Transcript Remote Sensing - Hunter College, Department of Geography
Introduction to Remote Sensing
Resolution Digital Images Image Interpretation Satellites and Sensors
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Remotes Sensing Technology Remote Sensing Images can be obtained from
:
Aerial Photographs • Contract a company to take the aerial photographs • Obtain from local Property Appraiser’s Office • Obtain from USGS Satellite Images • There are a number of countries that operate satellites that collect images of the Earth for commercial purposes • LANDSAT is operated by the United States
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Digital Images
A digital image can be broken down layers (or CHANNELS or BANDS) representing different types of light •each layer is black and white, •combination of three channels result in a color image into a regular grid of PICTURE ELEMENTS or PIXELS
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Digital Images
An aerial photograph or satellite image has three different resolutions The
SPATIAL
resolution The
SPECTRAL
resolution The
RADIOMETRIC
resolution The
TEMPORAL
resolution
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Resolution & Remote Sensing Systems
4 major resolutions
associated with each remote sensing system Spectral resolution Spatial resolution Temporal resolution Radiometric resolution These resolutions should be
understood
scientist in order to extract
meaningful
by the
biophysical or hybrid information
remotely sensed imagery.
from
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Resolution
Resolving power Measure of the ability of a sensor to distinguish between signals that are spatially near or spectrally similar Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Spectral Resolution
Number and size of the bands which can be recorded by the sensor – nominal spectral resolution
Course – sensitive to large portion of ems contained in a small number of wide bands Fine – sensitive to same portion of ems but have many small bands Goal – finer spectral sampling to distinguish between scene
objects and features
More detailed information about how individual features reflect or emit em energy increase probability of finding unique characteristics that enable a feature to be distinguished from other features.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Spectral Resolution
Difficult to create detector that has extremely sharp bandpass boundaries such as describe in previous slide More precise method of stating bandwidth is look at typical Gaussian-shape of the detector sensitivity Describe bandwidth as Full Width at Half Maximum (FWHW) Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Spectral Resolution
The SPECTRAL resolution defines the range of light stored in the image A black and white photograph stores a visible light; it has one channel that stores the light for 0.4 to 0.7 micrometers A natural color image stores reflected red, blue and green light in different channels; e.g. 0.45 - 0.52 m m for blue, 0.52 - 0.60 m m for green and 0.63 - 0.69 m m for red A LANDSAT image contains 7 channnels as described above that store reflected light other than visible light.
A HYPERSPECTRAL image contains hundreds of channels. E.g. A hyperspectral image that collects visible light may divide the visible light range into 300 channels, each channel containing a narrow range of wavelengths.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Spatial Resolution
Measure of the smallest angular or linear separation between 2 objects that can be resolved by the sensor
In practice, sensor system’s nominal spatial resolution is the dimension in
meters (or feet) on the ground projected instantaneous field of view (IFOV) Generally, smaller spatial resolution
greater the resolving power of the sensor system Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Spatial Resolution
The SPATIAL resolution defines that size of Earth’s surface that is stored in a pixel In a LANDSAT image a pixel represents 30 m by 30 m of the Earth’s surface.
In an USGS orthophotograph a pixel repesents 1 m by 1 m of the Earth’s surface.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Graphic representation showing differences in spatial resolution among some well known sensors (Source: Landsat 7 Science Data Users Handbook )
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Spatial Resolution
Useful rule
: To detect a feature, the spatial resolution of the sensor system should be less than ½ the size of the feature measured in its smallest dimension.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Temporal Resolution
How often the remote sensing system records imagery of a particular area.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Radiometric Resolution
radiance.
6 = (0-63) 64 2 8 = (0-255) 256 a change in recorded brightness value takes place.
generated by the sensor Landsat 7 ETM+ - 8bit
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Radiometric Resolution
The RADIOMETRIC resolution defines the range of values that an individual pixel can have Typical digital images have a range of values from 0 – 255 (a total of 256 possible values). An image that just shows black or white pixels would only store 0 (black) or 1 (white).
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Summary of Resolution
• By increasing 1 or any combination of these resolutions, increase chance of obtaining remotely sensed data about a target that contains accurate, realistic, and useful information.
