Research on Urban Land Use based on Remote Sensing Technology

Abstract

The advancement of urbanization has brought urban land use change into the spotlight of research. Remote sensing technology, as the primary means of capturing this change, provides valuable data for research. The main research object of this paper is the four classification methods of land use in cities based on remote sensing technology, and it outlines the main roles and applications of these four classification methods. This paper concludes that the visual interpretation method is less efficient but widely used. In addition, the accuracy of supervised classification and deep learning methods for classification is low. Unsupervised classification is simple, but the results differ greatly from reality. The above commonly used land classification methods have their advantages and disadvantages, and their combined use ensures that remote sensing technology provides real-time, effective, and comprehensive land use information for urban planning and management. Finally, this paper looks forward to the combination of remote sensing technology and modern technology, such as artificial intelligence. The integrated technology can provide more accurate and efficient technical support for future urban development.