Tracking and Data Relay Satellite System (TDRSS)
Images with continuous gray tone or color like a photograph
is called analog image
Digital image is the numerical record of the radiance leaving
each of the pixel in each of the spectral bands
Rayleigh Scattering: dominant scattering mechanism in the upper
atmosphere ( 9-10 km), also called clear atmosphere scattering
Mie scattering:Occurs when the particles are just about the same size as the
wavelength of the radiation (Dust, pollen, smoke and water
vapour), occurs in lower atmosphere. (0 – 5 KM)
By measuring the energy that is reflected (or emitted) by targets
on the Earth's surface over a variety of different wavelengths,
we can build up a spectral response for that object, termed a
spectral reflectance curve.
Specular Reflection: angle of incidence is same as angle of reflection
Diffused Reflection: angle of incidence is different from angle of reflection
The spatial property defines the dimensions of the
corresponding ground area.
The spectral property defines the intensity of the
spectral response for a pixel in a particular band
Spatial resolution refers to the size of the smallest possible
feature that can be detected by the sensor.
Spectral resolution describes the wavelength intervals
in the electromagnetic spectrum that a sensor can
record or sense
The ability of an imaging system to record many levels of
Brightness is Radiometric Resolution.
Geography - Pattern and process of human and
physical phenomena on the surface of earth.
URISA Urban and Regional Information Systems Association
DIME Dual Independent Map Encoding
TIGER Topologically Integrated Geographic Encoding And Referencing
CAD: Computer Assisting Drawing, e.g. AutoCad, Micro station
GDS: Graphic Design System, e.g. CorelDraw, Illustrator
DBMS: Database Management System, e.g. Oracle, Sybase
DIPS: Digital Image Processing System, e.g. PCI, Erdas
GPS: Global Positioning Systems, e.g. Garmin, Trimble
�Using the tools and helping to build the tools of
geographic information systems (GISystems)
�Studying the theory and concepts that lie behind GIS and
other geographic information technologies (GIScience)
�Study the societal context of geographic information –
legal context, issues of privacy, economics of geographic
ESRI: Environmental Systems Research Institue
Arcinfo uses Arc Macro Language (AML)
ArcView uses Visual Basic and Python
ArcGIS comes in three different versions based on the capabilities
provided by the software: ArcView, ArcEditor and ArcInfo.
Gis data types:
A data model is a :
Logical Construct for representing real world phenomenon and objects in a
Coverages and shapefiles are examples of the Georelational
Geodatabases are examples of the Object‐Based Data
The Georelational Data Model stores spatial and attribute data
separately in a split system
Spatial data in ‘graphic files’
Attribute data in ‘relational database files’.
The link between the two ‘systems’ is usually a “Feature Label”
Object‐based data model stores spatial and attribute data of
spatial features in a single system. Spatial data are stored in a
field using a data type called “BLOB” (binary large object)
Topology is the science and mathematics which defines the spatial or
geometrical relationship between spatial features or vector objects in a GIS.
Topology is the study of those properties of geometric objects that remain
invariant under certain transformations such as bending or stretching.
Adjacency and Incidence are two relationships that can be established
between nodes and arc in digraphs. If a line joins two points, the points are said
to be adjacent and incident with the line.
Connectivity, Contiguity/Adjacency, Direction ,Containment
Topological data model makes spatial analysis feasible, automatic corrections
in plottings, faster processing of larger datasets. But it is expensive and time
consuming. Updating topology becomes necessary once spatial data is
updated. Complex data form making it difficult for developers to interpret.
Spaghetti Data model is the simplest and direct vector representation of a real
world object. Easy to produce, display and understand but no spatial analysis
TIGER- census data linked to boundary data of counties, block groups etc.
ESRI Coverage model:-
Point coverage: node ID + coordinates
Line coverage: arc IDs + S and E node, arc ID + coordinates.
Polygon coverage: arc IDs + L and R polygon, polygon + arc IDs, arc IDs +
DIME:- Arc IDs + S and E node + L and R polygon, Coordinate file for nodes
Composite features refer to those spatial features that are better represented as
composites of points, lines, and polygons.
TINS: Triangulated Irregular Networks
Formed by using Delaunay Triangulation which is an iterative process of
connecting points with their two nearest neighbors to form triangles.
Raster data model:-
Storage increases with the square of the resolution.
1. Cell value. Each cell in a raster carries a value, which represents the
characteristic of a spatial phenomenon at the location denoted by its row and
column. The cell value can be integer or floating-point.
2. Cell size. The cell size determines the resolution of the raster data model.
3. Raster bands. A raster may have a single band or multiple bands.
4. Spatial reference. Raster data must have the spatial reference information so
that they can align spatially with other data sets in a GIS.
Attribute data is stored logically in flat files.
Cell by cell: row n: 0110
Run length encoding: 23
Quad tree or hierarchical encoding
DOQ is a image prepared from an aerial photograph or other remotely sensed
data, in which the displacement caused by camera tilt and terrain relief has
DEM is a digital representation of a topographic surface. It is mutli-faceted.
