CliMA
Datasets
This issue page is meant for contributing new datasets and documenting existing datasets, for the bibtex information, please visit https://clima.github.io/GriddingMachine.jl/stable/API/#Collector.
Change logs
- Add uncertainty (filled with NaN)
- Make the map to global scale (fill with NaN)
- Reformatted from GeoTIFF or binary to NetCDF
- Latitude and Longitude re-oriented to from South to North and from West to East
- Data scaling removed (from log(x), exp(x), or kx+b to x)
- Data regridded to coarser resolution by averaging all data falling into the new grid
- Unit standardization
- Reorder the dimensions to (lon, lat, ind)
- Unrealistic values to NaN
The datasets that are not supposed to be updated:
| Dataset type | LABEL | EXTRALABEL | IX | JT | YEAR | VK | Reference | Change logs |
|---|---|---|---|---|---|---|---|---|
| Biomass | BIOMASS | ROOT | 120X | 1Y | - | V1 | Huang et al. (2021) | 1,2 |
| BIOMASS | SHOOT | 120X | 1Y | - | V2 | Santoro et al. (2021) | 1,2 | |
| Canopy height | CH | - | 20X | 1Y | - | V1 | Simrad et al. (2021) | 1 |
| CH | - | 2X | 2Y | - | V2 | Boonman et al. (2020) | 1,3,4,5 | |
| Clumping Index | CI | - | 240X | 1Y | - | V1 | He et al. (2012) | 1,3,4 |
| CI | - | 2X | 1Y | - | V1 | He et al. (2012) | 1,3,4,6 | |
| CI | - | 2X | 1Y | - | V2 | Braghiere et al. (2019) | 1 | |
| CI | - | 20X | 1M | - | V3 | Wei et al. (2019) | 1,3,4 | |
| CI | - | 2X | 1M | - | V3 | Wei et al. (2019) | 1,3,4,6 | |
| Elevation | ELEV | - | 4X | 1Y | - | V1 | Yamazaki et al. (2017) | 1,4 |
| Land mask | LM | - | 4X | 1Y | - | V1 | ERA5 | 1 |
| Leaf nitrogen content | LNC | - | 2X | 1Y | - | V1 | Butler et al. (2017) | |
| LNC | - | 2X | 1Y | - | V2 | Boonman et al. (2020) | 1,3,4,5 | |
| Leaf phosphorus content | LPC | - | 2X | 1Y | - | V1 | Butler et al. (2017) | |
| Plant functional type | PFT | - | 2X | 1Y | - | V1 | Lawrence and Chase (2007) | 1,4,7 |
| Solar induced luminescence | SIL | - | 20X | 1Y | - | V1 | Köhler et al. (2021) | 1,3,4 |
| Specific leaf area | SLA | - | 2X | 1Y | - | V1 | Butler et al. (2017) | |
| SLA | - | 2X | 1Y | - | V2 | Boonman et al. (2020) | 1,3,4,5 | |
| Soil color | SC | - | 2X | 1Y | - | V1 | Lawrence and Chase (2007) | 1,4,6 |
| Soil hydraulic parameters | SOIL | SWCR | 12X | 1Y | - | V1 | Dai et al. (2019) | 1,3,6 |
| SOIL | SWCR | 120X | 1Y | - | V1 | Dai et al. (2019) | 1,3 | |
| SOIL | SWCS | 12X | 1Y | - | V1 | Dai et al. (2019) | 1,3,6 | |
| SOIL | SWCS | 120X | 1Y | - | V1 | Dai et al. (2019) | 1,3 | |
| SOIL | VGA | 12X | 1Y | - | V1 | Dai et al. (2019) | 1,3,6 | |
| SOIL | VGA | 120X | 1Y | - | V1 | Dai et al. (2019) | 1,3 | |
| SOIL | VGN | 12X | 1Y | - | V1 | Dai et al. (2019) | 1,3,5,6 | |
| SOIL | VGN | 120X | 1Y | - | V1 | Dai et al. (2019) | 1,3,5 | |
| SOIL | KSAT | 100X | 1Y | - | V2 | Gupta et al. (2021) | 1,2,3,4,5 | |
| Surface area | SA | - | 1X | 1Y | - | V1 | Lawrence and Chase (2007) | 1,4,6 |
| SA | - | 2X | 1Y | - | V1 | Lawrence and Chase (2007) | 1,4 | |
| Tree density | TD | - | 2X | 1Y | - | V1 | Crowther et al. (2017) | 1,3,4,6 |
| TD | - | 120X | 1Y | - | V1 | Crowther et al. (2017) | 1,3,4 | |
| Maximum carboxylation rate | VCMAX | - | 2X | 1Y | - | V1 | Smith et al. (2019) | 1,2,4 |
| VCMAX | - | 2X | 1Y | - | V2 | Luo et al. (2019) | 1,8 | |
| Wood density | WD | - | 2X | 1Y | - | V1 | Boonman et al. (2020) | 1,3,4,7 |
These datasets are supposed to be updated on annually basis:
| Dataset type | LABEL | EXTRALABEL | IX | JT | YEAR | VK | Reference | Change logs |
|---|---|---|---|---|---|---|---|---|
| Gross primary productivity | GPP | MPI_RS | 2X | 1M, 8D | 2001-2019 | V1 | Tramontana et al. (2016) | 4,9 |
