style: lint trailing spaces

docs/source/team/classroom.rst

@@ -12,7 +12,7 @@ To access Google Classroom for SEPAL, open your professional Google account and
 
 .. image:: ../_images/team/classroom/dashboard.png
 
-Each class is composed of several :code:`Topics`. 
+Each class is composed of several :code:`Topics`.
 
 Each **Topic** can include different types of content, including: :code:`exercices`, :code:`exams`, and :code:`material` (see following image).
 
@@ -62,7 +62,7 @@ Select the **General class content** folder.
 
 .. image:: ../_images/team/classroom/shared-with-me.png
 
-Enter :code:`maj+Z`. 
+Enter :code:`maj+Z`.
 
 Select **Add** to connect the folder your own Google Drive account (see following image).
 

docs/source/team/contribute.rst

@@ -15,11 +15,11 @@ Then, communicate feedback or proposed contributions via:
 Introduction
 ------------
 
-The :code:`sepal-doc` repository has a fixed structure that needs to be respected to follow Sphinx builder requirements. 
+The :code:`sepal-doc` repository has a fixed structure that needs to be respected to follow Sphinx builder requirements.
 
-All modifications should be made in the folder, :code:`sepal-doc/docs/source/`. 
+All modifications should be made in the folder, :code:`sepal-doc/docs/source/`.
 
-Images associated with a page should be stored in the corresponding folder, :code:`sepal-doc/docs/source/_images/`. 
+Images associated with a page should be stored in the corresponding folder, :code:`sepal-doc/docs/source/_images/`.
 
 If files are misplaced, their build into .html pages cannot be guaranteed.
 
@@ -28,9 +28,9 @@ If files are misplaced, their build into .html pages cannot be guaranteed.
 Tools
 ^^^^^
 
-The :code:`sepal-doc` repository creates and organizes .rst files by leveraging: 
+The :code:`sepal-doc` repository creates and organizes .rst files by leveraging:
 
--    the Python `Sphinx <https://www.sphinx-doc.org/en/master/>`_ library to create the build; and 
+-    the Python `Sphinx <https://www.sphinx-doc.org/en/master/>`_ library to create the build; and
 -    the `ReadTheDoc <https://readthedocs.org>`_ website to distribute the build.
 
 .. attention::
@@ -181,7 +181,7 @@ If you would like to make modifications to an existing article in the documentat
 
     The **Edit on GitHub** button on the landing page.
 
-When you are finished modifying the file in the **GitHub editor**, select :code:`propose change` at the bottom of the page. 
+When you are finished modifying the file in the **GitHub editor**, select :code:`propose change` at the bottom of the page.
 
 This will create a **Pull request (PR)** that includes your modifications, which will be reviewed and evaluated by the SEPAL team before being published.
 
@@ -246,7 +246,7 @@ In this section, we will present the full process to make major changes to the d
 Fork project
 ^^^^^^^^^^^^
 
-To work on multiple files at the same time, you cannot work directly from GitHub. Rather, you need to install a local version of the source. 
+To work on multiple files at the same time, you cannot work directly from GitHub. Rather, you need to install a local version of the source.
 
 To avoid the publication of low-quality documentation, SEPAL users don't have the rights to directly push edits to master files. Instead, you must fork the project into their own accounts by selecting the :code:`fork` button in the upper-right side of the `GitHub page of the documentation <https://github.com/openforis/sepal-doc>`_:
 
@@ -309,7 +309,7 @@ To check that the doc can be built without error, go to the **doc folder** and r
 
 A new folder, :code:`build`, has been created in your **sepal-doc** folder.
 
-Double-click on :code:`sepal-doc/docs/build/html/index.html`. 
+Double-click on :code:`sepal-doc/docs/build/html/index.html`.
 
 Your browser should open and lead to the landing page of SEPAL documentation (Note that it's a local .html page. The URL at the top of the browser should start with **file://** rather than **https://**. There should be no advertisements in the side bar.)
 
@@ -414,7 +414,7 @@ Add the page you've created to the :code:`toctree` (Table of contents) directive
         my_page
         page3
 
-The title of your page should appear as a link in the **Section navigation** pane on the left side of your browser. 
+The title of your page should appear as a link in the **Section navigation** pane on the left side of your browser.
 
