SlideShare una empresa de Scribd logo
1 de 35
Overview of Remote Sensing technology




                          Shefali Agrawal
             Photogrammetry and Remote Sensing Division
                                IIRS
                     Email: shefali_a@iirs.gov.in




                What Is Remote Sensing?

 Technique of obtaining information about an object,
 area, or phenomenon from a distance
  Remote sensing is the process of collecting data about objects or
  landscape features without coming into direct physical contact with
  them. In its broadest sense it refers to the activities of
  recording/observing/perceiving (sensing) objects or events at far
  away (remote) places

• “Science of measuring the GEOMETRIC and THEMATIC properties
  of objects in the environment without touching them and using various
  devices in the air or space”
• It is the technique of collecting information from a distance
• “From a distance” is generally considered to be large relative to what
  a person can reach out and touch
The Remote Sensing Process
Energy Source                    Sensor                                SatCom




                                                                                  Application



      Target
                                        Processing
                                        Station                      Analysis




 The EM spectrum
                          ‘Optical range’

 Cosmic Gamma  X-
                                                                      Radio   Electric power
                          U-V            Infrared   Micro-waves TV
  rays   rays Rays


                                Visible spectrum




   Ultraviolet           Blue             Green             Red               Infrared (IR)




  0.3μm            0.4               0.5μm            0.6             0.7μm     10.0      15.0

  300nm                             500nm                             700nm

                                     Wavelength
The size of a cell we call image resolution, depending on…
 Such as 1 m, 30 m, 1 km, or 4 km




           Types of remote sensing
• Passive: source of              • Active: source of
  energy is either the Sun,         energy is part of the
  Earth, or atmosphere              remote sensor system
   – Sun                              – Radar
     - wavelengths: 0.4-5 µm            - wavelengths: mm-m
   – Earth or its atmosphere          – Lidar
     - wavelengths: 3 µm -30            - wavelengths: UV,
     cm                                 Visible, and near
                                        infrared
Remote sensing is classified into three types with respect
      to the wavelength regions;

    • Visible and Reflective Infrared Remote Sensing,
      0.4µm to 3 µm

    • Thermal Infrared Remote Sensing and
      3 µm to 35 µm

    • Microwave Remote Sensing,
      1mm to 1m




               Interactions with the Atmosphere
  The two major atmospheric effects are scattering and
   absorption
         A) Scattering                                     B) Absorption




⇒ Scattering occurs when particles or large gas molecules present in the atmosphere interact with
   and cause the electromagnetic radiation to be redirected from its original path

⇒ Absorbption causes molecules in the atmosphere to absorb energy at various wavelengths.
   Ozone, carbon dioxide, and water vapour are the three main atmospheric constituents which
   absorb radiation
Atmospheric windows suitable for Earth observations
           from space,



Atmosphere
transmission (%)
  100




   50




    0
        0.4 0.7     1       2      3      5           10          (...)      10,000       µm




              Interactions with the surface

                   Sun


scattered        Incident energy
radiation**
                                                           R.S. Instrument




                                       Scattered                                Atmospheric
        Clouds                         radiation*                                 emission

        Atmospheric       transmitted         Reflected      Thermal emission
         absorption         radiation          radiation


   Earth                 Reflection processes                 Emission processes
•  For example A white surface reflects equal amounts of
  radiation of all wavelengths of visible light.
• A green object reflects less in red and blue parts of the
  spectrum than in green. The excess reflection in green
  wavelength makes makes the object appear green.
• So, the composition of electromagnetic reflection (spectral
  signature )tells us about the surface reflecting the
  radiation.




     Spectral reflectance of vegetation
Spectral Reflectance
 Characteristics of
      Leaves
Spectral Reflectance of Snow
(a)
                                                                   (b)




 IRS LISS-3 image over part of Himalayas. (a) is in band-2 (Green) and (b) in band-5 (SWIR).
Both cloud and snow have higher reflectance in visible and hence cannot be discriminated
(except from shadow). In SWIR, low reflectance of snow can discriminate snow from cloud.
Platforms

   Sensing from 1 meter to 36,000 km
   height

   Platforms are:
        •Ground based
        •Airborne
        •Spaceborne
Space borne remote sensing




                                                                  Spot off nadir




                                Geostationary Orbit
                 A satellite that appears to remain in the same position above
                         the Earth is called a "geostationary satellite."




Credit: C.M.Kishtawal, SAC
Polar Orbits

                                 An orbit with a inclination of 90
                                 degrees, or close to it, is called a
                                 "polar orbit." Because the Earth is
                                 rotating as the satellite follows a
                                 polar orbit, the satellite can survey
                                 the whole of the Earth's surface,
                                 including the poles, in a few days.
                                 Many observation satellites that
                                 need to cover the entire Earth are in
                                 polar or near-polar orbits.



