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Air Photo Interpretation and Photogrammetry, Image Mosaicking, Digital Orthophoto
created by :
Idung Risdiyanto
MIT Student/99731
Background
One of remote sensing technology is aerial photo. This are interpreted for mapping purposes has become a profession and some features are clearly visible, while others are more difficult to recognize. It often use to make the map with high scale such us to plan road development, forest boundary, water dam and others. It use to there, because the aerial photo has some advantages over than on the ground observatories (Lilesand and Kiefer, 1994). That are :
> Improved vantage point, aerial photo gives a bird’s eye view of larges area, enabling to use to see earth surface feature in their spatial context
> Capability stop action, different with human eye, it can give us a stop action view of dynamic condition,
> Permanent recording, it is virtually permanent records of existing conditions
> Broadened spectral sensitivity, It can see and record over a wave length range twice as broad as that of the human eye
> Increase spatial resolution and geometric fidelity
> Maybe cost effective
The subject to learn about how to manage the aerial photo is called Photogrametry. These are the science, art and technology of obtaining reliable measurements, maps, DEMs and other derived products from photograph. Emphasis on quantitative measurements can be derived by aerial photograph are length, area, height and volume.
To interpreted photograph based extracting information from shape size, patterns, shadow, gray tones, color, and texture and through context and comparison with congruous areas. That also consider about black and white (panchromatic) type and color (infrared) type of photograph. When we create the interpreted of aerial photograph we must to consider about the basic element of aerial photo interpretation. The basic elements can divide three orders as basic order, geometric and spatial arrangement order and locational/positional and interpreted order.
a. Element of aerial photo interpretation
Basics elements or 1st order consider about by two path, first is tone/color, that will be explained about distinguishable variations in shades of black to white or color. It can distinguish many more colors than shades of gray and second one is resolution. That is ability of the entire system to create a sharply defined image, may be discussed in terms of camera lens and ground resolution.
Geometric and spatial arrangement or 2nd order, geometric arrangement consider about size and shape. Size can be used for judging the significance of object and features, actually the relative and absolute sizes are important to think. To aids in identifications we use the shape elements. It may make by interpreter (man made) and natural. Man made main tend to have straight edges and natural is irregular shapes. Spatial arrangement interest about texture and pattern on the surface, which had been capture by aerial photo sensor. Texture is frequency of change and arrangement of tones; it will be explained about visual inspection of smoothness or roughness. There are always exceptions. Other spatial arrangement is patterns, for example such as network of street, irrigated and drainage. Each of objects on the surface will be shown different pattern and texture depend on object characteristic.
The last order of elements air photo interpretation is locational/positional and interpreted order. Positional derived by site and association. Site is how the objects on the surface arrange with respect to one another or terrain features. Including in site are aspect, topography, geology, soil, vegetation and cultural features. Association is some object is commonly identified with other features and tend to confirm the existence of another. It will be aids for manmade installations such as telephone and electric network. Interpreted order explained about height and shadow. The height provides detail about many features and is useful for analytical studies such as height of tress and depth of valley. Shadow use to inhibited interpretation and enhance. For example for identification of tress can be enhanced by the shadow that are recorded and other example is geologist often use a low sun angle to interpret the mineral deposit on the surface.
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Figure 1.1. Basic diagram to measurements the vertical aerial photo
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In
this assignment we will be done to calculate aerial photo, therefore as
background we only explained about how to measurement scale and height. To understanding the height and scale we can see this figure.
Refer from figure explanation we can derive equations to measurement the
scale and height.
Scale
calculation
Scale can
calculated using this equation : S
= d/D
Where : S : photo scale d : photo distance
D : ground distance For
a vertical photo taken over flat terrain scale is a function of focal
length and height of focal plane above ground.
So, the equation is : S
= f/H’
Where
:
S
: photo scale (RF)
f
: camera focal length
H’ : flying
height above terrain Flying
height above terrain derived from height of the plane above the datum and
terrain elevation. The
equation is : H’
= H – h
Where : H
: Height of the plane
above the datum h : terrain elevation |
Height
of the object on the surface can be calculated using fuction as relief
displacement, radial distance, and height above the datum and flying height.
The equation is :
H = d.H/r
d
: relief displacement
r : radial distance on the photograph from the principal point to the displaced image point
h : height above the datum of the object point
H : flying height above the same datum
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c.
Image Mosaic Mosaic
can be definition if when adjacent somewhat overlapping images/photos are
joined to get a larger image. This technique is important, because when we
want to get the larger image from several image that the near or with the
same area. Sometimes it is useful to join two or more image or air
photo. For example Java
Island to be represent 16 Landsat Image, then, if we want to get the
larger area in order to can represent all Java Island we need to create
the mosaic provide by 16 Landsat Image. The image will be generating mosaic must be geometrically corrected and in the same coordinate space. To generating mosaic can use three techniques, there are cutlines, color balancing and feathering. Cutlines is line manual digitizer by user and the line should follow the natural features such as road, tree line or river. It used to hide the edge where the images connect. This technique in Er Mapper Software is called Stitch lines). For illustration about this technique can be seen in Figure 1.2
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Figure 1.2. Cut Lines two images for mosaicking |
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Figure 1.3. Histogram matching |
Color balancing used to correct for color differences between to images or
orthophotos.
If images have the different color or tone maybe caused by
different date to capture data by sensor. This technique also consider
about the intensity. In Er Mapper software, color balancing will be done
with the histogram manipulation or histogram matching.
Many type transformation of DN value that used for color balancing.
Necessary to think, we must use the same type of transformation on
the both of image that will be create the mosaic.
For example if we use 99% transformation for band 2 (RGB 321) on
image A, so on image B must also used 99% transformation type (Figure
1.3).
The last one technique is feathering. This technique uses the specified distance or buffer where the output image is a combination of both input images. Feathering used to ensure a smooth transition between images that will be creating the mosaic. It will be reduce the visual effect of seams between two or more image. On the area of over lap the color influences by original image have the value fifty-fifty percentage (figure 1.4) |
Figure 1.4 Feathering
For Procedures, Result, Discussion and Conclusion, you should contact us
REFERENCES
Jensen,
John R. 1986. Introductory Digital Image Processing – A Remote Sensing
Perspective. Prentice Hall, New Jersey. USA
Lillesand,
Thomas M.,Kiefer, Ralp W. 1994. Remote Sensing and Image Interpretation 3rd
edition. John Wiley and Sons. USA
O’Brien, R.. 2000. Lecturer’s Handout of Advance Digital Image Processing (ITM 532). MIT Programme, SEAMEO BIOTROP – Bogor, Indonesia.
