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Lecture on Dt. 16 - 02 - 2017 at BMCET , Surat Basics of Remote Sensing and GIS Bhasker V. Bhatt PG in - charge (ME TCP) & Assistant Professor Faculty of Civil Engineering SCET , Surat For the Students of Civil Engineering

Basics of RS and GIS

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Lecture on Dt. 16-02-2017 at

BMCET, Surat

Basics of Remote Sensing and GIS

Bhasker V. BhattPG in-charge (ME TCP) & Assistant Professor

Faculty of Civil Engineering

SCET, Surat

For the Students of Civil Engineering

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Outline

Remote Sensing Defined

Resolution

Electromagnetic Energy (EMR)

Types

Interpretation

Applications

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Remote Sensing Defined

Remote Sensing is:

“The art and science of obtaining information about an object without being in direct contact with the object” (Jensen 2000).

There is a medium of transmission involved.

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Remote Sensing Defined

Environmental Remote Sensing:

… the collection of information about Earth surfaces and phenomena using sensors not in physical contact with the surfaces and phenomena of interest.

We will focus on data collected from an overhead perspective via transmission of Electromagnetic Radiation.

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Remote Sensing Defined

Remote Sensing Includes:

A) The mission plan and choice of sensors;

B) The reception, recording, and processing of the signal data; and

C) The analysis of the resultant data.

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Orbits

Low Earth orbit (LEO): geocentric orbits with altitudes from 160 to 2,000 km (100–1,240 miles).

Medium Earth orbit (MEO): geocentric orbits ranging in altitude from 2,000 km (1,240 miles) to just below geosynchronous orbit at 35,786 kilometers (22,236 mi).

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https://en.wikipedia.org/wiki/List_of_orbits

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When a satellite reaches exactly 42,164 kilometers from the center of the Earth

(about 36,000 kilometers from Earth's surface), it enters a sort of “sweet spot” in

which its orbit matches Earth's rotation.

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A satellites orbit the Earth in one of two basic types of orbit.

•Circular satellite orbit: For a circular orbit, the distance from the Earth remains

the same at all times.

•Elliptical satellite orbit: The elliptical orbit changes the distance to the Earth

•Geocentre: When satellites orbit the Earth, either in a circular or elliptical orbit, the

satellite orbit forms a plane that passes through the centre of gravity or geocentre of

the Earth.

Source: http://www.radio-electronics.com/info/satellite/satellite-orbits/satellites-orbit-definitions.php

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Energy Source or Illumination (A)

Radiation and the Atmosphere (B)

Interaction with the Target (C)

Recording of Energy by the Sensor

(D)

Transmission, Reception, and

Processing (E)

Interpretation and Analysis (F)

Application (G)

Source: Canadian Centre for Remote Sensing

Remote Sensing Process Components / Principle of RS

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Resolution

All remote sensing systems have four types of resolution:

Spatial

Spectral

Temporal

Radiometric

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High vs. Low?

Spatial Resolution

Source: Jensen (2000)

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Source: Jensen (2000)

SpectralResolution

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Temporal Resolution

Time

July 1 July 12 July 23 August 3

11 days

16 days

July 2 July 18 August 3

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Radiometric Resolution

6-bit range

0 63

8-bit range

0 255

0

10-bit range

1023

Every time an image is acquired on

film or by a sensor, its sensitivity to the

magnitude of the electromagnetic

energy determines the radiometric

resolution.

The radiometric resolution of an

imaging system describes its ability to

discriminate very slight differences in

energy.

The finer the radiometric resolution of

a sensor, the more sensitive it is to

detecting small differences in reflected

or emitted energy.

Source: http://www.nrcan.gc.ca/node/9379#answer

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Radiometric Resolution

Imagery data are represented by positive digital numbers which vary from 0 to (one less than) a selected power of 2.

This range corresponds to the number of bits used for coding numbers in binary format. Each bit records an exponent of power 2 (e.g. 1 bit=2 1=2).

The maximum number of brightness levels available depends on the number of bits used in representing the energy recorded.

Thus, if a sensor used 8 bits to record the data, there would be 28=256 digital values available, ranging from 0 to 255.

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Whiz Quiz

Suppose you have a digital image which has a radiometric resolution of 6 bits. What is the maximum value of the digital number which could be represented in that image?

