated Using GlobeLand30 for Kenya

See, Linda, Laso Bayas, Juan Carlos, Schepaschenko, Dmitry, Perger, Christoph, Dresel, Christopher, Maus, Victor, Salk, Carl, Weichselbaum, Juergen, Lesiv, Myroslava, McCallum, Ian, Moorthy, Inian, and Fritz, Steffen

Remote Sensing 2017. 📎 🔗 DOI Tweet
Production of docosahexaenoic acid by Aurantiochytrium sp. ATCC PRA-276

Furlan, Valcenir Júnior Mendes, Maus, Victor, Batista, Irineu, and Bandarra, Narcisa Maria

Brazilian Journal of Microbiology 2017. 📎 🔗 DOI Tweet

A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping

Maus, Victor, Camara, Gilberto, Cartaxo, Ricardo, Sanchez, Alber, Ramos, Fernando M., and Queiroz, Gilberto R.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2016. 📎 🔗 DOI Tweet
Production of docosahexaenoic acid (DHA) from Thraustochytrium sp. ATCC 26185 using different nitrogen concentrations

Furlan, Valcenir Júnior Mendes, Castelo Paulo, Maria, Maus, Victor, Ferreira, Júlia, Batista, Irineu, and Bandarrac, Narcisa Maria

Boletim Centro de Pesquisa de Processamento de Alimentos 2016. 📎 🔗 DOI Tweet

Building a hybrid land cover map with crowdsourcing and geographically weighted regression

See, Linda, Schepaschenko, Dmitry, Lesiv, Myroslava, McCallum, Ian, Fritz, Steffen, Comber, Alexis, Perger, Christoph, Schill, Christian, Zhao, Yuanyuan, Maus, Victor, Siraj, Muhammad Athar, Albrecht, Franziska, Cipriani, Anna, Vakolyuk, Maryana, Garcia, Alfredo, Rabia, Ahmed H., Singha, Kuleswar, Marcarini, Abel Alan, Kattenborn, Teja, Hazarika, Rubul, Schepaschenko, Maria, Velde, Marijn, Kraxner, Florian, and Obersteiner, Michael

ISPRS Journal of Photogrammetry and Remote Sensing 2015. 📎 🔗 DOI Tweet

Tratamento do lixiviado de aterro de resíduos sólidos urbanos por processo Fenton

Maus, Victor, Costa, Adilson Ben, and Righes, Afranio Almir

Tecno-lógica 2009. 📎 🔗 DOI Tweet

STILF - A spatiotemporal interval logic formalism for reasoning about events in remote sensing data

Maciel, Adeline Marinho, Vinhas, Lubia, Camara, Gilberto, Maus, Victor, and Assis, Luiz Fernando Ferreira Gomes

In Proceedings of the Brazilian Symposium of Remote Sensing 2017. 🔗 Tweet
Satellite Multisensor spatiotemporal analysis: a TWDTW preview approach

Olivera Simoes, Rolf Ezequiel, Pletsch, Mikhaela Aloisia Jessie Santos, Santos, Lorena Alves, Camara, Gilberto, and Maus, Victor

In Proceedings of the Brazilian Symposium of Remote Sensing 2017. 🔗 Tweet

Big data streaming for remote sensing time series analytics using MapReduce

Assis, Luiz Fernando, Ribeiro, Gilberto, Ferreira, Karine Reis, Vinhas, Lubia, Llapa, Eduardo, Sanchez, Alber, Maus, Victor, and Camara, Gilberto

In Proceedings of the Brazilian Symposium on Geoinformatics 2016. 🔗 Tweet
Big Earth Observation Data Analytics: Matching Requirements to System Architectures

Camara, Gilberto, Assis, Luiz Fernando, Ribeiro, Gilberto, Ferreira, Karine Reis, Llapa, Eduardo, Vinhas, Lubia, Maus, Victor, Sanchez, Alber, and Souza, Ricardo Cartaxo

In Proceedings of the 5th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data 2016. DOI Tweet
Using dynamic geospatial ontologies to support information extraction from big Earth observation data sets

Maciel, Adeline Marinho, Camara, Gilberto, Maus, Victor, Vinhas, Lubia, and Sanchez, Alber

In International Conference on GIScience 2016. 📎 DOI Tweet

Open boundary dynamic time warping for satellite image time series classification

Maus, Victor, Camara, Gilberto, Cartaxo, Ricardo, Ramos, Fernando Manuel, Sanchez, Alber, and Ribeiro, Gilberto

