You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This is the updated LCSPP dataset (v3.2), reconstructed using the MODIS record from 2001–2023. Previously referred to as "LCSIF," the dataset was renamed to emphasize its role as a SIF-informed long-term photosynthesis proxy derived from surface reflectance and to avoid confusion with directly measured SIF signals. The MODIS-based LCSPP is generated as an ancillary product to complement and benchmark the LCSPP-AVHRR product from 1982-2023.
Key updates in version 3.2 include:
Improved Calibration: Enhanced consistency in calibration methods, addressing technical limitations in version 3.1 including applying more stringent quality filtering and snow masks.
Quality Flags: New quality flag layer enables users to identify whether a pixel is derived from observed surface reflectance (QA=0), high-quality gap-filled values (QA=1), lower-quality gap-filled based on the mean seasonal cycle (QA=2), or missing entirely (QA=3). We advice the user to rely only on observed and high-quality gap-filled values for their analyses.
Extension to include observations from the year of 2023.
LCSPP-AVHRR repositories can be accessed via the following links:
LCSPP-AVHRR v3.2 (1982-2000): 10.5281/zenodo.7916850
LCSPP-AVHRR v3.2 (2001-2023): 10.5281/zenodo.11906675
The user can choose between LCSPP-AVHRR and LCSPP-MODIS for the overlapping period from 2001-2023. The two datasets are generally consistent during this overlapping period, although LCSPP-MODIS shows a stronger greening trend between 2001-2023. For studies exploring the long-term vegetation dynamics, the user can either use only LCSPP-AVHRR or use a blend dataset of LCSPP-AVHRR and LCSPP-MODIS as a sensitivity test.
In addition, the updated long-term continuous reflectance datasets (LCREF), used for the production of LCSPP, can be accessed using the following links:
LCREF-AVHRR v3.1 (1982-2023): 10.5281/zenodo.11905959
LCREF-MODIS v3.1 (2001-2023): 10.5281/zenodo.11657458
A manuscript describing the technical details is available at https://arxiv.org/abs/2311.14987, while detailed the uses and limitations of the dataset. In particular, we note that LCSPP is a reconstruction of SIF-informed photosynthesis proxy and should not be treated as SIF measurements. Although LCSPP has demonstrated skill in tracking the dynamics of GPP and PAR absorbed by canopy chlorophyll (APARchl), it is not suitable for estimating fluorescence quantum yield.
All data outputs from this study are available at 0.05° spatial resolution and biweekly temporal resolution in NetCDF format. Each month is divided into two files, with the first file “a” representative of the 1st day to the 15th day of a month, and the second file “b” representative of the 16th day to the last day of a month.
Size
35.3 GB in compress and bout 283 GB in uncompressed format
License
Creative Commons Attribution 4.0 International
Data Format
NetCDF
Data Format (other)
.tar and needs to be decompressed to .nc
Access protocol
HTTP(S)
Source File Organization
.tar and needs to be decompressed to .nc
The other information is included above. The dataset is developed by Jianing from Gentine Lab
Example URLs
Authorization
None
Transformation / Processing
No response
Target Format
Zarr
Comments
No response
The text was updated successfully, but these errors were encountered:
Dataset Name
LCSPP-AVHRR 2001–2023
Dataset URL
https://zenodo.org/records/14614329
Description
This is the updated LCSPP dataset (v3.2), reconstructed using the MODIS record from 2001–2023. Previously referred to as "LCSIF," the dataset was renamed to emphasize its role as a SIF-informed long-term photosynthesis proxy derived from surface reflectance and to avoid confusion with directly measured SIF signals. The MODIS-based LCSPP is generated as an ancillary product to complement and benchmark the LCSPP-AVHRR product from 1982-2023.
Key updates in version 3.2 include:
Improved Calibration: Enhanced consistency in calibration methods, addressing technical limitations in version 3.1 including applying more stringent quality filtering and snow masks.
Quality Flags: New quality flag layer enables users to identify whether a pixel is derived from observed surface reflectance (QA=0), high-quality gap-filled values (QA=1), lower-quality gap-filled based on the mean seasonal cycle (QA=2), or missing entirely (QA=3). We advice the user to rely only on observed and high-quality gap-filled values for their analyses.
Extension to include observations from the year of 2023.
LCSPP-AVHRR repositories can be accessed via the following links:
LCSPP-AVHRR v3.2 (1982-2000): 10.5281/zenodo.7916850
LCSPP-AVHRR v3.2 (2001-2023): 10.5281/zenodo.11906675
The user can choose between LCSPP-AVHRR and LCSPP-MODIS for the overlapping period from 2001-2023. The two datasets are generally consistent during this overlapping period, although LCSPP-MODIS shows a stronger greening trend between 2001-2023. For studies exploring the long-term vegetation dynamics, the user can either use only LCSPP-AVHRR or use a blend dataset of LCSPP-AVHRR and LCSPP-MODIS as a sensitivity test.
In addition, the updated long-term continuous reflectance datasets (LCREF), used for the production of LCSPP, can be accessed using the following links:
LCREF-AVHRR v3.1 (1982-2023): 10.5281/zenodo.11905959
LCREF-MODIS v3.1 (2001-2023): 10.5281/zenodo.11657458
A manuscript describing the technical details is available at https://arxiv.org/abs/2311.14987, while detailed the uses and limitations of the dataset. In particular, we note that LCSPP is a reconstruction of SIF-informed photosynthesis proxy and should not be treated as SIF measurements. Although LCSPP has demonstrated skill in tracking the dynamics of GPP and PAR absorbed by canopy chlorophyll (APARchl), it is not suitable for estimating fluorescence quantum yield.
All data outputs from this study are available at 0.05° spatial resolution and biweekly temporal resolution in NetCDF format. Each month is divided into two files, with the first file “a” representative of the 1st day to the 15th day of a month, and the second file “b” representative of the 16th day to the last day of a month.
Size
35.3 GB in compress and bout 283 GB in uncompressed format
License
Creative Commons Attribution 4.0 International
Data Format
NetCDF
Data Format (other)
.tar and needs to be decompressed to .nc
Access protocol
HTTP(S)
Source File Organization
.tar and needs to be decompressed to .nc
The other information is included above. The dataset is developed by Jianing from Gentine Lab
Example URLs
Authorization
None
Transformation / Processing
No response
Target Format
Zarr
Comments
No response
The text was updated successfully, but these errors were encountered: