Geosynchronous Orbit A satellite in geosynchronous orbit circles the earth once each day. The time it takes for a satellite to orbit the earth is called.

Slides:



Advertisements
Similar presentations
NOAA National Geophysical Data Center
Advertisements

Resurs-P. Capabilities. Standard products. A. Peshkun The 14 th International Scientific and Technical Conference “From imagery to map: digital photogrammetric.
AMwww.Remote-Sensing.info Ch.2 Remote Sensing Data Collection
Some Basic Concepts of Remote Sensing
Resolution.
Spencer Anderson Brent Fogleman Daryl Vonhagel.  Objectives:  C-band (w = 3.8 – 7.5 cm) & X-band (w = 2.4 – 3.8 cm) IFSAR to acquire topographic data.
Remote Sensing Media Aircraft BasedAircraft Based –photography (BW, Color), infrared (BW, Color) –RADAR (SLAR, SAR) –LIDAR (light detection and ranging)
Remote Sensing II Sensors Konari, Iran Image taken 2/2/2000
Orbits and Sensors Multispectral Sensors
Multispectral Remote Sensing Systems
Remote Sensing Systems. Early Satellite Sensing Spy satellites gave exquisite but very local views and were classified Even before satellites were launched,
Characteristics of remote sensing systems
Integration of sensors for photogrammetry and remote sensing 8 th semester, MS 2005.
Remote Sensing of Our Environment Using Satellite Digital Images to Analyze the Earth’s Surface.
Detector Configurations Used for Panchromatic, Multispectral and Hyperspectral Remote Sensing Jensen, 2000.
Introduction, Satellite Imaging. Platforms Used to Acquire Remote Sensing Data Aircraft Low, medium & high altitude Higher level of spatial detail Satellite.
History and Features of Landsat 7 By: Andy Vogelsberg Photo of Landsat 7 taken from tures/litho/landsat/land.jpg.
Remote Sensing of Mesoscale Vortices in Hurricane Eyewalls Presented by: Chris Castellano Brian Cerruti Stephen Garbarino.
Satellite Thermal Remote Sensing of Boiling Springs Lake Jeff Pedelty NASA Goddard Space Flight Center Goddard Center for Astrobiology.
Remote Sensing Part 1.
Remote Sensing of Our Environment Using Satellite Digital Images to Analyze the Earth’s Surface.
Meteorological satellites – National Oceanographic and Atmospheric Administration (NOAA)-Polar Orbiting Environmental Satellite (POES) Orbital characteristics.
Geosynchronous Orbit A satellite in geosynchronous orbit circles the earth once each day. The time it takes for a satellite to orbit the earth is called.
Hyperspectral Satellite Imaging Planning a Mission Victor Gardner University of Maryland 2007 AIAA Region 1 Mid-Atlantic Student Conference National Institute.
Outline Further Reading: Chapter 04 of the text book - satellite orbits - satellite sensor measurements - remote sensing of land, atmosphere and oceans.
Fundamentals of Satellite Remote Sensing NASA ARSET- AQ Introduction to Remote Sensing and Air Quality Applications Winter 2014 Webinar Series ARSET -
Carolyn J. Merry NCRST-Flows The Ohio State University.
Lecture 21: Major Types of Satellite Imagery By Austin Troy University of Vermont Using GIS-- Introduction to GIS.
Course: Introduction to RS & DIP
©2008 Austin Troy Lecture 21: Major Types of Satellite Imagery By Austin Troy and Weiqi Zhou University of Vermont Using GIS-- Introduction to GIS.
Outline Further Reading: Chapter 04 of the text book - satellite orbits - satellite sensor measurements - remote sensing of land, atmosphere and oceans.
Remote Sensing High Resolution Satellite Systems.