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Answer

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Answer

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The number of digital values possible in an image is equal

to the number two (2 - for binary codings in a computer)

raised to the exponent of the number of bits in the image

(i.e. 2# of bits).

The number of values in a 6-bit image would be equal to 26

= 2 x 2 x 2 x 2 x 2 x 2 = 64.

Since the range of values displayed in a digital image

normally starts at zero (0), in order to have 64 values, the

maximum value possible would be 63.

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Electromagnetic Radiation

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Electromagnetic Spectrum

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Signature Spectra

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Types of Remote Sensing

Aerial Photography

Multispectral

Active and Passive Microwave and LIDAR

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Aerial Photos

Balloon photography (1858)

Pigeon cameras (1903)

Kite photography (1890)

Aircraft (WWI and WWII)

Space (1947)

Images: Jensen (2000)

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Multispectral

NOAA-AVHRR (1100 m)

GOES (700 m)

MODIS (250, 500, 1000 m)

Landsat TM and ETM (30 – 60 m)

SPOT (10 – 20 m)

IKONOS (4, 1 m)

Quickbird (0.6 m)

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AVHRR (Advanced Very High Resolution Radiometer) NASA

NOAANational Oceanic and Atmospheric Administration

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GOES (Geostationary Operational Environmental Satellites) IR 4

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MODIS (250 m) (Moderate Resolution

Imaging Spectro-radiometer)

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Landsat TM (False Color Composite)

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SPOT (2.5 m)

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QUICKBIRD (0.6 m)

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IKONOS (4 m Multispectral)

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IKONOS (1 m Panchromatic)

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RADAR (Radio Detection and Ranging)

Image: NASA 2005

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LIDAR (Light Detection and Ranging)

Image: Bainbridge Island, WA courtesy Pudget Sound LIDAR Consortium, 2005

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Elements of Image Interpretation

Shape:

Many natural and human-made features have unique shapes.

Often used are adjectives like linear, curvilinear, circular, elliptical, radial, square, rectangular, triangular, hexagonal, star, elongated, and amorphous.

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Jensen (2000)

Shape

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Elements of Image Interpretation

Shadow:

Shadow reduction is of concern in remote sensing because shadows tend to obscure objects that might otherwise be detected.

However, the shadow cast by an object may be the only real clue to its identity.

Shadows can also provide information on the height of an object either qualitatively or quantitatively.

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Jensen (2000)

Shadow

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Elements of Image Interpretation

Tone and Color: A band of EMR recorded by a remote sensing

instrument can be displayed on an image in shades of gray ranging from black to white.

These shades are called “tones”, and can be qualitatively referred to as dark, light, or intermediate (humans can see 40-50 tones).

Tone is related to the amount of light reflected from the scene in a specific wavelength interval (band).

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Jensen (2000)

Tone and Color

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Elements of Image Interpretation

Texture:

Texture refers to the arrangement of tone or color in an image.

Useful because Earth features that exhibit similar tones often exhibit different textures.

Adjectives include smooth (uniform, homogeneous), intermediate, and rough (coarse, heterogeneous).

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Jensen (2000)

Texture

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Elements of Image Interpretation

Pattern:

Pattern is the spatial arrangement of objects on the landscape.

General descriptions include random and systematic; natural and human-made.

More specific descriptions include circular, oval, curvilinear, linear, radiating, rectangular, etc.

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Jensen (2000)

Pattern

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Elements of Image Interpretation

Height and Depth: As discussed, shadows can often offer clues to the

height of objects.

In turn, relative heights can be used to interpret objects.

In a similar fashion, relative depths can often be interpreted.

Descriptions include tall, intermediate, and short; deep, intermediate, and shallow.

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Height and Depth

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Elements of Image Interpretation

Association:

This is very important when trying to interpret an object or activity.

Association refers to the fact that certain features and activities are almost always related to the presence of certain other features and activities.

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Jensen (2000)

Association

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Imaging Tools and Data Google Earth

USGS Data

Bhuvan (of ISRO)

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GIS OVERVIEW

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A Model… A model is simply a means of representing “reality” and, spatial data

models provide abstraction of spatially referenced features in the real world.