In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015. 🔗 DOI Tweet

Contaminant transport in porous media under biodegradation and non-equilibrium sorption reactions

Maus, Victor, Toledo, Elson Magalhães, and Silva Barra, Luis Paulo

In Proceedings of the Iberian Latin American Congress on Computational Methods in Engineering 2011. 🔗 Tweet

Open database on global coal and metal mine production

Jasansky, Simon, Lieber, Mirko, Giljum, Stefan, and Maus, Victor

2023. DOI Tweet

dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis

Maus, Victor

2022. 🔗 Tweet
Global-scale mining polygons (Version 2)

Maus, Victor, Silva, Dieison M., Gutschlhofer, Jakob, Rosa, Robson, Giljum, Stefan, Gass, Sidnei L.B., Luckeneder, Sebastian, Lieber, Mirko, and McCallum, Ian

2022. DOI Tweet

Global-scale mining polygons (Version 1)

Maus, Victor, Giljum, Stefan, Gutschlhofer, Jakob, Silva, Dieison M., Gass, Sidnei L.B., Luckeneder, Sebastian, Lieber, Mirko, and McCallum, Ian

2020. DOI Tweet
Global 30 arc-seconds dataset for land-use modelling

Maus, Victor, Giljum, Stefan, Kuschnig, Nikolas, and Luckeneder, Sebastian

2020. DOI Tweet
Web application for mining area polygonization

Jakob, Gutschlhofer, and Maus, Victor

2020. DOI Tweet

SITS - Satellite Image Time Series Analysis

Simoes, Rolf, Camara, Gilberto, Maus, Victor, Carvalho, Alexandre, Andrade, Pedro, Queiroz, Gilberto, Sanchez, Alber, Assis, Luiz, Marinho, Adeline, and Santos, Lorena

2019. 🔗 Tweet

wtss: An R Client for a Web Time-Series Service

Maus, Victor, Andrade, Pedro, Sanchez, Alber, Assis, Luiz Fernando, Ribeiro, Gilberto, and Camara, Gilberto

2018. 🔗 Tweet

Copernicus Global Land Service: Land Cover 100m: version 3 Globe 2015-2019: Validation Report

Tsendbazar, Nandin-Erdene, Tarko, Agnieszka, Li, Linlin, Herold, Martin, Lesiv, Myroslava, Fritz, Steffen, and Maus, Victor

2021. 🔗 DOI Tweet

Land use and land cover monitoring using remote sensing image time series. PhD thesis

Maus, Victor

2016. Tweet

Satellite time series analysis for land use/cover change detection

Maus, Victor

2014. 🔗 Tweet

Guia Prático para formatação do TCC no LibreOffice Writer

Gudolle, Fabiane, Ogassawara, Jéssica, Bonorino, Liliane, and Maus, Victor

2013. 📎 Tweet
Elaboração de Certificados utilizando Mala Direta do LibreOffice

Santos, Graziela Carrazzoni, Marques, Leonardo Caires, Bonorino, Liliane, Epping, Nelson, and Maus, Victor

2013. 📎 Tweet

Computational modelling applied to contaminant transport in groundwater. MSc thesis

Maus, Victor

2011. Tweet

Treatment of leachate from municipal solid waste by Fenton process. BSc thesis

Maus, Victor

2009. Tweet

Using satellite earth observations to map global resource extraction and related environmental impacts: examples from agriculture and mining

Maus, Victor, and Giljum, Stefan

2020. 🔗 Tweet
Crafting mines from satellite images

Maus, Victor

2020. 🔗 Tweet

Europe’s expanding non-food bioeconomy is heavily dependent on foreign land areas

Bruckner, Martin, Häyhä, Tiina, Giljum, Stefan, \textbfMaus, Victor, Fischer, Günther, Tramberend, Sylvia, and Börner, Jan

2019. 🔗 Tweet
Independent confirmation of Brazil’s rapidly rising deforestation in 2019

Fritz, Steffen, Danylo, Olha, Maus, Victor, See, Linda, Hofhansl, Florian, McCallum, Ian, and Obersteiner, Michael

2019. 🔗 Tweet

Open science and reproducibility: The FINEPRINT infrastructure

Maus, Victor, Kuschnig, Nikolas, and Giljum, Stefan

2018. 🔗 Tweet

New open-source software supports land-cover monitoring

Maus, Victor

2017. 🔗 Tweet