Copyright © 2003 Leica Geosystems GIS & Mapping, LLC Turning Imagery into Information Suzie Noble, Product Specialist Leica Geosystems Denver, CO.
OC3522Summer 2001 OC Remote Sensing of the Atmosphere and Ocean - Summer 2001 Land/Ice Surface & Applications.
Geography 1010 Remote Sensing. Outline Last Lecture –Electromagnetic energy. –Spectral Signatures. Today’s Lecture –Spectral Signatures. –Satellite Remote.
Satellite Imagery and Remote Sensing NC Climate Fellows June 2012 DeeDee Whitaker SW Guilford High Earth/Environmental Science & Chemistry.
Geography 372 Fall 2003November 4, Remote Sensing of the Land Surface: High Spatial Resolution Michael D. King & Compton J. Tucker Outline  Land.
Digital Numbers The Remote Sensing world calls cell values are also called a digital number or DN. In most of the imagery we work with the DN represents.
Remotely Sensed Data EMP 580 Fall 2015 Dr. Jim Graham Materials from Sara Hanna.
Intro to Remote Sensing Lecture 1 August 25, 2004.
Resolution A sensor's various resolutions are very important characteristics. These resolution categories include: spatial spectral temporal radiometric.
Resolution Resolution. Landsat ETM+ image Learning Objectives Be able to name and define the four types of data resolution. Be able to calculate the.
10/12/2015 GEM Lecture 10 Content Other Satellites.
Remote Sensing and Image Processing: 8 Dr. Hassan J. Eghbali.
Remote Sensing Data Acquisition. 1. Major Remote Sensing Systems.
Satellite Image Products. NOAA AVHRR ( Advanced Very High Resolution Radiometer – AVHRR) AVHRR/3 Channel Characteristics Channel Number Resolution at.
Terra Launched December 18, 1999
Remote Sensing SPOT and Other Moderate Resolution Satellite Systems
CHARACTERISTICS OF OPTICAL SENSORS Course: Introduction to RS & DIP Mirza Muhammad Waqar Contact: EXT:2257 RG610.
Environmental Remote Sensing GEOG 2021 Lecture 8 Observing platforms & systems and revision.
Land Observation Satellites Dr. M. M. Yagoub URL :
SATELLITE ORBITS The monitoring capabilities of the sensor are, to a large extent, governed by the parameters of the satellite orbit. Different types of.
M. Shah Alam Khan Associate Professor Institute of Water and Flood Management, Bangladesh University of Engineering and Technology Hydro-ecological Investigation.
REMOTE SENSING DATA Markus Törmä Institute of Photogrammetry and Remote Sensing Helsinki University of Technology
Reading assignments for chapter 6 Pages – – – –
Orbits and Sensors Multispectral Sensors. Satellite Orbits Orbital parameters can be tuned to produce particular, useful orbits Geostationary Sun synchronous.
PLATFORMS & SENSORS Platform:
Remote Sensing.
Hyperspectral Sensing – Imaging Spectroscopy
Basic Concepts of Remote Sensing
LANDSAT OBSERVATİON SATELITE SYSTEM
ERT 247 SENSOR & PLATFORM.
From balloon, launched by students in Massachusetts, September 2, 2009
Landsat Program The World’s Most Sophisticated Optical Observatories of the Earth The World’s Model for International Collaboration in Earth Observation.
Digital Numbers The Remote Sensing world calls cell values are also called a digital number or DN. In most of the imagery we work with the DN represents.
Satellite Sensors – Historical Perspectives
CNES’s SPOT 5 (Satellite Pour l’Observation de la Terre)
IKONOS ~Derived from the Greek term eikōn, meaning image~
EMP 580 Fall 2015 Dr. Jim Graham Materials from Sara Hanna
High Resolution Sensors – QuickBird
Presentation transcript:

Geosynchronous Orbit A satellite in geosynchronous orbit circles the earth once each day. The time it takes for a satellite to orbit the earth is called its period. To stay over the same spot on earth, a geostationary satellite also has to be directly above the equator. Otherwise, from the earth the satellite would appear to move in a north-south line every day.

Sun-Synchronous Orbit Because the valid comparison of images of a given location acquired on different dates depends on the similarity of the illumination conditions, the orbital plane must also form a constant angle relative to the sun direction. This is achieved by ensuring that the satellite overflies any given point at the same local time, which in turn requires that the orbit be sun- synchronous The satellite crossed the equator at approximately the same local sun time (9:42) every day

Earth Resource Satellites Operating in the Optical Spectrum Landsat SPOT Meteorological Satellites –NOAA satellites –GOES satellites Ocean Monitoring Satellites –Radar Satellites –Seasat –ERS-1 –JERS-1 –Radarsat

Landsat-7 This program is jointly managed by NASA and USGS ( pdate.html) Launched on April 15, 1999 ( A new sensor : Enhanced Thematic Mapper Plus (ETM+) Same swath as ETM, similar orbits and characteristics Swath: The area imaged on the surface.

ETM+ Resolution –Bands1-5, 7: 30 meters –Band 6 (Thermal band): 60 meters –Band 8 (Panchromatic band): 15 meters Complete global view four times a year

ETM+ Ground transmission of data either directly or stored onboard for later transmission GPS is included for subsequent geometric processing of the data Primary receiving station: EROS Dara Center, SD

ETM+ Spectral Bands

Landsat 7 +ETM Spectral Bands

Landsat Resources Data acquisition (

Enhanced Thematic Mapper Plus (ETM+) 8 8-bit bands: bands 1-7 are the same as TM; additional panchromatic band 8, μm IFOV 30 x 30m (bands 1-5 and 7), 60 x 60m (band 6), 15 x 15m (band 8); swath width 185 km. Images the earth once every 16 days; 1999 to present

EOS Terra ASTER –The ASTER is a cooperative effort between NASA and Japan’s Ministry of International Trade and Industry –Primary applications include study vegetation, rock types, volcanoes, clouds, and produce DEM’s – 6 SWIR bands: band 6 centered at the clay absorption feature and band 8 at the carbonate absorption feature – 5 TIR bands: bands 10, 11, and 12 at sulfate and silica absorption features

ASTER Characteristics Wide Spectral Coverage 3 bands in VNIR (0.52 – 0.86 μm) 6 bands in SWIR (1.6 – 2.43 μm) 5 bands in TIR (8.125 – μm) High Spatial Resolution 15m for VNIR bands 30m for SWIR bands 90m for TIR bands Quantization (bits) 8 for VNIR AND SWIR 12 for TIR Swath width 60 km Images are not acquired based on researcher scheduling 1999 to present

ASTER consists of 3 subsystems: VNIR, SWIR and TIR

ASTER TM Repeat Orbit: 16 d16 d Scene60 km185km Bands: Pan01 15m VIS2 15m3 30m NIR1 30m1 30m SWIR 6 30m 2 30m TIR5 90m1 90m

ASTER Images of San Francisco Bay False Color Image (VNIR) Sediment Load (VNIR) Water Temperature (TIR)

IKONOS Launched on 24 September 1999 Commercial remote sensing system operated by Space Imaging Inc. of Denver, Colorado, USA

IKONOS Orbit Type: Sun-Synchronous Altitude: 681 Km Inclination: 98.1 degree Period: 98 minute Off-Nadir Revisit: 2.9 days at 1-m resolution, 1.5 days at 1.5 m at 40°

IKONOS (cont.) Ground resolution: 1-m panchromatic; 4-m multispectral Imagery Spectral Response –Panchromatic:  m –Multispectral: ; ; ;  m Nominal swath width: 13 km at nadir Areas of interest (Single scene ) : 13x13 km The IKONIS satellite is equipped with onboard GPS, enabling it to acquire imagery with very high positional accuracy Radiometric digitization: 11 bits

Sensor Characteristics (IKONOS) Spectral band Wavelength (  m( Resolution (m) 1 (blue) (green) (red) (NIR) Panchromatic