Credit: C.M.Kishtawal, SAC
Selection of Sensor Parameters
 Information collected by sensor should be sufficient enough to meet
 accuracy in class discrimination and mapping.




• Spatial resolution


• Spectral resolution
                                                                       λ
• (Radiometric resolution)


• Temporal resolution (revisit time)


                                                                1/
Spatial Resolution
 SPATIAL     -      THE PHYSICAL DIMENSION ON
                    EARTH IS RECORDED : SPATIAL
                    RESOLUTION

• Spatial resolution refers to the amount of detail that
can be detected by a sensor.


• Detailed mapping of land use practices requires a
much greater spatial resolution than observations of a
large scale storm system.




                 AWIFS (56 m)
ETM (30 m)




IRS-LISS III (23.5 m)
ASTER(15 m)




IRS-PAN (5.8 m)
IKONOS MSS (4 m)




IKONOS PAN (1 m)
Spectral Resolution
SPECTRAL-                Relating of wavelength
                         characteristics of EMR measured
                         number of bands, bandwidth:
                         spectral resolution

•Describes the ability of a sensor to define fine
wavelengths intervals
•The finer the spectral resolution, narrower the
wavelength range of a particular band




   Spectral Bands : LANDSAT TM




  Band (.45 to .515μm)    Band (.525 to .605 μm)    Band (.63 to .690 μm)




  Band (.75 to .90 μm)     Band (1.55 to 1.75 μm)   Band (2.09 to 2.35μm)
Colour Composite




 True Color Composite (3,2,1)   False Color Composite          IR Colour Composite
                                (4,3,2)                        (7,5,4)




                    Radiometric Resolution

 • Measure of capability of sensor to differentiate the
   smallest change in spectral reflectance of a earth
   feature.




                                 High
              D                                         For same reflectance,
              N                                         High RR :DN = 4096(12)
                                            slope       Low RR DN = 64 (6 bit)


                                             |
                    0
                                 reflectance 1.0
Radiometric Resolution




Low Radiometric resolution         High Radiometric resolution




                Temporal Resolution

• High TR enhances utility of mission
• Key Factors deciding orbit repetivity
    – Cross-track width of imaging strip
    – Application demand
        • Meteorological - hourly need to monitor clouds
        • Oceanographic - 2-3 days of repetivity
        • Stereo viewing - 0-1 days of repetivity
        • Vegetation monitoring - 5 days of repetivity
INDIAN IMAGING CAPABILITY



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




        IRS-1A/1B sensors
IRS-1A was launched in 1988 and provided data up to 1992
IRS-1B launched in 1991 and continues to provide good quality data till date


     • LISS-I
         – Operates in 4 bands in the visible and near infrared
           regions
         – Resolution 72 m
         – Swath 148 km
     • LISS-II
         – Operates in same 4 bands as LISS-I
         – Resolution 36.5 m
         – Swath 74 km
IRS-1C/1D Mission
                      Sensors
                              • LISS-III
• PAN                           – Operates in 4 bands (3 in visible
                                  and near infrared and 1 band in
  – Operates in one visible
                                  shortwave infrared)
    band
                                – Resolution 23 m
  – High resolution 5.8 m
                                – Swath 141 km
  – Swath 70 km at nadir
  –      90 km off nadir      • WiFS
  – Tilt capability +/- 26      – Operates in 2 bands in visible and
    Degrees                       near infrared
                                – Resolution 188 m
                                – Swath 810 km




  Indian Remote Sensing Satellite Resourcesat (IRS P6)
IRS Resourcesat (P6) Payloads
      LISS-3: 141 km swath, 23.5 m resolution (all bands).
           –   B2: 0.52 - 0.59
           –   B3: 0.62 - 0.68
           –   B4: 0.76 – 0.86
           –   B5:1.55 – 1.70

      LISS-4: 23.5 km (Mx mode) & 70.3 km (mono) swath, 5.8 m resolution
      (all bands).
           – B2: 0.52 - 0.59
           – B3: 0.62 - 0.68
           – B4: 0.76 – 0.86

      AWiFS: 737 km combined swath, 56 m resolution at nadir, 70 m resolution
      at field edges.
           –   B2: 0.52 - 0.59
           –   B3: 0.62 - 0.68
           –   B4: 0.76 – 0.86
           –   B5: 1.55 – 1.70




                            LISS-4 Sensor
  – Sensor: 12 K CCD per band

  –     Spectral bands: 3 bands (0.52- 0.59, 0.62- 0.68 and 0.77- 0.86μ)

