Lecture 2 Flashcards

1
Q

Earths orbital revolution
an _____ path around the sun

____(angle) with the _____ plane

A
  • An elliptical path around Sun
  • Earth–Sun distance varies between aphelion &
    perihelion points
  • 23.50 with the ecliptic plane
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2
Q

Celestial Coordinate system

A

North & South celestial pole - point in sky directly
above north/south pole on earth (zenith of north/south
pole & + 90o/- 90o respectively)
• Celestial equator – circle surrounding equator on
earth
• Ecliptic – pathfollowed by the sun through the sky over the course of the year.

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3
Q

declination

A

Declination – angle from celestial equator (0o
), positive going
UP, negative going Down

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4
Q

celestial Prime meridian

A
• Celestial Prime meridian – point where sun is located at the
vernal equinox (spring)
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5
Q

Right ascension

A

Right ascension (RA)
– angle (degree) from celestial “prime meridian”
(equivalent of celestial longitude) 68
RA – typically expressed as a time going east – 0 to
24 hours is 3600

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6
Q

georeferencing

A

“To establish a relationship between page
coordinates on a planar map and known realworld
coordinates”.
Or other way
…..is the act of assigning geographic locations
to features of the spatial data that do not have
any real world coordinates

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7
Q

Geographic transformation

Transformation involves: _____, _____, ______, and ______ a dataset to a given set of
geographic or projected coordinates

A

“The process of converting a digitized map, satellite
image, or aerial photograph from one coordinate system
to another by using a set of control points and a
transformation equation”.

Transformation involves: scaling, rotation,
translation, and skew a dataset to a given set of
geographic or projected coordinates

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8
Q

3 steps in geographic tranformation

A
Step 1 updates the control points to
real-world coordinates.
 Step 2 uses the control points to run a
transformation.
 Step 3 creates the output by applying
the transformation equations to the
input features.
h
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9
Q

Transformation methods are distinguished by the _______ properties it can preserve and the changes it allows

the changes could be
change of ____ and ____
change of _____
change in _____ and ______

A

Many mathematical models (equations)
Each method distinguished by the geometric
properties it can preserve and the changes it allows
The changes could be
Change of position and direction
Change of scale
Changes in shape and size

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10
Q

4 Commonly used tranformation methods

A
  1. Equiarea Transformation allows rotation and
    preserves shape and size
  2. Similarity Transformation allows rotation and
    preserves shape but not size
  3. Affine Transformation allows angular distortion
    but preserves parallelism
  4. Projective transformation allows both angular
    and length distortion. So a rectangle to be
    transformed into an irregular quadrilateral

EAT SAUSAGES AT PRISON

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11
Q

______ transformation method is most

commonly use

A

Affine transformation method is most

commonly use

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12
Q

Resampling of pixel values

A

Result of geometric transformation of a image is a
new image based on a given coordinate system
New image has no pixel values. These must be
filled through resampling
Resampling refers to filling of each pixel of new
image with a value derived from original image
Various methods exist

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13
Q

3 common resampling of pixel methods

A

Three common resampling methods:
1. Nearest neighbor resampling:
fills each pixel of the new image with the nearest
pixel value from the original image.
2. Bilinear interpolation method:
uses the average of the four nearest pixel values
from three linear interpolations.
3. Cubic convolution method:
uses the average of the 16 nearest pixel values
from five cubic polynomial interpolations.

NEVER BITE COCKS

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14
Q

Affine Transformation

A
X = Ax + By + C ……….. (1)
Y = Dx + Ey + F ………...(2)

.x, y are input coordinates and X, Y are output
coordinates
.Coefficient C represents translation in the x
direction, and coefficient F the translation in
the y direction
.Coefficients A, B, D, and E are related to
rotation, skew, and scaling

Allows rotation,
translation, skew,
differential scaling
while preserving line
parallelism
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15
Q

Affine transformation Allows rotation, translation, skew,

differential scaling while preserving _____ _____

A
Allows rotation,
translation, skew,
differential scaling
while preserving line
parallelism
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16
Q

