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Tomislav Hengl

Showing results (1-10 of 29) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|August 23, 2017
Soil carbon debt of 12,000 years of human land useJonathan Sanderman, Tomislav Hengl, Gregory J Fiske
Journal of the American Mosquito Control Association|September 13, 2007
Spatiotemporal monitoring of floodwater mosquito dispersal in Osijek, CroatiaMirta Sudarić Bogojević, Tomislav Hengl, Enrih Merdić
Peerj|June 28, 2023
Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetationCarmelo Bonannella, Tomislav Hengl, Leandro Parente, et al.
Peerj|June 12, 2023
Ecodatacube.eu: analysis-ready open environmental data cube for EuropeMartijn Witjes, Leandro Parente, Josip Križan, et al.
Scientific Data|July 25, 2022
Global Soil Hydraulic Properties dataset based on legacy site observations and robust parameterizationSurya Gupta, Andreas Papritz, Peter Lehmann, et al.
Peerj|September 7, 2018
Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variablesTomislav Hengl, Madlene Nussbaum, Marvin N Wright, et al.
Peerj|August 30, 2018
Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potentialTomislav Hengl, Markus G Walsh, Jonathan Sanderman, et al.
Parasites & Vectors|January 24, 2025
Assessing tick attachments to humans with citizen science data: spatio-temporal mapping in Switzerland from 2015 to 2021 using spatialMaxentLisa Bald, Nils Ratnaweera, Tomislav Hengl, et al.
Peerj|August 1, 2022
Forest tree species distribution for Europe 2000-2020: mapping potential and realized distributions using spatiotemporal machine learningCarmelo Bonannella, Tomislav Hengl, Johannes Heisig, et al.
Peerj|December 9, 2024
A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial resolutionDavide Consoli, Leandro Parente, Rolf Simoes, et al.
Pageof 3

Showing results (1-10 of 29) with videos related to

Sort By:
Pageof 3
Proceedings of the National Academy of Sciences of the United States of America|August 23, 2017
Soil carbon debt of 12,000 years of human land useJonathan Sanderman, Tomislav Hengl, Gregory J Fiske
Journal of the American Mosquito Control Association|September 13, 2007
Spatiotemporal monitoring of floodwater mosquito dispersal in Osijek, CroatiaMirta Sudarić Bogojević, Tomislav Hengl, Enrih Merdić
Peerj|June 28, 2023
Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetationCarmelo Bonannella, Tomislav Hengl, Leandro Parente, et al.
Peerj|June 12, 2023
Ecodatacube.eu: analysis-ready open environmental data cube for EuropeMartijn Witjes, Leandro Parente, Josip Križan, et al.
Scientific Data|July 25, 2022
Global Soil Hydraulic Properties dataset based on legacy site observations and robust parameterizationSurya Gupta, Andreas Papritz, Peter Lehmann, et al.
Peerj|September 7, 2018
Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variablesTomislav Hengl, Madlene Nussbaum, Marvin N Wright, et al.
Peerj|August 30, 2018
Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potentialTomislav Hengl, Markus G Walsh, Jonathan Sanderman, et al.
Parasites & Vectors|January 24, 2025
Assessing tick attachments to humans with citizen science data: spatio-temporal mapping in Switzerland from 2015 to 2021 using spatialMaxentLisa Bald, Nils Ratnaweera, Tomislav Hengl, et al.
Peerj|August 1, 2022
Forest tree species distribution for Europe 2000-2020: mapping potential and realized distributions using spatiotemporal machine learningCarmelo Bonannella, Tomislav Hengl, Johannes Heisig, et al.
Peerj|December 9, 2024
A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial resolutionDavide Consoli, Leandro Parente, Rolf Simoes, et al.
Pageof 3