Automatic Field Boundary Detection Using Neural Networks
Agriculture of the 21st century is facing difficult challenges: feeding the growing population in a sustainable way is not going to be easy. We at EOSDA understand this problem and keep coming up with more and more advanced technological solutions to help growers, agri-businesses, retailers, and various institutions on a global scale.
We use high-resolution imagery and powerful boundary detection algorithms developed by the EOSDA’s own experienced team of scientists to achieve a high level of detail in field delineation. Our models can be adjusted to any territory by incorporating locally obtained data from the clients.
How We Do It
We offer an accuracy of above 80% depending on region, image characteristics, and season.
This solution is tailored for projects exceeding 10,000 hectares of land.
We use the intersection over union (IOU) method of validating the results, i.e. comparing the field boundaries we've detected with the data received from the client.
Discover EOSDA Field boundaries detection solution
Accurate field delineation is the foundation for best crop management practices. Increase profits in a sustainable way with the EOSDA Field boundaries solution that facilitates land use planning, allows you to more effectively schedule sustainable and informed allocation of resources and generate insights into soil characteristics to optimize irrigation. EOSDA Team of RnD scientists and geospatial analysis experts have worked tirelessly to ensure accuracy of up to 90%, training the model on datasets from 10 different countries.
What You Get
Comprehensive Field Delineation
- Get detailed field boundary maps for large areas that make crop classification much easier. We offer maps in .shp and .geotiff formats alike.
Field Delineation And API
- Along with the field boundary maps, we offer fast and easy API access so you get all the information you need on particular fields of your clients.
High Accuracy
- Reliable satellite imagery and innovative field boundary detection algorithms ensure the high accuracy of field delineation.
Stand-alone & Combined
- We offer our field boundary detection as both a stand-alone solution and as the first stage for other EOSDA solutions, such as crop classification, advanced soil moisture analytics, yield prediction, and more.
Advantages Of EOSDA Field Delineation
Efficiency
Field boundary detection is carried out remotely and at an instant.
Completely Automatic
No hands are required to carry out the field delineation; the algorithms do the whole job themselves.
Up-to-date
The EOS SAT-1 allows us to use the latest satellite imagery ensuring the field boundary maps are up-to-date.
Country-level Accuracy
High level of detail ensured even over large territories, such as a country.
Field-size Delineation
Our algorithms are capable of detecting the boundaries of even the smallest fields.
Change Detection
Detect changes in the field outlines by comparing the new boundaries with the existing databases.
Scalability
We can train our field boundary algorithms for any location and resolution.
Compatibility
Our field boundary maps are in formats compatible with any other GIS software.
Ready Maps
Several field boundary maps are already available for you.
Field Delineation In Practice
Field boundary detection has many real-world applications:
For Governments
Governments and administrative institutions can use this solution to determine subsidies, stay up-to-date about the state of crops in the area of interest, monitor production efficiency, and more.
There is also a sustainability angle here as the accurate field boundary maps allow for ensuring the successful implementation of new agricultural regulations that reduce the negative impact on the environment.
Accurate field boundary maps provide the foundation of large and detailed databases on various aspects of the crops growing in these fields, such as crop rotation, chlorophyll content, and more.
Crop classification, yield estimation, and harvest dynamics monitoring, and other solutions based on precision field delineation can empower decision-makers, helping them cut expenses and increase profits.
Success Stories
The EOSDA Crop Monitoring platform employs its own innovative field delineation method using convolutional neural networks (CNN) and artificial intelligence (AI).
The method allows us to: Automatically detect croplands. Outline farm boundaries on the map. Determine the acreage of the cultivated area. Obtaining this data significantly improves the accuracy of crop classification on a large scale.
Boundaries of Sugarcane Fields Detected in Brazil
Ukraine. Field Boundary Mask example.
