Assuming we have high resolution satellite imagery (multi-spectral raster image) of a large urban area, then how can Python be implemented for the extraction of impervious surfaces?
Please try Object Based classification of ENVI or other similar software.... It can extract upto 90% data.
You can follow the work of Dr. Fan Yang using temporal mixture analysis :
http://www.sciencedirect.com/science/article/pii/S0924271612001189
Dear Mr. Lalu,
Nice reference... Is there is any reference for High Resolution Data.
Jibran ji Please specify Sensor for High Resolution Data.
@Rakesh: Thank you for your suggestion. I have been already using Object-based Image Analysis (OBIA) of ENVI software. However, there are some classification inaccuracies as well that have been identified. For an improved analysis with more accuracy, Python programming can be the best tool for the extraction of impervious surfaces features. That's why I emphasized more on Python in the question.
@Jaelani: Thank you for the wonderful reference. However, it exhibits a usage of MODIS data which is medium resolution satellite data. Also, I believe there is a bit difference between the extraction of impervious surface area and impervious surface features such as roads, vegetation, open space and rooftops etc. I intended to know the Python approach that can be used for the extraction of roads and sideways for example using high resolution satellite data.
@Rakesh: I intended to use satellite data such as Quick bird or Digital globe imagery having high spatial resolution.
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