  –     Swath, MSS Mode: 23.9 km, selectable over 70 Km

  –     Swath, Pan Mode: 70 km in red band

  – Ground Resolution: 5.8 meter pixel in all 3 bands

  – Radiometric Resolution: 7 Bits selectable over 10bits

  – Steering Capability: ± 26 degrees

  – BBR: < 0.25 pixel

  – Revisit Capability: 5 days
RESOURCESAT-1 LISS-IV MX IMAGE OF MUMBAI




           Cartosat-1 PAN Sensor
      Real time stereo viewing

                                     SPATIAL RESOLUTION 2.5 m
  Satellite Path
                                     Two Pan cameras - fore with 26
                                     deg.                              and
                                     aft with -5 deg. Tilt( 500 nm- 850
     Fore look            Aft look   nm)
                                     Swath 27.5 km for stereo and 55
                                     km for monoscopic mode.
                                     8 km overlap between adjacent
                                     paths
                                     10 bits
                                     Facility for across track tilt to give
                                     better revisit
ON
   -      ORBIT CONFIGURATION OF CARTOSAT- 2SATELLITE

PAYLOAD : PAN     : 0.8 M

          SWATH   : 9.6K M

SPACECRAFT WEIGHT: 680 KGS


ORBIT             : 632 KM


REVISIT           : 4/5 DAYS


EQUATORIAL CROSS
OVER TIME        : 9:30 AM


LAUNCHED ON       : 10TH JAN 2007




                CARTOSAT PANCHROMATIC DATA (2.5 M)




                                              IIRS
IRS P6 LISS IV(5.8m) MSS and CARTOSAT(2.5m) PAN FUSED




             Cartosat 1 : Chandigarh
Hyderabad (Khairatabad and its environs), India as seen by CARTOSAT-2




         Perth Airport, Australia as seen by CARTOSAT-2
IKONOS SATELLITE DETAILS
PAYLOAD :PAN      : I M RESOLUTION

            MS    : 4 M, 4 BANDS

          SWATH   : 11 KMS


SPACECRAFT MASS   : 720 KGS



ORBIT             : 680 KM


REVISIT           : EVERY 3 DAYS


EQUATORIAL CROSS
OVER TIME        : 10:30AM


LAUNCH DATE       : SEPTEMBER 1999
ORBVIEW 5 (GEOEYE 1
          -         - )


  PAYLOAD            : PAN & MS CAMERA
                       0.41 M PAN
                       1.64 M MS IN 4 BANDS

  SWATH              : 15.2 KM

  DYNAMIC RANGE      : 11 BITS

  ORBIT              : 684 KM

  REVISIT            : < 3 DAYS

  EQUATORIAL CROSS
  OVER TIME                       : 10:30 AM



  LAUNCH DATE        : 2007




Thermal Images



                                               Day time




                                               Night time
RADAR Images




             ERS SAR image (pixel size=12.5 m)
Flat surfaces such as paved roads, runways or calm water
normally appear as dark areas in a radar image since most of the
incident radar pulses are specularly reflected away.
Microwave images




           This SAR image shows an area of the sea near
           a busy port. Many ships can be seen as bright
           spots in this image due to corner reflection.
           The sea is calm, and hence the ships can be
           easily detected against the dark background
Photogrammetry




STEREOSCOPIC COVERAGE




    sidelap   endlap
StereoView




Anaglyph viewing system
Digital Elevation Model




Triangulated Irregular Network
Contours




             3D mapping from Cartosat-1 stereo Dataset




PI: Ashutosh Bhardwaj, IIRS, Dehradun

Más contenido relacionado

La actualidad más candente

La actualidad más candente (20)

Types of Map Scales
Types of Map ScalesTypes of Map Scales
Types of Map Scales
 
Development of Geographical Thoughts and Explanation in Greek period
Development of Geographical Thoughts and Explanation in Greek periodDevelopment of Geographical Thoughts and Explanation in Greek period
Development of Geographical Thoughts and Explanation in Greek period
 
Digitalcartography
DigitalcartographyDigitalcartography
Digitalcartography
 
Map Elements
Map ElementsMap Elements
Map Elements
 
Scale - Geography Skill
Scale - Geography SkillScale - Geography Skill
Scale - Geography Skill
 
Computer application in geography
Computer application in geographyComputer application in geography
Computer application in geography
 
Quantitative revolution and phenomenology
Quantitative revolution and phenomenologyQuantitative revolution and phenomenology
Quantitative revolution and phenomenology
 
Introduction to GIS
Introduction to GISIntroduction to GIS
Introduction to GIS
 
Maps Ppt
Maps PptMaps Ppt
Maps Ppt
 
Gis Geographical Information System Fundamentals
Gis Geographical Information System FundamentalsGis Geographical Information System Fundamentals
Gis Geographical Information System Fundamentals
 
