This paper analyzes remote sensing data and satellite image analysis; remote sensing data is one of the most important data sources used in GIS. This a data is acquired within time frames ranging from weeks to hours. Easy access to remote sensing data allows for rapid satellite image analysis into a Geographical information system. Satellite image analysis is the extraction of meaningful information form digital images using processing techniques. Image processing greatly depends on remote sensing data.
remotes sensing data and satellite image analysis
THE MAIN TYPES OF REMOTE SENSING DATA
There are several types of remote sensing data, this paper however looks at the four main types. Light Detection and Ranging (LIDAR) is the main data type used for satellite imagery classification. Satellites that use the sun as a source of energy effectively extract this data. The geographical information system also uses remote sensing data from satellites that detect radio waves. This data is called Radio Detection and Ranging (RIDAR). Aerial photography is also a type of remote sensing data though it is not common. Thermal imaging is another type of data in which soft wares convert heat radiations into visible images. Therefore, all these types of data are important in satellite image analysis.
main types of remote sensing data
THE PROCESS OF SATELLITE IMAGE ANALYSIS
Satellite image analysis begins with image preparation. This process uses appropriate software packages like ESRI ArcMap and the Quantum GIS for viewing the images. Therefore, The actual image analysis uses MultiSpec, ERDAS Imagine, and Opticks. Also, Geographical information system programs are advantageous for geo-referencing. Lastly, these soft wares appropriately display the multispectral images of remote sensing data with a combination of red, green, and blue bands.
process of satellite image analysis
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