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noisecapture_exploit_data.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="Noise-Planet - Scientific tools for environmental noise assessment">
<meta name="author" content="Gwendall Petit (CNRS , Lab-STICC UMR 6285 / DECIDE Team)">
<meta name="author" content="Judicael Picaut (Ifsttar / LAE)">
<title>Noise-Planet - Exploit data</title>
<!-- Bootstrap core CSS -->
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<!------------------------------------------------------------------------------------------------------------------------------------------------------------------>
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<!------------------------------------------------------------------------------------------------------------------------------------------------------------------>
<!-- ==== Presenation ==== -->
<div class="container" id="Presentation" name="Presentation">
<div class="row">
<h1 class="centered"><img class="img-responsive" style="display: inline;" src="./assets/img/logos/Logo_noisecapture.png" height="80px" width="80px" alt="Logo NoiseCapture" /> Exploit NoiseCapture data </h1>
<hr>
<div class="col-lg-offset-2 col-lg-8">
<p align="left">
This page presents the 5 different ways to exploit data coming from the NoiseCapture app, listed below:
<ol>
<li><a href="#direct_reading">Direct reading</a> in the application</li>
<li><a href="#local_data">Local .zip files</a> on the smartphone</li>
<li><a href="#raw_files">Raw files</a> stored on our server</li>
<li><a href="#formatted_data">Formatted data</a> via data.noise-planet.org</li>
<li><a href="#geoservices">Geoservices</a></li>
</ol>
These different levels, which give access to more or less information, call for varying user skills.
</p>
</div>
</div><!-- row -->
</div><!-- container -->
<!------------------------------------------------------------------------------------------------------------------------------------------------------------------>
<!-- ==== NoiseCapture - Direct reading ==== -->
<div class="container" id="direct_reading" name="direct_reading">
<div class="row">
<h2 class="centered">1. Direct reading</h2>
<hr>
<div class="col-lg-offset-2 col-lg-8">
<p align="center">
As described on the page <a href="./noisecapture_protocol.html">here</a>, you have three ways to visualize the measured sound levels in NoiseCapture:
</p>
</div><!-- col-lg -->
<div class="col-lg-4">
<h4 class="centered">1. Home page</h4>
<p align="center">
Display the live sound levels, with 3 representation modes (spectrum, spectrogram or map).
</p>
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture/1.2.7/NoiseCapture_Measurement_spectrum.jpg" alt="Home page" width="150px"></p>
</div><!-- col-lg-4 -->
<div class="col-lg-4">
<h4 class="centered">2. Resulting page</h4>
<p align="center">
Presents the physical indicators (average dB, time repartition, ...) resulting from the measurement.
</p>
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture/1.2.7/NoiseCapture_Results.jpg" alt="Results" width="150px"></p>
</div><!-- col-lg-4 -->
<div class="col-lg-4">
<h4 class="centered">3. History page</h4>
<p align="center">
List, visualize (opens the resulting page) and manage all the measurements already carried out.
</p>
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture/1.2.7/NoiseCapture_History.jpg" alt="History" width="150px"></p>
</div><!-- col-lg-4 -->
</div><!-- row -->
<p align="center"><a href="#Presentation">Go to top</a></p>
</div><!-- container -->
<!------------------------------------------------------------------------------------------------------------------------------------------------------------------>
<!-- ==== NoiseCapture - Local data ==== -->
<div class="container" id="local_data" name="local_data">
<div class="row">
<h2 class="centered">2. Local data</h2>
<hr>
<div class="col-lg-offset-2 col-lg-8">
<p align="center">Through the history menu, you can also retrieve the data from the measurement.
</p>
</div><!-- col-lg -->
</div><!-- row -->
</div><!-- container -->
<!-- Data retrival -->
<div class="container" id="local_retrival" name="local_retrival">
<div class="row">
<h3 class="centered">Data retrival</h3>
<div class="col-lg-offset-2 col-lg-8">
<p align="center">
In the <code>History</code> menu, select a measurement by pressing on it. In the menu that appears, select <code>Export Result</code>. From there, Android offers you to choose how to export the result (e.g. via email).