Affine Transformation properties

the equations requires at least ____ known points to
estimate its six coefficients. Points also known as ____’s

At least ____ known points are commonly used for
reducing problems with measurement errors and to
allow for a least-squares solution

From the ___ ____ ____ (RMS) error value is the
indicator for the goodness of control points that
derives from the least-square equation

A

The equations requires at least Three known points to
estimate its six coefficients.
The known points are also knows as tics/ground
control points (GCPs)
At least Four known points are commonly used for
reducing problems with measurement errors and to
allow for a least-squares solution
From the Root Mean Square (RMS) error value is the
indicator for the goodness of control points that
derives from the least-square equation.

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17
Q

Polynomial order in transformations

Describe 3 orders of polynomial

A
  1. 1st order polynomial (affine)
    requires a minimum of 3 displacement links, but should have more
    even though 3 gives RMSE=0!
    is a homogeneous transformation: only shifts origin, scales and
    rotates
    straight lines will be preserved
  2. 2nd order polynomial
    requires 6 points (displacement links) minimum
    is a differential transformation so it “warps” the raster
    straightlines on raster may no longer be straight
  3. 3rd order polynomial
    requires 10 points minimum

Polynomials are global transformations which strive to achieve a best fit globally or
overall. Only 1st order with exactly 3 points will exactly match control points.

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18
Q
  1. ___ order polynomial (affine)
A
  1. 1st order polynomial (affine)
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19
Q

Root mean square error

A

The root mean square (RMS) error is a common measure of
the goodness of control points.
It measures the average deviation between the actual (true)
and estimated (digitized or selected) locations of control
points.
The RMS error is derived from the equation:

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20
Q

T OR F

Low acceptable RMS error does not always ensure the data accuracy

A

T

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21
Q

_____ ______ method is the most commonly used as
resampling techniques that fills each pixel of the new
image with the nearest pixel value from the original image.

A

Nearest neighbor method is the most commonly used as
resampling techniques that fills each pixel of the new
image with the nearest pixel value from the original image.

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22
Q

Reprojection

A

Reprojection:

.using data from different projection systems to bring into one system under same

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23
Q

point registration

A

Registration: bringing to points together that are on different projections/maps but represent the same location

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24
Q

When a map is scanned, an image is divided into individual pixels which are assigned a value based on ________

A

When a map is scanned, an image is divided into individual pixels which are assigned a value based on grayscale (gray colour level- 0 is black, higher #’s are lighter)

