Remote Sensing Presentations

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GNR630 Introduction to Geo-Spatial

TechnologiesInstructors:

Prof. B. Krishna MohanDr. (Mrs.) P. Venkatachalam

Prof. S. S. GedamCSRE, IIT Bombay

bkmohan/pvenk/[email protected]

Slot 6 Lecture 01-02 Overview of the Course and Introduction

January 04/11, 2012 11.05 AM 12.30 PM

Overview of the Course

Syllabus to be Covered Motivation for Choice of Topics Assessment Take Home Message from Course

IIT Bombay Slide 1

GNR630 Lecture01-02 BKM/PV/SSG

Jan 04/11, 2012 Lecture01-02 Overview of Course and Introduction

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Part-1 Remote Sensing and Image Processing

IIT Bombay Slide 2


1. Introduction to Remote Sensing

2. Sensors, Resolution and Atmosphere

3. Georeferencing4. Image Processing

Operations5. Image Transforms6. Band Arithmetic and

PCT

7. Concept of Image Classification

8. Supervised and Unsupervised Image Classification

9. Feature Evaluation10. Accuracy

Estimation11. Change Detection

Part-2 GISIIT Bombay Slide 3


1. Introduction to GIS2. Spatial Data Models

and Data Sources3. Spatial Data Structures4. Map Projections5. Spatial Data Analysis6. Georeferencing7. Spatial Interpolation

and Terrain Modeling8. Watershed Delineation

9. Error Modeling and Analysis

10. Case Studies and Applications

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Part-3 Global Positioning Systems (Tentative)

IIT Bombay Slide 4


1. Concept of GPS2. Segments in GPS3. GPS Operations4. GPS Signals5. Position

Determination using GPS

6. Errors in GPS Signals

7. Types of GPS8. GPS Applications

Motivation

We live in a geographic space Where we live and work, the

environment that surrounds us relates to a geographic space

IIT Bombay Slide 5


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Why Geo-spatial Technologies? Managing our natural resources, carrying out

development activities, preserving our environment, human and animal habitats require detailed information

Geo-spatial technologies deal with data Acquisition Management Analysis Visualization and Dissemination Security and Retrieval

IIT Bombay Slide 6


Components of Geo-spatial Technologies

GIS geographic information system that can be viewed as an all-encompassing technology

Can be used to locate position of objects in their 3-dimensions, perform geo-spatial analysis, infer trends and carry out predictions / projections

An important component in DSS

IIT Bombay Slide 7


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Remote Sensing data covering a vast area can be obtained and contents inferred by visual analysis / computer classification

Remote sensors onboard satellites provide data on a periodic basis for years together

Very important for updating databases in a GIS and observing changes

IIT Bombay Slide 8



Digital Image Processing data analysis mechanism considering current data sets are acquired and disseminated directly in digital form

Routine operations can be very easily performed by batch mode computer processing

Many useful products are derived by computer based analysis

IIT Bombay Slide 9


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GPS data analysis mechanism including basic definitions

Components of a GPS Data acquisition using a GPS Applications of GPS

IIT Bombay Slide 10


Selected Applications of Geo-spatial Technologies

Resource Management Base map preparation for new airport Digital Elevation Modeling Urban Management Rural Development

IIT Bombay Slide 11


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Assessment Pattern (Tentative) Mid-term Examination 30% Semester End Examination 50% Quizzes 20%

IIT Bombay Slide 12


Prescribed Text Books (Remote Sensing and Image

Processing) Remote Sensing Digital Image Analysis

- J.A. Richards and X. Jia Remote Sensing: Models and Methods

for Image Processing- Robert Schowengerdt

IIT Bombay Slide 13


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Prescribed Text Books (GIS)

Introduction to Geographic Information Systems-Chang Kang-tsung

Concepts and Techniques of Geographic Information Systems-Lo, C.P. and Albert K.W. Yeung

IIT Bombay Slide 14


Prescribed Text Books (GPS)To be specified

IIT Bombay Slide 15


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Expected Outcome from the Course Basic idea of remote sensing and Digital

image processing of satellite remotely sensed images

Knowledge of geospatial data models, processing methods and applications

Basic concepts of GPS, structure of GPS signals, Position estimation from GPS, Errors, ApplicationsGNR630 Lecture01-02 BKM/PV/SSG

IIT Bombay Slide 16

What is Remote Sensing?

