Related Experiment Video
Updated: Jul 20, 2025
08:47
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
Published on: February 9, 2024
1.5K
Crop Identification Using Deep Learning on LUCAS Crop Cover Photos
Momchil Yordanov1, Raphaël d'Andrimont2, Laura Martinez-Sanchez2
1SEIDOR Consulting S.L., 08500 Barcelona, Spain.
Sensors (Basel, Switzerland)
|July 29, 2023
Summary
Computer vision accurately identifies major European crops from close-up photos using the largest in situ dataset. This method enhances agricultural monitoring by leveraging the Land Use Cover Area frame Survey (LUCAS) data for policy-relevant insights.
Area of Science:
- Agricultural Science
- Computer Vision
- Remote Sensing
Background:
- High-quality in situ data are crucial for Earth observation in agriculture.
- Traditional field surveying is resource-intensive.
- Computer vision offers a potential solution for automated crop recognition.
Purpose of the Study:
- To benchmark computer vision models for crop recognition using in situ photos.
- To utilize the largest multi-year labeled close-up photo dataset from the Land Use Cover Area frame Survey (LUCAS).
- To provide timely and accurate crop-specific information for agricultural policy.
Main Methods:
- Utilized a dataset of 169,460 labeled close-up crop images (2006-2018).
- Employed MobileNet hyper-parameterization and information theory for post-processing.
- Incorporated crop calendars to identify mature crop stages.
Main Results:
- The best model achieved a macro F1 (M-F1) of 0.75 on 8,642 test images.
- Information theory metrics improved performance by 6%.
- Optimal M-F1 of 0.82 was achieved using minimal auxiliary data.
Conclusions:
- Computer vision can effectively recognize major crops from close-up images.
- The LUCAS dataset is valuable for training and validating agricultural monitoring models.
- Methodology demonstrates potential for policy-relevant crop identification with minimal external data.
Related Concept Videos
02:16Light Acquisition
8.5K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.5K
01:28Methods of Classification and Identification
37
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
37
01:22Force Classification
1.3K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.3K