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README.md

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+---
+tags:
+- object detection
+- image classification
+- land quality monitoring
+- ecological degradation risk assessment
+- agricultural management
+license: cc-by-nc-sa-4.0
+task_categories:
+- object-detection
+language:
+- en
+pretty_name: Land Degradation Monitoring Dataset
+size_categories:
+- 1B<n<10B
+---
+
+# Land Degradation Monitoring Dataset
+
+The current agricultural field faces land degradation issues, affecting crop production and ecological balance. Existing monitoring methods largely rely on manual inspection, which is inefficient and prone to omissions, making real-time monitoring difficult. The Land Degradation Monitoring Dataset aims to provide a set of high-quality image data to help AI systems effectively monitor land quality and ecological degradation risks. This dataset includes soil images collected from different regions, recording varying degrees of land cracking conditions and supports object detection tasks.
+Data collection was performed using drones under different climate conditions, covering various terrains. Each image underwent multiple rounds of annotation and consistency checks to ensure high data quality and accuracy. The data storage format is JPG, organized by image ID for easy subsequent processing and analysis.
+The core advantage of this dataset is its high annotation accuracy, with annotation consistency above 95% and data integrity over 90%. Novel annotation methods and data augmentation techniques were used to improve the model&#039;s generalization ability, effectively enhancing monitoring accuracy, and are expected to increase the accuracy of land degradation detection by 20%. Simultaneously, the size and diversity of the dataset provide researchers with a rich set of training samples, promoting the development of related technologies.
+
+## Technical Specifications
+
+| Field | Type | Description |
+| :---  | :---  | :--- |
+| file_name | string | File name |
+| quality | string | Resolution |
+| crack_degree | string | The degree of land cracking in the image, such as slight, moderate, severe. |
+| vegetation_coverage | float | The proportion of land vegetation coverage in the image. |
+| soil_color | string | The color of the soil in the image, such as red, brown, grey, etc. |
+| land_use_type | string | The type of land use depicted in the image, such as agricultural, barren land, etc. |
+
+## 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/6ebeb2cc2643939e1ea53157b93e4ceb?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com