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README.md

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+---
+tags:
+- Object Detection
+- Condition Recognition
+- Crop Monitoring
+- Agricultural Management
+- Environmental Monitoring
+license: cc-by-nc-sa-4.0
+task_categories:
+- object-detection
+language:
+- en
+pretty_name: Crop Waterlogging Condition Detection Dataset
+size_categories:
+- 1B<n<10B
+---
+
+# Crop Waterlogging Condition Detection Dataset
+
+The current agricultural sector faces challenges related to climate change and water resource management. The issue of crop waterlogging is becoming increasingly serious, affecting crop growth and yield. Existing monitoring methods largely rely on manual inspection, which is inefficient and prone to errors, unable to provide real-time feedback on crop status. This dataset aims to help AI systems quickly identify and predict crop waterlogging and hypoxia status through image data. Data is collected using drones and ground camera equipment in various fields and environmental conditions to ensure coverage of different growth stages and waterlogging scenarios. Regarding quality control, multiple rounds of annotation and expert review are conducted to ensure label consistency and accuracy. Data is stored in JPG format, organized by image ID, facilitating subsequent analysis and use. The core advantage of this dataset is its high annotation precision and consistency, with annotation accuracy exceeding 95%, significantly improving monitoring efficiency. Newly introduced image enhancement technology increases the model&#039;s robustness, allowing accurate waterlogging condition identification under various environmental conditions, helping farmers take timely actions to improve crop yield and address issues in practical production.
+
+## Technical Specifications
+
+| Field | Type | Description |
+| :---  | :---  | :--- |
+| file_name | string | File name |
+| quality | string | Resolution |
+| crop_type | string | Identify the type of crop appearing in the image, such as rice, wheat, etc. |
+| water_level | string | Identify the level of water flooding the crops, such as no flooding, mild flooding, moderate flooding, or severe flooding. |
+| crop_health | string | Evaluate the impact of flooding on crop health, such as healthy, damaged, or severely damaged. |
+| growth_stage | string | Identify the growth stage of crops, such as seedling stage, growth stage, or mature stage. |
+| soil_condition | string | Assess the moisture level or other visual characteristics of the soil. |
+| image_quality | string | Evaluate the clarity and quality of the image, such as clear, blurred, or too noisy. |
+| light_condition | string | Identify the lighting condition when the image was taken, such as bright or dim. |
+| weather_condition | string | Confirm the weather condition when the image was taken, such as sunny, cloudy, or rainy. |
+
+## Compliance Statement
+
+<table>
+  <tr>
+    <td>Authorization Type</td>
+    <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
+  </tr>
+  <tr>
+    <td>Commercial Use</td>
+    <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
+  </tr>
+  <tr>
+    <td>Privacy and Anonymization</td>
+    <td>No PII, no real company names, simulated scenarios follow industry standards</td>
+  </tr>
+  <tr>
+    <td>Compliance System</td>
+    <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
+  </tr>
+</table>
+
+## Source & Contact
+
+If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/ec271bf3a4be30ddafc48ff7283cfa3c?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com