JAXA MENA Region Climate Change Impact Challenge | bitgrit
Competition banner

JAXA MENA Region Climate Change Impact Challenge

Predict vegetation index on the MENA Region

13 days to go
267 Participants
226 Submissions
bitgrit linkedin

Welcome to the JAXA MENA Region Climate Change Impact Challenge!

In the critical arena of climate research, understanding and mitigating the effects of climate change in the Middle East and North Africa (MENA) region has never been more crucial. With the MENA region facing unique environmental challenges, exacerbated by its vulnerability to climate variability, the quest for innovative solutions is paramount.

This backdrop sets the stage for a groundbreaking initiative by bitgrit. As part of its commitment to fostering cutting-edge research and community engagement, bitgrit is proud to collaborate with the Japan Aerospace Exploration Agency (JAXA) to launch this challenge, aimed at leveraging satellite data to predict the Vegetation Index. This key indicator of vegetation health stands at the core of our competition, reflecting the broader implications of climate change on the region's ecosystems.

This challenge emerges at a pivotal moment, inviting participants from around the globe to delve into a rich dataset that includes variables like land temperatures, ground moisture, precipitation, and more, spanning up to the year 2024. With the dual goals of advancing scientific understanding and promoting practical applications, this competition is a clarion call to data scientists, climate researchers, and environmental advocates. Whether you're deeply entrenched in the field of climate science or a data enthusiast eager to apply your skills to a cause of global importance, the JAXA MENA Region Climate Change Impact Challenge offers a unique platform to contribute to meaningful climate action.

In the spirit of bitgrit's mission to drive innovation and community-building, we invite you to join this critical endeavor, leveraging your expertise to illuminate the impacts of climate change and explore sustainable futures for the MENA region.


1st Prize: $1500

2nd Prize: $1000

3rd Prize: $500


Competition Starts: 05/04/2024

Competition Ends: 05/08/2024

Winners Announcement: 27/08/2024

Data Breakdown

The dataset is composed of satellite data over a rectangular box of geographical coordinates denoting the MENA Region (Middle East and North Africa) as well as a portion of Southern Europe. This is organized into different climate-related measurements taken from space over the same bounding box, each of which is sampled monthly across a time period that goes between the year 2000 to the year 2023 (although with some variations).

These measurements are:
- Land Temperature
- Aerosol Depth
- Ground Moisture
- Precipitation (Rain)
- Shortwave Radiation
- Vegetation Index

The last measurement--Vegetation Index--corresponds to the target variable of this data science problem. The values for which this variable has to be predicted correspond to the same MENA Region bounding box over the following dates:
- 2023-09-01
- 2023-12-01
- 2024-03-01

The values to be predicted are specified on the submission_format.csv file, which contains one index column and one value column. 
The format of the index column is the following: YYMMDD-(LAT:LONG) where YYMMDD is one of the above dates (in order) and LAT/LONG are Latitude (Rows/Index of the other files) and Longitude (Columns/Header of the other files), respectively.
The format of the value column should simply be the value of the Vegetation Index, with -1 denoting null/NaN values (for example, the ocean). An error will occur is this rule is not respected.

For each one of the measurements in the dataset, and as per the above paragraph, the first column (index) indicates the LATITUDE and the first row (header) indicates the LONGITUDE in the geographical coordinate system.
Null/NaN values indicate invalid measurements (like the Ocean). Note that when predicting that a certain geographical point is null it should be set to -1.

Due to differences in the resolution of the satellite images, some measurements have smaller resolution over the same coordinate space. Keep this in mind when working with this data. The resolution for the measurements (including Null/NaN values) is described as:
- Vegetation Index, Aerosol Depth, Land Temperature, Shortwave Radiation: 1659 x 610
- Precipitation, Ground Moisture: 829 x 305

The evaluation metric for this competition is based on RMSE (Root Mean Squared Error). Specifically, exp(-RMSE). 

