Automatic Creation of Fertility Maps in Precision Agriculture

One of the important problems in farming is to decide on variable fertilizer rates based on the inputs about varying soil types and some other factors. This is a key component for optimizing productivity and sustainability in precision agriculture. The main objective of this project is to use datasets captured by satellite imaging to develop computer algorithms for:
1. automatic creation of fertility maps to guide soil test points selection,
2. visual analytic tools to help agronomists to make decisions about variable fertilizer rates and yield goals of crops across multiple fields.

Faculty Supervisor:

Faramarz Samavati

Student:

Partner:

Decisive Farming Corp.

Discipline:

Computer science

Sector:

Agriculture and Food; Information and Communications Technology; Sustainability & the Environment

University:

University of Calgary

Program:

Accelerate

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