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Remote sensing
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CE 701: Remote sensing Technology
Lab Exercise 4
Image interpretation using elements of visual interpretation,
Manual Digitization and Map Composition
Instructor-In Charge: Prof. E.P. Rao Prepared by: Anita Chandrasekaran
(TA- PhD Research Scholar)
Image Interpretation
Aerial photographs are different from "regular" photos in at least three important ways:
• Objects are taken from an overhead or aerial position. Most people are used to seeing objects
from the ground, and not from the air.
• Photos are taken at scales most people are not used to.
• Sometimes, images obtained from satellites and high-altitude aircraft use color-infrared
photography. Color-infrared photography allows scientists to see things that are not visible to the
human eye. This provides scientists with a tool to study landforms, environmental pollution, and
other effects of human activities on the planet's surface.
Keys/Elements for Image Interpretation:
These following “basic elements" can aid in identifying objects in aerial photographs/satellite
images:
• Tone (also called Color or Hue): Tone refers to the relative brightness or color of elements on
a photograph. Some objects appear darker and crisper than others.
For example in this image, this image shows many different types of crops in agricultural fields.
You can see this from the many different shades of green.
• Size: The size of objects must be considered in the context of the scale of a photograph. The
scale will help you determine if an object is a small pond or a large lake. Major highways can be
distinguished from smaller roads. Long rivers can be distinguished from smaller tributaries.
Here we can identify the small blocks as houses.
• Shape: Shape refers to the general outline of objects. Regular geometric shapes are usually
indicators of human presence and use. Agricultural areas tend to have geometric shapes like
rectangles and squares. Streams are linear (line) features that can have many bends and curves.
Roads frequently have fewer curves than streams. Some objects can be identified almost solely
on the basis of their shapes.
Example: Man-made features tend to have straight edges while natural features do not.
You can tell that this feature is a river because it does not have straight lines
Whereas this straight feature is a man-made canal.
• Texture: The impression of "smoothness" or "roughness" of image features is caused by the
amount of change of tone in photographs. Grass, cement, and water generally appear "smooth",
while a forest canopy may appear "rough". Texture is one of the most important elements for
distinguishing features in radar imagery.
• Pattern (spatial arrangement): The patterns formed by objects in a photo can be used to
identify those objects. For example, consider the difference between (1) the random pattern
formed by an unmanaged area of trees and (2) the evenly spaced rows formed by a tree orchard.
The above figure is a picture of the regular street pattern in San Francisco, whereas, below
picture shows the irregular drainage patterns in the mountains.
• Shadow: Shadows aid interpreters in determining the height of objects in aerial photographs.
However, they also obscure objects lying within them.
Below is an image of buildings in downtown San Francisco. Shorter buildings have smaller
shadows while taller buildings have longer shadows.
• Site: Site refers to topographic or geographic location. This characteristic of photographs is
especially important in identifying vegetation types and landforms
• Association: Some objects are always found in association with other objects. The context of
an object can provide insight into what it is. For instance, a nuclear power plant is not likely to
be found in the midst of single-family housing. A vegetated area within an urban setting may be
a park or a cemetery. Wetlands may be located next to rivers, lakes, or estuaries. Commercial
centers will likely be located next to major roads, railroads, or waterways.
Manual Digitization of Maps and Images
A vector layer is defined as a set of features where each feature has a location and attributes
(ESRI 1989). Vector layers contain both the vector features (points, lines, polygons) and the
attribute information
In ERDAS IMAGINE, the digitizing of vectors refers to the creation of vector data from
hardcopy materials or raster images that are traced using a mouse on a displayed image.
Map composition should be a simple, quick process of creating an image-based map from a
remote sensing image and interactively adding key map components.
Digitization of Point Line and Polygon
Open and display a raster image
Right click on Mouse on the View and select the New Vector Layer
Input the file name. Files of type: shapefile
Select a shapefile: Arc/Point/Polygon
Go to the “Drawing Tab”
Select Polygon/Point/ Polyline
Then click on the image and digitize the desired feature
Set Display Properties
In order to access the display properties of the shapefile,
Select your desired layer in the Contents panel
Select Format/Vector Symbology/Viewing Properties from the Menu bar.
Select the Points, Arcs and Polygon checkboxes
Change the symbol
Edit the features
If you want to modify the digitized features
Select the desired layer in the contents pane
Select the feature in the Viewer
Select Line/Area in the Drawing Tab
Line: tools for existing polyline elements
Reshape: display all vertices in the currently selected polyline so that they can be moved
by left drag
Replace a portion of a line: digitize a new polyline which replace an existing one to
replace the portion that lies between the two intersection points with the newly added
vertices.
