Image Interpretation

From Wiki.GIS.com

Contents 1 Definition 2 Spatial Interpretation 3 Image Interpretation Elements 4 References

[edit] Definition

Image interpretation is the process of examining images and identifying and judging their significance by considering their location and extent. Expertise in image interpretation is achieved over the period of time through experience.

[edit] Spatial Interpretation

Spatial interpretation is recognizing features using locational characteristics of objects shown on images.

[edit] Image Interpretation Elements

Once a satellite image is acquired it is very important to make sure the interpretation of image is accurate for its intended purpose. For a novice the image might just look like a fusion of color and some structures; however a trained person will be able to identify and delineate the feature.

Image interpretation and analysis uses some pointers or keys to identify the features. Some of them are - Shape, Size, Color, Shadow, Texture, Pattern, Association, Site, Time and Resolution.

Shape: As the name suggests a shape of the feature helps in identifying a feature. A round or oval shape feature could be a stadium. A straight line with very few turns could be a railway track. An assimilation of various elements of recognition will help to ascertain/identify the feature. A natural water body is more likely to have irregular shape.

Size: Size of a feature in relation to the nearby feature plays an important role in successful identification of a feature.

Shadow: Shadow of a feature helps in delineating boundary of the feature. A big object would cast a large shadow as compared to smaller ones. The shadow is also used to measure the height of an object.

Color/Tone: Color or tone of an object is the relative brightness/darkness of an object. A dark blue to black colored huge feature could be water. If there is a shade of red color on top of the water body then it could be mangroves. Variation in the tone could be attributed to reflectance, remittance, absorption or transmission of the feature.

Texture: Texture is the frequency of the tonal changes of the surface. This element is quiet important in case of agriculture and forestry. A group of trees may have a specific texture and that will help to distinguish between a species of tree. A rocky mountain will have a different texture than the mountain with lots of plantation.

Pattern: Spatial arrangement of features in a particular format is pattern. A river will have number of tributaries and on the basis of arrangement of these tributaries you can identify them. A city area with well defined rectangular plots could help you to identify the sectors in the city.

Association: The relationship between different features at the area of interest is the association. A long canal/pipeline along the wide spread area of agricultural fields. If there is a water body with well defined edges then it could be a man made water body, like dam.

Site: A site is the presence of a feature at a particular geographical location. A large vessel or lighthouse will be associated with the sea..

Time: A temporal change in a feature over a period of time can provide a lot of information for image interpretation. Volume of water in pond, river etc can be used to analyze the water supply of a city. Temporal images of an agricultural field can be used to determine the health of the crop.

Resolution: Resolution of the image is also a key aspect in image interpretation. Sometimes an image can be seen very clearly or sometimes it’s too small in relation to nearby feature; hence identifying it clearly can be difficult. In a low resolution imagery a city boundary can be delineated however delineating a building structure can be difficult. In case of high resolution imagery identifying a building structure can be easy.

Apart from above scale, color balance and condition of the image (prints) also play a role in image interpretation.^[1]

[edit] References

Remote sensing from air and space By Richard C. Olsen (2007), published by SPIE – The international society of Optical Engineering, page 137. ISBN 978-0-8194-6235-0

Image Interpretation of Remote Sensing data