Change Detection between Landsat 8 images and Sentinel-2 images

  • Nawfal S. Abd-Alwahab Department of Physics, College of Science, Baghdad University, Baghdad, Iraq
  • Nawal K. Ghazal Department of Remote Sensing & GIS, Science College, Baghdad University, Baghdad, Iraq

Abstract

     The technology of change detection is a technique by which changes are verified in a certain time period. Remote sensing images are used to detect changes in agriculture land for the selected study area located south of Baghdad governorate in Agricultural Division of AL-Rasheed district because this method is very effective for assessing change compared to other traditional scanning techniques. In this research two remotely sensed images for the study area were taken by Landsat 8 and Sentinel-2, the difference between them is one month to monitor the change in the winter crops, especially the wheat crop, where the agriculture began for the wheat crop there in the Agricultural Division of AL-Rasheed district at 15/11/2018. The first preprocessing procedure was the extraction of the NDVI (Normalized Difference Vegetation Index) values for the two scenes of Landsat 8 and the two scenes of Sentinel-2B and then using the change detection between them to compare the changes in agriculture land. Also, change detection was implemented between NIR bands because they are most severely affected by biomass or the amount of available chlorophyll-containing in plant structures. The results of the change detection for Sentinel-2B were more accurate than for the Landsat 8 as demonstrated by field visits for the study area, where the changes in the distribution of vegetal cover (wheat and other winter crops) were clear and accurate in the image of Sentinel-2B, as opposed to Landsat's 8 image, where the variation in vegetation cover was not accurate, especially for the change detection between NIR bands.

Published
Aug 26, 2019
How to Cite
ABD-ALWAHAB, Nawfal S.; GHAZAL, Nawal K.. Change Detection between Landsat 8 images and Sentinel-2 images. Iraqi Journal of Science, [S.l.], p. 1868-1876, aug. 2019. ISSN 2312-1637. Available at: <http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/933>. Date accessed: 17 sep. 2019.
Section
Remote Sensing