A global terrestrial ecosystem respiration dataset (2001-2010) estimated with MODIS land surface temperature and vegetation indices

ABSTRACT

This paper describes how a validated semi-empirical, but physiologically based, remote sensing model – Ensemble_all – was up-scaled using MODIS land surface temperature data (MOD11C2), enhanced vegetation indices (MOD13C1) and land-cover data (MCD12C1) to produce a global terrestrial ecosystem respiration data set (Reco) for January 2001–December 2010. The temporal resolution of this data set is 1 month, the spatial resolution is 0.05°, and the range is from 55°S to 65°N and 180°W to 180°E (crop and natural vegetation mosaic is not included). After cross-validating our data set using in-situ observations as well as Reco outputs from an empirical variable_Q10 model, a LPJ_S1 process model and a machine learning method model, we found that our data set performed well in detecting both temporal and spatial patterns in Reco’s simulation in most ecosystems across the world. This data set can be found at http://www.dx.doi.org/10.11922/sciencedb.934.

KEYWORDS:

• Terrestrial ecosystem respiration
• MODIS data product
• up-scaling
• remote sensing model

Acknowledgments

We are grateful for the freely available MODIS data at https://modis.gsfc.nasa.gov/data/and the flux data at http://www.fluxdata.org/.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data set is openly available from the Science Data Bank at http://www.dx.doi.org/10.11922/sciencedb.934.

Additional information

Funding

This work was jointly supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19030401), the Natural Science Foundation for Young Scientists of Hunan Province (Grant No. 2020JJ5557) and the General Project of the Hunan Provincial Education Department (Grant no. 19C1845).