Spline: Fits a spline through the existing vertices to form a smoother polyline with new
vertices spaced at the Grain tolerance
Densify: Add new vertices to the selected polyline elements spaced at the grain tolerance
without modifying the shape of the existing line
Generalize: Removes vertices from the selected polyline element if they are closer than
the weed tolerance to another vertex
Split: Split a polyline into two lines by clicking at the point where you wish to split the
line
Join: combines two selected polylines that share a node
Area: tools for existing polygon elements
Reshape: display all vertices in the currently selected polyline so that they can be moved
by left drag
Split polygon with polyline: split an existing polygon into two polygons by digitizing a
polyline which bisects polygon.
Append to existing polygon: create a new polygon which precisely butt-joins an existing
polygon by digitizing a polyline which intersects the existing polygon at two points
Map Composition:
The ERDAS Imagine Map Composer is an editor for creating cartographic-quality maps
and presentation graphics. Maps can include raster layers, thematic (GIS) layers, vector
layers.
Open and display your raster and vector (which you want to include in the map) in 2D
viewer
Click on the File---New----Map View
The Map View appears. Click on “Layout” menu
Click on the “Map frame”.
Drag it in the map view. “Map Frame data Source” will appear
In the Fill frame with data from menu: click on “Viewer”
“Create frame Instruction menu” will appear. Click on the “2D viewer” where you
display the raster and vector layers. (Note: remove the raster image layer so that only
the shapefile layer remains, then only the shapefile layer will appear on the map)
“Map frame” will then appear
In the Map Frame dialog, click Change Map and Frame Area (Maintain Scale) so that
you can accurately size the map frame. Now enter the value of 5.5 in both the Frame
Width and the Frame Height fields. (you can modify the width and height according to
your need and visualization).
Now click on Change Scale and Map Area (Maintain Frame Area) and enter the Upper
Left Frame Coordinates X value of 1.0 and a Y value of 7.0. Set the Scale to 10,000.
Now position the cursor box in the viewer to the area you want to display in the map
composition, and click OK
The area displayed in the viewer will appear in the map view
We will add a neatline and some tick marks to our composition. A neatline is a
rectangular border around a map frame. Tick marks are small lines along the edge of the
map frame that indicate the map units (meters, feet, etc.). You must be using a
georeferenced image in order to produce tick marks.
Click on “Layout”------“Map Grid” and the n click on the “Map View”
In the “Set Grid/Tick Info” dialog box (set the values according to your need)
Horizontal Axis (Length Inside) = 0.06
Spacing = 500
Click on Copy to Vertical (to copy to vertical axis)
Click Apply
If you are satisfied with the appearance of the neat line, click Close in the Set Grid/Tick
Info dialo
Click on “North Arrow” and insert it in the map view
As you click on the “scale bar” “scale bar instruction will appear”. Click on the map
frame
“Scale bar properties” will appear
Maximum length: 3 inches
Units : kilometers
Go to “Drawing” Tab click on “Text element”
Click on map view and put the title
Position the title by double-clicking on the text and enter the parameters in the Text
Properties dialog:
Save your map Go to file----save as---Map composition as—
Reopen your map for visualization
Assignment 4:
1. Images from National Aerial Photography Program (NAPP) of New York city (1984-
1985) and Quickbird are given in Lab 4 folder. Open each image in ERDAS Imagine
and identify the various land cover/use classes and features and fill up the table like the
one below for each image: (Locate at least 10 features)
Image Name:
Details: Resolution (Spatial, Spectral and Radiometric), Date/Month of
Acquisition
Feature Which characteristics (elements) did you use to identify the
feature?
Note: While submitting your answers attach the corresponding images and indicate the
location of the identified features.
2. Use the Quickbird image in question 1 to generate a Land use/ land cover map with all
the map elements.
Note:
National High Altitude Photography (NHAP)
NHAP browse images are created from medium resolution digital products that are captured by a
digital camera. The browse files are resampled to 72 dpi. NHAP scenes for Color Infrared (CIR)
cover approximately an 8 x 8 mile area and Black and White (B/W) cover approximately an 11 x
11 mile area. NHAP browse on GloVis have been clipped to remove the excess film margins and
the images have been oriented "north up".
Quickbird
QuickBird is a high-resolution commercial earth observation satellite, owned by Digital
Globe and launched in 2001 as the first satellite in a constellation of three scheduled to be in
orbit by 2008. The satellite collects panchromatic (black and white) imagery at 60 centimeter
resolution and multispectral imagery at 2.4- and 2.8-meter resolutions. The various bands are:
MS Channels: blue (450-520 nm), green (520-600 nm), red (630-690 nm), near-IR (760-
900 nm). Its radiometric resolution is 11 bit.