Farmland Soil Moisture Estimation Dataset

#Object detection #image segmentation #Farmland management #precision agriculture #soil monitoring
  • 5000 records
  • 1.5G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-10

AI Analysis & Value Prop

The current agriculture industry faces challenges such as insufficient soil moisture monitoring, scattered data, and lack of precision management. Existing solutions mostly rely on traditional soil moisture measurement, which lacks real-time capability and accuracy, making it difficult to meet the needs of precision agriculture. This dataset aims to solve the real-time and accuracy issues of soil moisture monitoring by providing high-quality soil moisture estimation data, supporting intelligent agricultural decision-making. Data collection is done using high-resolution cameras under different climatic conditions, combined with soil moisture sensors for annotation. Quality control measures include multiple rounds of annotation and consistency checks to ensure data accuracy and reliability. The data is stored in JPG format, organized in a way that each sample is equipped with corresponding annotation information, facilitating subsequent model training and application.

Dataset Insights

Sample Examples

0141240e**.jpg|4528*3016|2.62 MB

56f00ecf**.jpg|6960*4640|6.85 MB

ed66acd4**.jpg|5760*3840|4.97 MB

3bf5fddd**.jpg|6000*4000|7.88 MB

Technical Specifications

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

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Cite this Work

@dataset{Mobiusiundefined,
  title={},
  author={Mobiusi},
  year={undefined},
  url={https://www.mobiusi.com/datasets/d33a20017fb938a66f69b00b81b66ef4},
  urldate={},
  keywords={},
  version={}
}

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