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25
For artimus error you need _____ control points
4
26
GIS STORES two types of geographic information : _______ and ______
attribute features
27
The functions of a GIS are _______, geodata _______, and geographic ________
visualization, management, analysis,
28
Geographic Data vs Data
``` (a collection of) facts about a geographic entity (Earth’s physical features, inhabitants, and phenomena) from which conclusions may be drawn ``` a collection of facts from which conclusions may be drawn
29
Geographic Data model
the methods of representation of geographical data into the computerized geographic information system. • The location of a geographic entity is linked to a geometry (point, line, poly, or a pixel), which refers to as spatial data. • Then the geometry is linked to its attribute(s). • An attribute could be quantitative or qualitative.
30
Geographic data can be ______ or _______ data
spatial(features) and Attribute data spatial-->Qualitative and Discrete Attribute data-->Quantitative and Qualitative-->discrete and continuous
31
What is a node? What is a polygon?
Nodes: connect multiple lines (start node and end node) Polygon: all the lines connect together and enclose a shape
32
Continuous vs Discrete: 1. Elevation 2. Aspect 3. Land Use 4. Rainfall 5. Vegatation Type 6. Pollution 7. Roads 8. Wells
discrete: Land use, Vegetation type, Roads, Wells Continuous: Elevation, Aspect, Pollutions, Rainfall
33
Spatial Data is split in two: _____ and ____
raster and vector
34
Vector Data model
1. it uses points and their coordinates to represent spatial features as points, lines, and polygons  Dimensionality and property distinguish the point, line, polygons 2. it organizes geometric objects and their spatial relationships into digital data files that computer can access, interpret, and process Features are generally represented in Coordinates are most often pairs (x,y) or triplets (x,y,z, where z represents a value such as elevation).
35
Describe Point, line , and Polygon
Point •No length, width or height, only location implied •Defined by x, y coordinates •Also called a node or vertex Line • defined by a set of connected points • One-dimension, length, determined by the distance between the end points • Lines also known as edges, links • Examples: roads, streams, contour lines Polygon • Two-dimension, length and width give area and perimeter • Boundary is defined by a set of lines • Examples: political entities, water bodies
36
Raster Data Model
```  Cell - also known as pixel  Cell value , Cell Size  Rows, number, Columns, number  Number of bands  Attribute table in raster dataset ```  Raster data represent  points by a single cells,  lines by sequences of neighboring cells, and  areas by collections of contiguous cells. ```  Some raster datasets contain attribute tables  Typically cell values can represent or define a class, group, category, or membership ``` E.g.: a satellite image may have undergone a classification analysis to create a raster dataset that defines land uses Cell values can be Integer or Floating-point
37
In _____ data model what is integer and floating-point?
``` Integer:  Number with no decimal digits  Used for represent categorical data or discrete data  e.g.: land use, forest category, soil type ``` ``` Floating point:  Number with decimal digits  Used to represent continuous data  Require more computer storage space  e.g.: precipitation, slope, DEM ```
38
4 types of attribute data
1.Nominal • data are qualitative only, • no computation possible . no data order 2.Ordinal • qualitative or quantitative, • represent an order of the individuals 3.Interval • quantitative only • a zero entry simply represents a position on a scale 4.Ration • Interval type with a meaningful zero entry • a ratio of two data values can be formed so one data value can be expressed as a ratio of the other. NEVER ORDER INDIAN RICE
39
Metadata
The term refers to any data used to aid the identification, description, quality, reference information, entry information, distribution information and data authority, etc. of geospatial data.
40
Topology
 Topology is a mathematical approach of studying those properties of geometric objects that remain invariant under certain transformations such as bending or stretching.  i.e. topology remains constant through distortion  When a map is stretched or distorted, some properties of objects are changed:  Distance, Angles , Relative proximities ```  Some properties won’t change,  Adjacencies and incidence  Spatial relationships, such as "is contained in", "crosses"  Types of spatial objects - areas remain areas, lines remain lines, points remain points  These unchanged properties are called topological properties. ```
41
Topological Data and GIS
 a spatial database is often called "topological" if the topological relationships have been computed, stored, and maintained. Such as,  connectedness of links at intersections  ordered set of lines (chains) forming each polygon boundary  adjacency relationships between areas
