Performance analysis of change detection techniques for land use land cover

Aarti Karandikar, Avinash Agrawal


Remotely sensed satellite images have become essential to observe the spatial and temporal changes occurring due to either natural phenomenon or man-induced changes on the earth’s surface. Real time monitoring of this data provides useful information related to changes in extent of urbanization, environmental changes, water bodies, and forest. Through the use of remote sensing technology and geographic information system tools, it has become easier to monitor changes from past to present. In the present scenario, choosing a suitable change detection method plays a pivotal role in any remote sensing project. Previously, digital change detection was a tedious task. With the advent of machine learning techniques, it has become comparatively easier to detect changes in the digital images. The study gives a brief account of the main techniques of change detection related to land use land cover information. An effort is made to compare widely used change detection methods used to identify changes and discuss the need for development of enhanced change detection methods.


change detection; deep learning; land use land cover; post classification; remote sensing;

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).