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tags:
  - Image classification
  - machine learning training
  - deep learning
  - Crop monitoring
  - disaster assessment
  - artificial intelligence applications
license: cc-by-nc-sa-4.0
task_categories:
  - image-classification
language:
  - en
pretty_name: Crop Flood Disaster Classification Dataset
size_categories:
  - 1B<n<10B

Crop Flood Disaster Classification Dataset

The current agricultural industry faces challenges of frequent flood disasters, making it difficult to quickly assess crop damage, affecting the stability of agricultural production and supply chains. Existing solutions largely rely on manual assessments which are inefficient and highly subjective, failing to meet the need for rapid response. This dataset aims to help AI models quickly assess damage by providing images of crops with varying levels of flooding, improving the accuracy and efficiency of post-disaster assessments. Data collection is performed using a combination of high-altitude drone photography and ground sampling under different weather conditions and geographic environments. All data undergo multiple rounds of annotation and consistency checks to ensure accuracy and reliability of the labels, and are ultimately stored and organized in JPG format to facilitate subsequent machine learning and data analysis.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
crop_type string Identify the type of crop in the image, such as rice, wheat, etc.
flood_severity string Determine the severity of flood impact based on the image, such as mild, moderate, and severe damage.
vegetation_health string Assess the health status of the crops through the image, such as normal, damaged, and dead.
lighting_condition string Identify the lighting conditions of the image, such as sunny, cloudy, or overcast.

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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com