42
Evolution of Vector Data Model by ESRI systems In "Georelational Data Model" and "Object Oriented data model" Describe all 4 within these two models
Georelational Data Model: First two 1980's: PC Arc/Info Workstation Arc/Info began with a coverage data format 1990's: ArcVIEW then used 'shapefile' Object Oriented data model: These two 2000's:ArcGIS 8 & 9 then started using geodatabase 2010: ArcGIS 10.x continued with geodatabase
43
Georelational Data Model- coverage
 Based on the georelational data model, an Arc/Info Coverage has two components:  A set of graphic files for spatial data and  A set of INFO files for attribute data.  The label connects the two components through feature ID.  “Coverage” is the name of a GIS data layer in ESRI Arc/Info data structure.  A “Coverage” in Arc/Info data structure is like a Folder, that contain a number of files.  Some of the files represent spatial feature geometry,  Some files for attribute data, and  some others for holding other information, such as maximum spatial extent, annotation, projection parameter, etc.  “Coverage” maintains topological properties in spatial data structure
44
collection of multiple 'coverage' is called a __________
workspace
45
what is a tic file?
Tic file= use to pinpoint where info came from
46
Shapefile
Also known as ESRI ArcView Shapefiles.  Geographic features in a shapefile is also represented by points, lines, or polygons (areas)  File-based based data  collection of graphic and info files  same file name but different extensions (suffixes)  The workspace may also contain dBASE tables, which can store additional attributes that can be joined to a shapefile's features.
47
Geodatabase 3 feature geometry types
 Geodatabase data model is an Object-based data model  The Geodatabase model is a collection of objects, properties and methods held in  a common file system  a Microsoft Access database  or a multiuser relational database e.g.: Oracle, Microsoft SQL Server, or IBM DB2  Point feature: represented as single point or multi-point set of points  Polyline feature: a line or a set of line segments, which may or may not be connected. -User-shaped, Curves, Single / multi-part  Polygon feature: a set of one or many rings. a ring is a set of connected, closed, nonintersecting line segment. -Single / multi-part
48
Polyline vs. line
-polyline feature instead of line because it can be a set of line segments which may or may not be connected .lines all have to be connected somehow
49
Geodatasets in Geodatabase
 Feature class  Stores spatial data of the same geometry type  Can be broken down into subtypes  Feature dataset  Stores feature data classes that share the same coordinate system and area extent  Feature classes included in a feature dataset ‘share’ topological relationships with each other  Contains different theme layers, multiple dataset ```  Standalone feature class  Feature class that is not included in a feature dataset ```
50
Feature Data set vs. Feature class
 Feature dataset  Stores feature data classes that share the same coordinate system and area extent  Feature classes included in a feature dataset ‘share’ topological relationships with each other  Contains different theme layers, multiple dataset  Feature class  Stores spatial data of the same geometry type  Can be broken down into subtypes
51
Spatio-temporal vs. Non-spatio-temporal
 Spatial (absolute location, shape, size)  Temporal (time, duration, frequency)  Spatio-temporal (changes in a spatial description over time, example change of extent)  Non-spatial (name, owner, quality, color, …………)  Non-spatio-temporal (changes in a non-spatial descriptions over time, example change of colors)
52
General GIS Spatial/temporal info analysis
 GIS provides data, tools, and methods that enable the representation, description, measurement, comparison, understanding relationships, and modeling the past and present of spatial phenomena and prediction of future.
53
GIS Data Anlysis
 Single-layer analysis e.g.: how close each other, how different from each other in pattern  landuse classification  Multi-layer analysis e.g.: change detection  pre & post desaster, spatial model  Universal Soil Loss Equation (USLE)  Integrated analysis - both spatial and attribut data - involves attributes, location and topology
54
Attribute Data Query
 Attribute data query retrieves a data subset by | working with attribute data
55
Selection of attribute data or the data | query requires an ______
expression  ArcGIS uses SQL (Standard Query Language) for query expressions
56
SQL (Structured Query Language)
designed for relational databases, by IBM in the 1970s, and used by many commercial database management systems  The basic syntax of SQL includes the following: .select [ selects fields as a list] .from [name of the table of the database] .Where [specify the selection criteria]
57
Query expressions consist of ______ _____ and ______