Iirs overview -Remote sensing and GIS application in Water Resources Management
Iirs overview -Remote sensing and GIS application in Water Resources ManagementIirs overview -Remote sensing and GIS application in Water Resources Management
Iirs overview -Remote sensing and GIS application in Water Resources Management
 
Geography Skills
Geography SkillsGeography Skills
Geography Skills
 
Data sources and input in GIS
Data  sources and input in GISData  sources and input in GIS
Data sources and input in GIS
 
Maps & globes
Maps & globesMaps & globes
Maps & globes
 
Contribution of Greek philosophers in geography
 Contribution of Greek philosophers in geography Contribution of Greek philosophers in geography
Contribution of Greek philosophers in geography
 
Basic coordinate system
Basic coordinate systemBasic coordinate system
Basic coordinate system
 
datamodel_vector
datamodel_vectordatamodel_vector
datamodel_vector
 
Contribution of Greek geographers/scholars
Contribution of Greek geographers/scholarsContribution of Greek geographers/scholars
Contribution of Greek geographers/scholars
 
MEANING AND NATURE OF GEOGRAPHY
MEANING AND NATURE OF GEOGRAPHY MEANING AND NATURE OF GEOGRAPHY
MEANING AND NATURE OF GEOGRAPHY
 
Cartography
CartographyCartography
Cartography
 

Destacado

Iirs lecturers & gis for regional planning
Iirs lecturers & gis for regional planningIirs lecturers & gis for regional planning
Iirs lecturers & gis for regional planning
Tushar Dholakia
 
Iirs lecture space inputs to disaster management in india
Iirs lecture space inputs to disaster management in indiaIirs lecture space inputs to disaster management in india
Iirs lecture space inputs to disaster management in india
Tushar Dholakia
 
electrification in gated structure
electrification in gated structureelectrification in gated structure
electrification in gated structure
Tushar Dholakia
 
inspection of mechanical gates
inspection of mechanical gatesinspection of mechanical gates
inspection of mechanical gates
Tushar Dholakia
 
Drip irrigation............
Drip irrigation............Drip irrigation............
Drip irrigation............
Bhupesh Katriya
 

Destacado (16)

Iirs lecturers & gis for regional planning
Iirs lecturers & gis for regional planningIirs lecturers & gis for regional planning
Iirs lecturers & gis for regional planning
 
Iirs lecture space inputs to disaster management in india
Iirs lecture space inputs to disaster management in indiaIirs lecture space inputs to disaster management in india
Iirs lecture space inputs to disaster management in india
 
Iirs lecure notes for Remote sensing –An Overview of Decision Maker
Iirs lecure notes for Remote sensing –An Overview of Decision MakerIirs lecure notes for Remote sensing –An Overview of Decision Maker
Iirs lecure notes for Remote sensing –An Overview of Decision Maker
 
Drip irrigation
Drip irrigationDrip irrigation
Drip irrigation
 
Drip irrigation
Drip irrigationDrip irrigation
Drip irrigation
 
automation of gates
automation of gatesautomation of gates
automation of gates
 
electrification in gated structure
electrification in gated structureelectrification in gated structure
electrification in gated structure
 
Iirs Institutions-Geospatial services in India
Iirs Institutions-Geospatial services in IndiaIirs Institutions-Geospatial services in India
Iirs Institutions-Geospatial services in India
 
effective use of consultant
effective use of consultanteffective use of consultant
effective use of consultant
 
Operational Remote sensing Applications
Operational Remote sensing ApplicationsOperational Remote sensing Applications
Operational Remote sensing Applications
 
Agriculture of Gujarat State- Green Revolution
Agriculture of Gujarat State- Green RevolutionAgriculture of Gujarat State- Green Revolution
Agriculture of Gujarat State- Green Revolution
 
inspection of mechanical gates
inspection of mechanical gatesinspection of mechanical gates
inspection of mechanical gates
 
Drip irrigation............
Drip irrigation............Drip irrigation............
Drip irrigation............
 
