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Updated: Sep 19, 2025

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Parcel-level vector data for scaled land utilization analysis in Xinjiang based on remote sensing image.

Wei Wu1, Yikai Zhao2, Liao Yang3

  • 1Zhejiang University of Technology, College of Geoinformatics, Hangzhou, 310014, China. wuwei@zjut.edu.cn.

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|June 16, 2025
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Summary

This study introduces a new vector dataset for cultivated land in Xinjiang, improving accuracy for agricultural analysis. The novel method enhances land parcel extraction from satellite imagery, aiding decision-making.

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Area of Science:

  • Agricultural Science
  • Remote Sensing
  • Geographic Information Systems (GIS)

Background:

  • Optimizing agricultural development requires accurate spatial quantification of cultivated land.
  • Xinjiang, a key Chinese grain region, faces challenges due to its unique geography and fragile environment.
  • Existing cultivated land studies often use outdated raster data, limiting precision.

Purpose of the Study:

  • To develop a high-accuracy, vector-based cultivated land dataset for Xinjiang.
  • To introduce an advanced parcel extraction methodology for improved land use analysis.
  • To provide a reliable dataset for agricultural decision-making and land management.

Main Methods:

  • Utilized Sentinel-2 imagery (10-meter resolution) from the Copernicus Open Access Hub.
  • Developed a novel parcel extraction technique integrating Swin Transformer and DiffusionEdge.
  • Employed multi-scale semantic analysis and fine boundary detail capture for enhanced accuracy.

Main Results:

  • Generated a practical and up-to-date vector dataset of cultivated land in Xinjiang.
  • Achieved enhanced accuracy in land parcel extraction compared to traditional methods.
  • Validated the dataset's reliability and applicability through technical analysis.

Conclusions:

  • The proposed methodology offers a replicable approach for robust cultivated land extraction.
  • The new vector dataset supports precise, parcel-wise cultivated land analysis.
  • This work contributes to improved agricultural management and decision-making in Xinjiang.