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.
When the knowledge bar turns yellow and the elephant's ball spins, the system is computing the information queried.
There are several sections to organize the access to the different information made available in the application:
The first 4 sections were specifically developed for the People EA project and will be the main focus of this guide.
When the 3 dots are displayed horizontally, it means that the options in the menu are hidden 
By clicking on the 3 dots they get disposed vertically 
and a drop-down menu lists the options available.
The main output of an observation can be a table 
, or a map 
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.
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.
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
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.
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."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)
The table can be copied or downloaded (click on the symbols at the right bottom of the table to export it)
To explore the geospatial explicit information in the maps used to summarize the results in the table, go back to the View Data section:
Expand the View Tree to visualize all inputs, intermediate and final output
Select the map that you want to visualize
When the knowledge bar turn yellow and the elephant's ball spins, the system is computing the information queried.
In this case, is loading the map
This can be visualized in the explorer or downloaded as a raster file (.tiff format) for further analyisis in a GIS system.
One can download a map by clicking on the arrow pointing down (↓) that appears when hovering over the observation ( an observation is any of the element observed in the workflow and listed in this menu)
This was the main output, but any input and intermediate output of a workflow can be observed by ticking their boxes.
The results for NDVI are shown below.
Notice how observations that changes over time in the context selected, have the symbol of a clock next to them, and at the bottom of the menu, you'll see a timeline, in a light blue color.
In this example, as there are just two temporal observations, there is just one separator (small tick in yellow), dividing the 2 temporal observations (2015 and 2016).
Selecting a different temporal observation, the map will change and the system displays the result for that year
2015
2016
