Detection and Prediction of Soil Nutrient Deficiency using Satellite Imagery (Part I)

Start Date: July 17, 2022 | 4 years ago

Challenge Background

Goal of the Project

1. Extract and process the satellite data available from our partner institutions and organizations (NASA, UNWP, FAO, Worldbank, local organizations and other possible sources). Here are the suggested data to be extracted from the satellite imagery: a. Nitrogen b. Phosporous c. Soil Erosion d. Precipitation 2. Educate our volunteers about how to extract and process a satellite Imagery Ideate and create a solution pipeline to build a dashboard that detects and predicts soil nutrient deficiency. Here the some guidelines for this goal: a. What other data do we need to build the model? b. What model(s) to utilize? c. What technology to utilize? 3. Prepare the volunteers for the upcoming part 2 of the challenge

Project Timeline

What you'll learn

First Omdena Local Chapter Project?

Beginner-friendly, but also welcomes experts

Education-focused

Duration: 4 to 8 weeks

Open-source

Your Benefits

Address a significant real-world problem with your skills

Build your project portfolio

Access paid projects (as an Omdena Top Talent)

Get hired at top organizations

Requirements

Good English

Suitable for AI/ Data Science beginners but also more senior collaborators

Learning mindset

Application Form

Application Closed.