Urban planning is the most essential requirement for any city to develop.This analysis shows the results of built-up area growth relative to the population at that period.

1. SSmart Citymart City
Sustainability AnalysisSustainability Analysis

2. IndexIndex
● Introduction
● Objective
● Buildup Analysis
● Visualization of Data
● Data Interpretation
● Comparison
● Conclusion

3. IntroductionIntroduction
● A Smart city is the city maintaining the health
of ecological systems ,where a healthy
economy’s industrial base supports the quality
of both human and ecological systems.
● Urban planning is most important for any city to
maintain the basic infrastructural needs and
facilities that are essential.
● Smart city enables the citizens to interact with
the real world through digital means and it is
highly productive for any country to develop.

4. Objective
Visakhapatnam is one of the developing cities in the
world. So we have taken the study area as Vizag.
To identify the change in built-ups in our study
area using an IBI index.
To compare change in urban area with increasing
population.
To analyze the sustainability of the city and to
identify the sustainable and non-sustainable areas.
To correlate the rate urbanization with road length.

5. Build-up analysis
Satellite images Topographic Maps
Preprocessing
EBBI IBI
Thresholding
Polygonisation Analysis Comparision with osm
Thresholding
Boundary
Count and Buildup extraction
Buildup area growth

6. FCC 1993
LANDSAT-5 (MSS) image of Visakhapatnam 1993
WRS_PATH = 141 WRS_ROW = 48
Satellite imageS
FCC 2018
LANDSAT-8(OLI) image of Visakhapatnam2018
WRS_PATH = 141 WRS_ROW = 48

7. Index used
IBI(Index-based Built-up Index): It is an index indicating built-
up within a threshold value.
Using raster calculator, IBI is calculated as follows:
IBI=[{2MIR/(MIR+NIR)}-{(NIR/(NIR=Red))+(Green/(Green+MIR))]
/[{2MIR/(MIR+NIR)}+{(NIR/NIR+Red)+(Green/(Green+MIR))}]
Where,
NIR=B4 (ETM+), B4 (LISS-III) & B5 (OLI);
Red=B3 (ETM+), B3 (LISS-III) & B4 (OLI);
Green=B2 (ETM+), B2 (LISS-IIl) & B3 (OLI);
MIR=B5 (ETM+), B5 (LISS-III) & B6 (OLI);

8. Images of Built-up(Binary)
STATISTICS_MAXIMUM=1
STATISTICS_MEAN=-9131.7072327654
STATISTICS_MINIMUM=-9999
STATISTICS_MAXIMUM=1
STATISTICS_MEAN=0.17874965190754
STATISTICS_MINIMUM=0
Builtup area of vizag1993 Builtup area of vizag 2018

9. Growth of Urban area in 1993
This Map shows the area of
built-up that has been
developed during that period.
Area covered by built-up
during 1993 was
119.68sqkm.
Growth of Urban area in 2018
Comparatively the area of
built-up have been increased
rapidly more than that in the
year 1993 it was about
367.41sqkm.
Around 68% change in built-
up taken place from 1993 to
2018.

10. The differences in the
image shows the
various urban
developments that
underwent from year
1993 to that of present
year 2018.
Areas such as
Madhurawada ,
Kommadi, yendada ,
Anandapuram,
Bheemunipatnam,
Arilova, Rushikonda
etc have highly
grownup.
Areas such as NAD ,
Gopalapatnam,
Peddamusirivada etc.,
have moderately
grown built-ups.
Variation in Urban Growth

11. This graph clearly shows
the population of past
years and the present year
where urban area is also
increased.
As per recorded census,
population of
visakhapatnam is 752,037
during 1991, 1,345,938
during 2001 and 1,728,128
during 2011.
Estimated population in
2018 is nearly 2,090,000.
Graph showing increased population and
development in urban areas

12. Road Network
The road networks
relative to urban are
shown in the map.
Total roadlength
seen in this road
map vs urban is
3606.65m.
This road map
shows various areas
and regions of roads
of different patterns.
As we can see here
more roads were
connected and linked
to the urban areas
from various paths.
Areas such as RTC
complex,Railway
station,Jagadamba
are always highly
populated and traffic
oriented.

13. Conclusion
The Present results are done as per the urban
area growth rate relative to population.For
estimating urban growth flat counts were
used.This analysis shows the current
concentration of built-up is higher than past
years indicating the future developments may
be higher relative to population.Further these
estimations can be useful for rapid
developments of smart city with collaboration of
many government and private companies along
with IOT technology.

14. AcknowledgmentAcknowledgment
The outcomes of the project is done only through open source softwares and data
that are be publicly available.QGIS , Openstreetmaps ,USGS earthexplorer , ,
Population Statistics
Our Special thanks to KAIINOS (https://www.kaiinos.com) for their
extensive support and care taken for completion of this project.
Praveen : https://www.linkedin.com/in/praveen-kumar
Naveen : https://www.linkedin.com/in/chintada-naveen
Mallika : https://www.linkedin.com/in/mallika-patnaik
Sidhardha : https://www.linkedin.com/in/yeleti-rama-sidhardha
Thank you