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Abhishek Sharma, Mandeep Singh, Mohit Srivastava, Pradeep Kumar Gaur, Gagandeep Kaur, Priyanka Sood, Dinesh Kumar,
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- Associate Professor, Associate Professor, Associate Professor, Associate Professor, Associate Professor, Associate Professor, Associate Professor Electronics & Communication Engineering Department, Chandigarh Engineering College (CEC-CGC), Landran, Electronics & Communication Engineering Department, Chandigarh Engineering College (CEC-CGC), Landran, Electronics & Communication Engineering Department, Chandigarh Engineering College (CEC-CGC), Landran, Electronics & Communication Engineering Department, Chandigarh Engineering College (CEC-CGC), Landran, Electronics & Communication Engineering Department, Chandigarh Engineering College (CEC-CGC), Landran, Electronics & Communication Engineering Department KIET Group of Institutions, Delhi-NCR, Ghaziabad, Electronics & Communication Engineering Department KIET Group of Institutions, Delhi-NCR, Ghaziabad Punjab, Punjab, Punjab, Punjab, Punjab, Uttar Pradesh, Uttar Pradesh India, India, India, India, India, India, India
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Abstract
nNatural phenomena including weathering, erosion, volcanic eruptions, and plate tectonics, as well as human activities like agriculture, deforestation, and urbanization, cause the Earth’s surface to change continuously. In many different applications, such as environmental monitoring, disaster management, urban planning, agriculture and forestry, climate change studies, resource management, and infrastructure monitoring, it may be extremely beneficial to detect and track these changes. There are various algorithms and methods proposed by many researchers which can detect the change by comparing the images captured at different times. In this paper, a comparison of various change detection methods using images processing has been made and their performance has been compared on the basis of various parameters like accuracy, kappa coefficients, false alarms etc. Change detection in high-resolution photos has drawn a lot of interest because it can be used in a variety of scenarios, including environmental monitoring, urban planning, and disaster relief. A comparison of several change detection techniques applied to high-resolution images is presented in this article. We explore the workings, elements, and uses of different approaches, emphasising their advantages and disadvantages. A thorough conclusion on the best use of each strategy is provided after providing insights into the efficiency of these techniques in various settings in the discussion section.
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Keywords: Discrete wavelet transform, Climate change, kappa coefficients, discrete wavelet transform, Image Clustering Method.
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Remote Sensing & GIS(jorsg)]
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| Volume | 15 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | June 15, 2024 | |
| Accepted | July 15, 2024 | |
| Published | August 17, 2024 |
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