Earth Science Satellite Remote Sensing
Title | Earth Science Satellite Remote Sensing PDF eBook |
Author | John J. Qu |
Publisher | Springer Science & Business Media |
Pages | 356 |
Release | 2007-04-29 |
Genre | Technology & Engineering |
ISBN | 3540372946 |
This book provides information on the Earth science remote sensing data information and data format such as HDF-EOS. It evaluates the current data processing approaches and introduces data searching and ordering from different public domains. It further explores the remote sensing and GIS migration products and WebGIS applications. Both volumes are designed to give an introduction to current and future NASA, NOAA and other Earth science remote sensing.
Earth Science Satellite Remote Sensing
Title | Earth Science Satellite Remote Sensing PDF eBook |
Author | |
Publisher | |
Pages | |
Release | 2006 |
Genre | |
ISBN |
Earth Science Satellite Remote Sensing: Data, computational processing, and tools
Title | Earth Science Satellite Remote Sensing: Data, computational processing, and tools PDF eBook |
Author | |
Publisher | |
Pages | |
Release | 2006 |
Genre | Earth sciences |
ISBN |
Data, Computational Processing, and Tools
Title | Data, Computational Processing, and Tools PDF eBook |
Author | |
Publisher | |
Pages | 335 |
Release | 2006 |
Genre | Earth sciences |
ISBN |
Earth Science Satellite Remote Sensing
Title | Earth Science Satellite Remote Sensing PDF eBook |
Author | John J. Qu |
Publisher | Springer Science & Business Media |
Pages | 445 |
Release | 2007-05-18 |
Genre | Technology & Engineering |
ISBN | 3540372938 |
This book provides information on the Earth science remote sensing data information and data format such as HDF-EOS. It evaluates the current data processing approaches and introduces data searching and ordering from different public domains. It further explores the remote sensing and GIS migration products and WebGIS applications. Both volumes are designed to give an introduction to current and future NASA, NOAA and other Earth science remote sensing.
Earth Science Satellite Remote Sensing
Title | Earth Science Satellite Remote Sensing PDF eBook |
Author | John J. Qu |
Publisher | Springer |
Pages | 0 |
Release | 2007-01-19 |
Genre | Technology & Engineering |
ISBN | 9783540356301 |
This book provides information on the Earth science remote sensing data information and data format such as HDF-EOS. It evaluates the current data processing approaches and introduces data searching and ordering from different public domains. It further explores the remote sensing and GIS migration products and WebGIS applications. Both volumes are designed to give an introduction to current and future NASA, NOAA and other Earth science remote sensing.
Big Data for Remote Sensing: Visualization, Analysis and Interpretation
Title | Big Data for Remote Sensing: Visualization, Analysis and Interpretation PDF eBook |
Author | Nilanjan Dey |
Publisher | Springer |
Pages | 163 |
Release | 2018-05-23 |
Genre | Science |
ISBN | 3319899236 |
This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed. This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.