Query expressions consist of Boolean expressions and connectors ``` Boolean expressions:  A simple Boolean expression contains two operands(Parcel.Pin and P101) and a logical operator(=) .ex: Parcel. PIN = ‘P101’ -Other operators [ =, , >=, <=, <>] ``` Connectors:  Boolean connectors are AND, OR, XOR, and NOT are used in query functions and overlay operations. .Connect two or more expressions in a query statement. .NOT, AND, and OR are actually used in the operations of Complement, Intersect, and Union on sets in probability
58
Boolean Connector: "Not"
The blue shaded portion represents the complement of data subset B-->contains elements of the set A that do NOT belong to B
59
Boolean Connector: XOR
Everything in subset A and B except what is in both A and B
60
Boolean Connector: Or
The union of data subsets A and B |  the set of elements that belongs to A OR B
61
Boolean Connector: and
The intersection of A and B |  the set of elements that belongs to both A AND B
62
Spatial Data Query:
 Uses a graphic, such as a circle, box, line or polygon to select features that fall inside or are intersected by the graphic  Examples: .selecting restaurants within a radius of a hotel .selecting land parcels that intersect a proposed highway, or .finding owners of land parcels within a proposed nature reserve
63
Spatial Data Query: Feature Selection by ______ explain
 Uses a GRAPHIC, such as a circle, box, line or polygon to select features that fall inside or are intersected by the graphic  Examples: .selecting restaurants within a radius of a hotel .selecting land parcels that intersect a proposed highway, or .finding owners of land parcels within a proposed nature reserve
64
Feature Selection by Spatial Relationship 3 spatial relationships
 Select features based on their spatial relationship to other features .In the same layer or in different layers .Containment, intersect, proximity  Containment .Select features that fall completely within features for selection, .E.g.: Schools within a particular county or state parks within a particular state  Intersect .Select features that intersect other features .E.g.: Selecting land parcels that intersect a proposed road, urban areas that intersect a fault line  Proximity .Select features within a specified distance of other features .E.g.: State parks within ten miles of an interstate highway
65
Vector Data Analysis
 Vector data analysis uses the geometric objects .What are those? -point, line, and polygon. .The accuracy of analysis results depends on -the accuracy of these objects in terms of location and shape.  Topology is an important factor for some vector data analysis such as buffering and overlay.
66
Buffering: Vector Data Analysis
.is based on the concept of proximity .is a single layer operation .creates two areas: 1. within a specified distance of selected features ----buffer zone 2. the other area that is beyond the buffer zone .Buffering around points, lines, and areas:
67
3 Variations in Buffering for Vector Data Analysis
1. distance can vary according to the values of a given field 2. buffering around line features can be either on the left side or on the right side 3. boundaries of buffer zones may remain intact so that each buffer zone is a separate polygon
68
Methods of Overlay In vector Data
 Relationship-->containment and overlaps  Multi-layer operation -layer must be spatially registered -based on same coordinate system  An important consideration in a overlay operation is the feature types.  Two groups 1. Uses two polygon feature layers 2. Uses one polygon feature layer and the other point or polyline-feature layers  polygon-on-polygon  point-in-polygon  line-in-polygon
69
Overlay
 Combines the geometries and attributes of two feature layers to create a single output layer with a modified set of attribute table.  Each feature on the output contains a combination of attributes from the input layers Vector:  polygon-on-polygon  point-in-polygon  line-in-polygon
70
For overlay you always use ______ as the overlay theme. Output is the same as input!
Polygon Input: Point= Output: Point
71
Boolean Operators: Overlay
AND: True for all areas that meet both criterion ex: which areas are steep and forested OR: True for all areas that meet atleast one of the two criterion ex:which areas are steep or forested XOR: True for all areas that meet ONLY one of the two criterion. Cannot be BOTH ex: which areas are either steep or forested NOT: True for all areas that meet the first criterion but not the second ex: which areas are forested but not steep
72
Match name with associated boolean operator Intersect=____ Union=_____ Symmetrical Difference or Difference= ____ Identity or Minus=_____
1. Intersect if it uses the AND connector 2. Union if it uses the OR connector 3. Symmetrical Difference or Difference if uses the XOR connector 4. Identity or Minus
73
Explain Dissolve(_____ _____)
 Identical to spatial merge  Removes boundaries between polygons or nodes between arcs  Features with same attributes are dissolved
74
Underlapping
“Under-lapping” features from input layer are erased  Order of input layer and overlay layer is important
