Brown Fields

Category: Best data-driven reporting (small and large newsrooms)

Country/area: China

Organisation: Caixin Media

Organisation size: Big

Publication date: 8 Feb 2019

Credit: Jiaxin Liu, Xu Gao, Bo Zhao

Project description:

Brown fields are lands which were polluted by industries and would be used for othere purposes. For a long time, China’s brown field data is secretary for people. This project is the first report which visuliazed the data for the public. Based on open files and government information, Nanjing University and the NGO Greenpeace collected brown field data from provincial capitals and municipal cities. 174 brown fields are visualized to tell where they are, how they were polluted, and what they will be transferred to.

Impact reached:

It helps readers know more about the fields they are living in. Residential areas, malls, hospitals and schools, these should have been the safest places. But a lot of brown fileds were transferred into these purposes without enough environmental repair. Some tragedies happended years after these buildings came into use.

Local governments have been ordered to start open brown field data to the public. But information is scattered in their websites, difficult to find and understand. This project is an easy way to check important information about these fields. It’s not only a project with analysis, but also a tool for tracking open data.

Techniques/technologies used:

We used excel to analyze and restructure data, Adobe Illustrator and Photoshop for design, and html/css/js(d3.js) for web page and interactive data visualization.

What was the hardest part of this project?

Making professional enverinmental knowledges and data easy to understand for normal readers is the hardest part. We used different colors to represent four mainly harmful elements. By scrolling, readers can easily get how harmful they are from previous tragedy cases. We also rearranged plots by cities and industries to show which city open the most brown field data and what industry has the most ones.

What can others learn from this project?

The final part is a data query tool. Readers can locate their living position on the map and find whether there are some brown fields around them, and how they would be repaired. This can improve readers’ rights to be informed about their living enveriments.

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