• Downside of increased resolution need for increased storage space, more powerful processing tools, more highly trained individuals.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Aerial Photography
Types depend on: the altitude of the plane the camera the angle of view and the type of film used
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
The angle of view Vertical (directly over)
shows the scale and distance
Oblique (at an angle)
shows the object size
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
A Vertical Aerial Photograph
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
An oblique photograph
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Photographic films
Black and White Color InfraRed beyond the visible part of the spectrum
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Monochrome
(black and white)
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Panchromatic
(color)
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Used for vegetation studies Green vegetation strongly reflects IR Vigorously growing vegetation appears red
Color Infrared
(heat)
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Image Interpretation
Size of objects relative to one another Shape depends on the object outline Image tone brightness - hue, colour Patterns arrangement of features
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Image Interpretation
Texture smooth or coarse Shadow Site helps determine heights location helps recognition Association features that are normally found near others
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Interpretation
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Difficulties with Interpretation
unfamiliar prospective
viewing from above
use of wavelengths outside visible light range
Images often display different types of infrared light Colors in image not that same as colors seen by us • E.g. False infrared images displayed reflect near infrared light using red
unfamiliar scales and resolution
Landsat image’s pixels are 30 m by 30 m SPOT image’s pixels are 20 m by 20 m Aerial photograph’s pixels can be smaller than 6inches
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Shape
the general form of the object stereo photographs also show height which further defines shape
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Size
this needs to be considered in reference to scale What is the object in the image • The image covers approx 1 square mile?
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Pattern
this is the spatial arrangement of objects e.g. Orchard vs. Forest Man made objects vs. natural objects
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Tone (Hue)
the relative brightness of an object or its color
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Texture
frequency of tonal changes e.g. grass appears ‘smoother’ than forest depends on scale
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Shadows are both useful and a nuisance
define the profile of the object hide objects in the shadow area
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Characteristics of Objects
Site
topographical location e.g. palm trees are not found in New England
Association
what objects are found together e.g. a Ferris wheel
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Strategies
Other information in addition to the image
e.g. for crop identification use information on typical planting dates, recent weather conditions etc
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Strategies
There are two types of Interpretation keys.
Selective keys provide a set of example images.
E.g. pictures of different trees from above
Elimination keys makes the interpreter make a series of decision.
Is the ‘crown’ of the tree large or small: small might suggest pine tree in a given location rather than oak trees.
better for man made objects rather than vegetation.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Strategies
Consider film / filter combinations (or sensor channels)
Would a false infra red image be better than a natural color image?
Consider the Arial extent of the photograph
Do you need to have great detail or large aerial coverage?
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Approaching Classification
Define the classifications.
What objects are you trying to identify in the image What objects are considered the same • Pine tree forest and oak tree forest considered as just forest?
‘fuzzy’ edges, • Try to give good definition of where boundaries lie between natural objects – E.g. where desert ends and non-desert starts
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
What is a satellite?
The term
Satellite
body. simply refers to a body in orbit around another In 1957 the first artificial satellite SPUTNIK, was launched by the Soviet Union. Today there are hundreds of these spacecraft in orbit around the Earth. Satellites may serve many different purposes; they may be part of a television or telephone network or they can carry instruments to investigate the Earth’s surface or the Earth’s atmosphere. Other spacecraft point towards the Sun and monitor this star, or travel for many years carrying probes or landers which investigate the atmosphere, moons or surface features of distant planets. There are also manned spacecraft such as the US shuttle spacecraft and space stations such as MIR, the Soviet space station launched in 1986.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Satellite Orbits
Satellites generally have either polar orbits or geostationary orbits.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Meteosat
A program sponsored by 17 European weather services. It started with the successful launch of METEOSAT 1 in 1977 and has continued unabated. METEOSAT 7, the last in the current series was launched in early September 1997.
They are stationed above the equator at 0° longitude above the Gulf of Guinea and image this part of the globe every 30 minutes in three wavebands. These are:
the visible (0.4 to 1.1 micrometers), the water vapour (5.7 to 7.1 micrometers) and the thermal infrared (10.5 to 12.5 micrometers).
The first has a resolution of 2.5 km The first has a resolution of 2.5 km at the sub-satellite point (SSP) while the two infrared wavebands both have one of 5 km.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
NOAA (National Oceanic & Atmospheric Administration) Polar Orbiters
The programme that started with the successful launch of TIROS-1 in 1960 continues today with the NOAA polar orbiters. The satellites' AVHRR instruments image the planet in five bands:
8 to 0.68 micrometres 0.725 to 1.10 micrometres 3.55 to 3.93 micrometres 10.30 to 11.30 micrometres 11.50 to 12.50 micrometres
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Geostationary Operational Environmental Satellites (GOES)
This NOAA series of geostationary weather satellites began in 1974 and continues today with the launch of a new ‘GOES-NEXT series of more advanced satellites in 1994.
The resolution varies from 4 to 8 km.
They have five wavebands:
0.55 to 0.75micrometres
3.80 to 4.00 ” 6.50 to 7.00 “ 10.20 to 11.20 ” 11.50 to 12.50 "
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
The Space Shuttle
The space shuttle is a manned spacecraft mission, carrying astronauts and scientists as well as instruments.
The most important sensors that have been carried on the Shuttle for Earth imaging are:
The Shuttle Imaging Radar The Metric Camera. The Large Format Camera (LFC) The Modular Optical-Electronic Multispectral Scanner (MOMS).
