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Abstract
Abstract. Dynamic changes in urbanisation of a city is best analyzed through spatio-temporal analysis of classified data. Decadal Land use data for India for years 1985, 1995 and 2005 and Copernicus Global Land service Dynamic Land Cover layers (CGLS-LC100 products) for year 2015 have been used to conduct analysis for multi-temporal analysis of urban expansion and its dynamics using Landscape Metrics by FRAGSTATS and Shannon’s Entropy Values (Hn) over the 4 directional zones of Lucknow city namely North-East (NE), South-East (SE), South-West (SW) and North-West (NW). The metrics used to find characteristics of urbanisation are Landscape Shape Index (LSI), Largest Patch Index (LPI), Mean Euclidean Nearest Neighbor Distance (ENN_MN) and Aggregation Index (AI). Results showed the increase in LSI for Built-up patches over the years from 1985 to 2015, explaining the increase in complexity of shapes of Built-up patches in all zones. The increase in LPI indicates the increase of Built-up land use class over the years but also the convergence of urbanisation in the study area as indicated by lower entropy values. NW zone of Lucknow city area being poor in Vegetation is having highest ENN_MN which is decreasing over the years indicating more centrality. AI is same for Built-up patches from 1985 to 2015 which is due to either edge-filling or outlying urban growth in study area in all 3 change durations 1985-1995, 1995–2005 and 2005–2015. Among all 4 zones of Lucknow city, decrease in vegetation is major factor to urbanisation in city over the years.
Highlights
Modern tool and techniques are helping in modelling and monitoring of urbanisation in metropolitan cities all over the world (Sapena and Ruiz, 2015)
CGLS-LC100 product is obtained via Google Earth Engine (GEE) and Decadal Land use data if India has been downloaded from ORNL DAAC website
CGLS-LC100 product obtained from GEE for study area contain 11 land use classes, which are reclassified into 5 useful classes, same as in ORNL DAAC data reclassification in Table 1 for analysis purpose in this study
Summary
Modern tool and techniques are helping in modelling and monitoring of urbanisation in metropolitan cities all over the world (Sapena and Ruiz, 2015). Urbanisation is an event, upon unfolding of which landscape of city becomes more diverse in land use (Liu et al 2016). Study of landscape patterns in context of urbanisation is an effective method to plan urban sustainability (Yang et al 2019). Zonal-Gradient approach can be efficient one to materialise the spatial patterns of urbanisation at local level (Ramachandra and Aithal, 2013). To capture the typicality and intrinsic features of urban sprawl of an individual city, a geo-spatial index is the best indicator (Jiang et al 2007)
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