In the .zip file you get, you will find the following 3 files:
<ul>
<li><code>meta.properties</code>: measurement metadata,</li>
<li><code>README.txt</code>: describing text,</li>
<li><code>track.geojson</code>: the measure track.</li>
</ul>
</p>
</div><!-- col-lg-6 -->
</div><!-- row -->
</div><!-- container -->
<!-- Home page -->
<div class="container" id="local_info" name="local_info">
<div class="row">
<h3 class="centered">Provided informations</h3>
<div class="col-lg-6">
<br>
<h4 class="centered">The <code>meta.properties</code> file</h4>
<p align="justify">
Metadata file with the following information:
<ul>
<li><code>date</code> and <code>time</code> of export</li>
<li><code>uuid</code>: unique identifier of the NoiseCapture application (allows to attach the measurement to a smartphone and its features)</li>
<li><code>version_number</code>: NoiseCapture version</li>
<li><code>method_calibration</code>: calibration method (manual, reference value or automatic thanks to road traffic)</li>
<li><code>build_date</code>: compilation date of NoiseCapture</li>
<li><code>device_manufacturer</code>: smartphone brand</li>
<li><code>record_utc</code>: Unix epoch utc measurement time in milliseconds</li>
<li><code>version_name</code>: NoiseCapture release number</li>
<li><code>user_profile</code>: indicates whether you have declared yourself as a novice or an expert</li>
<li><code>time_length</code>: track duration (in seconds)</li>
<li><code>device_model</code>: smartphone model</li>
<li><code>leq_mean</code>: measure's mean Leq</li>
<li><code>gain_calibration</code>: gain used for smartphone calibration (in dB)</li>
<li><code>tags</code>: list of the tag(s) associated with the measure <i>(may be empty)</i></li>
<li><code>device_product</code>: smartphone reference</li>
</ul>
</p>
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<br>
<h4 class="centered">The <code>track.geojson</code> file</h4>
<p align="justify">
Measurement information and acoustic indicator:
<ul>
<li><code>leq_mean</code>: mean Leq</li>
<li><code>marker_color</code>: hexadecimal color used to display the point</li>
<li><code>accuracy</code>: GPS accuracy</li>
<li><code>location_utc</code>: GPS epoch time</li>
<li><code>leq_utc</code>: Unix epoch utc measurement time in milliseconds. You can use <a href="https://www.epochconverter.com">this website</a> in order to convert it</li>
<li><code>leq_id</code>: measurement id</li>
<li><code>leq_100</code>, <code>leq_125</code>, <code>leq_160</code>, <code>leq_200</code>, <code>leq_250</code>, <code>leq_315</code>, <code>leq_400</code>, <code>leq_500</code>, <code>leq_630</code>, <code>leq_800</code>, <code>leq_1000</code>, <code>leq_1250</code>, <code>leq_1600</code>, <code>leq_2000</code>, <code>leq_2500</code>, <code>leq_3150</code>, <code>leq_4000</code>, <code>leq_5000</code>, <code>leq_6300</code>, <code>leq_8000</code>, <code>leq_10000</code>, <code>leq_12500</code>, <code>leq_16000</code>: Leq values at the respective frequencies</li>
</ul>
</p>
</div><!-- col-lg-6 -->
<br>
</div><!-- row -->
<p align="center"><a href="#Presentation">Go to top</a></p>
</div><!-- container -->
<!------------------------------------------------------------------------------------------------------------------------------------------------------------------>
<!-- Manage -->
<div class="container" id="raw_files" name="raw_files">
<div class="row">
<h2 class="centered">3- Raw files on our server</h2>
<hr>
<div class="col-lg-offset-2 col-lg-8">
<br>
<p align="center">
You can download the raw data available on the Noise-Planet server. You will get <code>.geojson</code> files.
<br>
To exploit these data in numbers, we propose you a "turnkey" tutorial, based on Python and R languages.
