Detecting Cadastral Boundary from Satellite Images Using U-Net model

Neda Rahimpour Anaraki, Maryam Tahmasbi, Saeed Reza Kheradpisheh
2/16/2025
cs.CVcs.LG

No confident code implementation found for this paper.

Abstract

Finding the cadastral boundaries of farmlands is a crucial concern for land administration. Therefore, using deep learning methods to expedite and simplify the extraction of cadastral boundaries from satellite and unmanned aerial vehicle (UAV) images is critical. In this paper, we employ transfer learning to train a U-Net model with a ResNet34 backbone to detect cadastral boundaries through three-class semantic segmentation: "boundary", "field", and "background". We evaluate the performance on two satellite images from farmlands in Iran using "precision", "recall", and "F-score", achieving high values of 88%, 75%, and 81%, respectively, which indicate promising results.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Multi-Region Transfer Learning for Segmentation of Crop Field Boundaries in Satellite Images with Limited Labels

84% match2024

Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source

83% match2025

Deep Learning for automated multi-scale functional field boundaries extraction using multi-date Sentinel-2 and PlanetScope imagery: Case Study of Netherlands and Pakistan

83% match2024

fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model

83% match2025

Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagery

83% match1 repo1382025

Convolutional Neural Network Segmentation for Satellite Imagery Data to Identify Landforms Using U-Net Architecture

82% match2025

Cite this paper

@article{anaraki2025detecting,
  title  = {Detecting Cadastral Boundary from Satellite Images Using U-Net model},
  author = {Neda Rahimpour Anaraki and Maryam Tahmasbi and Saeed Reza Kheradpisheh},
  year   = {2025},
  eprint = {2502.11044},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.11044v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2502.11044.svg)](https://codeofpaper.com/paper/2502.11044)

Discussion