Compile the accounts in the k.Explorer
To trigger the computation of an output in a specific area, for a specific period, the user should first select the context that has been set, the user simply checks the box of the condition metrics (raw variables, indicators or index) or the ecosystem service to compute their results.
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Before computing any of these results, the guide provides the theoretical background followed to obtain these output in the previous section, so users are invited to carefully read that documentation to be able to select the options of calculations available in the app, as well as to interpret correctly their results.
Users can observe:
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
This option only triggers the computation of the table of the Forest Condition Index, so while indicators and variable involved in the computation are calculated, their results are not summarized in tables.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.
High-resolution observation should only be done over small contexts defined as testing areas in the project.
This is due to the computational cost and time associated with these observations, which is much higher.
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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.
Soil Retention Ecosystem Service
As a demonstration of the interoperability between ARIES and OpenEO systems, the Soil erosion model can be computed in two different ways:- using the dynamic C-Factor from Open EO → select the OpenEO Cover Management and only after select the Sediment Regulation model:
select the OpenEO Cover Management
Once obtained the Cover Management, call the Sediment Regulation model
Once obtained the Cover Management, call the Sediment Regulation model
The breakdown of the results focuses on the contribution of the service by type of forest
- using the static information about the C-Factor → just select the Sediment Regulation model
In this case, the static C-Factor is used in the workflow
And the Soil Retention results are comparable but have a coarser resolution
The breakdown of the results focuses on the contribution of the service by type of forest
- A third option, is to compute the results using the SEEA EA methodology, accessible in the ARIES for SEEA accounting tables section
The outputs of the ES are the same
but the breakdown of the results focuses on the contribution of each Ecosystem Type
Note title Observations are live digital twins Any observation done in ARIES happens on the fly and is not a predefined combination (or workflow) of models and data. The system builds the most appropriate strategy to answer such questions using the information available in the system, at the moment in which a query is made. For this reason, as new information is integrated into ARIES, its results improve. ARIES looks for the "best" available combination of data and models to estimate Soil retention. By selecting the input (C-Factor from OpenEO) and later the model to be computed, we steer the system to build an observation of Soil Retention using the Cover Management dataset previously selected.
Tip title Why do you have to select the OpenEO dataset? "How come the OpenEO datasets are not picked automatically by ARIES, besides being more appropriate for this specific query?"
A legitimate question given the highest temporal and spatial resolution of the data, would mean this dataset should have priority. On the other hand, since the data are not publicly available, they are not chosen to build the model. This is necessary to ensure that only Early Adopters have access to the data, but this may be the case for NSOs and other agencies sharing other sensitive data and information in ARIES. So the dataset is not only available to the whole community but as an Early Adopter, you have the right to observe the model built using the dynamic cover management factor from OpenEO by observing it before querying the Soil Retention model.Tip title "Can I substitute or add new information to compute results based on different inputs?? Yes, the system is built to allow maximum flexibility and local knowledge can be integrated into the system, to adjust or to simply compare results using a different methodology. This means that other datasets can be integrated, parameters can be fine-tuned, and partial or entirely new models can be added as part of the workflow.
- using the dynamic C-Factor from Open EO → select the OpenEO Cover Management and only after select the Sediment Regulation model:
Results of the accounts
Once the account is computed, the k.Explorer moves automatically from the Data view, to the Documentation section, showing the Table section (for more information on the different sections check this chapter of the guide)
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