| GPP | VPM | 5X, 12X | 8D | 2000-2019 | V2 | Zhang et al. (2017) | 1,4 | |
| Leaf area index | LAI | MODIS | 2X, 10X, 20X | 1M, 8D | 2000-2020 | V1 | Yuan et al. (2011) | 1,4,9 |
| Latent heat flux | LE | MPI_RS | 2X | 1M, 8D | 2001-2015 | V1 | Jung et al. (2019) | 4,9 |
| Solar induced chlorophyll fluorescence | SIF | TROPOMI_683, TROPOMI_683DC | 1X, 2X, 4X, 5X, 12X | 1M, 8D | 2018-2020 | V2 | Köhler et al. (2020) | 1,8 |
| SIF | TROPOMI_740, TROPOMI_740DC | 1X, 2X, 4X, 5X, 12X | 1M, 8D | 2018-2021 | V1 | Köhler et al. (2018) | 1,8 | |
| SIF | OCO2_757, OCO2_757DC, OCO2_771, OCO2_771DC | 5X | 1M | 2014-2020 | V3 | Sun et al. (2017) | 1,8 | |
| Vegetation cover fraction | VCF | MODIS_MOD44B | 2X | 1Y | 2000-2021 | V1 | DiMiceli et al. (2022 | 7,9 |
Example of contributing data via tagging an issue.
NOTICE: By submitting the issue, you authorize us to share your data to the public!
| Fields | Please fill in this form |
|---|---|
| Data URL | (A public url to download the data) |
| Publication DOI | (DOI to the publication) |
| Propsed TAG | (A unique tag for the data, e.g., VCMAX_1X_1Y_V3) |
| Description of the Data | (breifly describe the data so we know how to deal with it) |
@Yujie-W Thank you for these amazing datasets! Can you tell me if GriddingMachine also will have a global gridded forest cover fraction (FCF) dataset available soon (e.g., from MODIS)? Thank you!
@Yujie-W Thank you for these amazing datasets! Can you tell me if GriddingMachine also will have a global gridded forest cover fraction (FCF) dataset available soon (e.g., from MODIS)? Thank you!
Does this data work for you? If so, we can download and reprocess it to meet the requirements. It may take a few days. https://icdc.cen.uni-hamburg.de/thredds/catalog/ftpthredds/modis_vcf/global_0.5deg/catalog.html
That would be great, thanks Yujie!!
On Mon, Feb 6, 2023, 6:32 PM Yujie Wang @.***> wrote:
@Yujie-W https://github.com/Yujie-W Thank you for these amazing datasets! Can you tell me if GriddingMachine also will have a global gridded forest cover fraction (FCF) dataset available soon (e.g., from MODIS)? Thank you!
Does this data work for you? If so, we can download and reprocess it to meet the requirements. It may take a few days. https://icdc.cen.uni-hamburg.de/thredds/catalog/ftpthredds/modis_vcf/global_0.5deg/catalog.html
— Reply to this email directly, view it on GitHub https://github.com/CliMA/GriddingMachine.jl/issues/62#issuecomment-1419936579, or unsubscribe https://github.com/notifications/unsubscribe-auth/AGLFYNR3TC3LIO7FU7ZQ3Y3WWGCXLANCNFSM5GC37U7A . You are receiving this because you commented.Message ID: @.***>
@Yujie-W Hi, just checking in to see if/when the MODIS FCF dataset will be available from GriddingMachine. Thank you!
@Yujie-W Also, a suggestion. For your forest canopy height (CH) datasets, you could add the GEDI (Global Ecosystem Dynamics Investigation) LIDAR observations too. While GEDI itself is limited in expanse globally, there is some work from UMD that combines GEDI and Landsat ARD:
https://glad.earthengine.app/view/global-forest-canopy-height-2019 https://glad.umd.edu/dataset/gedi/ https://daac.ornl.gov/cgi-bin/dataset_lister.pl?p=40
P. Potapov, X. Li, A. Hernandez-Serna, A. Tyukavina, M.C. Hansen, A. Kommareddy, A. Pickens, S. Turubanova, H. Tang, C. E. Silva, J. Armston, R. Dubayah, J. B. Blair, M. Hofton (2020). https://doi.org/10.1016/j.rse.2020.112165
@Yujie-W Hi, just checking in to see if/when the MODIS FCF dataset will be available from GriddingMachine. Thank you!
You may find the data with the lasted version, see changes in #77
Thanks for the suggestions of the datasets, we will add the data in the next round after we finish a general template to process the data