 If you forget to link your page, you will see the following message:
 
@@ -492,7 +492,7 @@ New modules
 
 Have you created a new module (Shiny or Python-based) and have been asked to add it to the **App** dashboard of SEPAL (following the issue template)?
 
-One of the requirements to have your module accepted by the SEPAL team is to create a documentation file. 
+One of the requirements to have your module accepted by the SEPAL team is to create a documentation file.
 
 To maintain consistency across modules, we store the documentation in the module's original repository.
 
@@ -564,20 +564,20 @@ In the **Pull request** interface, select the :code:`New pull request` button:
 
     Create a new pull request.
 
-Select what is going to be pushed and where. 
+Select what is going to be pushed and where.
 
-If you've followed this article of the documentation, you have not created any branch in your fork. 
+If you've followed this article of the documentation, you have not created any branch in your fork.
 
-On the left side, leave :code:`openforis/sepal-doc/master`. 
+On the left side, leave :code:`openforis/sepal-doc/master`.
 
-On the right side, leave :code:`<account>/sepal-doc/master` (see **1** in the following image; some extra information on the commit that will be added to the master is displayed in **2**). 
+On the right side, leave :code:`<account>/sepal-doc/master` (see **1** in the following image; some extra information on the commit that will be added to the master is displayed in **2**).
 
 If everything is set properly (normally you don't have to change anything), select the :code:`Create pull request` button.
 
 .. figure:: ../_images/team/contribute/compare_pr.png
     :alt: Compare branches
 
-Finally, enter the **title** and **description** of the PR (**1**) (please respect the template provided, as shown in the following image). 
+Finally, enter the **title** and **description** of the PR (**1**) (please respect the template provided, as shown in the following image).
 
 As explained at the beginning of this article, you started your modifications to address an issue reported in the **GitHub Issue Tracker**, which should be referenced in your **PR message** (in Line 2 using the :code:`#<issue number>`). This will help the SEPAL team, who will review your PR, by ensuring that they understand what you are adding to the documentation.
 

docs/source/workflows/bayts.rst

@@ -4,23 +4,23 @@ BayTS NRT-FDM
 Background
 ----------
 
-Near real-time forest disturbance monitoring (NRT-FDM) entails remote sensing techniques that are based on dense time series, targeting the generation of recent disturbance events in forested areas. 
+Near real-time forest disturbance monitoring (NRT-FDM) entails remote sensing techniques that are based on dense time series, targeting the generation of recent disturbance events in forested areas.
 
-The main objective is to detect those changes as early as possible. This prioritization usually comes at the cost of accuracy, as the methods are optimized for speed and timeliness. 
+The main objective is to detect those changes as early as possible. This prioritization usually comes at the cost of accuracy, as the methods are optimized for speed and timeliness.
 
 NRT-FDM is a rapidly evolving field of research and many different approaches have been proposed. The most common ones are based on the detection of abrupt changes in the time series, which are then classified as disturbance events.
 
 This page provides background information and a detailed **How-to guide** (see below) for the implementation of the BayTS algorithm on the SEPAL platform that is optimized for the generation of NRT alerts using Sentinel-1 radar data. The advantage of using radar data is its independence from cloud cover and sensitivity to structural elements of vegetation cover.
 
 Methodology
 -----------
-To detect forest cover loss in NRT in dense Sentinel-1 time series, a pixel-based approach is applied. 
+To detect forest cover loss in NRT in dense Sentinel-1 time series, a pixel-based approach is applied.
 
-First, a historic reference is created by calculating the mean and standard deviation of the backscatter values for each pixel. 
+First, a historic reference is created by calculating the mean and standard deviation of the backscatter values for each pixel.
 
 Then, the reference is used to calculate the probability of a pixel being in a disturbed state using the Bayes Theorem, a statistical approach that allows for the calculation of the probability of an event based on prior knowledge of conditions that might be related to the event. In this case, the event is a forest disturbance and the conditions are the backscatter values of the pixel.
 
