A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images
Technological advancement in smart cities can have adverse effects on the environment. Timely monitoring of smart cities to preserve environmental sustainability is a thrust area of research. It can be done by using change detection with multi-temporal satellite data. The success of these methods so...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/172519 |
| _version_ | 1811684494206304256 |
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| author | Pal, Ramen Mukhopadhyay, Somnath Chakraborty, Debasish Suganthan, Ponnuthurai Nagaratnam |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Pal, Ramen Mukhopadhyay, Somnath Chakraborty, Debasish Suganthan, Ponnuthurai Nagaratnam |
| author_sort | Pal, Ramen |
| collection | NTU |
| description | Technological advancement in smart cities can have adverse effects on the environment. Timely monitoring of smart cities to preserve environmental sustainability is a thrust area of research. It can be done by using change detection with multi-temporal satellite data. The success of these methods solely depends on the calibre of the backend image segmentation and Land-use Land-cover classification technique. The limitation of using cutting-edge classification algorithms is the availability of a proper dataset and identification of the edge structure of different LULC classes. In contrast, a segmentation algorithm cannot detect LULC classes automatically. In this research, we eliminated these shortcomings by considering a hybrid approach. We proposed a multi-class Support Vector Machine (SVM) and ISODATA-embedded large-scale change detection method. This method can automatically segment, detect, and perform LULC change analysis. We have considered the multi-sensor dataset of Barasat, West Bengal, India, obtained from the WorldView satellite sensor for the experimental study. The proposed method is validated concerning three different cutting-edge methods. |
| first_indexed | 2024-10-01T04:29:31Z |
| format | Journal Article |
| id | ntu-10356/172519 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:29:31Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1725192023-12-12T06:57:14Z A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images Pal, Ramen Mukhopadhyay, Somnath Chakraborty, Debasish Suganthan, Ponnuthurai Nagaratnam School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Smart City Change Detection Technological advancement in smart cities can have adverse effects on the environment. Timely monitoring of smart cities to preserve environmental sustainability is a thrust area of research. It can be done by using change detection with multi-temporal satellite data. The success of these methods solely depends on the calibre of the backend image segmentation and Land-use Land-cover classification technique. The limitation of using cutting-edge classification algorithms is the availability of a proper dataset and identification of the edge structure of different LULC classes. In contrast, a segmentation algorithm cannot detect LULC classes automatically. In this research, we eliminated these shortcomings by considering a hybrid approach. We proposed a multi-class Support Vector Machine (SVM) and ISODATA-embedded large-scale change detection method. This method can automatically segment, detect, and perform LULC change analysis. We have considered the multi-sensor dataset of Barasat, West Bengal, India, obtained from the WorldView satellite sensor for the experimental study. The proposed method is validated concerning three different cutting-edge methods. 2023-12-12T06:57:14Z 2023-12-12T06:57:14Z 2023 Journal Article Pal, R., Mukhopadhyay, S., Chakraborty, D. & Suganthan, P. N. (2023). A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images. IETE Journal of Research, 69(9), 5748-5754. https://dx.doi.org/10.1080/03772063.2022.2163928 0377-2063 https://hdl.handle.net/10356/172519 10.1080/03772063.2022.2163928 2-s2.0-85146235351 9 69 5748 5754 en IETE Journal of Research © 2023 IETE. All rights reserved. |
| spellingShingle | Engineering::Electrical and electronic engineering Smart City Change Detection Pal, Ramen Mukhopadhyay, Somnath Chakraborty, Debasish Suganthan, Ponnuthurai Nagaratnam A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images |
| title | A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images |
| title_full | A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images |
| title_fullStr | A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images |
| title_full_unstemmed | A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images |
| title_short | A hybrid algorithm for urban LULC change detection for building smart-city by using Worldview images |
| title_sort | hybrid algorithm for urban lulc change detection for building smart city by using worldview images |
| topic | Engineering::Electrical and electronic engineering Smart City Change Detection |
| url | https://hdl.handle.net/10356/172519 |
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