integration of sensors for photogrammetry and remote sensing 8 th semester, ms 2005

Integration of sensors for photogrammetry and remote sensing

8th semester, MS

2005

Overview on satellites and sensors operating in the optical spectrum

• Earth observing system (EOS)• Landsat• SPOT• NOAA• Other satellite programs

• Exercise: supervised classification of a Landsat TM image

NASA’s ESE

• 1991: NASA started the Earth Science Enterprise (ESE), a program studying the Earth as an environmental system

• ESE consists of:– Earth observing system (EOS)– Advanced processing network for processing, storing, and

distributing data– Teams of scientists all over the world who will study the data

Earth observing system (EOS)

• consists of a series of satellites equipped with different sensors for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans

EOS Terra

• launched on December 18, 1999• five onboard sensors

– ASTER: Advanced Spaceborne Thermal Emission and Reflection Radiometer

– CERES: Clouds and Earth's Radiant Energy System– MISR: Multi-angle Imaging Spectroradiometer– MODIS: Moderate-resolution Imaging Spectroradiometer – MOPITT: Measurements of Pollution in the Troposphere

• program has been running since 1970’s• provides repetitive acquisition of high resolution multispectral

data of the Earth's surface on a global basis• integral component of NASA's Earth Sciences Enterprise

• 7 missions until 2005• five different types of sensors:

– Return Beam Vidicon (RBV)

– Multispectral Scanner (MSS)

– Thematic Mapper (TM)

– Enhanced Thematic Mapper (ETM)

– Enhanced Thematic Mapper Plus (ETM+)

Landsat satellite program

Landsat missions

Landsat sensors

Goals of Landsat 7 mission

• provide timely, high quality visible and IR images of all landmass and near-coastal areas on the Earth

• continually refreshing an existing Landsat database• data will be consistent with currently archived data in terms of

acquisition geometry, calibration, coverage and spectral characteristics to allow comparison for global and regional change detection and characterization

• support government, international and commercial communities• improved access to International Ground Station data

Landsat 7 data distribution system

Landsat 7 orbit

• circular• Sun-synchronous (between 10:00 AM

and 10:15 AM on the Equator)• near polar• repetitive (16-day Earth coverage

cycle )• nominal altitude of 705 km at the

Equator• velocity 7.5 km/sec, each orbit takes

nearly 99 min• just over 14 orbits per day

Landsat 7 swath pattern

ETM+ design

• nadir-viewing, eight-band multispectral scanning radiometer

• silicon detectors for bands 1-4 and 8 (panchromatic) are located in the the Primary Focal Plane

• detectors for bands 5, 7, and 6 are located in the Cold Focal Plane

• 32 detectors for band 8, 16 detectors for bands 1-5 and 7, and 8 detectors for band 6

Landsat 7 image acquisition

• scenes placed the standard worldwide reference system• the WRS indexes orbits (paths) and scene centers (rows) into a global

grid system comprising 233 paths by 248 rows

• the ETM+ does not acquire data continually, acquisitions are scheduled in advanced using a Long Term Acquisition Plan (LTAP)

• LTAP aspects : – seasonality of vegetation, niche-science communities – predicted vs. nominal cloud-cover – sun angle – missed opportunities for previous acquisitions – quality (cloud-cover) of previous acquisitions – scene clustering – system constraints (duty cycle, ground station locations, recorder capacity,

etc.)

Landsat 7 image products

Program philosophy: to provide raw data

LevelRadiometric corrections

Geometric corrections

Format

0R - - HDF

1R + - HDF

1G ++

(systematic errors, projection)

HDF, GeoTIFF

Landsat 7 0R product

BandNumber

Resolution(meters)

Samples(columns)

Data Lines(rows)

Bits perSample

1-5, 7 30 6600 6000 8

6 60 3300 3000 8

8 15 13200 12000 8

Image Dimensions for a Landsat 7 0R Product

Size of the scene approx. 185 km x 180 km

Applications of Landsat images

• middle and small scale mapping• forest monitoring• mapping volcanic surface deposits• monitoring of natural disasters (floods, fires, slides)

SPOT satellite program

• SPOT = Système Pour l’Observation de la Terre• program started from an initiative of the French government in

