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.