IKONOS Colour Image Beijing City 22/10/1999

IKONOS Colour Image Sydney Olympic Park 2000

IKONOS Colour Image

IKONOS Images Manhattan: before (left) and after (right) 11 September 2001 attack

IKONOS Images The Pentagon: before (left) and after (right) 11 September 2001 attack

QuickBird Commercial remote sensing system developed and operated by Digital Globe QuickBird 1 was launched on 20 Nov, 2000, but failed to reach orbit QuickBird 2 was Launched on 18 October 2001

Quickbird-2 orbit Type: Sun-Synchronous Altitude: 450 Km Inclination: 98 degree Period: 93.4 minute Off-Nadir Revisit: 1 to 3.5 days

QuickBird Features Panchromatic and multispectral images High spatial resolution: up to 61 cm panchromatic images; 2.44 m multispectral images at nadir Buildings, cars, and even large individual trees can be recognized using QuickBird Nominal swath width: 16.5 km at nadir Radiometric response: 11bits (2048 grey levels)

Sensor Characteristics (Quickbird) Spectral bandWavelength (  m) Resolution (at nadir) Resolution (at 30 deg. off nadir) 1 (blue) m2.9 m 2 (green) m2.9 m 3 (red) m2.9 m 4 (NIR) m2.9 m Panchromatic m0.73 m

QuickBird Panchromatic Image QuickBird Panchromatic image with 61 cm resolution, taken over Fairfax, Virginia, USA.

QuickBird Colour Image QuickBird natural colour image with 2.44 m resolution, taken over Fairfax, Virginia, USA

Quickbird

Hyperion The Hyperion is a high resolution hyperspectral imaging instrument The Hyperion images the earth's surface in 220 contiguous spectral bands with high radiometric accuracy, covering the region from 400 nm to 2.5 µm, at a ground resolution of 30 m

Hyperion Sensor Characteristics Spatial Resolution: 30 m Swath Width: 7.75 km Spectral Channels 220 unique channels. VNIR (70 channels, 356 nm nm), SWIR (172 channels, 852 nm nm) Spectral Bandwidth 10 nm (nominal) Digitization 12 bits Signal-to-Noise Ratio (SNR) 161 (550 nm); 147 (700 nm); 110 (1125 nm); 40 (2125 nm) Primary uses: General earth materials mapping geology, mining, forestry, agriculture, and environmental management

Land Observing Sensors and their Features Weather, Global Coverage Satellites Sensor NamePixelSwathNo. SpectralSpectralTemporal ResolutionWidth, kmBandsCoverageRepeat, days AVHRR1.1km27005VNIR, TIR4*day SPOT Vegetation1.15km22504VNIR, SWIR26 MODIS0.25,0.5,1km233036VNIR, SWIR, TIR2* day Regional Satellites SensormkmbandsSpectralRepeat ASTER15, 30, VNIR, SWIR, TIR16 Landsat ETM+30, 60, Pan + TM16 SPOT HRV10, 20604Pan, VNIR26 SPOT HRVIR10, 20605SWIR + HRV26 Local Coverage Satellites SensormkmbandsSpectralRepeat Quickbird0.61 Pan, Pan, VNIR2 to 11 IKONOS1.0 Pan, Pan, VNIR3

Medium and coarse resolution sensors SensorPixel Size, m ‘blue’ nm ‘green’ nm ‘red’ nm ‘NIR’ nm ‘SWIR’  m ‘Thermal’  m SPOT- VEGETATION Swath 2250 km NOAA- AVHRR Swath 2700 km MODIS (Terra, Aqua) Swath 2330 km

Medium and coarse resolution sensors Ikonos Swath 13 km 4 1 (pan) QuickBird Swath 16.5 km (pan) SensorPixel Size, m ‘blue’ nm ‘green’ nm ‘red’ nm ‘NIR’ nm ‘SWIR’  m ‘Thermal’  m