75
clip
```  “Cookie cutter”  Only input theme features and attributes exist in output  Polygon on polygon, line, or point ```
76
Eliminate
 It merges the selected polygons with neighbouring polygons keeping the largest shared border or the largest area  “Eliminate” is used most often to remove sliver polygons created in an overlay of two layers
77
Append
 Append combines features from two or more layers into a single output layer  It does not calculate new topological relationships between the resulting features.
78
T OR F | Appending calculates new topological relationships between the resulting features
FALSE
79
Split
```  Split creates output layer by overlaying two sets of features.  Split performs a series of Clip operations, one for each output layer.  Each output layer contains only those portions of input layer features that are overlapped by the specified polygons of the Split Layer. ```
80
Raster Data Analysis
 Raster data model -a regular grid to cover space -value in each cell represents a characteristic  Popular use in application model  Various type of raster data (GRID, DEM, DRG…)  Software package defines what type raster data can be analyzed-->required conversion  large variety of analysis operations
81
Map Algebra is used for ____ data analysis
RASTER  Algebraic operations in  a single layer or  multiple raster layers  output is a single layer  Statistics (max, min, range, mean, median, mode, sd..) of the input layers cell values to the output layer  Majority, minority, or unique value of the input layers cellvalues to the output layer  Multi-layer analyses are Similar to the vector overlay operations
82
In map algebra explain how to get the MAJORITY and MEAN
Majority: most common number from input layers Mean: average all inputs
83
Two types of energy used in remote sensing
Incident energy-from sun Reflected energy-from ground by up to sattelite
84
Remote sensing can be done at 4 positions:
Ground observation Low altitude High Altitude Satellite
85
Camera
 Cameras are framing systems which acquire a near-instantaneous "snapshot" of an area (A), of the surface.  Camera systems are passive optical sensors that use a lens (B) (or system of lenses collectively referred to as the optics) to form an image at the focal plane (C), the plane at which an image is sharply defined.  Things to consider for determining what makes one photograph different from another -The film -Focal length -Scale -Look direction and angle
86
optics
system of camera lenses
87
focal plane
``` focal plane (C), the plane at which an image is sharply defined. ```
88
Stereoscopic analysis
Stereoscopy, sometimes called stereoscopic imaging, is a technique used to enable a three-dimensional effect, adding an illusion of depth to a flat image. Stereopsis, commonly (if imprecisely) known as depth perception, is the visual perception of differential distances among objects in one's line of sight.
89
7 Recognition elements for ariel images:
shape, size, pattern, shadow, tone/colour, texture, site/association SSPSTTS
90
Photos taken from ______ are the most widely used because:
``` Photographs taken from aircraft remain the most widely used source of imagery for large-scale mapping. Because:  aerial photographs are usually high resolution,  have a simple geometry  they can easily interpreted with the unaided eye or simple instruments ```
91
Describe how camer generally works
All cameras rely on the same essential features: – Light enters a darkened enclosure (camera, from the Latin word for room) through a small aperture, the size of which can often be controlled mechanically – A shutter is opened and closed to admit light for a specified period of time – Inside the camera, a glass lens gathers and concentrates the light, focusing it on a light sensitive field at the back of the camera • Traditionally - the film • Today, in digital cameras, employ arrays of detectors to record incident energy levels
92
Camera Film:
• The films are basically coating of light sensitive emulsion over a base material, • Most air photo missions are flown using black & white films, however Infrared, colour, and colour infrared (CIR) film are sometimes used for special projects
93
Panchromatic
• Panchromatic: films are sensitive to light from 0.3 μm to 0.7 μm that covers ultraviolet (UV) and visible (VIS) portion of the EM spectrum, good for infrastructure mapping.
94
Infrared
• Infrared: Infrared films response to light from 0.3 μm to 0.9 μm, which covers UV, VIS and Near Infrared (NIR) portion  Infrared films are useful for detecting differences in vegetation cover, due to its sensitivity to IR reflectance  Water becomes darker in IR Image than that in Panchromatic image. Exposed soil is brighter in IR image than that in Panchromatic image
95
EM RADIATION:
EM radiation is the carrier of electro-magnetic energy by transmitting the oscillation of the electric and magnetic fields through space or matter.
96
Shorter the wavelength = _____ the frequency
