The proposed course provides basic understanding about digital image processing of Remote Sensing datasets / images acquired by different earth resources satellites. Today most of the remote sensing data is recording in digital formats. Introduction To Remote Sensing e. Detection of Reflected/Emitted Energy by the Sensor: The sensors recording the energy that they receive are placed in a near– polar sun synchronous orbit at an altitude of 700 – 900 km. These data is storing in various formats like BSQ (Band sequential), BIP (Band Interleaved by Line) and BIP (Band interleaved by Pixel) and so on and these images are undergoing various image processing steps. (European Space Agency). Most raw, NASA Earth observation satellite data (Level 0, see data processing levels ) are processed at Science Investigator-led Processing Systems ( SIPS ) facilities. Different Stages in Digital Image Processing Satellite remote sensing data in general and digital data in particular have been used as basic inputs for the inventory and mapping of natural resources of the earth surface like forestry, soils, geology and agriculture. Click here to see the Section Editorial Board of "Remote Sensing Image Processing". Presently, remote sensing datasets available from various earth orbiting satellites are being used extensively in various domains including in civil engineering, water resources, earth sciences, transportation engineering, navigation etc. In this chapter, we have tried to cover majority of the artificial intelligence (AI) techniques that has contributed to the remote sensing community in the form of satellite data processing, right from the basics to advanced level. Digital Image Processing in Remote Sensing @article{Fonseca2009DigitalIP, title={Digital Image Processing in Remote Sensing}, author={Leila Maria Garcia Fonseca and L. Namikawa and E. Castejon}, journal={2009 Tutorials of the XXII Brazilian Symposium on Computer Graphics and Image Processing}, year={2009}, pages={59-71} } The Landsat TM images were geo-processed for detection of changes in the land cover types. Indian Remote Sensing Series). It demonstrated effective use of the remote sensing data and spatial analysis for vegetation studies: a combination of digital satellite images, GIS cartographic tools and methods Ideally, it is desirable to have a high spatial resolution image with many spectral bands covering a wide area. Presently, remote sensing datasets available from various earth orbiting satellites are being used extensively in various domains including in civil engineering, water resources, earth sciences, transportation engineering, navigation etc. In the near future, image registration will be one of the basic image processing operations in remote sensing. of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. Digital image processing is the use of a digital computer to process digital images through an algorithm. Dragon refers to any of several remote sensing image processing software packages. I have over 15 plus years of experience in processing and analyzing real big Earth observation data from various sources including Landsat, MODIS, Sentinel-2, SRTM and other remote sensing products. The choice of specific techniques or algorithms to use depends on the goals of each individual project. Special Issues. CONTENTS: Introduction to Digital Image Processing. Download free satellite images from sentinel Sentinel Satellite. 3.3 Digital Image processing. Remote Sensing and Digital Image Processing book series. Remote sensing is the acquisition of Physical data of an object without touch or contact. Earth observation satellites have been used for many decades in a wide field of applications. Satellite images from various sensors and digital aerial photographs are often used as data sources, along with modern techniques such as laser altimetry. This software provides capabilities for displaying, analyzing, and interpreting digital images from earth satellites and raster data files that represent spatially distributed data. Sentinel is developed under copernicus programme which is maintained and co-funded by European Union and ESA. 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