8 Works

ISIMIP2a Simulation Data from the Regional Forests Sector

Mats Mahnken, Alessio Collalti, Daniela Dalmonech, Carlo Trotta, Volodymyr Trotsiuk, Andrey Lessa Derci Augustynczik, Rasoul Yousefpour, Martin Gutsch, David Cameron, Harald Bugmann, Nica Huber, Timothy Thrippleton, Friedrich Bohn, Daniel Nadal-Sala, Santiago Sabaté, Rüdiger Grote, Annikki Mäkelä, Francesco Minunno, Mikko Peltoniemi, Patrick Vallet, Marek Fabrika, Katarína Merganičová, Iliusi Vega del Valle, Jan Volkholz & Christopher Reyer
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a...

Full dataset

William Schueller, Johannes Wachs, Vito Servedio, Stefan Thurner & Vittorio Loreto
Dataset and replication materials for "Evolving Collaboration, Dependencies, and Use in the Rust Open Source Software Ecosystem" by Schueller, Wachs, Servedio, Thurner and Loreto.

Wildlife documentaries present a diverse, but biased, portrayal of the natural world

Kate Howlett, Ho-Yee Lee, Amelia Jaffé, Matthew Lewis & Edgar C. Turner
1. Wildlife-documentary production has expanded over recent decades, while studies report reduced direct contact with nature. The role of documentaries and other electronic content in educating people about biodiversity is therefore likely to be growing increasingly important. This study investigated whether the content of wildlife documentaries is an accurate reflection of the natural world and whether conservation messaging in documentaries has changed over time. 2. We sampled an online film database (n = 105) to...

A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia

Hadi Hadi, Ping Yowargana, Muhammad Thoha Zulkarnain, Fathir Mohamad, Bunga K. Goib, Hultera -, Tobias Sturn, Matthias Karner, Martina Duerauer, Linda See, Steffen Fritz, Adis Hendriatna, Afi Nursafingi, Dian Nuraini Melati, F.V. Astrolabe Sian Prasetya, Ita Carolita, Kiswanto -, Muhammad Iqbal Firdaus, Muhammad Rosidi & Florian Kraxner
This collection represents geographically diverse, temporally consistent, and nationally relevant land cover (LC) reference data collected by visual interpretation of very high spatial resolution imagery, in a national-scale crowdsourcing campaign (targeting seven generic LC classes) and a series of expert workshops (targeting seventeen detailed LC classes) in Indonesia. The interpreters were local citizen scientists (crowd/non-experts) and local LC visual interpretation experts from different regions in the country. This helps to ensure that the LC map...

Full dataset

William Schueller, Johannes Wachs, Vito Servedio, Stefan Thurner & Vittorio Loreto
Dataset and replication materials for "Evolving Collaboration, Dependencies, and Use in the Rust Open Source Software Ecosystem" by Schueller, Wachs, Servedio, Thurner and Loreto.

A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia

Hadi Hadi, Ping Yowargana, Muhammad Thoha Zulkarnain, Fathir Mohamad, Bunga K. Goib, Hultera -, Tobias Sturn, Matthias Karner, Martina Duerauer, Linda See, Steffen Fritz, Adis Hendriatna, Afi Nursafingi, Dian Nuraini Melati, F.V. Astrolabe Sian Prasetya, Ita Carolita, Kiswanto -, Muhammad Iqbal Firdaus, Muhammad Rosidi & Florian Kraxner
This collection represents geographically diverse, temporally consistent, and nationally relevant land cover (LC) reference data collected by visual interpretation of very high spatial resolution imagery, in a national-scale crowdsourcing campaign (targeting seven generic LC classes) and a series of expert workshops (targeting seventeen detailed LC classes) in Indonesia. The interpreters were local citizen scientists (crowd/non-experts) and local LC visual interpretation experts from different regions in the country. This helps to ensure that the LC map...

Sample Dataset

William Schueller, Johannes Wachs, Vito Servedio, Stefan Thurner & Vittorio Loreto
Sample data for testing and demonstration.

Sample Dataset

William Schueller, Johannes Wachs, Vito Servedio, Stefan Thurner & Vittorio Loreto
Sample data for testing and demonstration.

Registration Year

  • 2022
    8

Resource Types

  • Dataset
    8

Affiliations

  • International Institute for Applied Systems Analysis
    7
  • Santa Fe Institute
    4
  • Complexity Science Hub Vienna
    4
  • Medical University of Vienna
    4
  • Helmholtz Centre for Environmental Research
    1
  • Technical University in Zvolen
    1
  • Centre for Ecology & Hydrology
    1
  • University of Cambridge
    1
  • University of Barcelona
    1
  • University of Freiburg
    1