Remote Sensing Big Data for Environmental Classification

Sivabalan, Kr

ISBN 10: 644643846X / ISBN 13: 9786446438461

Published by Mohd Abdul Hafi, 2022

About this Item

Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less 0.53.

Seller Inventory # G644643846XI2N00

Bibliographic Details

• Title: Remote Sensing Big Data for Environmental Classification
• Publisher: Mohd Abdul Hafi
• Publication Date: 2022
• Language: English
• ISBN 10: 644643846X
• ISBN 13: 9786446438461
• Binding: Paperback
• Condition: As New
• Dust Jacket Condition: No Jacket
• Weight: 0.53 pounds

About this title

Synopsis

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.