Inspiration

The project was inspired by a community tree-planting project from Lilongwe Malawi. A group of volunteers planted trees at a school that is being planted in the community and Patrick Kalonde (the lead applicant) took an initiative to collect geographical coordinates of all the locations where the trees were planted and monitored the survival of trees after two months. This initiative inspired Alick Austin (another team member) to check tree survival after 11 months. The two came up with static maps which showed them the spatial patterns of tree survival.

The duo realized that trees are used in global efforts to mitigate climate change through carbon sequestration. During the hackathon, the team built a dashboard to enable visualization of tree survival over time. The dashboard is effective at communicating tree survival over time and can be used in monitoring tree survival in large-scale tree-planting programs. This can be revolutionary given that it has been reported in Malawi that tree survival monitoring efforts lack geo-referenced data and it is difficult to track tree survival over time. In particular, our solution will help organizations that are implementing tree planting programs to have a reliable and transparent tool for communicating the achievements and impacts of their work (this will enable them to get more funding for their work). Additionally, the dashboard will provide a unique platform that will help to identify locations where tree planting is successful and such locations can be targeted to learn more about factors and best practices that have to be considered to accelerate the success of a tree-planting program. This is in line with the Malawi Forest Landscape restoration strategy.

What it does

The dashboard presents locations where trees were planted. When a user clicks the play button on the time slider, the maps change and it shows how trees survived over time. While that the dashboard alone does not provide information regarding why some trees are able to survive in the long run, the dashboard still presents an excellent example of extraordinarily data-driven solutions that can be used to build resilient and sustainable communities.

How we built it

We developed our dashboard using CSS, HTML, and JavaScript. We hosted a feature layer for tree presence on ArcGIS online. Initially, our data layer had three fields which were dates for tree survival. We restructured the data using a wide - that meant each record was replicated three times, each representing a time point and observed tree survival status. We uploaded this data on ArcGIS online as a CSV file and we configured the properties of our date field.

Next, we categorized all observations based on survival status - we give red color to trees that died and green to those that survived. We also created an API key using our ArcGIS developer account and we shared our tree layer on this API key. While mindful of potential security concerns that may come when we share the API key with others, we restricted the use of this API key to only matching HTTP referer headers.

Finally, we used HTML and CSS to structure and style a webpage, and we used Javascript to pull the maps from ArcGIS online using our API. In addition to this, we used existing widgets to add a time slider on our dashboard to enable visualization of tree survival over time.

Challenges we ran into

Working with a time slider presented a number of challenges to us. First, it was the first time for the team to use such as a tool and it took time for the team to realize that for the time slider to work, the data had to be structured and formatted in a unique way for it to be recognized by ArcGIS online. We consulted with mentors from ESRI and we were able to fix the problem. Additionally, we also currently have few data points (across both space and time), and this has limited animation tree survival in our current project.

Accomplishments that we're proud of

Accumulation of Greenhouse gases is of great concern today. With levels of carbon dioxide in the atmosphere, having exceeded 400 ppm, carbon sequestration through tree planting and other options seems to be options for mitigating climate change. We are really excited to have contributed to this by developing the dashboard in this submission as a tool for monitoring tree survival, and communicating the outcomes and achievements, offering room for improving existing tree planting programs.

What we learned

First, we learned that hackathons are more than just an event where people create ideas. We have realized that in the process of creating ideas for sustainable development, we deepened our technical knowledge and skills in working with GIS. For example, our team met several mentors from the hackathon and we learned about several tools for debugging. We also learned about data structures and formats, particularly on time series data. This is a skill that can easily be transferred to our daily lives and our studies as students. Additionally, we have also learned about security issues that might arise when one shares an API together with the developed solution. We realize that even though people can steal one’s API, within one’s developer account one can restrict the use of this API key to matching HTTP referer headers.

What's next for Monitoring Tree Survival to Support Climate Mitigation.

If successful during this hackathon, we plan to use the prize money to procure a multispectral drone. Our intention will be to explore the operational feasibility of using such tools for monitoring and quantifying carbon storage in larger trees. Our next step will also involve further refinement of our dashboard. Ideally, we would like to use ArcGIS Runtime SDK and Xamarin forms to develop Android and iOS applications that will be used by ground teams in locating trees and reporting their survival status in the long run. We intend to add features that will enable random sampling, which is a simple and yet highly effective approach of minimizing sampling bias in selecting trees to be included in the sample for monitoring and reporting survival. Another feature that we are going to add is the ability to capture photographs of the three locations. We hope that this will improve the transparency of reporting. Additionally, the captured photographs will provide valuable data that can be used later in developing machine learning models and this will deepen our understanding of factors that affect tree survival and tree management in general. These two tools will be useful in monitoring large-scale tree-planting programs.

Beyond monitoring tree survival, we would also like to expand the system to incorporate drone and satellite data to map the canopy of already established trees and quantify carbon storage in the trees. This will become a reliable tool for monitoring, verifying, and reporting commitments to carbon mitigation as stipulated in the Kyoto agreement. We are also going to establish partnerships with governments, non-profits, companies such as ESRI, and other entities that are interested in climate mitigation and pilot a project in Malawi, for a start.

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