Remote sensing application in Urban Planning

1. REMOTE SENSING APPLICATIONS IN URBAN PLANNING
INTRODUCTION
The modern technology of Remote Sensing which includes both aerial as
well as satellite based systems, allow us to collect lot of physical data easily,
with speed and on repetitive basis, and together with GIS helps us to
analyze the data spatially, offering possibilities of generating various options
(including modelling), thereby optimizing the whole planning process. These
information systems also offer interpretation of physical (spatial) data with
other socio-economic data, and thereby providing an important linkage in
the total planning process and making it more effective and meaningful.
Generally, these Remote Sensing data products have following applications
ü in mapping
ü in interpretation / analysis
ü as map substitutes

2. REQUIREMENT OF URBAN AND REGIONAL PLANNERS
Apart from topographical mapping, the planners also look forward to
the Remote Sensing (data products) technology to provide them
information on existing land use and their periodic updating and
monitoring. In addition, with appropriate technique and methodology
the same data products can be used to:
Ø Study urban growth/sprawl and trend of growth.
Ø Updating and monitoring using repetitive coverage.
Ø Study of urban morphology, population estimation and other
physical aspects of urban environment.
Ø Space use surveys in city centers.
Ø Slum detection, monitoring and updating.
Ø Study of transportation system and important aspects both in
static and dynamic mode.
Ø Site suitability and catchment area analysis.
Ø Study of open/vacant space.
Ø -------------------

3. Satellite Imagery for Different Levels of Development Planning
Level of Planning Macro Level (Regional & Meso Level ( District/ Micro Level ( Project, Micro-
Micro-
Perspective) Development) watershed, Village)
Low Resolution (80 -360 M)
(80- Medium Resolution (20 – 40 M) High Resoution (0.6M – 5 M)
Scale Mapping 1: 50000 to 1:1M 1:25000 to 1: 50000 1:1000 to 1:5000
Urban Planning •Urban Sprawl analysis •Urban landuse mapping (level-1)
(level- •Urban landuse mapping (level 1, 2
•Urban land use at level-1
level- •Urban suitability analysis & 3)
•Transportation network •Mapping of major transport •Slum typology
•(Highways, Railways etc.) network •Mapping of street level Urban road
•Updation of city guide maps network
•Mapping of property parcels
•Inputs for infrastructure
development
•Utilities and service maps
•Population estimation
Infrastructure Regional level corridor planning •Broad Site Suitability analysis Specific Project Site Analysis
Planning •Mapping of major road network •Dams
•Highways
•Canal
•Industries
•Power Plants
Disaster •Flood Prone Area Maps •Post Disaster Damage assessment • Post Disaster Relief Management
•Cyclone Monitoring •Property Insurance for Natural Support
•Drought Monitoring & Forecast Disasters • Tracing of approach routes
•Earthquake prone areas • Waste disposal and solid waste
management
•Landslide prone area mapping
•Slope stability mapping
Rural Development •Regional maps •Land and water resources •Cadastral level landuse maps
Planning •Settlement network development maps •Land parcel maps
•Micro level watershed/ village
planning

4. SATELLITE MISSIONS supported by NRSC
• IRS series • Landsat series
– MSS and TM (archived)
– IRS-1A/1B/P2 (L-II) – NOAA series
• LISS-I and LISS-II – AVHRR & TOVS
– IRS-1C/1D • ERS-1 & 2
• PAN, LISS-III and WiFS – SAR
– IRS-P3 • SPOT
• MOS and WiFS – MLA/PLA(archived)
– IRS-P4 • RADARSAT, ENVISAT
• OCM and MSMR (Only data distribution)
– IRS-P6 • IKONOS, QUICK BIRD
(Only data distribution)
• LISS-IV,LISS-III and
AWiFS
ORBVIEW
(Only data distribution)
- IRS-P5 • MODIS (Hyper spectral)
• PAN

5. INDIAN IMAGING CAPABILITY
•1 Km to 1 m spatial Resolution
•24 Days to every 30 mts. Repetitivity
•1 Million scale to Cadastral Level