Remote sensing is the art and science of making measurements about an object or the environment without being in physical

contact with it

IIT Bombay Slide 17


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Importance of Remote Sensing Remote Sensing provides vital data for many critical

applications Resources management Environmental monitoring Defence Urban / rural development and planning Crop yield forecasting Hazard zonation and disaster mitigation


IIT Bombay Slide 18

Stages in Remote Sensing Electromagnetic energy reflected / emitted by earth

surface features Energy received by the remote sensors Energy converted to electrical signal Electrical signal converted to DIGITAL form Digital signal transmitted to ground Ground station organizes data on CDs/DVDs Data distributed to users Users analyze data and produce information products

IIT Bombay Slide 19


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Snapshot of Remote Sensing

IIT Bombay Slide 20


Electromagentic SpectrumIIT Bombay Slide 21


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Visible and Reflective Infrared Reflectance measurements in different

wavelengths ratio of incident to reflected energy Ranges 0% to 100% Highly wavelength dependent

Basic Premise of RS

Each object on the earth surface has a unique reflectance pattern as a function of wavelength

IIT Bombay Slide 22


IIT Bombay Slide 23

CSRE


1m x 1m

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Vegetation Reflectance SpectrumIIT Bombay Slide 24


Low reflectance in Visible Region

High reflectance in NIR

Reflectance Spectra of Earth ObjectsIIT Bombay Slide 25


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Atmospheric Windows The atmosphere interferes with the radiation

passing through it It is essential to block the harmful UV rays in

solar radiation from reaching the earth Should not block the radiation in in wavelengths

used for earth observation Choice of wavelengths

Clear response of earth surface features Minimal interference from atmospheric

constituents

IIT Bombay Slide 26



IIT Bombay Slide 27

From Richards and Jias book

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Short Wave Infrared (SWIR)(0.7 - 2 microns)

Visible(0.4 - 0.7 microns)

wavelength (in microns)1 10 102 103

Long Wave Infrared (LWIR)(8 - 12 microns)

Millimeter Wave (MMW)(3200 - 8600 microns)

104

Mid Wave Infrared (MWIR)(3 - 5 microns)


IIT Bombay Slide 28

Atmospheric WindowsIIT Bombay Slide 29


Tran

smis

sio

n (%

)

Wavelength (microns)

Visible Near Infrared Far Infrared

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Role of AtmosphereIIT Bombay Slide 30


Wavelengths less affected by atmosphere are chosen to design the sensors to operate in:

Visible 400 nm 700 nm Near infrared 700 nm 2500 nm with a few gaps Thermal infrared 8 microns 15 microns Microwave 1 cm 30 cm (approx.)

Other wavelengths are blocked by atmosphere

Specifications of Remote Sensors Technology used Resolution

IFOV of sensing element Number of wavelengths in which data are

recorded Number of levels in which data values are

recorded Frequency of data collection over a given area

IIT Bombay Slide 31


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Sensor TechnologyIIT Bombay Slide 32


Sensors are broadly of two types:Electromechanical scanning is performed by an oscillating mirror deflecting upwelling radiation from earth onto wavelength sensitive photodetectors. Maintaining constant angular velocity of the mirror is a problemSolid state sensor consists of a linear array of detectors, equal in number to the number of pixels in a row of the image. Much more stable compared to electromechanical scanning

Electromechanical TechnologyIIT Bombay Slide 33


Detector system

Oscillating mirror system

A pixelDirection of flight

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Solid State TechnologyIIT Bombay Slide 34


Detector Array

Direction of flight

Linear Array of pixels

Lens

Focal plane of lens

Concept of ResolutionIIT Bombay Slide 35


Four types of resolution in remote sensing:Spatial resolutionSpectral resolutionRadiometric resolutionTemporal resolution

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Spatial ResolutionIIT Bombay Slide 36


Ability of the sensor to observe closely spaced features on the groundFunction of the instantaneous field of view of the sensorLarge IFOV Coarse spatial resolution pixel covers more area on groundSmall IFOV Fine spatial resolution pixel covers less area on groundA sensor with pixel area 5x5 metres has a higher spatial resolution than a sensor with pixel area 10x10 metres

Point to Note

IFOV is 10 metres x 10 metres square does not mean that objects smaller than this size will not be visible

If a smaller object has very high or very low reflectance relative to its background, such object will be visible despite its size being smaller than the pixels IFOV

GNR630 Lecture01-02 B. Krishna Mohan

IIT Bombay Slide 37

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Effect of Spatial Resolution When resolution is very high we perceive

individual objects such as buildings or roads

When resolution is medium, we perceive very large objects as individual features, and areas as textured regions

When resolution is coarse, we perceive color or tone variations, and large area based features.