</p>
<h3 class="centered">Requirements</h3>
<br>
<p align="center">
To download and process the raw data, the user has to have installed:
<ul>
<li>Python 3 (<a href="https://www.python.org/" target="_blank">https://www.python.org/</a>)</li>
<li>R (<a href="https://cran.r-project.org/" target="_blank">https://cran.r-project.org/</a>)</li>
</ul>
</p>
</div><!-- col-lg -->
</div><!-- row -->
<div class="row">
<h3 class="centered">Data recovery</h3>
<br>
<h4 class="centered">Step 1: Get the filtered data</h4>
<div class="col-lg-6">
<p align="center">
<ol>
<li>Go to our Metabase dashboard : <a href="https://dashboard.noise-planet.org/public/question/52ee2bde-2d28-4377-bcbb-061d7cbfa343" target="_blank"><b>here</b></a></li>
<li>Modify the parameters at will (1) in order to filter data (2)</li>
<li>Download the complete list as a <code>.csv</code> file (small arrow at the bottom right of the screen) (3)</li>
<li>Rename this file to <code>query.csv</code></li>
</ol>
<br>
</p>
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/metabase.png" alt="Metabase dashboard" width="800px"></p>
</div><!-- col-lg-6 -->
</div><!-- row -->
<div class="row">
<h4 class="centered">Step 2: Download files (need python)</h4>
<div class="col-lg-6">
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/download_python.png" alt="Metabase dashboard" width="500px"></p>
<!--
<pre><code>import requests
import os
lines = open("query.csv", "r").readlines()
for line in lines[1:]:
url = line.split(",")[1][:-1]
filename = "data"+ os.sep + url[url.rfind("/") + 1:]
open(filename,"wb").write(requests.get(url).content)</code></pre>
-->
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<p align="center">
<ol>
<li>Download the <code>download.py</code> file <a href="./assets/doc/noisecapture/script/exploit_raw_data/download.py" target="_blank"><b>here</b></a>,</li>
<li>Open this file in a text editor and replace the default <code>query.csv</code> file adress by yours (<i>e.g</i> <code>"home/data_noisecapture/query.csv"</code>),</li>
<li>Execute <code>download.py</code> (<i>e.g</i> in a Linux terminal, just execute the command <code>python3 download.py</code>) → the filtered .zip files (in metabase) will be downloaded in the <code>/data/</code> folder. In each of these .zip files (prefixed with <code>track_</code>), you will find the two <code>meta.properties</code> and <code>track.geojson</code> files described before.</li>
</ol>
</p>
</div><!-- col-lg-6 -->
</div><!-- row -->
<div class="row">
<h3 class="centered">Tip: filter your own data</h3>
<br>
<div class="col-lg-6">
<p align="center">
You have the possibility to filter your own data, using your Unique User Identifier (UUID)
<ol>
<li>In the NoiseCapture app, go to the "About" menu.</li>
<li>Check and copy your ID (in this theorical example <code>aabbccdd-d5d3-4c50-87aa-014593de95c9</code>)</li>
<li>In a web browser:</li>
<ol>
<li>Enter the following address <a href="https://data.noise-planet.org/raw/" target="_blank">https://data.noise-planet.org/raw/</a>,</li>
<li>Add your six first UUID caracters (in our example <code>aa/bb/cc/</code>),</li>
<li>Add your UUID (in our example <code>aabbccdd-d5d3-4c50-87aa-014593de95c9</code>)</li>
<li>The theorical resulting URI should be as follow: <a href="https://data.noise-planet.org/raw/aa/bb/cc/aabbccdd-d5d3-4c50-87aa-014593de95c9" target="_blank">https://data.noise-planet.org/raw/aa/bb/cc/aabbccdd-d5d3-4c50-87aa-014593de95c9</a> (check a real example <a href="https://data.noise-planet.org/raw/a7/09/db/a709dbd8-22a2-4851-8203-dde41e575ede/" target="_blank">here</a>).</li>
</ol>
<li>This way, only the measures made by this user are listed</li>
</ol>
<br>
</p>
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/noisecapture_about_id.png" alt="UUID" width="600px"></p>
</div><!-- col-lg-6 -->
</div><!-- row -->
<div class="row">
<h3 class="centered">Exploit the raw data</h3>
<br>
<p align="center">
To illustrate this tutorial, we will use the <a href="https://rstudio.com/" target="_blank">RStudio</a> application to run R scripts. There are many other similar applications that you can use in the same way.
</p>
<h4 class="centered">Open files and compute indicators (need R)</h4>
<div class="col-lg-6">
<p align="center">
<ol>
<li>Download the <code>indicators.r</code> file <a href="./assets/doc/noisecapture/script/exploit_raw_data/indicators.r" target="_blank"><b>here</b></a> and open it in RStudio,</li>
<li>Define your working directory in the menu <code>Session</code> / <code>Set working directory</code> / <code>To source file location</code></li>
<li>Adapt to your needs the input and output folders:
<ul>
<li><code>dir <- paste(getwd(),"/data/",sep="")</code></li>
<li><code>dirzip <- paste(getwd(),"/unzip/",sep="")</code></li>
<li>By default, the input data directory is set to <code>/data/</code> and the resulting files will be placed in the <code>/unzip/</code> folder.</li>
</ul>
</li>
<li>Run <code>indicators.r</code>. Depending on the spatial extent of your selected tracks, this process may take some time as the script will generate a regular grid over the entire study area. </li>
<li>In the <code>Viewer</code> menu tab, the showed mapped is a copy of the map in <a href="http://noise-planet.org/map.html" target="_blank">Noise-Planet.org website</a>, but now you can plot your own indicators!</li>
</ol>
<br>
</p>
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/rstudio_map.png" alt="RStudio user interface" width="800px"></p>
</div><!-- col-lg-6 -->
<br>
</div><!-- row -->
<p align="center"><a href="#Presentation">Go to top</a></p>
</div><!-- container -->
<!------------------------------------------------------------------------------------------------------------------------------------------------------------------>
<!-- Formatted data -->
<div class="container" id="formatted_data" name="formatted_data">
<div class="row">
<h2 class="centered">4. Formatted data</h2>
<hr>
<div class="col-lg-offset-2 col-lg-8">
<p align="center">
The measurements made by the community are collected, cleaned and then processed on our central database. From there, a daily export (every night) is made in order to generate <code>.geojson</code> files exploitable under open license (<a href="https://opendatacommons.org/licenses/odbl/" target="_blank">ODbL</a>).