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
LANDSAT Satellite Series
First LANDSAT satellite launched in 1972 Lasted until 1978 Six Landsat satellites to date LANDSAT-4 and -5 still operational LANDSAT -6 experienced launch failure
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Technical Information
Landsat 4 (launched 16.07.82) Landsat 5 (launched 01.03.84) Orbit near polar sun-synchronous complete orbit every 99 mins Altitude - 705 km, 438 miles Re-visit - 16 days
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Landsat 1, 2 and 3
Landsat was the first satellite to be designed specifically for observing the Earth’s surface.
Landsat 1, 2 and 3 carried a multispectral scanner (MSS) system which records reflected energy from the Earth’s surface or atmosphere across four wavebands; three visible channels and one near infrared. The MSS has a pixel resolution of 80 metres.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Landsats 4 & 5 - Thematic Mapper
LANDSATs 4 and 5 have a more refined multispectral scanner, the Thematic Mapper (TM), instrument on board.
TM is a multispectral sensor since it detects energy across seven wavelength bands.
The pixel resolution of six of the wavelength bands is 30 metres but the thermal infrared band has a pixel resolution of 120 metres.
On this Landsat TM true colour image of west and central London
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Landsat 7
After a successful launch on April 15 1999, Landsat 7 is up and running. Visit http://www.eurimage.com/ to see "Quick Looks" of some of the first acquired images..
LANDSAT 7 carries a TM sensor developed from that on Landsat 5. Key differences are: (1) extra 15m panchromatic band co-registered with the multi-spectral, and (2) band 6 resolution at 60m.
The fires of Dili, east Timor The Turkish earthquake
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
LANDSAT’s Thematic Mapper Sensor Collect 7 different types of light B G R Near IR Mid IR Thermal IR 1 2 3 4 5 7 6 1.
2.
3.
4.
0.45 - 0.52 m m 0.52 - 0.60 m m 0.63 - 0.69 m m 0.76 - 0.90 m m blue green red near IR R R R R 5.
6.
1.55 - 1.75 m m 10.4 - 12.5 m m mid IR thermal IR R E 7. 2.08 - 2.35 m m mid IR R and E
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Technical Information
Payload MSS TM (4 channels) (7 channels) Resolution MSS 80 m Resolution TM 30 m (band 6, 120 m) Swath 185 km x 185 km
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Applications of LandSat Imagery
Geology surveys for oil and mineral exploration Agriculture crop monitoring / yield forecast Cartography large area maps, to 1:50,000 Environment environmental audits and pollution monitoring Forestry woodland mapping / species identification
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Applications of LANDSAT Imagery
Planning land use analysis and change detection Utilities highway / power / resource management Commerce insurance damage assessment, civil engineering and commodities forecasting Marine coastal zone management and bathymetric mapping
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
SPOT (Systeme Probatoire de l’Observation de la Terre)
•SPOT satellites are placed in near-polar, sun-synchronous orbits at an altitude of 832 km. •The satellites have a pushbroom scanner system which can view the surface immediately below them (nadir view), or can be directed so that they view the surface to the side. This is important because it means that two views of the same area can be collected within a short time of each other, by two adjacent over-passes. Because the system can take two images of the same area with different look angles, it is possible to create stereoscopic (3-D) images. This is similar to having two eyes, enabling us to view in three dimensions because each eye views the same scene from a slightly different position, the brain then creates a 3-D picture. A computer can create a Digital Elevation Model (DEM) from two stereoscopic images, which means the shape of the land can be measured.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
SPOT
Images with two different spatial resolutions can be produced from SPOT data. The first is a panchromatic (black and white) image with a spatial resolution of 10 m. The second is an image from the multi-spectral sensor (SPOT XS) which collects 3 bands of data, with a resolution of 20 m.
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Active Sensors: ERS-1 and ERS-2
In July 1991, the first European Remote Sensing Satellite (ERS-1) was launched by the European Space Agency (ESA). It had a sun-synchronous circular orbit (near polar) at 770 km. Its purpose was to collect information on areas of the world that are difficult to observe from the surface, such as oceans and ice covered areas. It also produces images of the land surface in all weather conditions, 24 hours a day. ERS-1 was so successful that the ERS-2 was launched in April 1995, carrying additional equipment called Global Ozone Monitoring Experiment (GOME). Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)
Active Sensors: Radarsat
RADARSAT-1 spacecraft was launched in November 1995, by the Canadian Space Agency. The satellite carries a Synthetic Aperture Radar system providing all-weather, day and night observations of land and sea surfaces.The satellite’s SAR system has been designed to make it useful for a range of applications including: crop investigations coastal zone mapping ship detection hydrological applications geological applications ice monitoring oil spill detection ocean applications
e.g. mapping the ocean depths/shape of the sea floor)
Introduction to Mapping Sciences: Lecture #7 (Remote Sensing)