Estimation of gross land-use change and its uncertainty using a Bayesian data assimilation approach
We present a method for estimating land-use change using a Bayesian data assimilation approach. The approach provides a general framework for combining multiple disparate data sources with a simple model. This allows us to constrain estimates of gross land-use change with reliable national-scale...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-03-01
|
| Series: | Biogeosciences |
| Online Access: | https://www.biogeosciences.net/15/1497/2018/bg-15-1497-2018.pdf |
| Summary: | We present a method for estimating land-use change using a Bayesian data
assimilation approach. The approach provides a general framework for
combining multiple disparate data sources with a simple model. This
allows us to constrain estimates of gross land-use change with reliable
national-scale census data, whilst retaining the detailed information
available from several other sources. Eight different data sources, with
three different data structures, were combined in our posterior estimate
of land use and land-use change, and other data sources could easily be
added in future. The tendency for observations to underestimate gross
land-use change is accounted for by allowing for a skewed distribution
in the likelihood function. The data structure produced has high
temporal and spatial resolution, and is appropriate for dynamic
process-based modelling. Uncertainty is propagated appropriately into
the output, so we have a full posterior distribution of output and
parameters. The data are available in the widely used netCDF file format
from <a href="http://eidc.ceh.ac.uk/" target="_blank">http://eidc.ceh.ac.uk/</a>. |
|---|---|
| ISSN: | 1726-4170 1726-4189 |