Data Visualization Project

July 14, 2022

Mission

The Data Visualization Project aims at contributing to research via Visual Analytics as well as to Scientific Communication / Dissemination by working closely with other Scientists and Research groups at the department, creating movies/animations, interactive apps and high quality images. Most projects are done with internal data products and some are external due to their social importance. This allow us to promote our research within the academic community as well as to the general public.

Precipitation and vapour pressure deficit

Latest entry: MPI Jena weather station.
Precipitation and vapour pressure deficit.

Here we see the cumulative values for measured rain and vapor pressure deficit. The colors represent the mean value for that specific month whereas the height shows the cumulative value. When viewed from the back we can see if a year was wet or dry.
Vapor pressure deficit represents how much more water vapor can be stored in the air column. Higher values (more red) correlate to an increase in evaporation. Thus, during red months and drier years, we’d expect drier soils.

Images and interactive apps

Videos / Animations

Large datasets on the DeepCube project. Showcasting operations on chuncks of data across different dimensions, i.e. time, space and in parallel.

DeepCube

Large datasets on the DeepCube project. Showcasting operations on chuncks of data across different dimensions, i.e. time, space and in parallel.
https://www.youtube.com/watch?v=5s86y8lkDtk
Didan, K. (2015). MOD13C1 MODIS/Terra Vegetation Indices 16-Day L3 Global 0.05Deg CMG V006 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MOD13C1.006<br /><br />Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2018): ERA5 hourly data on single levels from 1959 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). 10.24381/cds.adbb2d47&nbsp;

MODIS and ERA5 for global observations

Didan, K. (2015). MOD13C1 MODIS/Terra Vegetation Indices 16-Day L3 Global 0.05Deg CMG V006 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MOD13C1.006

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2018): ERA5 hourly data on single levels from 1959 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). 10.24381/cds.adbb2d47 
https://www.youtube.com/watch?v=pQ0x8spfJ2Q
Giglio, L., J. T. Randerson, and G. R. van der Werf (2013), Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4),&nbsp;J. Geophys. Res. Biogeosci.,&nbsp;118, 317&ndash;328.

Largest World Fires 

Giglio, L., J. T. Randerson, and G. R. van der Werf (2013), Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res. Biogeosci., 118, 317–328.
https://www.youtube.com/watch?v=qqk697RNh44
DeepCube Project

Sampled minicubes over Africa

DeepCube Project
https://www.youtube.com/watch?v=iwRy0_j4IYM
Global 30 Arc-Second Elevation (GTOPO30)&nbsp;Digital Object Identifier (DOI) number: /10.5066/F7DF6PQS<br /><br />Friedl, M., Sulla-Menashe, D. (2019). MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MCD12Q1.006

Topography and vegetation types

Global 30 Arc-Second Elevation (GTOPO30) Digital Object Identifier (DOI) number: /10.5066/F7DF6PQS

Friedl, M., Sulla-Menashe, D. (2019). MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MODIS/MCD12Q1.006
https://www.youtube.com/watch?v=D9SQEEuTSDE
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