DRIP IRRIGATION
DRIP IRRIGATIONDRIP IRRIGATION
DRIP IRRIGATION
 
Irrigation
IrrigationIrrigation
Irrigation
 
Irrigation PPT
Irrigation PPTIrrigation PPT
Irrigation PPT
 

Similar a Iirs rstechnologypdf

rsbasics-150227022648-conversion-gate01.pptx
rsbasics-150227022648-conversion-gate01.pptxrsbasics-150227022648-conversion-gate01.pptx
rsbasics-150227022648-conversion-gate01.pptx
BSuresh26
 
Fundamentals of remote sensing
Fundamentals of remote sensingFundamentals of remote sensing
Fundamentals of remote sensing
Ashok Peddi
 

Similar a Iirs rstechnologypdf (20)

Basics of Remote Sensing
Basics of Remote SensingBasics of Remote Sensing
Basics of Remote Sensing
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
rsbasics-150227022648-conversion-gate01.pptx
rsbasics-150227022648-conversion-gate01.pptxrsbasics-150227022648-conversion-gate01.pptx
rsbasics-150227022648-conversion-gate01.pptx
 
RS - Presentation by AP2023.pptx
RS - Presentation by AP2023.pptxRS - Presentation by AP2023.pptx
RS - Presentation by AP2023.pptx
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
remote sensing-converted.pptx
remote sensing-converted.pptxremote sensing-converted.pptx
remote sensing-converted.pptx
 
Fundamentals of remote sensing
Fundamentals of remote sensingFundamentals of remote sensing
Fundamentals of remote sensing
 
.remote sensing.Ece 402 unit-2
.remote sensing.Ece 402 unit-2.remote sensing.Ece 402 unit-2
.remote sensing.Ece 402 unit-2
 
Remote sensing: Its Application & Types
Remote sensing: Its Application & TypesRemote sensing: Its Application & Types
Remote sensing: Its Application & Types
 
Microwave remote sensing
Microwave remote sensingMicrowave remote sensing
Microwave remote sensing
 
APPLICATION OF REMOTE SENSING AND GIS IN AGRICULTURE
APPLICATION OF REMOTE SENSING AND GIS IN AGRICULTUREAPPLICATION OF REMOTE SENSING AND GIS IN AGRICULTURE
APPLICATION OF REMOTE SENSING AND GIS IN AGRICULTURE
 
Surveying ii ajith sir class5
Surveying ii ajith sir class5Surveying ii ajith sir class5
Surveying ii ajith sir class5
 
Remote sensing in entomology
Remote sensing in entomologyRemote sensing in entomology
Remote sensing in entomology
 
Remote sensing - Scanners
Remote sensing - ScannersRemote sensing - Scanners
Remote sensing - Scanners
 
Remote sensing - Sensors, Platforms and Satellite orbits
Remote sensing - Sensors, Platforms and Satellite orbitsRemote sensing - Sensors, Platforms and Satellite orbits
Remote sensing - Sensors, Platforms and Satellite orbits
 
Introduction to Remote Sensing- by Wankie Richman
Introduction to Remote Sensing- by Wankie RichmanIntroduction to Remote Sensing- by Wankie Richman
Introduction to Remote Sensing- by Wankie Richman
 
Als seminar
Als seminarAls seminar
Als seminar
 
Chapter09_Radar.ppt
Chapter09_Radar.pptChapter09_Radar.ppt
Chapter09_Radar.ppt
 
Chapter09_Radar.ppt
Chapter09_Radar.pptChapter09_Radar.ppt
Chapter09_Radar.ppt
 
Remote Sensing Vivek
Remote Sensing VivekRemote Sensing Vivek
Remote Sensing Vivek
 

Más de Tushar Dholakia

trouble shooting and remedy of Dam Gates
trouble shooting and remedy of Dam Gatestrouble shooting and remedy of Dam Gates
trouble shooting and remedy of Dam Gates
Tushar Dholakia
 

Más de Tushar Dholakia (20)

Iirs Artificial Naural network based Urban growth Modeling
Iirs Artificial Naural network based Urban growth ModelingIirs Artificial Naural network based Urban growth Modeling
Iirs Artificial Naural network based Urban growth Modeling
 
Iirs district plan1
Iirs district plan1Iirs district plan1
Iirs district plan1
 
Iirs remote sensing data policy (RSDP)
Iirs remote sensing data policy (RSDP)Iirs remote sensing data policy (RSDP)
Iirs remote sensing data policy (RSDP)
 
Iirs Role of Remote sensing and GIS in Ground water studies
Iirs Role of Remote sensing and GIS in Ground water studiesIirs Role of Remote sensing and GIS in Ground water studies
Iirs Role of Remote sensing and GIS in Ground water studies
 
Iirs gps dmc 2010
Iirs gps dmc 2010Iirs gps dmc 2010
Iirs gps dmc 2010
 
Iirs - Overview of GIS
Iirs - Overview of GISIirs - Overview of GIS
Iirs - Overview of GIS
 
Iirs Remote sensing and GIS application in Agricultur- Indian Experience
Iirs Remote sensing and GIS application in Agricultur- Indian ExperienceIirs Remote sensing and GIS application in Agricultur- Indian Experience
Iirs Remote sensing and GIS application in Agricultur- Indian Experience
 
