157
NDVI value, almost each and every urban centre of West Bengal shows spatial
decrease of NDVI (Figs. 8.2, 8.3, 8.4 and 8.5). All the cities are belonging in high to
very high group in recent times. After the analysis of data and map, it is observed
that BUI of Kolkata remains almost the same throughout the recent times, whereas
in case of Durgapur and Asansol, their BUI values remain low in industrial region,
and it is growing over the years (Table 8.6).
8.6 Major Findings and Conclusion
Appropriate and effective remote sensing technology can fulfil the main purpose of
the planning and, henceforth can minimise the time as well for decision. Indexbased remote sensing models are useful, as they are simple and easy to compute.
Overall the NDBI response very good in different temporal images to detect the
built-up area in AMC, DMC, KMC and SMC, although, the response of is good in
2018 satellite image. NDVI useful to detect the growth and change of the vegetation
health conditions throughout of the all MC, it detect that the vegetation health condition of the core of the MC has decreases in SMC, while it has increases in KMC. It
Fig. 8.3 (a) Normalised Difference Built-Up Index (NDBI), (b) Normalised Difference Vegetation
Index (NDVI), (c) Enhanced Built-up and Bareness Index (EBBI) and (d) Built-Up Index (BUI)
of Asansol
8 Spatio-Temporal Transformation of Urban Built-Up Areas for Sustainable…
NDVI value, almost each and every urban centre of West Bengal shows spatial
decrease of NDVI (Figs. 8.2, 8.3, 8.4 and 8.5). All the cities are belonging in high to
very high group in recent times. After the analysis of data and map, it is observed
that BUI of Kolkata remains almost the same throughout the recent times, whereas
in case of Durgapur and Asansol, their BUI values remain low in industrial region,
and it is growing over the years (Table 8.6).
8.6 Major Findings and Conclusion
Appropriate and effective remote sensing technology can fulfil the main purpose of
the planning and, henceforth can minimise the time as well for decision. Indexbased remote sensing models are useful, as they are simple and easy to compute.
Overall the NDBI response very good in different temporal images to detect the
built-up area in AMC, DMC, KMC and SMC, although, the response of is good in
2018 satellite image. NDVI useful to detect the growth and change of the vegetation
health conditions throughout of the all MC, it detect that the vegetation health condition of the core of the MC has decreases in SMC, while it has increases in KMC. It
Fig. 8.3 (a) Normalised Difference Built-Up Index (NDBI), (b) Normalised Difference Vegetation
Index (NDVI), (c) Enhanced Built-up and Bareness Index (EBBI) and (d) Built-Up Index (BUI)
of Asansol
8 Spatio-Temporal Transformation of Urban Built-Up Areas for Sustainable…