1978, Sweden and Belgium joined before the launch of the first series of satellites

• first system that employed pushbroom scanning techniques and off-nadir viewing (stereoscopic coverage)

SPOT program – general features

SPOT sensorsSPOT 1, 2, 3 high resolution visible (HRV) imaging system

SPOT 4 high resolution visible and infrared (HRVIR) imaging system

SPOT 5 high resolution geometric (HRG) and high resolution stereoscopic (HRS) imaging system

Acquisition of stereoimagesacross-track

Acquisition of stereoimagesalong-track, only HRS on SPOT 5

Fore-and-aft stereo data collection

Derivation of a DEM at resolution of 10 m

SPOT products• Level 1A

– radiometric corrections– average location accuracy 350m/50m (SPOT 1 - 4/SPOT 5)

• Level 1B– radiometric corrections and systematic geometric corrections– average location accuracy better than 350m/50m

• Level 2A– images rectified to UTM/WGS8 system without GCPs, a global DEM used for

SPOT 5 images– average location accuracy better than 350m/50m

• Level 2B (Precision)– images georeferenced into a given map projection using GCPs– average location accuracy better than 30 m in flat terrain

• Level 3 (Ortho)– images georeferenced into a given map projection using GCPs and orthorectified– average location accuracy better than 15m

Applications of SPOT images

               monitoring urban growth

detection of a leak on a pipeline

inventorying crops, estimating yields and organizing harvesting

Environmental satellites NOAA

• series of polar orbit satellites launched from 1978• altitude approx. 830 km• collect global data on

– cloud cover– surface conditions such as ice, snow, and vegetation– atmospheric temperatures, moisture, aerosol, and ozone

distributions

Sensors on NOAA satellites

• Advanced Very high Resolution radiometer (AVHRR)– six channels detecting visible, near IR, and thermal IR channels– nominal spatial resolution of 1.1 km at nadir

• High Resolution Infrared Radiation Sounder (HIRS)– one visible channel, seven shortwave IR channels, and 12

longwave IR channels– nominal spatial resolution at nadir of 20.3km and 18.9 km

• Advanced microwave sounding units (AMSU)– provide measurements for calculating global atmospheric

temperature and humidity profiles, vertical water vapor profiles

…

Among others: Search and Rescue Instruments» program for receiving emergency signals

NOAA’s imagery applications

Sea surface temperature map produced from the AVHRR measurements

Cloud covers, storms.

The image with an original resolution of 1.1km was produced from a composite of channels 1, 2, and 4 from of the AVHRR instrument.

Ozone profiles and maps of total ozone values

Links

• Earth Observing Systemhttp://eospso.gsfc.nasa.gov/

• Landsathttp://landsat.gsfc.nasa.gov/

• SPOThttp://www.spot.com/html/SICORP/_401_.php

• NOAAhttp://www.oso.noaa.gov/poes/

Literature:Lillesand,T.,M., Kiefer, R., W.: remote sensing and image

interpretation, Wiley & Sons, 2000 (2004)

Digital Image Processing

• Data Acquisition

• Image Rectification and Restoration

– geometric and radiometric corrections, noise elimination

• Image Enhancement

– contrast, filtering, edge enhancement, ...

• Image Classification

– supervised, unsupervised

• Data Merging and GIS Integration

• Image Transmission and Compression

• automatically categorisation of all pixels in an image into land

cover classes

• basic idea: in multispectral images different features types show

different combinations of digital numbers

• supervised classification

• unsupervised

– classification stage

– determining land cover identity of clusters

Classification

Classification algorithms

Minimum distance classifier

Parallelepiped classifierMaximum likelihood classifier

Supervised classification

– training stage (training areas)

– classification stage

Principal Component Analysis

• images from various wavelength bans

appear similar, obtained information is

almost the same (interband correlation)

• all information contained in an original

n-band data set is compressed to n1<n

bands called COMPONENTS

• principal component (PC) data values are

linear combinations of the original data

values

• total scene variance of PC1 > PC2 > PC3…

• data contained in PCs are uncorrelated

(orthogonality)B

and

2

Band 1

Axis I

Axis II