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This handbook contains all the necessary information for participants of the event. If you have any queries about the materials provided or find a problem, please email helpdesk@joefennell.org
Through our partnerships with UKRI STFC, STFC Hartree Centre, IBM Research, and the Centre for Sustainable Agriculture we have identified a need to provide smallholder farmers with timely and location-specific advice about the crop types and varieties they should grow. Our challenge for the hackathon is to bring together hugely varied datasets - from market price data to soil maps - to design an integrated open access platform for recommending crop type, planting date and management advice for smallholder farmers in India.
More information about the e-Krishi project can be found in the pdf: SFN Hackathon-CSA-eKrishi-TRANSSITioN-SC.pdf
This data service is part of the Indian Open Government Data initiative and provides a large number of datasets across multiple sectors. It is important to register for an account as you will need an API Key to access the database.
Google Earth Engine allows you to access and process different geospatial datasets. The service is free with a limit on the amount of processing you can request.
Firstly, please read the code of conduct and the terms and conditions of entry. By participating in this event, you agree to adhere to the behaviour code and the terms and conditions.
Secondly, please make a note of the times of the two mandatory sessions: 10:00 - 11:00 GMT on Tuesday 2nd November and 14:15 - 16:15 GMT on Friday 5th November.
| Tuesday 2nd November | ||
|---|---|---|
| 10:00-10:30 GMT | Welcome and Introduction | Professor Sonal Choudhury |
| 10:30-11:00 GMT | Q&A: Technical/Practical Advice | Dr Joe Fennell |
| Friday 5th November | ||
| 14:00 GMT | Deadline for slide submission | send to helpdesk@joefennell.org |
| 14:15-15:30 GMT | Team pitch | |
| 15:30-16:00 GMT | Judging (offline) | |
| 16:00 - 16:15 GMT | Award |
Your team will produce a 10 minute pitch that showcases your idea and present this in the session on Friday. The format is up to you, but remember this is a pitch for funding, so you need to present a coherent argument for why and how your app will support the objectives of the project.
It could include :
- User Stories Descriptions of why and how your users will interact with the platform
- Results from the data experiments you carry out during the hackathon
- How the app will work This could include a description of analysis strategies
- Visualisations This could be example interfaces shown as mock-ups, wireframes or prototype demonstrations
- Management How your team will use the investment to produce the platform. How will you keep it running?
You must submit your slides by 14:00 GMT on Friday 5th of November (email slides or a link to helpdesk@joefennell.org). Slides submitted later than this will not be accepted, but you will still be able to pitch (without slides).
Alternatively, you are welcome to submit a video presentation of no more than 10 minutes by the slide deadline. This should be hosted on Youtube or Vimeo and cannot be edited after the deadline. Note that these services take time to process a video, so you should aim to upload an hour before the deadline. Please email the link as above.
We have included data gathered by project partners as well as relevant 3rd party geospatial data providers.
The following assumes you have a working Python Anaconda 3 installation and some experience of Jupyter Lab/Jupyter Notebook. If you do not have this, you can download and install Anaconda here and find learning resources on their webpages.
If you would like to run the tutorials, you will need to clone the repository and install the dependencies into a conda environment:
git clone git@github.com:joe-fennell/stfc-food-network-cop26-hackathon.git
cd stfc-food-network-cop26-hackathon
conda env create --file=environment.yaml
conda activate cop26You can now launch a Jupyter Labs server session:
jupyter labThis will start the server and open a web browser pointing to the correct url (normally http://localhost:8888/lab).
You will then be able to access the three notebooks (.ipynb file extension) included with this handbook.
This is a 4 year farm survey with the yield and crop type along with incomplete spatial information. The dataset is included in this repository at data/sample_data_gov_in.csv
| Field | Description | dtype |
|---|---|---|
| Year | Year of survey | int |
| Farmer Tracenet code | unique farmer code | str |
| Village | Village of farm | str |
| District | District of farm | str |
| State | State of farm | str |
| Latitude | Latitude of farm. Although may not be exact | float |
| Longitude | Longitude of farm (May not be exact) | float |
| Crops | Crop type | str |
| Area (HA) | Area of that crop type | float |
| Estimated yield | Weight of crop in metric tonnes | float |
You can find a quick introduction and example analysis in the notebook 1_Farm_survey_data.ipynb.
The data.gov.in website has over 300,000 datasets. Part of this hackathon is about exploring the breadth and quality of these data. The most relevant section is probably the agricultural markets section.
An example dataset is the Daily Market Prices of Garlic across India. The holding page is here: https://data.gov.in/resources/variety-wise-daily-market-prices-garlic-2021/api displaying the resource ID.
You can then make an API request over https to download a CSV. e.g.
Note that the
api-keyhas been set to a test key that limits the number of records to 10. You can replace this with the key in your user space (see section 2.2).
The response from this request is located in data/sample_data_gov_in.csv
There is a pip-installable package called datagovindia that offers a Python interface
to the data service: visit project pages.
We have not tested this.
Another option would be using the Requests library in Python to help you parse requests to the web service. You can find a short demonstration of retrieving data from the data.gov.in in the notebook 2_data_gov_india.ipynb
Your project may require soils data. One source is Soil Grids who provide a Web Mapping Service for various soil parameters. This is gridded at different spatial resolutions, but typically 250m.
You can access this in many different ways. One option would be the OWSLib Python interface. You can find a short demonstration of making a WMS request to the Soil Grids server in the notebook 3_SoilMap_WMS.ipynb.
Earth Engine is a tool giving access to many freely-available Remote Sensing datasets and allowing on-the-fly processing for various analyses. It can be accessed via the Code Editor GUI
Google Earth Engine Code Editor
Alternatively it can be accessed via the Python API. An introduction Jupyter Notebook to this can be found here that demonstrates how to authenticate and access Google Earth Engine resources.
A set of 7 CSV files have been previously generated by project partners for combining different agronomic datasets. These are located in data/agronomic/.
A PDF document has also been supplied containing yield-fertiliser relationships for a number of different crops. This is located at data/agronomic/eKrishi-Ferilizer Recommendation - yield equations.pdf
District polygons retrieved originally from here. The ESRI shapefile is located in data/geospatial/india_districts.shp
| Link | Type |
|---|---|
| Seednet | Crop groups and crops based on seednet |
| Crop Nutrition | Soil pH information |
| Natural Resource Conservation Service | Soil bulk density Information |
| FAO | Soil Classifications |
| AgroMonitoring | Alternative service for remotely-sensed imagery and weather data (polygon API) |
| Weather Stack | weather data |
| AccuWeather | weather data |
| Indian Weather Service | weather forecast data |
| Krishi | Agricultural study/monitoring data |
| Moqups | Wireframe and prototyping tools |