Urban Growth Monitoring using Remote Sensing and Geo-Informatics: Case Study of Gandhinagar, Gujarat State (India)

Abstract

The Gandhinagar town has undergone unprecedented urban growth after assuming the status of a capital of Gujarat state, India in 1971. The Gandhinagar city lies on the western bank of river Sabarmati and city is also known as the "Tree capital of India" because of greenery with 54% green cover. The urban sprawl in Gandhinagar town was analyzed using multi-temporal Landsat TM data from 1981 to 2015. Spectral indices namely Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI) and Built-up Index (BUI) were generated from the Landsat TM bands covering visible Red (R), Near Infrared (NIR) and Short Wave Infrared (SWIR) wavelength regions. Spectral variations in built-up, open spaces, urban vegetation and water areas were studied by generating two-dimensional spectral plots of NDBI and BUI. The spectral response of built up areas like Urban-dense and urban-sparse classes are quite distinct from other cover types like open spaces, urban vegetation and water. The results indicate that the normalized difference built-up index (NDBI) and Built-up Index (BUI) were very useful for mapping urban built-up areas in Gandhinagar town using Landsat Thematic Mapper (TM) data. The built-up area in Gandhinagar increased from 1100

Urban sprawl impact assessment on the land surface temperature over the green capital of Gujarat using a geo-spatial approach

“…54% (Badlani et al, 2017). The district is situated between latitude 22° 56' N to 23° 36' N and longitude 72° 23' N to 73° 05' N (Figure 1) and has four talukas (Mansa, Kalol, Gandhinagar and Dehgam).…”

Observed changes in rainfall extremes and current trends in Gandhinagar, Gujarat

“…Gandhinagar is the capital of Gujarat state situated between 22° 56' S to 23° 36' S (longitude) and 72° 23' N to 73° 05' N (latitude). It has around 54% of green area thus also known as the "Green capital of India" (Badlani et al, 2017) and has a total area of 2140 km 2 . Since the majority of Gujarat falls under arid and semi-arid climatic conditions, it has only seasonal rivers such as Sabarmati, Khari and Meshwo (Purswani et al, 2022).…”

Assessing Spatiotemporal Built-up Dynamics in Chiang Mai City, Thailand using Entropy approach

“…Remotely sensed data is an e cient database resource to extract a piece of various information's regarding urban management and sustainable planning (Kadhim et al, 2016) through space and time. It provides an enhancement in terms of spatial, temporal, radiometric, and spectral resolution (Hamedianfar & Shafri, 2015), large area coverage (Badlani et al, 2017a), cost effective, detection of landscape dynamics at subpixel level (Hamedianfar & Shafri, 2015;Raziq et al, 2016), and availability of multi-time series archival data. Previous study applied ASTER (Jianwen and Bagan, 2005), IKONOS (Zhang and Wang, 2003), SPOT 5 (Lu et al, 2012), RADARSAT-1 and ENVISAT SAR (Xu, 2007), Sentinel (Abdulhakim Mohamed, 2019) and Landsat (Alam et al, 2019) to monitor urban changes at separate regions.…”

“…Among various sensors, Landsat was commonly used to analyze urban sprawl and performed built-up pattern at provincial level with considerable accuracy, because of free charge, a long temporal resolution from 1972, spatial resolution of 30 m, and large swath area (Bhatti and Tripathi, 2014;Nautiyal et al, 2019;Ramachandra et al, 2012). The Landsat series consists of sensor with a various spatial resolution that can be used for different applications such as Operation Land Imagery (OLI) with Multi Spectral Sensor (MSS) for land use monitoring (Amalisana and Hernina, 2017;Badlani et al, 2017b;Phiri and Morgenroth, 2017), ice ow mapping (Fahnestock et al, 2016) and the thermal infrared band (TIR) for active re detections (Schroeder et al, 2016). In this study, Landsat imagery between 1988 and 2018 was applied for characterizing built-up changes in Chiang Mai city.…”

“…Migrating from rural to urban area is one of the primary sources of urban expansion, which re ects either increase in population and land size or urban patches (Maarseveen et al, 2019). Additionally, urban growth is considered as an indicator that characterized socio-economic development, whereas it also reveals the impacts of anthropogenic activities on the natural environment (Badlani et al, 2017b).…”