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Smart city article details
| Title | A Hybrid Algorithm For Urban Lulc Change Detection For Building Smart-City By Using Worldview Images |
|---|---|
| ID_Doc | 2122 |
| Authors | Pal R.; Mukhopadhyay S.; Chakraborty D.; Suganthan P.N. |
| Year | 2023 |
| Published | IETE Journal of Research, 69, 9 |
| DOI | http://dx.doi.org/10.1080/03772063.2022.2163928 |
| Abstract | 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. |
| Author Keywords | Change detection; ISODATA; Multi-class SVM; Smart city; VHR MS image |
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