6. IRS-P3
WiFS, MOS X-Ray
1995/1997
IRS-1C/1D LISS-3 (23/70M,
STEERABLE PAN (5.8 M);
1994 WiFS (188M)
IRS-P2 1999
LISS-2 INSAT-2E
CCD (1 KM)
1988/91
IRS-1A & 1B LISS-1&2 (72/36M)
INDIAN IMAGING 1999
IRS-P4 (OCEANSAT -1)
SYSTEMS OCM, MSMR
IRS-P6(Resourcesat-1)
1982 LISS III - 23M ; 140 Km; 4Xs
LISS IV - 5.8M ; 3Xs 2001
RS-D1 SMART SENSOR
AWiFS - 60M; 740 Km
TES
1979/81 STEP & STARE CONCEPT
BHASKARA VIDICON, SAMIR
2003
CARTOSAT-2/2A IRS-P5(Cartosat-1)
PAN – 1.0 m, 11km PAN-2.5M, 2005

7. IKONOS
Space Imaging EOSAT
IKONOS 1 failed April 1999
IKONOS 2 Sept., 29 1999
sensor: Kodak linear array
pixel size: 0.82m panchr. in nadir swath: 11.3km
3.2m multisp. In nadir swath: 11.3km
pointing in track: +/-52°, across track +/-52°
680km flying height, sun-synchr.
panchromatic: 0.45 – 0.90µm 13 816 pixel
multispectral: blue 0.45 – 0.52µm,
green 0.52 – 0.60µm, red 0.63 – 0.69µm,
NIR 0.76 – 0.90µm 3 454 pixel
quantization: 11bit
standalone geo-location: horizontal 12m, vert. 8m

8. QUICK BIRD DATA
• Panchromatic • Multispectral
– 1 band visible – 4 band
– 61 cm (nadir) 72 cm – 2.44 m (nadir) and
(off nadir) spatial 2.88 (off nadir)
resolution resolution
– 16.5 km swath – 16.5 km swath
- stereo acquisition – 11 bit acquisition
– 11 bit acquisition

9. Quick Bird Image
Vidhan Soudha,
Bangalore
♦ Panchromatic (single
band - black and white)
images with a spatial
resolution of 61 cm
with swath 16.5 km
♦ Multispectral images in
four spectral bands with
4 m spatial resolution.
The four bands are:
Blue : 0.45 - 0.52 mm
Green : 0.52 - 0.60 mm
Red : 0.63 - 0.69 mm
and
Near Infra Red: 0.76-
0.90 mm
• 11 bit

10. Quick Bird Image
Vidhan Soudha,
Bangalore
♦ Panchromatic (single
band - black and white)
images with a spatial
resolution of 61 cm
with swath 16.5 km
♦ Multispectral images in
four spectral bands with
4 m spatial resolution.
The four bands are:
Blue : 0.45 - 0.52 mm
Green : 0.52 - 0.60 mm
Red : 0.63 - 0.69 mm
and
Near Infra Red: 0.76-
0.90 mm
• 11 bit

11. GeoEye-1
GeoEye-1 launched on Sept. 6, 2008
—the world's highest resolution
commercial earth-imaging satellite.
GeoEye-1 is equipped with
sophisticated technology ever used
in a commercial satellite system.
It offers unprecedented spatial
resolution by simultaneously
acquiring 0.41-meter panchromatic
and 1.65-meter multispectral
imagery. The detail and geospatial
accuracy of GeoEye-1 imagery
further expands applications for
satellite imagery in every
commercial and government market
sector.

14. Application of Remote Sensing and GIS for change detection and
updation of maps using mobile mapping :
A case study of Gurgaon city.
DATA USED
SOFTWARE USED INSTRUMENT USED
GIS software: Arc GIS 9.1 GPS SX BLUE II
ERDAS imagine 8.7 MIO DIGI WALKER
SUPERPAD 2

15. 1993
5,369.60 ha.
2000
12,050.43 ha.
2005
13,068.21 ha.

