Water quality visualization service for Secchi3000

Track 01: Information design and visualization

Tags: water system monitoring, water quality, crowdsourcing, citizen observations, measurement devices, data visualization, GIS.

Sponsor: SYKE

 

Challenge

Visualize the available datasets or demonstrate how the visualization products/tools should look like. Consider the point of view of a limnologist or an environmental expert. The visualization and the tools should provide insights on water quality phenomena in the studied lakes.

Suggest practices that improve the information content and usability of information the above visualization products/tools. They should be applicable for single-volunteer observations or groups of volunteers.

 

Background

The primary Secchi3000 data was acquired with iQwtr device by volunteers in Mikkeli region during 2015. Additional data was analyzed in 2016.

The dataset is available as…

  1. summarized to turbidity statistics for each lake water body in ESRI ArcGIS Online service (see data section below),
  2. interpreted image data that includes the different black-gray-white areas in two panels and their red-green-blue color statistics at two water depths, and time and location of the observations as an Excel table.

Only a preliminary analysis was carried out for other parameters than turbidity and Secchi depth. Unfortunately, that data is not available as a training data. Moreover, volunteers were not given any schedule for making the observations. The reports didn’t include any standardized template for conditions such as ice cover and algae. The datasets were not connected with any other environmental data.

Changes in humus (CDOM, coloured dissolved organic matter), water colour, Secchi depth and turbidity can be considered the most significant information for the experts using the data. However, all parameters affecting the water quality can be of interest if monitorable by volunteers. For example, you can consider parameters described in the Water Framework Directive.

 

Approaches and considerations

How to capture seasonal variation during the year? What data is required?

Note: Available data is not necessarily representative of the whole lake, nor the whole year, and not possibly even accurate.

 

Data

Secchi3000 dataset (ESRI ArcGIS Online)

http://www.arcgis.com/home/item.html?id=883efc55b58b44ee9bab98b9aa960ae1

 

SYKE open data repositories 

http://www.syke.fi/avointieto

http://www.syke.fi/en-US/Open_information1

 

Recent local observations by Xamk environmental engineering students from november 2017.

https://drive.google.com/drive/folders/1WNphzTH6r5ksKKhjdGUlf0sfL_V7K1LJ?usp=sharing

 

Additional materials

Detailed description and background for Secchi3000

https://drive.google.com/file/d/11tlFMXlKHZmE0UbvS_Q484NJS8o2sqkE/view?usp=sharing

 

Results and market reviews of iQwtr implementation of Secchi3000 devices, and the associated documentation.

https://drive.google.com/drive/folders/1ejrhmxOSww3D9HQqDrGPItCiIlBl1aPC?usp=sharing

 

Test datasets of iQwtr measurements, including original images, interpreted results and software for basic manual analysis. Also, a Matlab-based software is available for manual reprocessing and visualisation (if necessary).

https://drive.google.com/drive/folders/1pb9luGHh_I_pp0XHQfc9w0fKdiUSSxgf?usp=sharing

 

Technology

You can consider and try out the below examples and technologies. However, you’re not limited to use them at all, or only them. You should explore different approaches and find technology that supports your idea.

 

IBM DSX (available in Bluemix)

https://datascience.ibm.com

https://datascience.ibm.com/community

 

Pixiedust (data visualisation helper)

https://github.com/ibm-watson-data-lab/pixiedust

https://www.youtube.com/watch?v=cYUdXFEmxP4

https://www.youtube.com/watch?v=rEo3klBpOV0&t=1525s

 

Watson IoT

https://developer.ibm.com/recipes/tutorials/?s=water

https://developer.ibm.com/recipes/tutorials/?s=IoT

 

Watson for Unity

https://github.com/watson-developer-cloud/unity-sdk

 

Bluemix service catalog (e.g. Watson and IoT)

https://console.bluemix.net/catalog/

 

IBM developer docs

https://console.bluemix.net/docs/

https://www.ibm.com/developerworks/

 

ArcGIS Online of Xamk

Hackathon groups are granted an account for ArcGIS Online GIS platform. Your account has professional map authoring, publishing and analysis capabilities and rights.

A username and a password for the first login are provided per group by the staff.

Do NOT try to sign in here: http://www.arcgis.com/
The SIGN IN address is https://xamk.maps.arcgis.com/

 

Esri ArcGIS Desktop

You can use a trial desktop installation.

http://www.esri.com/arcgis/about-arcgis

 

Esri developer docs

https://developers.arcgis.com/