Published June 13, 2024 | Version v1
Conference paper Open

A Comparative Study on Satellite Image Classification Using Various Deep Learning Techniques

Description

The satellite image classification procedure comprises categorizing 
the image pixel values. There are several approaches and procedures for classifying 
satellite images. Satellite image categorization algorithms are roughly divided into 
three categories: 1) automatic 2) manual and 3) hybrid. Satellite image classification 
requires the selection of an appropriate classification method depending on the 
criteria. This paper focuses on satellite image categorization methods and 
methodologies.

Files

Abdurashidova Kamola 106-110.pdf

Files (404.1 kB)

Name Size Download all
md5:bc18252a096ed2b3d247f52132193316
404.1 kB Preview Download

Additional details

References

  • [1] Muhammad, S., Aziz, G., Aneela, N. and Muhammad, S. 2012. "Classification by Object Recognition in SatelliteImages by using Data Mining". In Proc. Proceedings of the World Congress on Engineering (WCE 2012), Vol I, July 4 - 6, London, U.K.
  • [2] Chaichoke, V., Supawee, P., Tanasak, V. and Andrew, K, S. 2011. "A Normalized Difference Vegetation Index (NDVI) Time-Series of Idle Agriculture Lands: A Preliminary Study", Engineering Journal. Vol. 15, Issue 1, pp. 9-16.
  • [3] Zheng, X., Sun, X., Fu, K. and Hongqi Wang, 2013. "Automatic Annotation of Satellite Images via Multifeature Joint Sparse Coding With Spatial Relation Constraint", IEEE Geoscience and Remote Sensing Letters, VOL. 10, NO. 4, JULY 2013, pp.652-656.
  • [4] Anders Karlsson, 2003. "Classification of high resolution satellite images", August 2003, available at http://infoscience.epfl.ch/record/63248/files/TPD_Karlss on.pdf.
  • [5] Amanda Briney, 2014. "An Overview of Remote Sensing", May 16, 2014. [online] available at http://geography.about.com/od/geographictechnology/a/r emotesensing.htm