16. Map updation at micro level
Map preparation using Mobile Field visit
High Resolution Data mapping unit
Transfer to Update
Map computer location/attributes
Updation from PDA of objects in field

18. Pocket A 14.88 ha.

19. Strategy Development to mitigate the impact of Urban Heat Islands –
An input to Master Plan Preparation
Objectives:
- What are the major factors that govern Urban Heat Island?
- What is the relationship between land use/land cover to heat production?
- How Geoinformatics Technology can be used to monitor/control the impact of UHI?
- Economic value of trees /vegetation, water bodies and its effect on UHI?
- What are the legislative and regulatory mechanisms that can be adopted to
mitigate/control the impact of Urban Heat Island?
LANDSAT-
LANDSAT -7 ETM+ (22/10/1999 )
Day time
55.00
Temperature in degree Celsius
50.00
45.00
40.00
35.00
30.00
25.00
Water bodies Agricultural Dense Sparse Low dense Dense built-up Commercial and Bare soil/waste Fallow land
crop land vegetation vegetation built-up industrial land
Land use/ land cover
Minimum Maximum Mean

20. Surface Temperature Analysis with LU/LC
52.00
Temperature in degree Celsius
49.00
46.00
43.00
40.00
37.00
34.00
31.00
28.00
25.00
Dense vegetation
Water bodies
Waste land/bare soil
Low dense built-up
Fallow land
Commercial/industrial
Agricultural crop land
High dense built-up
Sparse vegetation
(forest)
Land use/land cover
Mean °C (day time) Mean °C (night time)
ASTER (18/10/2001) Day time
&
ASTER (07/10/2001) Night time

21. Industrial Hazard, Vulnerability and Risk Assessment for Land Use Planning:
A Case Study of Haldia, West Bengal, India
Objectives:
Generation of hazard scenarios for fire, explosion and toxic rel ease.
release.
(Support from ERRIS).
Quantification of elements at risk and risk zonation.
Impact of possible hazard scenarios on buildings and population at different time periods.
Utilization of risk maps for future land use planning.
Morning Day Evening Night
Medium
Population Risk Assessment for Toxic Release…
Release… High
Very High

22. Risk Assessment for Haldia ……
High
Risk Total No. of
Category Population households Medium
Very Low 41911 6987 Low
Low 43841 8061
0 125 250 500 750 1,000
Very Low
Medium 86960 18868
Meters
High 7117 1648

23. Environmental Monitoring of Vegetation, Temperature and
LU/ LC arameters and simulation of air pollutant dispersion

27. Gaussian plume model :
Q  − 1 y 2   −1 z − H 2   − 1 z + H 2 
• c(x, y, z : H) = exp  ( )   exp 
 2 ( )  + exp 
  2 ( σ )  
2πσ z σ y  2 σy   σz   
  z
C = concentration,
Q=emissions,
? y, ? z are dispersion parameters
u = wind speed,
x,y,z= downwind point location
H = plume height
u, ? y, ? z : meteorology input
? y, ? z increase with distance
downwind, and area function of
atmospheric stability (‘mixing’)

28. USER INTERFACE IN ARC GIS 8.1

30. Dehra Dun -Water Supply Study

31. Name Of the Tube Well LPM Year of Installation Hour LMD
Nehru Colony Tube Well -3 1800 1981 16 1.73
Nehru Colony Tube Well -5 2500 1989 16 2.4
Nehru Colony Tube Well -4 2200 1986 16 2.11

35. Internet
address
Map hosted
in ArcGIS
server
(Internet)

37. Conclusion
•More and more sensors and sensor types are available
•Number of available space images is growing permanently
•More and more companies are entering the space market
•Tendency to real private projects
•Competition will reduce the cost
•0.6m pixel size from space available – allowance up to 0.5m pixel size
is useful for mapping up to map scale 1 : 5000 – 1 : 10 000
•Stronger overlap of space and airborne applications

38. A