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Research on Land Utilization Spatial Classification Planning Method Based on Multiocular Vision.

Zhifei Zhang1,2, Shenmin Wang3

  • 1School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China.

Computational and Mathematical Methods in Medicine
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Summary

This study introduces a novel neural network algorithm for urban land use classification, crucial for China

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Area of Science:

  • Urban Planning and Remote Sensing
  • Geospatial Data Analysis
  • Artificial Intelligence in Environmental Science

Background:

  • Rapid urbanization in China necessitates effective land use spatial planning.
  • Current land use classification methods face challenges with high-resolution remote sensing data and feature deformation.
  • Accurate land use classification is vital for sustainable development and strategic implementation.

Purpose of the Study:

  • To improve the land use spatial classification system within urban planning frameworks.
  • To address limitations in current classification algorithms, particularly with limited labeled data and feature deformation.
  • To propose a robust and accurate land use classification method for high-resolution remote sensing images.

Main Methods:

  • Development of a neural network-based land use classification algorithm.
  • Utilizing multiscale adaptive fusion of convolutional layer features to mitigate feature deformation.
  • Employing depth features from a pretraining network for enhanced feature extraction and fine-tuning with an augmented dataset.

Main Results:

  • The proposed multiscale adaptive fusion method effectively reduces the impact of feature deformation on classification accuracy.
  • Pretraining and fine-tuning the network significantly improved classification performance.
  • The adaptive fusion approach demonstrated superior fusion effects and enhanced overall accuracy in land use spatial classification.

Conclusions:

  • The developed neural network algorithm offers a significant advancement in urban land use classification accuracy.
  • This method provides a valuable reference for improving land use spatial planning and classification systems.
  • Effective land use classification is essential for guiding sustainable urban development and resource management.