Soil Texture and Particle Segmentation Dataset
#Image segmentation #feature extraction #Soil analysis #agricultural monitoring #precision agriculture
- 15000 records
- 1.8G
- JPG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The current agricultural sector faces challenges in inadequate soil quality monitoring. Traditional soil analysis methods are often time-consuming and costly, making it difficult to meet the needs of precision agriculture. Existing solutions often lack sufficient precision and real-time capabilities, unable to effectively support agricultural decision-making. This dataset aims to provide high-quality semantic segmentation data on soil texture and particles to support automated image analysis technologies, enhancing the efficiency and accuracy of soil monitoring. Data collection is conducted using high-resolution cameras in different soil environments to ensure coverage of various soil types. In terms of quality control, we implemented multiple rounds of annotation and consistency checks, with annotation results reviewed by domain experts. Data is stored in JPG and JSON formats, organized in such a way that each image corresponds to one record, containing image data and its label information.
Dataset Insights
Sample Examples
838b16c0**.jpg|4528*3016|2.62 MB
f4f99164**.jpg|5760*3840|4.97 MB
e7982a94**.jpg|3963*5945|4.41 MB
ca8aae2b**.jpg|6000*4000|7.18 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| soil_type | string | The specific type of soil in the image, such as sand, loam, clay, etc. |
| particle_size_range | string | The size range of the particles in the image (e.g., fine, small, medium, large). |
| moisture_level | string | The moisture level of the soil in the image (e.g., dry, moist, wet). |
| color_variation | string | The color variation of the soil and particles. |
| particle_shape | string | The shape characteristics of the particles in the image (e.g., round, irregular, flaky). |
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 soil texture and particle segmentation dataset?
- The soil texture and particle segmentation dataset is a collection of images for semantic segmentation tasks involving soil texture and particles, aimed at improving the efficiency and accuracy of agricultural monitoring.
- What are the application scenarios for the soil texture and particle segmentation dataset?
- The dataset can be used in agricultural monitoring, soil research, and academic studies to enhance data analysis in crop management, soil remediation, and precision agriculture.
- How to use the soil texture and particle segmentation dataset for research?
- Researchers can use the images from this dataset to train deep learning models, improving the accuracy of soil texture and particle detection to optimize agricultural practices.
- What is the value of this dataset in the agricultural field?
- The dataset provides detailed soil texture information that can enhance decision-making in agricultural production, thus aiding in optimizing crop planting and resource allocation.
- How does the soil texture and particle segmentation dataset promote precision agriculture?
- By providing detailed information on soil and particle segmentation, this dataset helps farmers and researchers to more precisely analyze land characteristics and fertilization needs, promoting the development of precision agriculture.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Soil Texture and Particle Segmentation Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/74f7b733cdade993e0b677cd34968b3b},
urldate={2025-09-15},
keywords={Soil texture dataset, semantic segmentation, agricultural dataset, precision agriculture},
version={1.0}
}Using this in research? Please cite us.
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