Farmland Surface Water Detection Dataset
#object detection #image segmentation #water extraction #disaster monitoring #environmental monitoring
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-10-14
AI Analysis & Value Prop
The current agricultural sector faces many challenges in water monitoring and management, including water pollution and low irrigation efficiency. Traditional methods cannot quickly and accurately identify and assess water conditions. Existing solutions rely heavily on manual inspection and simple remote sensing image analysis, with low efficiency and insufficient accuracy. This dataset aims to provide high-quality data support for the application of AI technology in water extraction and disaster monitoring, addressing the limitations of traditional methods. Data collection is carried out using high-resolution cameras and remote sensing satellites, covering various climates and geographical environments to ensure data diversity and representativeness. To ensure data quality, multiple rounds of annotation, consistency checks, and expert reviews are implemented as quality control measures. Data is stored in JPG format with annotation information in JSON format to facilitate subsequent processing and analysis.
Dataset Insights
Sample Examples
a8794f9d**.png|1499*2000|3.85 MB
77b77642**.png|3045*2000|6.87 MB
956f7242**.png|1688*2000|3.98 MB
60453593**.png|1604*2000|2.94 MB
049fe30c**.png|2092*2000|3.96 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| water_body_type | string | The type of detected water body, such as pond, river, etc. |
| reflection_intensity | float | The intensity of light reflection on the surface of the water body. |
| image_brightness | float | The average brightness value of the image. |
| shadow_presence | boolean | Whether shadows are detected on the water body. |
| season | string | The season when the image was taken, such as spring, summer, etc. |
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 is the Agricultural Surface Water Detection Dataset?
- The Agricultural Surface Water Detection Dataset is an image data collection used for identifying and detecting surface water bodies in agriculture, containing annotated surface water information.
- What AI applications in agriculture is this dataset suitable for?
- This dataset is suitable for AI applications in agriculture such as automated detection of water resource management and irrigation system optimization.
- How to use this dataset for object detection?
- You can train object detection algorithms like YOLO or Faster R-CNN on the images in this dataset to detect water bodies in farmland.
- Why is surface water detection important in agriculture?
- Detecting surface water helps in effective water resource management, timely identification of water changes, improving irrigation, and enhancing agricultural productivity.
- What types of images does this dataset mainly include?
- This dataset mainly includes images of surface water bodies in agricultural settings, which are annotated for object detection tasks.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Farmland Surface Water Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/bd485274733ee853ec492500a56af46c},
urldate={2025-09-15},
keywords={farmland water detection, object detection dataset, water extraction, agricultural remote sensing},
version={1.0}
}Using this in research? Please cite us.
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