Earlier this month I was lucky enough to be part the annual Geo for Good User Summit, which brings together non-profits and public benefit organisations who use mapping technologies to make a difference in the world. The Google Earth Outreach team offered their support to participants to visualise their cause, share their story and raise awareness.
Google Earth Outreach Engineering Manager, Rebecca Moore, opened the summit by telling her own story: In 2005, local residents in California’s Santa Cruz Mountains received a legal notice in the mail about a proposed logging plan. It included a black and white map which offered no clear distinction between roads, topographic contour lines and the plan area. Most people struggled understanding it, so they simply threw it away. Consequently Rebecca Moore mapped the key elements in Google Earth. Her visualisation eventually led to the abolishment of the plan as well as the birth of Google Earth Outreach.
Inspired by this success story, the week continued with participants of the summit presenting their projects and sharing how they use mapping technology. The range of applications was big, including forest monitoring and other conservations practices, indigenous knowledge mapping, mapping of essential services for the urban poor and many more. The general agenda was a good mix of practitioners sharing their stories, and Google staff teaching us best practices of how to use their products. The training they provided covered the topics mapping and visualisation, data collection and storytelling. A list of tools with online tutorials can be found here.
In the following I list some of the training resources I used during the user summit:
Interactive KML playground
KML is a very powerful a language for encoding and annotating geographic data and can do a lot more than I was aware of. Of course there are many tools, like most GIS packages, that automatically generate KML code. However, some of the more advanced stuff requires to dig into the source code. Most of it is pretty straightforward and the KML playground provides you with a quick and efficient learning environment. It does require Firefox though since Chrome doesn’t support the Google Earth plugin anymore. Oh the irony…
PyKML
Once the structure of KML is understood, who wants to write code by hand? PyKML is a Python package for creating, parsing, manipulating, and validating KML.
Learn Maps API
This code tutor walks you through various components of the JavaScript Maps API. While websites are typically built by combining HTML (content) and JavaScript (behaviour), this website contains exercises with pre-built HTML, so you can efficiently improve your JavaScript mapping skills. After each couple of sections it poses a challenge for you to solve.
Google Earth Engine Playground
A tool that truly fascinates me, which anyone who has ever worked with large Earth observation datasets will understand, is Google Earth Engine. Even after solving the first hurdle of accessing and downloading datasets, which is often not straightforward, computational power requirements remains a challenge when working on a single machine. Google Earth Engine is a platform for environmental data analysis that makes global satellite imagery available online as well tools and computational power necessary to analyse and mine that vast amount of data. Typical applications include: detecting deforestation, classifying land cover and land cover change, estimating forest biomass and carbon, and visualising change over time. The data catalogue includes 40 years of Landsat imagery amongst other popular datasets such as MODIS, SRTM and Sentinel 1.
After we have received a crash course in using Google Earth Engine I was hooked and started putting together a few lines of code that checks all Landsat 8 data in the region of the Republic of Congo, my research area, and returns the median value for each pixel. This way I got an almost cloud-free image mosaic of a country situated in the tropical zone. I compared the result with another visualisation where I replaced cloud cover pixels with the latest cloud-free pixels in the same dataset. These computations took a couple of seconds and I am very pleased with my first results. I am looking forward to higher resolution data produced by the Sentinel 2 satellite being included in the data catalogue.
The playground, similar to the KML playground, provides you with a list of examples as well as an interactive coding environment. Google Earth Engine requires you to sign up, but this is a free and simple process.
Although being a fan of open access and open-source technology I must admit that Google does a great job in making their tools available to NGOs and other non-profits. They offer software grants for enterprise versions of their mapping products and it can be beneficial to take advantage of their popularity in order to raise awareness about projects by being added as a success story. If you use Google mapping tools “for good” in your project, they should happily give you exposure by adding the project to their website.
Many thanks to the Google Earth Outreach team and the other participants who made this week a truly inspirational experience!
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