-The method works without any training data, as a probability of being forest is derived from its historic reference expressed by the mean and standard deviation, from which a probability density function is derived. 
+The method works without any training data, as a probability of being forest is derived from its historic reference expressed by the mean and standard deviation, from which a probability density function is derived.
 
 The non-forest state is assumed to have the same probability density function centered at a 4 decibel (dB) backscatter below the forested one. Once the probability of being non-forest exceeds a user-defined threshold (0.6 by default), Bayesian Updating is applied until the alert either gets confirmed or rejected. Therefore, updating is repeated until the probability of being a change is above a high-confidence threshold (0.975 by default). If the alert is not confirmed within a certain time range (90 days by default), the alert is rejected.
 
@@ -31,11 +31,11 @@ The method capitalizes on both VV and VH polarized channels, whereas the highest
    :width: 800
    :align: center
 
-SEPAL allows for the displaying of different stages of confidence: 
+SEPAL allows for the displaying of different stages of confidence:
 
--    the initial one (where an alert is triggered by the probability of being non-forest above 0.6); 
--    low-confidence alerts (where the probability of change being > 0.85); and 
--    high-confidence alerts (where the probability of change being > 0.975). 
+-    the initial one (where an alert is triggered by the probability of being non-forest above 0.6);
+-    low-confidence alerts (where the probability of change being > 0.85); and
+-    high-confidence alerts (where the probability of change being > 0.975).
 
 In addition, the thresholds can be changed.
 

docs/source/workflows/nrt.rst

@@ -3,7 +3,7 @@ CCDC NRT-FDM
 
 Background
 ----------
-Near real-time forest disturbance monitoring (NRT-FDM) entails remote sensing techniques that are based on dense time series and target the generation of recent disturbance events in forested areas. 
+Near real-time forest disturbance monitoring (NRT-FDM) entails remote sensing techniques that are based on dense time series and target the generation of recent disturbance events in forested areas.
 
 The main objective is to detect those changes as early as possible. This priotization usually comes at the cost of accuracy, as the methods are optimized for speed and timeliness. They are therefore not suited for area estimations, such as for measurement, reporting and verification (MRV), where accuracy is the main objective.
 
@@ -13,11 +13,11 @@ This page provides background information and a detailed **How-to guide** (see b
 
 Methodology
 -----------
-The CCDC algorithm is a well-established pixel-based method for the detection of changes in dense time series, usually applied for mapping changes of land use and land cover over longer periods of time. 
+The CCDC algorithm is a well-established pixel-based method for the detection of changes in dense time series, usually applied for mapping changes of land use and land cover over longer periods of time.
 
-The algorithm is based on the assumption that the time series can be modelled by a harmonic function, which is fitted to the time series; the modelled values are compared to the observations. 
+The algorithm is based on the assumption that the time series can be modelled by a harmonic function, which is fitted to the time series; the modelled values are compared to the observations.
 
-If the difference between the modelled and observed values exceeds a certain threshold, a break is added, and a new segment is created based on the subsequent observations, fitting a new harmonic model. 
+If the difference between the modelled and observed values exceeds a certain threshold, a break is added, and a new segment is created based on the subsequent observations, fitting a new harmonic model.
 
 The threshold for a break is defined as a multiple of the root mean squared error (RMSE) of the harmonic model. (For more information, see `this article <https://www.sciencedirect.com/science/article/abs/pii/S0034425714000248>`_.)
 

docs/source/workflows/sop_template.rst

@@ -307,7 +307,7 @@ Lastly, you will need to revise the document in a methodical fashion. In these d
 * `AcATaMa QGIS plugin for Accuracy Assessment of Thematic Maps <https://smbyc.github.io/AcATaMa/>`_
 * `Collect Earth Online <https://collect.earth/support>`_
 * `Collect Earth (Desktop) <http://www.openforis.org/tools/collect-earth/>`_
-* `https://www.hsdl.org/?abstract&did=802131>`_ (generalized SOP guidelines for quality assurance for reporting all environmental data and procedures)
+* `<https://www.hsdl.org/?abstract&did=802131>`_ (generalized SOP guidelines for quality assurance for reporting all environmental data and procedures)
 
 **QA/QC Resources**: