Smart City Gnosys
Smart city article details
| Title | Urban Growth Analysis Using Multi-Temporal Remote Sensing Image And Landscape Metrics For Smart City Planning Of Lucknow District, India † |
|---|---|
| ID_Doc | 60006 |
| Authors | Maity N.; Mishra V.N. |
| Year | 2024 |
| Published | Engineering Proceedings, 82, 1 |
| DOI | http://dx.doi.org/10.3390/ecsa-11-20514 |
| Abstract | Rapid urbanization causes a high concentration of human population and economic activities that lead to the changes in landscape and spatial growth of the cities. Landscape features play a key role in understanding the land use and land cover (LULC) dynamics of urban areas. This work aims to analyze and quantify the changes in LULC over 24 years (1999 to 2023) in Lucknow District of India. It focuses on different land use types, including built-up area, cropland, water body, vegetation, and fallow land, using satellite imagery. Multi-temporal Landsat satellite data from the years 1999, 2008, 2015, and 2023 were employed to prepare LULC maps including major classes, namely built-up area, cropland, water body, vegetation, and fallow land. Several landscape metrics, such as number of patches (NP), patch density (PD), largest patch index (LPI), landscape shape index (LSI), edge density (ED), and total edge (TE), were calculated to analyze spatial patterns and changes in LULC categories. The study revealed significant changes in the landscape of Lucknow District, characterized by variations in the extent and distribution of the land use categories. Key findings include a remarkable increase in built-up area from 9.04% in 1999 to 25.91% in 2023 and a decrease in vegetation from 26.01% in 1999 to 11.71% in 2023. The PD and ED showed an increased fragmentation, especially in built-up areas where PD increased from 9.18 patches/100 ha in 1999 to 11.85 patches/100 ha in 2023. The LPI for built-up areas significantly grew, indicating larger continuous urban regions. The findings of this study emphasize the importance of monitoring landscape changes using multi-temporal remote sensing images over urban landscapes. Analyzing landscape metrics helps to understand the ongoing changes in LULC, providing essential information for effective sustainable land management practices. © 2024 by the authors. |
| Author Keywords | landscape metrics; LULC; remote sensing; sustainable development; urban growth |
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