Iirs Remote sensing application in Urban Planning
Iirs Remote sensing application in Urban PlanningIirs Remote sensing application in Urban Planning
Iirs Remote sensing application in Urban Planning
 
Iirs- Opensources software solutions and Data services for Domain
Iirs- Opensources software solutions and Data services for DomainIirs- Opensources software solutions and Data services for Domain
Iirs- Opensources software solutions and Data services for Domain
 
Nashik photos
Nashik photosNashik photos
Nashik photos
 
LARGE SCALE INSTALLATION OF SUBSURFACE DRAINAGE SYSTEM
LARGE SCALE INSTALLATION OF SUBSURFACE DRAINAGE SYSTEM LARGE SCALE INSTALLATION OF SUBSURFACE DRAINAGE SYSTEM
LARGE SCALE INSTALLATION OF SUBSURFACE DRAINAGE SYSTEM
 
Panam Project Presentation
Panam Project PresentationPanam Project Presentation
Panam Project Presentation
 
Design Aspects of Gates of Dam
Design Aspects of Gates of DamDesign Aspects of Gates of Dam
Design Aspects of Gates of Dam
 
Scope and prospects of micro irrigation
Scope and prospects of micro irrigationScope and prospects of micro irrigation
Scope and prospects of micro irrigation
 
Rule level & gate operation
Rule level & gate operationRule level & gate operation
Rule level & gate operation
 
Irrigation Efficiency
Irrigation EfficiencyIrrigation Efficiency
Irrigation Efficiency
 
Micro Irrigation in Gujarat
Micro Irrigation in Gujarat Micro Irrigation in Gujarat
Micro Irrigation in Gujarat
 
Dam safety & Safety Devices
Dam safety & Safety DevicesDam safety & Safety Devices
Dam safety & Safety Devices
 
Sectoral Allocation & Pricing of Ground Water
Sectoral Allocation & Pricing of Ground WaterSectoral Allocation & Pricing of Ground Water
Sectoral Allocation & Pricing of Ground Water
 
trouble shooting and remedy of Dam Gates
trouble shooting and remedy of Dam Gatestrouble shooting and remedy of Dam Gates
trouble shooting and remedy of Dam Gates
 

Último

Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
negromaestrong
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
ciinovamais
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
heathfieldcps1
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
PECB
 

Último (20)

Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdf
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
fourth grading exam for kindergarten in writing
fourth grading exam for kindergarten in writingfourth grading exam for kindergarten in writing
fourth grading exam for kindergarten in writing
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
psychiatric nursing HISTORY COLLECTION .docx
psychiatric  nursing HISTORY  COLLECTION  .docxpsychiatric  nursing HISTORY  COLLECTION  .docx
psychiatric nursing HISTORY COLLECTION .docx
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 