Due to the big file sizes that submissions for this competition will have, each participant will be limited to 3 submissions per day. For the same reason, please be patient when submitting a new file.

You are free to use your creativity for this challenge (but always abide by the rules). This is a data science competition, which means that you need to make use of all your data skills to make the most use of the available data.

Good luck and Have fun!

Who do I contact if I need help regarding a competition?
For any inquiries, please contact us at [email protected]
How will I know if I've won?
If you are one of the top three winners for this competition, we will email you with the final result and information about how to claim your reward.
How can I report a bug?
Please shoot us an email at [email protected] with details and a description of the bug you are facing, and if possible, please attach a screenshot of the bug itself.
If I win, how can I receive my reward?
Prizes will be paid by bank transfer. If for some reason you are not able to accept payment by bank transfer, please let us know and we will do our best to accommodate your needs as possible.
  1. This competition is governed by the following Terms of Participation. Participants must agree to and comply with these Terms to participate.

  2. Users can make a maximum number of 3 submissions per day. If users want to submit new files after making 3 submissions in a day, they will have to wait until the following day to do so. Please keep this in mind when uploading a submission.csv file. Any attempt to circumvent stated limits will result in disqualification.

  3. The use of external datasets is strictly forbidden.

  4. It is not allowed to upload the competition dataset to other websites. Users who do not comply with this rule will be disqualified.

  5. A competition prize will be awarded after we have received, successfully executed, and confirmed the validity of both the code and the solution (See 6.). Once winners are announced and our team reaches out to them, the winners must provide the following by June 10, 2024 to be qualified as a competition winner and receive their prize:

    • All source files required to preprocess the data

    • All source files required to build, train and make predictions with the model using the processed data

    • A requirements.txt (or equivalent) file indicating all the required libraries and their versions as needed

    • A ReadMe file containing the following:

      1. Clear and unambiguous instructions on how to reproduce the predictions from start to finish including data pre-processing, feature extraction, model training, and predictions generation

      2. Environment details regarding where the model was developed and trained, including OS, memory (RAM), disk space, CPU/GPU used, and any required environment configurations required to execute the code

      3. Clear answers to the following questions:

        • Which data files are being used?

        • How are these files processed?

        • What is the algorithm used and what are its main hyperparameters?

        • Any other comments considered relevant to understanding and using the model

  6. The submitted solution should be able to generate exactly the same output that gives the corresponding score on the leaderboard. If the score obtained from the code is different from what’s shown on the leaderboard, the new score will be used for the final rankings unless a logical explanation is provided. Please make sure to set the seed or random_state etc. so we can obtain the same result from your code.

  7. The final submission has to be selected manually before the end of the competition (you can select up to 2), or else it will be selected automatically based on your highest public score.

  8. In order to be eligible for the prize, the competition winner must agree to transfer to the Host and the relevant transferee of rights in such Competition all transferable rights, such as copyrights, rights to obtain patents and know-how, etc. in and to all analysis and prediction results, reports, analysis and prediction model, algorithm, source code and documentation for the model reproducibility, etc., and the Submissions contained in the Final Submissions.

  9. Any prize awards are subject to eligibility verification and compliance with these Terms of Participation. All decisions of bitgrit will be final and binding on all matters relating to this Competition.

  10. Payments to winners may be subject to local, state, federal and foreign tax reporting and withholding requirements.

  11. If two or more participants have the same score on the leaderboard, the participant who submitted the winning file first will be considered the winner.

  12. All submissions must be made individually; no teams are allowed in this competition. Users who do not comply with this rule will be immediately disqualified in the case that we find the same or very similar scores and/or uploaded solutions.

  13. If you have any inquiries about this competition, please don’t hesitate to reach out to us at [email protected].

New Submission
Step 1
Upload or drop your file
Upload or drop your csv file here.
Your submission should be in .csv format.
Step 2
Briefly describe your submission (400 characters or less)
3 submission(s) left

Thanks for your submission!

We'll send updates to your email. You can check your email and preferences here.
My Submissions