Soil Moisture Cycle Change Dataset
#object detection #image classification #agricultural monitoring #soil management #environmental research
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-14
AI Analysis & Value Prop
The current agricultural sector faces the challenge of insufficient monitoring of soil moisture changes, with existing methods often relying on manual measurements that are inefficient and lack accuracy. Traditional solutions cannot reflect the dynamic changes of soil in real-time during data collection, affecting crop management and decision-making. This dataset aims to provide a comprehensive soil moisture cycle change monitoring solution through high-quality image data, meeting the modern agricultural need for precise data. Data collection uses high-resolution cameras combined with professional soil moisture sensors, capturing in various environmental conditions to ensure diversity and authenticity of the data. For quality control, a multi-round annotation and expert review approach is adopted to ensure data accuracy. Data is stored in JPEG format, organized by time and location for easy subsequent analysis and use.
Dataset Insights
Sample Examples
5700fdb9**.jpg|4048*3032|4.15 MB
6503b084**.jpg|5760*3840|4.97 MB
9a546e15**.jpg|6000*4000|7.88 MB
cb7cedd8**.jpg|3963*5945|4.41 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| soil_type | string | Identify the specific type of soil, such as sandy soil, loam, clay, etc. |
| wetness_level | string | The level of soil wetness, such as dry, moist, very wet, etc. |
| texture | string | The textural characteristics of the soil surface, such as rough, smooth, etc. |
| color | string | The color of the soil, represented using standard color names. |
| vegetation_presence | boolean | Indicates if there is vegetation (such as grass, plants) present in the image. |
| crack_presence | boolean | Indicates if cracks can be observed on the soil surface. |
| light_exposure | string | The light exposure condition of the soil in the image, such as sunlight, shadow, etc. |
| particle_size | string | The size characteristics of soil particles, such as fine, small, medium, etc. |
| compaction | string | The degree of soil compaction, such as loose, firm, etc. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 main purpose of the Soil Moisture Cycle Variation Dataset?
- The dataset is primarily used for studying and monitoring the soil moisture cycle variations, which are crucial for soil management and crop cultivation in agriculture.
- How can this dataset help improve agricultural production?
- By analyzing soil moisture cycle variations, irrigation plans can be optimized and crop yield can be enhanced, thereby improving agricultural production efficiency.
- What are the features of the image data in the Soil Moisture Cycle Variation Dataset?
- The images in the dataset display visual changes in soil under different moisture levels, aiding in accurate detection and analysis of soil moisture conditions.
- How to use the dataset for object detection research?
- Researchers can utilize the image data within the dataset to train and validate object detection models to identify soil features under varying moisture conditions.
- What are the practical applications of this dataset in agricultural monitoring?
- The dataset can be used for real-time monitoring of soil moisture changes, providing decision support to farmers in developing effective irrigation strategies.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Soil Moisture Cycle Change Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/91bd2f70644d703eaf4622a3cc2af2c8?cate=2},
urldate={2025-09-15},
keywords={soil moisture changes, agricultural dataset, object detection, soil monitoring, environmental research},
version={1.0}
}Using this in research? Please cite us.
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