IIT Bombay Slide 38


IIT Bombay Slide 39

CSRE


0.6m x 0.6m

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IIT Bombay Slide 40

CSRE


1m x 1m

IIT Bombay Slide 41

GNR630 Lecture01-02 BKM/PV/SSG5.8m x 5.8m

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IIT Bombay Slide 42


23.25m x 23.25m

Effect of High Spatial Resolution High resolution images are information rich

Spatial information Multispectral information Textural information

Image can be viewed as a collection of objects with spatial relationships adjacent, north of, south of,

IIT Bombay Slide 43


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Spectral Resolution Ability of the sensor to distinguish

differences in reflectance of ground features in different wavelengths

Characterized by many sensors, each operating in a narrow wavelength band

Essential to discriminate between sub-classes of a broad class such as vegetation

IIT Bombay Slide 44


High Spectral ResolutionIIT Bombay Slide 45


Large number of contiguous sensorsNarrow bandwidth

wavelength

Response

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Coarse Spectral ResolutionIIT Bombay Slide 46


wavelength

Response

Small number of sensorsLarge bandwidth

Reflectance SpectraIIT Bombay Slide 47


wavelength

reflectance

Unique spectra of objects

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Temporal Resolution This depends on the return time of the

satellite Return time is a function of the altitude

at which the satellite is launched Higher the altitude, more circumference

of orbit, longer to orbit the earth

IIT Bombay Slide 48


Temporal Resolution Lower altitude satellites have a higher

frequency of revisit of the same area on earth

Normal revisit time is approximately 16-25 days for different satellites

Some satellites are launched in pairs with a time gap, e.g., IRS 1C / 1D

Temporal resolution doubles, revisit time decreases by 50%

IIT Bombay Slide 49


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Temporal Resolution Some sensors have steerable control

mechanism This enables revisit over any area

whenever desired Useful in applications like disaster

mitigation, military reconnaissance Steerable sensors also provide multiple

views of the terrain for stereo modeling

IIT Bombay Slide 50


Stee

rabl

e Se

nso

r Sy

stem

s

IIT Bombay Slide 51


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IIT Bombay Slide 52


International Space Programmes

USA China/BrazilRussia NigeriaFrance CanadaIndia European Space AgencyJapan South KoreaTaiwan Thailand

http://www.itc.nl/research/products/sensordb/searchsat.aspx

Selected Indian Satellites

(From IRS-1A onwards) IRS-1A OCM (IRS-P4) IRS-1B Resourcesat (IRS-P6) IRS-1C Cartosat 1 (IRS-P5) IRS-1D Cartosat 2A Risat 2 Chandrayaan 1

IIT Bombay Slide 53


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IIT Bombay Slide 54


IIT Bombay Slide 55


Resourcesat FCC image of Kuwait city 5.8m x 5.8m

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IIT Bombay Slide 56

CSRE


Resourcesat Mono image of Abu Dhabi airport 5.8m x 5.8m

IIT Bombay Slide 57


WiFS image of Sunderbans188m x 188m

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IIT Bombay Slide 58


Cartosat 1 image of Maldives

What is a Digital Image?A digital image is a representation of the real

world, discretized in space with energy reflected / emitted / transmitted by the objects in the image quantized to finite number of levels

IIT Bombay Slide 59


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Camera

Real World Scene Digital Image

Pixel


IIT Bombay Slide 60

Digitization Digitization involves three steps:

Sampling Quantization Coding

IIT Bombay Slide 61


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Sampling View area divided into cells Each cell is a picture element pixel The image now is a matrix of M rows, and

N columns M = Length of View area / Length of Cell N = Width of View area / Width of Cell Smaller cell size better ability to

distinguish between closely spaced objects


IIT Bombay Slide 62

Sampling In remotely sensed images the sampling is

essentially ground sampling i.e., on the ground a virtual grid is placed and the energy reflected / transmitted / emitted from each grid cell is collected by the sensors and stored as a pixel value

The grid cell corresponds to a pre-defined area on the ground; e.g., 5.8m x 5.8m as in case of ISROs Resourcesat Satellite

IIT Bombay Slide 63


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Sampling Smaller the grid cell area better the details

visible in the image The grid cell corresponding to a pre-

defined area on the ground; e.g., 5.8m x 5.8m

This is similar to dpi settings in desktop image scanners. Higher dpi, smaller size of dot, more pixels or cells in the image

IIT Bombay Slide 64


Spatial Resolution


IIT Bombay Slide 65

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Resolution

Progressively decreasing resolutionConstant area Increasing IFOV


IIT Bombay Slide 66

Impact of Pixel Size Pixel size corresponds to the

Instantaneous Field of View (IFOV) of the sensing system

Smaller the IFOV, better is the ability to resolve closely spaced objects (RESOLUTION)

Price to pay larger size of data Noise sensitivity of the sensor determines

the maximum possible resolution

IIT Bombay Slide 67


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Quantization Reflected / transmitted / emitted energy from

the object is converted into an electrical signal

The electrical signal converted to a digitalsignal by an analog-to-digital converter (ADC).

