Field Grass Navigation Dataset
#object detection #image segmentation #farmland monitoring #crop growth analysis #pest and disease detection
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-15
AI Analysis & Value Prop
The current agricultural industry faces challenges in crop health monitoring and weed management, particularly in large farmland areas where effective automated tools for detecting and classifying crops and weeds are lacking. Existing solutions often rely on manual monitoring, which is inefficient and prone to errors. Therefore, the Field Grass Navigation Dataset aims to provide high-quality annotated images to support research and applications in object detection and image segmentation. The dataset is constructed by capturing images in real farmland environments with high-resolution cameras, employing multiple rounds of annotation and expert reviews to ensure accuracy and consistency of annotations, and is stored in JPG format for convenient subsequent processing and analysis.
Dataset Insights
Sample Examples
3dac7dab**.jpg|4464*2976|2.59 MB
3b9193a5**.jpg|4000*2667|1.31 MB
d439b4e2**.jpg|5184*3456|3.85 MB
7968e0e8**.jpg|7360*4912|6.79 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| object_type | string | The type of agricultural-related object detected in the image, such as tractor, grassland, crops, etc. |
| object_count | integer | The number of agricultural-related objects in the image. |
| vegetation_density | float | The vegetation coverage of grassland or crops in the image, ranging from 0 to 1. |
| image_lighting | string | The lighting conditions of the image, such as sunny, cloudy, or nighttime. |
| weather_conditions | string | The weather conditions when the image was taken, such as sunny, rainy, or snowy. |
| tractor_presence | boolean | Indicates whether a tractor is present in the image. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What image information does the Field Grassland Navigation Dataset contain?
- The Field Grassland Navigation Dataset contains high-quality images of grassland and farmland areas in agricultural scenes, suitable for object detection tasks.
- How can the Field Grassland Navigation Dataset be applied in agricultural research?
- You can use this dataset for object recognition and environment perception research in agricultural scenes, assisting in the navigation of automated agricultural equipment.
- What machine learning algorithms are suitable for the Field Grassland Navigation Dataset?
- The dataset is primarily used for training and evaluating object detection algorithms such as YOLO, Faster R-CNN, etc.
- What are the potential agricultural applications of the Field Grassland Navigation Dataset?
- It can be used to develop agricultural robots for real-time crop growth tracking, weed detection, and precise pesticide spraying.
- How is the annotation quality of the Field Grassland Navigation Dataset?
- The dataset provides precise annotations to ensure the accuracy of the position and shape information of objects in the images.
- What role does the Field Grassland Navigation Dataset play in agricultural automation?
- The dataset provides training data for agricultural automation systems, improving algorithm performance in field navigation and crop monitoring.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Field Grass Navigation Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/6597484e88b9c69e5c37e13ea52b445a?cate=2},
urldate={2025-09-15},
keywords={agricultural dataset, object detection dataset, image recognition, farmland monitoring, grass navigation},
version={1.0}
}Using this in research? Please cite us.
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