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Digital Image Processing Tutorial – Image Interpretation of Satellite Images

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Principle of interpretation of aerial photographs and satellite images


This is the part of image processing, in which images are processed and relevant information in the form of land use/land cover maps can be created. Image interpretation is defined as the extracting quantitative and qualitative information using satellite image/aerial photographs by using field experience, direct recognition and inference.

Remote sensing– image interpretation is a powerful tool because it gives:
  • The aerial and regional perspective
  • The three dimensional depth perspective in the form of DEM
  • Knowledge beyond our human visual perception
  • The ability to obtain a historical image record to document change through Mapping
This topic/article has three important key words to discuss
  • Aerial photographs and satellite image
  • Principle
  • Interpretation

Aerial photographs and satellite image

Aerial photographs/satellite image are used as basic input for this procedure. These satellite images acquired and used as primary source to create information. Interpretation method deployed on the satellite image to create information and judging significance of objects.

Principle

Principle part in this topic can be defined that sort of steps, technique and methods used for the interpretation. In this, principles concept for interpretation -interpretation keys/elements and visual aids are performed using image processing software.

Interpretation

Interpretation means creating information using data or converting information from data. Here data means satellite data/aerial photographs, which are used for interpretation and creating information. Interpretation means identifying and judging significance of earth surface objects visible in satellite image/aerial photographs. 

Image interpretation in remote sensing is the examination of images, acquired by sensors using different portions of the electromagnetic spectrum, for the purpose of identifying objects and judging their significance.

Multi spectral satellite images are used for better interpretation. In this False color composites and natural color composites satellite images are used for this process. 

Below process followed for preparation of satellite image for interpretation and further in to classified map through classification process.


Figure- Image Interpretation Process

There are basically two methods adopted for interpretation-

Visual Interpretation: 

it uses visual methods to interpret aerial/Satellite Images. In this method objects are visually identified on satellite image/aerial photographs and judge their significance using interpretation keys/elements. 

This method was very common when most of the satellite images were produced in hard copies. Because this was only procedure as no digital input involve in the form of image processing software. 

Visual interpretation also becomes important in current scenario when satellite image are available in high resolution such as 60cm/30cm etc. But this method is not stand alone used for interpretation but in combination with digital method in current image processing methods. 

This visual interpretation method requires explicit knowledgeable image processing experts to complete the process of interpretation.

Digital Interpretation:

Uses computer-based methods to interpret digital satellite images/Aerial photographs. In this method, image processing software used for interpretation. 

Many mathematical operations such as subtraction, addition can be implemented to create better qualitative and quantitative information. Instead of these processes, other mathematical models- normalized difference vegetation index (NDVI), normalized difference water index (NDWI), principal component analysis (PCA) and tasselled cap transformation can be used to improve the interpretation quantitatively and qualitatively.

So it is understood that both interpretation procedure are significant for satellite image processing. These interpretation processes are used based on user expertise and requirement of image processing. 

In current scenario, it is important to understand that both interpretation methods should be used in combination for better qualitative and quantitative interpretation.
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