</p>
</div><!-- col-lg -->
</div><!-- row -->
<div class="row">
<h3 class="centered">Data recovery</h3>
<br>
<div class="col-lg-6">
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/data_noisecapture.png" alt="Noisecapture data" width="400px"></p>
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<p align="center">
To obtain these data, simply go to the page <a href="https://data.noise-planet.org/noisecapture/" target="_blank">https://data.noise-planet.org/noisecapture/</a> and choose the <code>.zip</code> file corresponding to the country of your choice.
<br>
<img class="img-responsive" src="./assets/img/noisecapture_exploit_data/data_noisecapture_zip.png" alt="Noisecapture data" width="400px">
</p>
</div><!-- col-lg -->
</div><!-- row -->
<div class="row">
<h3 class="centered">Provided informations</h3>
<br>
<p align="center">
In each of the <code>.zip</code> files, 3 <code>.geojson</code> files per administrative region are provided: tracks, points and areas.
<br>
For more information, feel free to have a look to the following open article: <a href="https://doi.org/10.1016/j.dib.2017.07.039" target="_blank">Bocher et al. 2017, Collaborative noise data collected from smartphones, Data in Brief 14C (2017) pp. 498-503</a>.
</p>
<div class="col-lg-6">
<h4 class="centered">The <code>*.tracks.geojson</code> file</h4>
<p align="center">
This file contains the data collecting along a GPS track. A GPS track is defined by 8 property values. Note that each feature of the GeoJSON is a measurement session over a time period (expressed in seconds). The geometry corresponds to the bounding box of measurements locations.
<ul>
<li><code>time_ISO8601</code>: start time of measurement, using the ISO 8601 representation.</li>
<li><code>time_epoch</code>: start time of measurement in Unix Time Stamp (UTC) epoch format (number of milliseconds since January 1st, 1970, 00:00:00 GMT).</li>
<li><code>pk_track</code>: Database of track primary keys. This value may change when the zip files are updated, but are unique in the same zip file. This value is linked with the *.points.geojson file and could be used to build a geometry representation of the path of the measures.</li>
<li><code>track_uuid</code>: Track Universally Unique Identifier. This unique value never changes between zip updates.</li>
<li><code>gain_calibration</code>: Signal gain in dB, provided by the user after the noise calibration of the smartphone. Indeed, it is recommended to the user to proceed to an acoustic calibration of its smartphone, using the specific feature provided in the NoiseCapture application. This signal gain is already applied to all noise levels related to this track.</li>
<li><code>noise_level</code>: Sound level LAeq along the track.</li>
<li><code>tags</code>: User supplied tags for describing the noise environment along the track.</li>
<li><code>pleasantness</code>: User supplied pleasantness 0–100 (may be null) of the noise environment along the track.</li>
</ul>
</p>
</div><!-- col-lg-6 -->
<div class="col-lg-6">
<h4 class="centered">The <code>*.areas.geojson</code> file</h4>
<p align="center">
This file corresponds to a basic post-processing of all measurements produced by the community. All data are aggregated in hexagons, in order to produce mean noise indicators and information in each hexagon (mean LAeq, LA50, mean pleasantness) Each feature is an area represented by an hexagon of 15 m radius where all *.points.geojson have been aggregated.
