Inspiration
Our inspiration is small scale farmers or growing hobbyists who want to make a impact on their environment by applying regenerative soil practices without the need for environmental scientists and consultants for advice on a decades timescale.
What it does
We receive input from the user about their address/location and find corresponding data about the soil in that region. We used data about soil from the Soil Survey Geographic (SSURGO) to determine the soil order and suborder for them. Using this, we provide recommendations and tips for soil regeneration.
How we built it
We built the backend using Python and the frontend using React. Using the address we received from the user, we use geocoding to get the exact coordinates of their location. We then map their coordinates to our data to find the order and suborder of their soil. We use this information to generate a response that provides them with the required soil regeneration recommendation.
Challenges we ran into
We found it difficult to find and sort through large sets of data and map the correct coordinates against our data.
Accomplishments that we're proud of
We are proud of having a working product that that effectively connects users with their local soil information and provides actionable recommendations for regenerative practices. Our successful integration of various technologies, such as geocoding and geographic data analysis, has enabled us to create a user-friendly platform that empowers small-scale farmers and hobbyists. Additionally, we’ve streamlined the process of accessing complex soil data, making it more accessible and understandable for our target audience.
What we learned
We learned how to use and read .shp files, how to use APIs such as geocoding
What's next for Soil Regeneration
We hope to be able to give users a more detailed recommendation perhaps by also analyzing weather data in their region.
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