Iirs rstechnologypdf

  • 1. Overview of Remote Sensing technology Shefali Agrawal Photogrammetry and Remote Sensing Division IIRS Email: shefali_a@iirs.gov.in What Is Remote Sensing? Technique of obtaining information about an object, area, or phenomenon from a distance Remote sensing is the process of collecting data about objects or landscape features without coming into direct physical contact with them. In its broadest sense it refers to the activities of recording/observing/perceiving (sensing) objects or events at far away (remote) places • “Science of measuring the GEOMETRIC and THEMATIC properties of objects in the environment without touching them and using various devices in the air or space” • It is the technique of collecting information from a distance • “From a distance” is generally considered to be large relative to what a person can reach out and touch
  • 2. The Remote Sensing Process Energy Source Sensor SatCom Application Target Processing Station Analysis The EM spectrum ‘Optical range’ Cosmic Gamma X- Radio Electric power U-V Infrared Micro-waves TV rays rays Rays Visible spectrum Ultraviolet Blue Green Red Infrared (IR) 0.3μm 0.4 0.5μm 0.6 0.7μm 10.0 15.0 300nm 500nm 700nm Wavelength
  • 3. The size of a cell we call image resolution, depending on… Such as 1 m, 30 m, 1 km, or 4 km Types of remote sensing • Passive: source of • Active: source of energy is either the Sun, energy is part of the Earth, or atmosphere remote sensor system – Sun – Radar - wavelengths: 0.4-5 µm - wavelengths: mm-m – Earth or its atmosphere – Lidar - wavelengths: 3 µm -30 - wavelengths: UV, cm Visible, and near infrared
  • 4. Remote sensing is classified into three types with respect to the wavelength regions; • Visible and Reflective Infrared Remote Sensing, 0.4µm to 3 µm • Thermal Infrared Remote Sensing and 3 µm to 35 µm • Microwave Remote Sensing, 1mm to 1m Interactions with the Atmosphere The two major atmospheric effects are scattering and absorption A) Scattering B) Absorption ⇒ Scattering occurs when particles or large gas molecules present in the atmosphere interact with and cause the electromagnetic radiation to be redirected from its original path ⇒ Absorbption causes molecules in the atmosphere to absorb energy at various wavelengths. Ozone, carbon dioxide, and water vapour are the three main atmospheric constituents which absorb radiation
  • 5. Atmospheric windows suitable for Earth observations from space, Atmosphere transmission (%) 100 50 0 0.4 0.7 1 2 3 5 10 (...) 10,000 µm Interactions with the surface Sun scattered Incident energy radiation** R.S. Instrument Scattered Atmospheric Clouds radiation* emission Atmospheric transmitted Reflected Thermal emission absorption radiation radiation Earth Reflection processes Emission processes
  • 6. • For example A white surface reflects equal amounts of radiation of all wavelengths of visible light. • A green object reflects less in red and blue parts of the spectrum than in green. The excess reflection in green wavelength makes makes the object appear green. • So, the composition of electromagnetic reflection (spectral signature )tells us about the surface reflecting the radiation. Spectral reflectance of vegetation
  • 9. (a) (b) IRS LISS-3 image over part of Himalayas. (a) is in band-2 (Green) and (b) in band-5 (SWIR). Both cloud and snow have higher reflectance in visible and hence cannot be discriminated (except from shadow). In SWIR, low reflectance of snow can discriminate snow from cloud.
  • 10. Platforms Sensing from 1 meter to 36,000 km height Platforms are: •Ground based •Airborne •Spaceborne
  • 11. Space borne remote sensing Spot off nadir Geostationary Orbit A satellite that appears to remain in the same position above the Earth is called a "geostationary satellite." Credit: C.M.Kishtawal, SAC
  • 12. Polar Orbits An orbit with a inclination of 90 degrees, or close to it, is called a "polar orbit." Because the Earth is rotating as the satellite follows a polar orbit, the satellite can survey the whole of the Earth's surface, including the poles, in a few days. Many observation satellites that need to cover the entire Earth are in polar or near-polar orbits. Credit: C.M.Kishtawal, SAC
  • 13. Selection of Sensor Parameters Information collected by sensor should be sufficient enough to meet accuracy in class discrimination and mapping. • Spatial resolution • Spectral resolution λ • (Radiometric resolution) • Temporal resolution (revisit time) 1/
  • 14. Spatial Resolution SPATIAL - THE PHYSICAL DIMENSION ON EARTH IS RECORDED : SPATIAL RESOLUTION • Spatial resolution refers to the amount of detail that can be detected by a sensor. • Detailed mapping of land use practices requires a much greater spatial resolution than observations of a large scale storm system. AWIFS (56 m)
  • 15. ETM (30 m) IRS-LISS III (23.5 m)
  • 17. IKONOS MSS (4 m) IKONOS PAN (1 m)
