• Save
Iirs Remote sensing application in Urban Planning
Upcoming SlideShare
Loading in...5
×
 

Iirs Remote sensing application in Urban Planning

on

  • 8,543 views

Remote sensing application in Urban Planning

Remote sensing application in Urban Planning

Statistics

Views

Total Views
8,543
Views on SlideShare
8,522
Embed Views
21

Actions

Likes
8
Downloads
0
Comments
0

4 Embeds 21

http://btechhome.blogspot.in 11
http://btechhome.blogspot.com 8
http://www.techgig.com 1
http://timesjobs.techgig.com 1

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Iirs Remote sensing application in Urban Planning Iirs Remote sensing application in Urban Planning Presentation Transcript

  • REMOTE SENSING APPLICATIONS IN URBAN PLANNINGINTRODUCTION The modern technology of Remote Sensing which includes both aerial aswell 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 toanalyze the data spatially, offering possibilities of generating various options(including modelling), thereby optimizing the whole planning process. Theseinformation systems also offer interpretation of physical (spatial) data withother socio-economic data, and thereby providing an important linkage inthe total planning process and making it more effective and meaningful.Generally, these Remote Sensing data products have following applicationsü in mappingü in interpretation / analysisü as map substitutes
  • 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 -------------------
  • Satellite Imagery for Different Levels of Development PlanningLevel 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 1:5000Urban 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 estimationInfrastructure Regional level corridor planning •Broad Site Suitability analysis Specific Project Site AnalysisPlanning •Mapping of major road network •Dams •Highways •Canal •Industries •Power PlantsDisaster •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 mappingRural Development •Regional maps •Land and water resources •Cadastral level landuse mapsPlanning •Settlement network development maps •Land parcel maps •Micro level watershed/ village planning
  • 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
  • INDIAN IMAGING CAPABILITY •1 Km to 1 m spatial Resolution •24 Days to every 30 mts. Repetitivity •1 Million scale to Cadastral Level
  • 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) 1988/91IRS-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 2001RS-D1 SMART SENSOR AWiFS - 60M; 740 Km TES 1979/81 STEP & STARE CONCEPTBHASKARA VIDICON, SAMIR 2003 CARTOSAT-2/2A IRS-P5(Cartosat-1) PAN – 1.0 m, 11km PAN-2.5M, 2005
  • IKONOSSpace Imaging EOSAT IKONOS 1 failed April 1999IKONOS 2 Sept., 29 1999sensor: Kodak linear arraypixel size: 0.82m panchr. in nadir swath: 11.3km 3.2m multisp. In nadir swath: 11.3kmpointing in track: +/-52°, across track +/-52°680km flying height, sun-synchr.panchromatic: 0.45 – 0.90µm 13 816 pixelmultispectral: blue 0.45 – 0.52µm, green 0.52 – 0.60µm, red 0.63 – 0.69µm, NIR 0.76 – 0.90µm 3 454 pixelquantization: 11bit standalone geo-location: horizontal 12m, vert. 8m
  • 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
  • Quick Bird ImageVidhan 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
  • Quick Bird ImageVidhan 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
  • GeoEye-1GeoEye-1 launched on Sept. 6, 2008—the worlds highest resolutioncommercial earth-imaging satellite.GeoEye-1 is equipped withsophisticated technology ever usedin a commercial satellite system.It offers unprecedented spatialresolution by simultaneouslyacquiring 0.41-meter panchromaticand 1.65-meter multispectralimagery. The detail and geospatialaccuracy of GeoEye-1 imageryfurther expands applications forsatellite imagery in everycommercial and government marketsector.
  • Application of Remote Sensing and GIS for change detection and updation of maps using mobile mapping : A case study of Gurgaon city. DATA USEDSOFTWARE USED INSTRUMENT USEDGIS software: Arc GIS 9.1 GPS SX BLUE IIERDAS imagine 8.7 MIO DIGI WALKERSUPERPAD 2
  • 19935,369.60 ha. 200012,050.43 ha. 200513,068.21 ha.
  • Map updation at micro levelMap preparation using Mobile Field visitHigh Resolution Data mapping unit Transfer to Update Map computer location/attributes Updation from PDA of objects in field
  • Pocket A 14.88 ha.
  • Strategy Development to mitigate the impact of Urban Heat Islands – An input to Master Plan PreparationObjectives: - 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 tomitigate/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
  • 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
  • Industrial Hazard, Vulnerability and Risk Assessment for Land Use Planning: A Case Study of Haldia, West Bengal, IndiaObjectives: 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
  • Risk Assessment for Haldia …… High Risk Total No. of Category Population households Medium Very Low 41911 6987 Low Low 43841 80610 125 250 500 750 1,000 Very Low Medium 86960 18868 Meters High 7117 1648
  • Environmental Monitoring of Vegetation, Temperature andLU/ LC arameters and simulation of air pollutant dispersion
  • 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      zC = concentration,Q=emissions,? y, ? z are dispersion parametersu = wind speed,x,y,z= downwind point locationH = plume heightu, ? y, ? z : meteorology input? y, ? z increase with distancedownwind, and area function ofatmospheric stability (‘mixing’)
  • USER INTERFACE IN ARC GIS 8.1
  • Dehra Dun -Water Supply Study
  • Name Of the Tube Well LPM Year of Installation Hour LMDNehru Colony Tube Well -3 1800 1981 16 1.73Nehru Colony Tube Well -5 2500 1989 16 2.4Nehru Colony Tube Well -4 2200 1986 16 2.11
  • Internet addressMap hostedin ArcGIS server (Internet)
  • 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 sizeis useful for mapping up to map scale 1 : 5000 – 1 : 10 000•Stronger overlap of space and airborne applications
  • A