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Remote sensing is a powerful technology to identify and classify earth surface objects
by using electromagnetic radiation. Remote sensing provides various tools for working as a
medium of interaction. Generally, remote sensing's working principle depends on sensors,
platform, pre processing, data acquisition, data interpretation and analysis. The technological
development of remote sensing is the proficiency of providing multi-temporal, synoptic,
multispectral and regular coverage of required area from the earth. Especially multi-temporal
data analysis is essential and necessary to characterize the land surface. Because, land surface
is change the properties from one season to another. The optical data availability during sky
conditions and cloudy season is difficult.
Remote sensing data are processed and utilized for various purposes such as land use,
geology, oceanography, agriculture, forestry, environment and meteorology. The earth's
surface measurement from a distance is based on the communication between
electromagnetic radiation (EMR) and the target object. In remote sensing, different stages of
data processing are available. Collect the source of electromagnetic energy (sun), energy
transmission made from source to the earth surface, communication between EMR and
required object, transmission of emitted energy from the targets to the remote sensors and
output data of remote sensors are the essential preprocessing methods and the major
interactions are absorption, transmission of energy and reflection.
Monitoring and detecting global changes (deforestation, global warming,
biomass, flooding, and ozone depletion).
Mapping of data using land use, topography and leaf area index.
Monitoring the environmental changes like soil erosion, hazardous waste etc.
Prediction of weather conditions in different seasons.
Prediction of vegetation condition and yield.
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Remote Sensing Big Data for Environmental Classification
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