Digital signal takes a range of values according to the specification of the ADC

IIT Bombay Slide 68


Shades in Image and Digital Values


IIT Bombay Slide 69

0 28 56

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ADC 8-bit ADC 28 distinct values, represented

in binary as 00000000 11111111, or 0 to 255 in decimal form or 00 to FF in hex

11-bit ADC 211 values, 0 to 2047 The number of levels indicate the number of

distinct individually differentiable levels of received energy

IIT Bombay Slide 70


64 levels (6 bit) more shades visible

4 levels (2 bit) severe contouring effect

IIT Bombay Slide 71

Impact of quantization levels


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Point to Note When an image contains regions of fine

detail, high spatial resolution (e.g. a stadium with large crowd) is important

When the image contains large regions of very little change such as a close-up of a person, high number of quantization levels is important

IIT Bombay Slide 72


Pixel Size Less Important

Original Pixel area 4 times original

IIT Bombay Slide 73


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Quantization Levels More Important

256 levels 8 levels

IIT Bombay Slide 74


Pixel Size Important

160 x150 80 x 75

IIT Bombay Slide 75

GNR630 Lecture01-02 B. Krishna Mohan24-bit 24-bit

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Number of Levels less Important

160 x150 160 x 150

IIT Bombay Slide 76

GNR630 Lecture01-02 B. Krishna Mohan24-bit 8-bit

Encoding Normally the quantized image is binary

encoded. If the number of quantization levels is

between 0 and 255, each pixel is represented by 1-byte

If the number of levels exceeds 255, each pixel is assigned two-bytes.

At present, American satellites Quickbird, Ikonos, Indian satellites Cartosat and a few others have 11 bit and 10 bit ADCs and store data in 2 bytes per pixel on disk.

IIT Bombay Slide 77


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Motivation for Digital Image Processing

Why Digital Image Processing for Remote Sensing? Nature of data (inherently digital) Flexibility offered by computers Reducing the bias of human analysts Standardizing routine operations Rapid handling of large volumes of data

IIT Bombay Slide 78


Motivation for Digital Image Processing

Why Digital Image Processing for Remote Sensing? Certain operations cannot be done

manually (removal of distortions) Generation of different views Archival in compact/compressed mode Easy to share and disseminate

IIT Bombay Slide 79


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The Origins of Digital Image Processing

Early 1920s: One of the first applications in the news-paper industry, cable transmission between NY and London Source: http://www. imageprocessingplace.com

IIT Bombay Slide 80


Historical Developments Mid to late 1920s: Improvements to the

Bartlane system resulted in higher quality imagesNew reproduction processes based on photographic techniquesIncreased number of tones in reproduced imagesImproved digital image.

IIT Bombay Slide 81


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Space Race for Moon Improvements in computing technology and

the onset of the space race for moon led to a surge of work in digital image processing

Computers used to improve the quality of images of the moon taken by the Ranger 7 probeSuch techniques were used in other space missions including the Apollo landings

IIT Bombay Slide 82


Medicine Digital image processing begins to be used

in medical applications1979:Sir Godfrey N. Hounsfield& Prof. Allan M. Cormack share the Nobel Prize in medicine for the invention of tomography, the technology behind Computerised Axial Tomography (CAT) scans

IIT Bombay Slide 83


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1980s and later 1980s -Today: The use of digital image

processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas

Image enhancement/restoration Artistic effects Medical visualization Industrial inspection Law enforcement Human computer interfaces

IIT Bombay Slide 84


Wavelengths used for Imaging Gamma Rays Wavelength X-Rays Visible/Infrared Rays Microwaves Radio waves Ultrasound waves Seismic waves Frequency

IIT Bombay Slide 85


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Components of an Image Processing System

Image Sensors Image Display Image Storage Computer Image Processing software Special Purpose graphics hardware Image printers/plotters

IIT Bombay Slide 86


Image Image ImageDisplays Storage Hardcopy

Dedicated Digital DIP/DIAGraphic Proc. Computer Software

Image Acquisitionfrom real world

IIT Bombay Slide 87


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PC-Based Image Processing Systems

Todays personal computers with a digital still / video camera and a printer can become full fledged image processing systems

Most commercial / shareware / freeware image processing software will run on normal personal computer configurations

IIT Bombay Slide 88


Steps in Image Processing

IIT Bombay Slide 89


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Steps in Digital Image Processing

Final Interpretation

IIT Bombay Slide 90

Image Acquisition

Image Corrections

Image Enhancement

Image Transforms

Feature Selection

Image Classification


Steps in Image Processing Image Acquisition Image Corrections Image Enhancement Image Transforms Feature Selection Classification Accuracy Assessment Change Detection Efficient Representation and Coding Applications

IIT Bombay Slide 91


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Remote Sensing Presentations

Documents

Transcript of Remote Sensing Presentations