Method and system for identifying rural idle land potential

By combining high-resolution remote sensing imagery and the YOLO-SEG model with ArcGIS methods, the potential of idle rural land is automatically identified, solving the problems of low efficiency and poor accuracy of traditional manual identification, and achieving efficient and accurate identification of idle land.

CN122067097APending Publication Date: 2026-05-19GUANGXI ZHUANG AUTONOMOUS REGION NATURAL RESOURCES ECOLOGICAL RESTORATION CENT
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Patent Information

Application Number
CN202610145687.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-02
Publication Date
2026-05-19

AI Technical Summary

Technical Problem

Existing traditional potential identification methods rely on manual processing and visual interpretation, resulting in low efficiency and poor accuracy in identifying idle rural land. They are unable to quickly identify different roof types, lack intelligence, and cannot use detailed thresholds as a reference.

Method used

High-resolution remote sensing image data was used to identify rooftops using the YOLO-SEG model. Data processing and potential land parcel screening were performed using ArcGIS. The proportion of tiled roof area was used as the judgment threshold to generate vector files containing potential land parcels.

Benefits of technology

It significantly improves the accuracy and consistency of identifying the potential of idle land, avoids human bias, realizes automated and intelligent identification, and enhances identification efficiency and scientific rigor.

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Abstract

The invention relates to the technical field of urban and rural construction, and discloses a method and system for identifying rural idle land potential, and the method comprises the steps: obtaining a high-resolution remote sensing image of a target area and a corresponding rural residence map layer, carrying out the contour marking of a roof in the remote sensing image according to a preset roof category system, generating a marking text with category information, and carrying out the recognition of the rural idle land potential. Converting the annotation file into a normalized coordinate format required by a target detection model, training a YOLO-SEG model, carrying out roof identification on cut image tiles, outputting contour and category results, carrying out statistics on the tile roof area proportion in each construction map spot, judging a land parcel of which the proportion exceeds a set proportion as an idle land potential land parcel, and carrying out the detection of the idle land potential land parcel. According to the invention, by integrating the remote sensing image and the GIS data and through the YOLO-SEG artificial intelligence model, the accuracy and consistency of the recognition result are significantly improved, the subjective deviation caused by the experience difference of personnel is avoided, and the recognition efficiency of the rural idle land potential is improved.
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