  • 18. Spectral Resolution SPECTRAL- Relating of wavelength characteristics of EMR measured number of bands, bandwidth: spectral resolution •Describes the ability of a sensor to define fine wavelengths intervals •The finer the spectral resolution, narrower the wavelength range of a particular band Spectral Bands : LANDSAT TM Band (.45 to .515μm) Band (.525 to .605 μm) Band (.63 to .690 μm) Band (.75 to .90 μm) Band (1.55 to 1.75 μm) Band (2.09 to 2.35μm)
  • 19. Colour Composite True Color Composite (3,2,1) False Color Composite IR Colour Composite (4,3,2) (7,5,4) Radiometric Resolution • Measure of capability of sensor to differentiate the smallest change in spectral reflectance of a earth feature. High D For same reflectance, N High RR :DN = 4096(12) slope Low RR DN = 64 (6 bit) | 0 reflectance 1.0
  • 20. Radiometric Resolution Low Radiometric resolution High Radiometric resolution Temporal Resolution • High TR enhances utility of mission • Key Factors deciding orbit repetivity – Cross-track width of imaging strip – Application demand • Meteorological - hourly need to monitor clouds • Oceanographic - 2-3 days of repetivity • Stereo viewing - 0-1 days of repetivity • Vegetation monitoring - 5 days of repetivity
  • 21. INDIAN IMAGING CAPABILITY •1 Km to 1 m spatial Resolution •24 Days to every 30 mts. Repetitivity •1 Million scale to Cadastral Level IRS-1A/1B sensors IRS-1A was launched in 1988 and provided data up to 1992 IRS-1B launched in 1991 and continues to provide good quality data till date • LISS-I – Operates in 4 bands in the visible and near infrared regions – Resolution 72 m – Swath 148 km • LISS-II – Operates in same 4 bands as LISS-I – Resolution 36.5 m – Swath 74 km
  • 22. IRS-1C/1D Mission Sensors • LISS-III • PAN – Operates in 4 bands (3 in visible and near infrared and 1 band in – Operates in one visible shortwave infrared) band – Resolution 23 m – High resolution 5.8 m – Swath 141 km – Swath 70 km at nadir – 90 km off nadir • WiFS – Tilt capability +/- 26 – Operates in 2 bands in visible and Degrees near infrared – Resolution 188 m – Swath 810 km Indian Remote Sensing Satellite Resourcesat (IRS P6)
  • 23. IRS Resourcesat (P6) Payloads LISS-3: 141 km swath, 23.5 m resolution (all bands). – B2: 0.52 - 0.59 – B3: 0.62 - 0.68 – B4: 0.76 – 0.86 – B5:1.55 – 1.70 LISS-4: 23.5 km (Mx mode) & 70.3 km (mono) swath, 5.8 m resolution (all bands). – B2: 0.52 - 0.59 – B3: 0.62 - 0.68 – B4: 0.76 – 0.86 AWiFS: 737 km combined swath, 56 m resolution at nadir, 70 m resolution at field edges. – B2: 0.52 - 0.59 – B3: 0.62 - 0.68 – B4: 0.76 – 0.86 – B5: 1.55 – 1.70 LISS-4 Sensor – Sensor: 12 K CCD per band – Spectral bands: 3 bands (0.52- 0.59, 0.62- 0.68 and 0.77- 0.86μ) – Swath, MSS Mode: 23.9 km, selectable over 70 Km – Swath, Pan Mode: 70 km in red band – Ground Resolution: 5.8 meter pixel in all 3 bands – Radiometric Resolution: 7 Bits selectable over 10bits – Steering Capability: ± 26 degrees – BBR: < 0.25 pixel – Revisit Capability: 5 days
  • 24. RESOURCESAT-1 LISS-IV MX IMAGE OF MUMBAI Cartosat-1 PAN Sensor Real time stereo viewing SPATIAL RESOLUTION 2.5 m Satellite Path Two Pan cameras - fore with 26 deg. and aft with -5 deg. Tilt( 500 nm- 850 Fore look Aft look nm) Swath 27.5 km for stereo and 55 km for monoscopic mode. 8 km overlap between adjacent paths 10 bits Facility for across track tilt to give better revisit
  • 25. ON - ORBIT CONFIGURATION OF CARTOSAT- 2SATELLITE PAYLOAD : PAN : 0.8 M SWATH : 9.6K M SPACECRAFT WEIGHT: 680 KGS ORBIT : 632 KM REVISIT : 4/5 DAYS EQUATORIAL CROSS OVER TIME : 9:30 AM LAUNCHED ON : 10TH JAN 2007 CARTOSAT PANCHROMATIC DATA (2.5 M) IIRS
  • 26. IRS P6 LISS IV(5.8m) MSS and CARTOSAT(2.5m) PAN FUSED Cartosat 1 : Chandigarh
  • 27. Hyderabad (Khairatabad and its environs), India as seen by CARTOSAT-2 Perth Airport, Australia as seen by CARTOSAT-2
  • 28. IKONOS SATELLITE DETAILS PAYLOAD :PAN : I M RESOLUTION MS : 4 M, 4 BANDS SWATH : 11 KMS SPACECRAFT MASS : 720 KGS ORBIT : 680 KM REVISIT : EVERY 3 DAYS EQUATORIAL CROSS OVER TIME : 10:30AM LAUNCH DATE : SEPTEMBER 1999
  • 29. ORBVIEW 5 (GEOEYE 1 - - ) PAYLOAD : PAN & MS CAMERA 0.41 M PAN 1.64 M MS IN 4 BANDS SWATH : 15.2 KM DYNAMIC RANGE : 11 BITS ORBIT : 684 KM REVISIT : < 3 DAYS EQUATORIAL CROSS OVER TIME : 10:30 AM LAUNCH DATE : 2007 Thermal Images Day time Night time
  • 30. RADAR Images ERS SAR image (pixel size=12.5 m) Flat surfaces such as paved roads, runways or calm water normally appear as dark areas in a radar image since most of the incident radar pulses are specularly reflected away.
  • 31. Microwave images This SAR image shows an area of the sea near a busy port. Many ships can be seen as bright spots in this image due to corner reflection. The sea is calm, and hence the ships can be easily detected against the dark background
  • 35. Contours 3D mapping from Cartosat-1 stereo Dataset PI: Ashutosh Bhardwaj, IIRS, Dehradun