CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Analytical Approach for Identification of Orbits from SCATTEROMETER Level-0 Noise Images

Published on August 2016 by Mudit J. Dholakia, C. K. Bhensdadia, Anuja Sharma
journal_cover_thumbnail

International Conference on Communication Computing and Virtualization
Foundation of Computer Science USA
ICCCV2016 - Number 2
August 2016
Authors: Mudit J. Dholakia, C. K. Bhensdadia, Anuja Sharma
77376beb-f91e-4dc4-8c18-564a79e97d75

Mudit J. Dholakia, C. K. Bhensdadia, Anuja Sharma . Analytical Approach for Identification of Orbits from SCATTEROMETER Level-0 Noise Images. International Conference on Communication Computing and Virtualization. ICCCV2016, 2 (August 2016), 1-5.

@article{
author = { Mudit J. Dholakia, C. K. Bhensdadia, Anuja Sharma },
title = { Analytical Approach for Identification of Orbits from SCATTEROMETER Level-0 Noise Images },
journal = { International Conference on Communication Computing and Virtualization },
issue_date = { August 2016 },
volume = { ICCCV2016 },
number = { 2 },
month = { August },
year = { 2016 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/icccv2016/number2/25600-0171/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Communication Computing and Virtualization
%A Mudit J. Dholakia
%A C. K. Bhensdadia
%A Anuja Sharma
%T Analytical Approach for Identification of Orbits from SCATTEROMETER Level-0 Noise Images
%J International Conference on Communication Computing and Virtualization
%@ 0975-8887
%V ICCCV2016
%N 2
%P 1-5
%D 2016
%I International Journal of Computer Applications
Abstract

Considering the raw data extraction algorithms designed for different sensor data this paper focuses on the SCATTEROMETER Level-0 data extracted from raw data products. An analysis of extracted noise images is shown. Then a very simple technique but a very important concept is described and implemented on such noise images. Paper shows the approach which can be help full for identification of number of orbits in to the raw data products. The main objective of this approach is to provide the statistics to the application specific user. The approach is based on analyzed behavior of noise images extracted from the raw product. This approach defines a very basic standard to identify number of orbits based on SCATTEROMETER noise images. An implementation algorithm with its time complexity is shown with the corresponding implementation in C language. The proposed approach is for noise images of Data Quality Evaluation Level-0 SCATTEROMETER noise images, but it can also be extended for other noise images. The assumption for the paper is, the scanning geometry of noise image has been established in terms of scans and pixels i. e. header or interpretation format of the noise data.

References
  1. SCATTEROMETER Payload Design Team-ISRO. OCEANSAT-II SCATTEROMETER PAYLOAD PRELIMINARY DESIGN REVIEW DOCUMENT. SAC-ISRO,2005
  2. Spencer, Michael W. , Chialin Wu, and David G. Long. Improved resolution backscatter measurements with the Sea-Winds pencil-beam scatterometer. Geoscience and Remote Sensing, IEEE Transactions on 38. 1 (2000): 89-104.
  3. Parmar, R. M. , et al. OCEANSAT 2: mission and its applications. Asia-Pacific Remote Sensing Symposium. International Society for Optics and Photonics, 2006.
  4. Misra, Tapan, et al. Oceansat-II Scatterometer: Sensor Performance Evaluation, Analyses, and Estimation of Biases. Geoscience and Remote Sensing, IEEE Transactions on 52. 6 (2014): 3310-3315.
  5. Singh, Randhir, Prashant Kumar, and Pradip Kumar Pal. Assimilation of Oceansat-2-scatterometer-derived surface winds in the weather research and forecasting model. Geoscience and Remote Sensing, IEEE Transactions on 50. 4 (2012): 1015-1021.
  6. Calla, O. P. N. Study of Ocean using Indian Space Borne Microwave Sensors. IJCST 2. 4 (2011).
  7. Joseph, George. Fundamentals of remote sensing. Universities Press, 2005.
  8. Palsule, S. S. , et al. Resourcesat-1 data quality evaluation system. International Journal of Applied Earth Observation and Geoinformation 10. 2 (2008): 147-158.
  9. Tummala, Kimeera. Synthetic Aperture Radar (SAR) Data Simulation for Radar Backscatter Cross-section Retrieval. Diss. ISRO, 2014.
  10. Tobler,W. R. Cellular geography. Philosophy in geography. Springer Netherlands, 1979. 379-386.
  11. Dholakia, Mudit. Muditdholakia/muditdholakia. github. io. GitHub. 1 Oct. 2015. Web. 30 Oct. 2015
  12. Balagurusamy, E. programming in ANSI C. Tata McGraw- Hill Education, 2004.
  13. Folk, Mike, Robert E. McGrath, and Nancy Yeager. HDF: an update and future directions. Geoscience and Remote Sensing Symposium, 1999. IGARSS99 Proceedings. IEEE 1999 International. Vol. 1. IEEE, 1999.
  14. Cormen, Thomas H. Introduction to algorithms. MIT press, 2009.
  15. Brassard, Gilles, and Paul Bratley. Fundamentals of algorithmics. Prentice-Hall, Inc. , 1996.
  16. ISRO, NRSC. National Remote Sensing Centre. NRSC. ISRO. Web. 25 Nov. 2015
Index Terms

Computer Science
Information Sciences

Keywords

Spatial Data Products Orbit-identification Noise-images Image Data Analysis