Image processing of Satellite Images

Question

Is it possible to analyze the satellite images to find the possibility of rainfall ares, moisture landscapes such as water bodies, forest areas, wasteland, etc by using computer languages such as C, C++, Java? Which is the best among these? Is It Complicated?

Is there any other option to do this project using advanced C, C++, Java versions? Do these languages have any special function to read pixel values without using tools such as MATLAB, LABVIEW?

Answer 1

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There is a section in the book "Digital Image Processing 3rd Edition" about land-mass analysis if I recall correctly. Also check out "Digital Image Processing in C" which you can download here.

IIRC and this NASA page seems to confirm, and I am no physicist, you will need satallite images with the complete (not just visible) electromagnetic spectrum. This allows you to pick out water, vegitation and so on.

Landsat 7 images are color composites, made by assigning the three primary colors to three bands of the Enhanced Thematic Mapper (ETM+) sensor. These images are not color photographs, they are "false color" images (green fields won't necessarily look green in the image).

The landsat bands will help:

1 coastal water mapping, soil/vegetation discrimination, forest classification, man-made feature identification
2 vegetation discrimination and health monitoring, man-made feature identification
3 plant species identification, man-made feature identification
4 soil moisture monitoring, vegetation monitoring, water body discrimination
5 vegetation moisture content monitoring
6 surface temperature, vegetation stress monitoring, soil moisture monitoring, cloud differentiation, volcanic monitoring
7 mineral and rock discrimination, vegetation moisture content

For more details see: Lillesand, T. and Kiefer, R., 1994. Remote Sensing and Image Interpretation. John Wiley and Sons, Inc., New York, p. 468.

You might also want to create a 3D relief of the images and try and relate the spectrum data with valleys, likely river points, coastal regions and so on. In short there is data to make estimates through image analysis