Forest Condition Accounts
At this stage of the project, condition accounts are focused on Forest Ecosystems, due to the ecosystems' relevance in terms of ecological conditions and the availability of information from remote sensing data.
Forest Condition Indexes
the first option is to compile the Forest Condition Index to estimate the overall condition based on a set of experts-defined weighted and selected indicators
The symbols next to the Indexes define the output produced as a result of that computation, while the first Condition Index produces maps and a table, the other two indexes produce maps, and can be compared to show how conditions estimates differ when using diverse methodologies.
Obtain summary tables for the indicators and variables
Forest Condition Variable (raw values)
within the section of the Condition metrics, the value of the Raw variables to compile the Variable Forest Ecosystem Condition Account(s),
Forest Condition Indicators
Switch to the Indicators option, to compile the Forest Condition Indicators Account(s),
High-resolution Forest Condition Variable
These variables are placed in another section to differentiate them from the other raw variables.
Caution is required when observing these datasets
High-resolution observation should only be observed over small contexts, taking as reference the location designed as testing areas in the project (i.e. level 3 of the nomenclature of territorial units for statistics - NUTS3).
This request is due to the computational cost and time associated with these observations, which when using these datasets is much higher.
Compilation of condition accounts
The selection of one of these options triggers the model(s) underlying the output(s) selected, in case more ecological metrics are selected, the computational flow is continuous. When the whole workflow to compute one metric is completed, the system moves to the next tasks in the queue of computation. The models to be computed follow the order of selection of the user.
Most of the metrics are modelled from different datasets, so the time of computation should be similar, but in case an account shares inputs used in a previous computation, those are not re-calculated, thus one should expect the additional output(s) to be computed faster.