HIGHER
97
_______ the wavelength = lower the frequency
longer
98
Human eye has a spectral sensitivity from __um to __um which is termed _______ wavelength of the EM spectrum
The spectral sensitivity of the human eye is from about 0.4 to 0.7 μm which is termed as visible wavelength of EM spectrum. • The main classes of visible wavelength are: • blue is about 0.4 to 0.5 μm • green is about 0.5 to 0.6 μm • red is about 0.6 to 0.7 μm
99
Main Classes of visible wavelength and um's
* blue is about 0.4 to 0.5 μm * green is about 0.5 to 0.6 μm * red is about 0.6 to 0.7 μm
100
LIDAR
LIDAR: gives more elevation information than digital
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HEAT IS _______ WAVELENGTH AND CAN PASS THROUGH WALLS WHILE LIGHT IS ______ WAVELENGTH AND CANNOT
LONGER SHORTER
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Two important parts of photos from camera Principal Point Field of view
. Principal point: most central point of photo | . Field of view: total area captured by camera
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Two general types of Black and White film
Panchromatic, Infrared
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Colour film
involves the use of a three layer film with each layer is sensitive to different ranges of light .Usually the top layer sensitive to Blue light, and second and the third layers sensitive to the Green and Red respectively .However, the second and the third layer also sensitive to the Blue light, therefore a filter is used in between the first and the second layer to blocking the penetration of Blue light .These photos appear to us as the same way that our eyes see the environment (i.e. trees appear green, etc.) .Major advantage of colour film is that the human eye can discriminate many more shades of colour than the tones of grey
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Colour infrared film
 …was developed during WWII to detect painted targets that were camouflaged to look like vegetation and cannot be detected by the color photography  ......also involves a three layer film where keeping the red and green sensitive layer, the blue light sensitive layer is replaced by the NIR light sensitive layer  It produces photograph with non natural color. In the process photograph, taken in color infrared, features showing high intensity of Green appears as blue and Red appears green, and feature that has high reflectance in NIR band that appears as Red --> vegetation appears as red
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Why choose Colour Infrared over natural colour?
 excellent haze penetration characteristics than normal color film because the shorter wavelengths are not recorded  good used for mapping forest and agricultural areas and detection of vegetation stress caused by insect damage, disease, flooding, or other factors  Water, which absorbs NIR strongly and appears blue to black, which clearly delineates the waters edge and makes it easier to map.  Even streams partially obscured by vegetation are much more easily distinguished on color infrared film than on normal color imagery
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Comparison of Different Films: Advantages of each 1. Advantages Panchromatic B&W and Normal color over infrared film: 2. Advantages of Infrared over Panchromatic B&W and normal Color : 3. Advantage of normal Color over Panchromatic B&W : 4. Advantages of Panchromatic B&W over normal Color:
1.Advantages Panchromatic B&W and Normal color over infrared film:  More natural to the eye  Better resolution  Better penetration over water 2.Advantages of Infrared over Panchromatic B&W and normal Color :  Better penetration of haze  Emphasizes water and wet areas  Good differentiation between hard wood and conifers  Good differentiation between healthy and diseased trees 3.Advantage of normal Color over Panchromatic B&W :  Human can discriminate 20,ooo – 5 million shades of color, but only about 200 shades of grey 4. Advantages of Panchromatic B&W over normal Color:  Color film is more expensive to process  Resulting images on color prints are usually not as sharp as on B&W prints
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2 main types of photography: angle of photos and description
Vertical : .Camera optical axis < 3 degrees off vertical Oblique: 2 types •Camera optical axis > 3 degrees off vertical High oblique=horizon visible Low oblique=horizon not visible
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Some advantages of vertical aerial | photography
• Vertical photographs present approximately uniform scale throughout the photo • Constant scale allows the determination of directions (i.e., bearing or azimuth) in the same manner as a map and easier to interpret • Minimal mathematical correction required to use photogrammetrically • Stereoscopic study is also more effective on vertical than on oblique photographs • They may be used as a map if a coordinate system and legend information are added
