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file_name
stringclasses
4 values
quality
stringclasses
4 values
crop_type
stringclasses
3 values
flood_severity
stringclasses
3 values
vegetation_health
stringclasses
2 values
lighting_condition
stringclasses
2 values
3a92512e20e7074248b93db6c4522ce4.png
3045*2000
corn
severely affected
damaged
cloudy
4405370e3f0d5e670920078ec3c26a89.png
1499*2000
corn
moderately affected
damaged
cloudy
7fb94efd5a2f8c23bb4aad224bf69fb9.png
2092*2000
Corn
Severely affected
Damaged
Cloudy
d5500e67d0c33cff0a89e6000ec0fd68.png
1604*2000
rice
severely affected
damaged
cloudy

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

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