<ul>
<li><code>cell_q</code>: Hexagon q coordinate using EPSG:3857 -- WGS84 Web Mercator.</li>
<li><code>cell_r</code>: Hexagon r coordinate using EPSG:3857 -- WGS84 Web Mercator</li>
<li><code>LA50</code>: Median sound level in dB(A) (i.e. the noise level just exceeded for 50% of the measurement period)</li>
<li><code>laeq</code>: Mean equivalent sound level LAeq in dB(A)</li>
<li><code>mean_pleasantness</code>: Mean pleasantness 0–100 (may be null)</li>
<li><code>measure_count</code>: Number of measurements (equivalent to the whole measurement time in seconds) in the hexagon (may be parts of different tracks)</li>
<li><code>first_measure_ISO_8601</code>: Date of the first measurement in the hexagon, using ISO8601 time representation. The timezone is provided by the localisation of the measurement, not by the configuration of the smartphone</li>
<li><code>first_measure_epoch</code>: Date of the first measurement in the hexagon, in UTC epoch format</li>
<li><code>last_measure_ISO_8601</code>: Date of the last measurement in the hexagon, using ISO8601 time representation. The timezone is provided by the localization of the measure, not the configuration of the smartphone</li>
<li><code>last_measure_epoch</code>: Date of the last measurement in UTC epoch format.</li>
</ul>
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<h4 class="centered">The <code>*.points.geojson</code> file</h4>
<p align="center">
This file stores the measurement points. Each feature corresponds to a measurement at each second. The file contains a geometry field called the_geom and 9 property values.
<ul>
<li><code>the_geom</code>: a point with X, Y and Z coordinates to store the GPS location.</li>
<li><code>pk_track</code>: Track primary key. This value may change when the zip files are updated, but are unique in the same zip file. This value is linked with the *.tracks.geojson file and could be used to build a geometry representation of the path of the measures.</li>
<li><code>time_ISO8601</code>: Time of the measurement using the ISO 8601 time representation.</li>
<li><code>time_epoch</code>: Time of measurement in UTC format.</li>
<li><code>time_gps_ISO8601</code>: GPS localisation may not be obtained each second, so the provided location is attached to the following "gps fix" time.</li>
<li><code>time_gps_epoch</code>: "GPS fix" time in UTC format.</li>
<li><code>noise_level</code>: Equivalent Noise level LAeq in dB(A), measured over a time period of 1 s.</li>
<li><code>speed</code>: GPS provided speed (may be not accurate).</li>
<li><code>orientation</code>: GPS provided orientation (may be not accurate)</li>
<li><code>accuracy</code>: GPS localization accuracy in meters</li>
</ul>
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<br>
<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/resulting_files.png" alt="Resulting files" width="400px"></p>
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<h2 class="centered">5. Geoservices</h2>
<hr>
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<p align="center">
NoiseCapture data are collected, hosted, manipulated and distributed through the <a href="http://noise-planet.org/onomap.html" target="_blank">Onomap SDI</a>, itself based on open tools, respecting <a href="https://www.ogc.org/" target="_blank">OGC</a> standards.
<br>
In this context, we are able to disseminate the data produced by the NoiseCapture community through 6 <a href="https://www.ogc.org/standards/wms" target="_blank">WMS</a> layers, available at the following adress <code>https://onomap-gs.noise-planet.org/geoserver/noisecapture/wms?</code> and listed below:
<br>
<h3 align="center">User oriented layers</h3>
<p align="center">
4 layers are users oriented:
<ol>
<li><code>noisecapture:noisecapture_area</code>: L50 sound levels calculated within an hexagonal cells,</li>
<li><code>noisecapture:noisecapture_area_laeq</code>: Laeq sound levels calculated within an hexagonal cells,</li>
<li><code>noisecapture:noisecapture_leaflet_point</code>: all the measurement points made by the community (within a NoiseCapture party or not),</li>
<li><code>noisecapture:noisecapture_points_party</code>: measurement points made within a NoiseCapture party.</li>
</ol>
</p>
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<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/wms_noisecapture_area_number.png" alt="L50 noise levels" width="250px"></p>
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<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/wms_noisecapture_area_laeq_number.png" alt="Laeq noise levels" width="250px"></p>
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<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/wms_noisecapture_leaflet_point_number.png" alt="All measurement points" width="250px"></p>
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<p align="center"><img class="img-responsive" src="./assets/img/noisecapture_exploit_data/wms_noisecapture_points_party_number.png" alt="Party measurement points" width="250px"></p>
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<h3 align="center">Noise-Planet oriented layers</h3>
<p align="center">
2 layers are rather dedicated to the Noise-Planet infrastructure since they meets technical needs:
<ul>
<li><code>noisecapture:noisecapture_area_cluster</code>: meshing of the earth surface, in the form of a cluster with adaptive size according to the density of the measurements. This layer is used, among other things, to count the number of measuring points per zone,</li>
<li><code>noisecapture:noisecapture_area_party</code>: L50 sound levels calculated within an hexagonal mesh, for a dedicated party. To do so, this layer has to be used with a CQL filter based on the party code (<i>e.g</i> pk_party=2).</li>
</ul>
<br>
<code>Warning</code>, most of these layers are configured to be displayed below a certain scale. So if you are not viewing the data, you probably need to zoom in.
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