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Some advantages of oblique aerial | photography
• Oblique photographs covers much more ground area • Area frequently covered by cloud layer may have enough clearance for oblique coverage • Have a more natural view because we are accustomed to seeing objects obliquely with perspective • Objects that are tall may be visible • Determination of feature elevations more accurate • They may be acquired from inexpensive cameras
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Photogrammetry
• Photogrammetry is the art and science of making accurate measurements of objects by means of aerial photography (Jensen, 2006); • or is the technique of obtaining reliable measurements of objects from their photographic images. • Some of the important measurements that can be obtained from a single vertical aerial photograph using either analog or digital photogrammetric techniques include:  Scale of the photography  Object height (buildings, tree crowns...)  Object length  Area of an object or polygon  Perimeter of an object or polygon, and  Grayscale tone or color of an object
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Stereo Viewing
Successive photo pairs display the overlap region from different perspectives and can be viewed through a device called a stereoscope to see a three -dimensional view of the area, called a stereo model. Many applications of aerial photography use stereoscopic coverage and stereo viewing.
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Finding scale in Aeriel Photography: 2
1.Finding scale from the known features: • Scale is the ratio of the distance between two points on a photo to the actual distance between the same two points on the ground (i.e. 1 unit on the photo equals "x" units on the ground) • If a 1 km stretch of highway covers 4 cm on an air photo, the scale is calculated as follows: -Photo distance/ground distance=scale 2.• Another method uses the ratio between the camera's focal length and the plane's altitude above the ground being photographed. • If a camera's focal length is 152 mm, and the plane's altitude Above Ground Level (AGL) is 7 600 m, using the same equation as above, the scale would be: -Focal length/Height Above Ground= Scale Scale(RF)=f(focal point)/H(height above ground)=f/A-h Height above ground= Altitude-h(Terrain Elevation) REMEMBER TO USE THE SAME UNITS(mm or cm not both)
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Scale(RF)=__/__ Height Above ground= _____-_______
Scale(RF)=f(focal point)/H(height above ground)=f/A-h Height above ground= Altitude-h(Terrain Elevation)
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Determining scale: Example 1: f = 152.4 mm, H = 3,000 m Example 2: f = 152.4 mm, A = 12,000 m, h = 2,000 m
Scale = 0.1524 m / 3,000 m = 1/19,685 => 1/19,700 Scale = 0.1524 m / (12,000 - 2000) m = 1/65,616 => 1/65,600
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Relief Displacement
.is the shift in an object's image position caused by its elevation above a particular datum Scale is not constant across uncorrected air photos, .Scale decreases towards the lower elevation areas of the landscape captured on a photograph . Any point will be displaced outward from the Principal Point relative to any lower point in the area. Orthorectification to remove the relief displacement and correction of scale
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_______ to remove the relief | displacement and correction of scale
Orthorectification to remove the relief displacement and correction of scale Relief displacement radiates out from Nadir (PP) Objects at the Nadir do not have any displacement
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______(Principal Point)
Nadir | the point on the celestial sphere directly below an observer.
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Length, example a shadow, can be found
The length, L, can be found by taking the length of the shadow measured on a photo (0.10 inches) and multiplying it by the photo scale (1:4000). So, 0.10 inches on the photo is 400 inches in the real world, or 33.33 feet. So, if you know the time and date of the photograph and figure out what was the sun`s angle, the height of the object can be measured.
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Figuring out Sun Angle: A 30 meter tall building can cast a 5 meter long shadow. What is the angle of elevation of the sun?
tan (-1)a=h/L Tan-1a=30/5=6 Tan-1a(6) =80.53 degrees PAY ATTENTION TO UNITS
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Figuring out Length of the shadow:
• The length, L, can be found by taking the length of the shadow measured on a photo (0.10 inches) and multiplying it by the photo scale (1:4000). So, 0.10 inches on the photo is 400 inches in the real world, or 33.33 feet. PAY ATTENTION TO UNITS
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Match images through stereoscope using ______/_____ POINTS | -as you move away from points things get distorted
PRINCIPAL/FOCAL