The challenge we chose was the agriculture challenge. According to the challenge information, 'Our challenge is to demonstrate the agricultural socio-economic impacts from COVID-19, especially with regard to restriction of human movement in-country and internationally. How can you assess the impacts on agriculture production by using publicly available time series trend information, especially in the lower Mekong region for rice crops?' We decided to developed a website (https://eodash-beauraz.web.app/). Our website is our version of EODashboard which already include our Thailand planting activity activity data in.

For example, the graph showcasing the number of crops/agricultural level in a certain place against the amount of human movement will have a summary that the more human movement there is, the better agricultural level there is. We then give a reason why this is it. We may say that 'we can assume the reason behind this is because of the amount of import and export goods.

If there is more human movement, more goods can be exported; thus, increasing the agriculture level.' Other than this our project also has a function where farmers can check which crops should be planted in which humidity/ places. We use information from the EO dashboard and other sources to show where the best places to plant which crops should be.

I think our project is very important and could make a difference in this world because it helps ensure that the agricultural level will always be high. It also helps farmers stay motivated since there's a higher chance the crops will live. Other than this, people who want to learn more about our world can use our graphs to show the correlation between things and also learn about plants and crops. Thus, learning about how farmers live. We believe that our project can have a very big impact.

It can improve the EO dashboard so that it is more user-friendly and also contains more information so that users can access all of them in one place. Furthermore, it also helps solve one of the biggest problem in Thailand which is crops dying due to the changes in the environment. We linked our project to possible achieving at least one of the SDGs (Sustainable development goals) such as climate action(13) and life on land(15). We believe that our project will be able to change the world.

Our entire team is based in Thailand, thus close to the Mekong region. We wanted to create a project that impacts our own homeland, to make it a better place. As someone who has lived around farmers, we deeply understand the problem farmers face. We decided to use our combined knowledge and skills and this amazing opportunity to create a project that - other than fitting the challenge - can also possibly solve the problems occurring in our home.

At the beginning of the challenge, we have to admit we were very confused about what we had to do. However, we persevered and used our communication skills and teamwork skills to develop this project. Our approach to this project was that we had to create a particular program which could be a website, app or any other programs. We then would have to use data from the EO dashboard to create maps/graphs.

This program should then later be able to be implemented onto the EO dashboard for other people to use. The tools we used to develop our project is Mamp pro, Vue.js, Python, PHP and Visual studio code. Our website runs on a regular MacBook. Mamp pro is a local developer environment. Vue.js is a framework solely for developing UI. Python and PHP is a programming language. Visual studio code is an IDE.

I think our biggest problem was we weren't very experienced with some of the software we were using. We had a wide range of skills. We decided to split up the tasks and help each other in our own speciality. Our biggest achievement was definitely when we saw that the code finally ran. This may seem like a small achievement but it filled us with hope and excitement. This was the moment we saw what the possible future could hold for us.

Our entire body filled with pride and hope. I think our biggest challenge and problem was time. This hackathon was a race against time. We joined a bit later than we would like. We had problems finding a team. Therefore, we ended up doing this hackathon by ourselves. We had to balance the work that was meant for 5 people between 2 people. We had to finish it in 4-5 days (since we joined late). No matter what happens, I believe that we did an exceptional job at completing as much as we did considering all the factors against us.

We believe that everything can be improved, nothing is perfect. Therefore, if we had more time the things we would add to the dashboard are a prediction function and more data so that we can help the rest of the world. A prediction will come in handy because crops take a long time to grow, thus it will help farmers to predict when they should grow more crops and grow fewer crops since they can’t just stop planting because of the weather. This can be done by using the data provided by ESA, JAXA and NASA and finding a trend to predict data. Obviously, this problem doesn’t only occur in Thailand but also occurs in the rest of the world. We want to improve the world so that it can become a better place for everyone.

Therefore, if we had more data we could find a correlation and write about each crop growing in each area in each country. Other than this, we could also cross the data of each crops type and where it grows and in which temperature. This will help farmers a lot and reduce a lot of superstition that farmers rely on.

In this project, we used JAXA (Japan Aerospace Exploration Agency) and ESA. We gathered information from these two agencies and implemented it onto our EO dashboard. We found information about temperature, moisture, wildfires and much more from these agencies. We then use these data to find the correlation/ trend and write a summary. This data can then later be applied to other aspects of our daily life. Such as checking the temperature. In this case, we used the temperature to help farmers indicate whether their crops are able to grow to ensure the highest amount of productivity is achieved and that everything works efficiently. Both these agencies provided amazing information that gave us a new unique insight into the world. We wanted to improve the data in the best way that we can. So that the data is used to its fullest potential. The data gave us many different creative ideas for the project. By as Thai citizen, we wanted to relate it to our homeland. Thus, producing the website.

Google slide

https://docs.google.com/presentation/d/1saxWNONOI6_EePooT2FoC_WrPnQUgxtepmjRce_-BPA/edit?usp=sharing

Youtube demo

https://www.youtube.com/watch?v=PYf7z1t2edQ

Live demo (forced localhost version)

https://eodash-beauraz.web.app/

As shared via above Google slide, our Whole Thailand, Planting Activity - Thailand

NDVI (Sentinel-2 & GCOM) - time series at specific point (N 15.555608299178454, W100.93) is the data pulled from below GUI:

https://apps.sentinel-hub.com/eo-browser/

and

https://www.jpmap-jaxa.jp/jpmap/en/

raw output of the data provided in the slide.

Also we went above and beyond to put this data into EOdash of our local version. (You can see in Youtube demo of above section)

The project is already 80% done, we are only left with automating the Python script to pull data directly from Sentinel & GCOM API which could be done quiet given more time. (As mentioned the current demo is pulling from a static csv which was manually converted into JSON format)

http://www.oae.go.th

http://www.oae.go.th/assets/portals/1/fileups/forecastdata/files/forecast/situation/1S_RI.pdf 

http://www.oae.go.th/assets/portals/1/fileups/forecastdata/files/forecast/situation/2S_RN.pdf 

http://www.oae.go.th/assets/portals/1/files/calendar.pdf 

http://www.thairicemillers.org/images/%E0%B8%A3%E0%B8%B2%E0%B8%84%E0%B8%B2%E0%B8%82%E0%B9%89%E0%B8%B2%E0%B8%A7%E0%B9%80%E0%B8%89%E0%B8%A5%E0%B8%B5%E0%B9%88%E0%B8%A2%E0%B8%9B%E0%B8%B5%202562%20new.pdf 

http://www.thairicemillers.org/images/column_1621569076/%E0%B8%A3%E0%B8%B2%E0%B8%84%E0%B8%B2%E0%B8%82%E0%B9%89%E0%B8%B2%E0%B8%A7%E0%B9%80%E0%B8%89%E0%B8%A5%E0%B8%B5%E0%B9%88%E0%B8%A2%E0%B8%9B%E0%B8%B5%202563.pdf 

#argriculture

This project has been submitted for consideration during the Judging process.