Representation of real world is often divided into,

(1) Entities (distinct objects like points, locations, roads, admin boundaries)

(2) Fields (convey the idea of values of some property at all locations)

Objects that are well described as distinct entities are sensibly represented using the VECTOR DATA MODEL.

Properties that tend to vary quite smoothly from place to place are frequently represented using RASTER DATA MODEL.

Exceptions are isolines / contours / temperature elevation etc…

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What is GIS?

Geographic Information Systems (GIS) are computerized systems designed for the storage, retrieval and analysisof geographically referenced data

GIS uses advanced analytical tools to explore at a scientific level the spatial relationships, patterns, and processes of cultural, biological, demographic, economic, geographic, and physical phenomena

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Tools for GIS Hardware

Computer

Digitizer

Scanner

Printer/Plotter

Software Desktop GIS

Internet GIS

CAD Software

Database Software

Multimedia (photos, videos, 3D models)

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Unique capabilities of GIS

GIS stores related geographic features in separate collections of files called map layers

Map layers can be reused easily and assembled into any number of map compositions and overlaid for analysis

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GIS answers the following

Location: What is at...? Where is it?

Condition: Status of features?

Trends: What has changed since...?

Patterns: What spatial patterns exist?

Modeling: What if…?

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Scale of GIS dataGlobal to local

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Vector data Map features

Vector data comprise Points (x & y) , lines (segment of arcs), polygons (lines with same start & end points)

Data comprise explicit spatial coordinates

Feature attributes

Every feature has attributes (e.g. name, area, population)

Shape Name Class Pop2000 State

Point New York City 8,008,278 NY

Point Los Angeles City 3,694,820 CA

Point Chicago City 2,896,016 IL

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Vector data is

also called ‘spaghetti’

data

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Vector data

Line feature comprises of two forms of point locations (vertices), which represent change in direction of ARCS…

NODES which represent the start & end of arcs, including locations where different arcs connect…

Vector data are divided into their SPATIAL component and ATTRIBUTE component. Attribute linked to each spatial feature are stored using RELATIONAL DATABASE SYSTEM.

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Raster Data

Stored electronic image or picture taken as an aerial photograph or satellite image

Composed of a rectangular array of square cells, called pixels, with a number in each cell representing the solid color fill of that cell…

Raster grids are conceptually simple structures, comprising square cells with numeric values or classes attached to each cell..

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TOPOLOGY

Topology can be defined as “The mathematical study of objects which are preserved through deformation, twistingsand stretchings.”

Operations concerned with connections between objects are dependent on information about topological relationships.

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Topology

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GIS DATA AND LAYERS

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GIS example

Identify polluting companies and their proximity to populations in poverty, water features, or schools.

Start with

Databases

Map layers

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DatabasesNot easy to interpret

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Data shown as GIS layers

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Additional layersPolitical features (municipalities)

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Additional layersPhysical features (lakes, rivers, etc.)

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Additional layersAdministrative data (schools)

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Maps and tables are interactive

Identify features

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Maps and tables are interactive

Select features

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Advanced GIS functionsProximity selections

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Advanced GIS functions Buffers

Select top polluting companies and show the number of schools within 2 miles of these companies.

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GIS APPLICATIONS AND EXAMPLES

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GIS applicationsEngineering Civil engineering, surveying, property mapping

Business Site location, delivery systems, marketing, media and press, real estate.

Defense/intelligence

Military operations, geospatial intelligence

Government Federal, state, local, economic development, elections, urban and regional planning.

Health Public health, health and human services, hospitals, managed care, research.

Natural resources Agriculture, archaeology, climate change, conservation,environmental management, forestry, marine and coast, mining,petroleum, water resources.

Public safety Computer-Aided Dispatch, emergency/disaster management,EMS, homeland security, law enforcement, fire protection,wildfire management

Transportation Aviation, highways, logistics, railways, ports and maritime, public transit

Utilities/communications

Electric, gas, pipeline, telecommunications, water/wastewater

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Thanks

Prof. Bhasker V. Bhattwww.bvbhatt.com+91-98258-35364

[email protected]

Content source credit courtesy is due, where not mentioned in specific:Remote Sensing by Gregory Vandeberg; Dept. of Geography, University of North Dakota, USA (Content created 21/10/2005)andGIS Tutorial 1 - Basic Workbook by Jay Loteria; Anne Connell (Content created 06/03/2010)