Data capture: Surveys,RS,Digitization
Data inputs/ sources: Maps, orthophotos, statistical reports, Satellite Imagery,GPS
Input is :
- Time consuming
- Labour intensive and error prone
- Accuracy of GIS analysis rests on accuracy of input data
Selection of input data: depends on price, availability, spatial analysis required,
scale, format, available skills and hardware and software
• Federal Geographic Data Committee (FGDC)
• Geospatial One‐Stop (GOS)
• US Geological Survey (USGS)
Metadata describes the characteristics, development and origin of the spatial
- Identification Information (Title, geographic data covered)
- Data Quality Information (positional, attribute, completeness, sources of
information, methods to produce spatial data)
- Spatial Data Organization Information (Raster or Vector)
- Spatial Reference Information (Datum, Projections, Coord Sys)
- Distribution Information (Information about obtaining dataset)
- Metadata Reference Information (currency of the metadata and
Geodesy, is the scientific discipline that deals with the measurement and
representation of the earth, its gravitational field, and other geodynamic
phenomena, such as crustal motion, oceanic tides, and polar motion.
PCS (Flat, inches feet metres), GCS( curved , Degrees minutes seconds).
60 N 45 E
Conversion of polar to Cartesian:
Transformation is the projection of a digitized map or image, in some cases from
its original coordinate system, onto a new coordinate system.
Two main types :- map to map and image to map.
4 methods: Affine( angular distortions but parallelism preserved, similarity shape
preserved not size, equiarea (area and shape preserved), projective( angular
and shape distortions).
Affine transformation allows: skew, rotation, differential scaling and translation
Affine used for above mentioned trans. , aerial photos need projective trans.
And satellite imagery needs polynomial or warping trans.
A geometric transformation typically involves three steps.
•Step 1 updates the control points to real-world coordinates.
•Step 2 uses the control points to run an affine transformation.
•Step 3 creates the output by applying the transformation equations to the input
A quantitative measure of the displacement (the deviation) between the actual
(true) and estimated (digitized) locations of the control points is RMS.
Resampling in this case means filling each pixel of the new image with a value
or a derived value from the original image.
– Nearest neighbor: fills each pixel of the new image with the nearest pixel value
from the original image
– Bilinear interpolation: uses the average of the four nearest pixel values from
three linear interpolations
– Cubic convolution: uses the average of the 16 nearest pixel values from five
cubic polynomial interpolations
Map algebra is a language specifically designed for
geographic cell‐based systems and provides the
basis for cartographic modeling. Uses mathematical expressions to create new
Arithmetic operators, relational operators, Boolean operators, Functions (trig,log)
Raster functions (Output grid generated using input grid as argument): Zonal
(cells chosen), local (more than one or one argument), global and focal (cells
immediate neighbours only).
Uses: Surface generation and analysis (hillshade, viewshed), Data
reclassification, Transformations, Distance Analysis (shortest path, cost
Buffer made. Layer of important features created, all queries applied and select
by attributes for final results.
Statistical local function
Overlay functions: union , intersect , identity
No data in cell no data in output ( set condition otherwise default value is -9999)
Raster data model Vector data model
Can store photos Processing of large data sets is easier
once topological relations between
features are established
Simple data structure Prints are aesthetically pleasing
Easier Spatial analysis especially
overlay (Grid based coincidence)
Can accurately represent continuous
Can accurately represent discrete
Prints appear blocky Cannot store photos
Processing of large datasets is time
Cannot represent continuous spatial
Quality and productivity largely
depends on resolution
Spatial Analysis is time consuming
without a developed topology
- Complex data structure
Photo vs remote
Quantitative and qualitative
Geometry vs radiometry
Visible vs invisible
Small area coverage vs large area coverage
Identification of source, techniques of obtaining/ Projection and coordinate systems/
Organization of spatial data/ developmental history
Data sharing possible
Data interpretation techniques
Uses GIS: Monitoring weather, disaster management, traffic management, urban and regional
planning, Crop yields, Effects of different phenomena on environment.
Uses Spatial analysis: Identifying developmental patterns, trends , making predictions,
modeling, monitoring changes in environments and their effects.
Digitizing adva. And disadva.:-
Automatic error detection vs error prone
Enabling spatial analysis and easier interpretation vs Slow process
Transformation possible vs need of digitizing equipment
UTM: 84 n to 80 S, 60 zones (6 deg. Each) East –west, Transverse Mercator projection, Alphabet
zones 20 north-south. Cartesian system.
Mosiacing, raster bands
AOI, Inquire box, Coordinates
Annotations, dynamic labels
Graduated color , graduated symbol, dot density, proportional symbol
Discrete color, unique color, classified,
Natural breaks is the default method. Developed by the cartographer
George Jenks, it creates
classes according to clusters and gaps in the data.
Equal interval creates classes of equal va lue ranges. If the range of
values is 1 to 100 and the
number of classes is 4, this method will create classes from 1-25,26-
50,51-75, and 76-100.
Defined interval resembles equal interval except that the interval
determines the number of
classes rather than the other way around. If the range of values is 1 (Q
100, and you choose
an interval of 10, this method will create 10 classes: 1- 10, 11-20, 21-30,
and so on.
Quantile creates classes containing equal numbers of features. If you
choose five classes for a
layer with 100 features, this method will create class breaks so that 20
features fall into each
class. The value range varies from class to class.
Standard deviation creates classes according (Q a specified number of
from the mean value.
Geometric intervals creates classes based on class intervals that have a
geometric series. A
geometric series is a pattern where a constant coefficient multiplies each
value in the series. It
produces a result that is visually appealing, cartographically
comprehensive, and minimizes
variance within classes.