Use of Sentinel 2 Satellite Images in Land Cover Mapping for Selected Areas in the Diwaniyah Government

  • Hussain Muhi Ali University of Al-Kufa/ Faculty of Education for Girls
  • Janan Adnan Aboud University of Al-Kufa/ Faculty of Education for Girls
Keywords: Sentinel 2, Land cover, Supervised classification, Diwaniyah, Iraq

Abstract

The use of remote sensing images in the preparation and monitoring of land covers proved to be a very effective and successful technique for various types of land covers such as urban, water or urban cover… etc. The aim of this study is to prepare the land covers classification maps for the years 2016 and 2022 by using European Satellite Sentinel 2 images, for the two seasons (Spring and Autumn). The Anderson land cover classification system was adopted at the first level, using the supervised classification technique, the maximum probability method, and taking advantage of the integration between geographic information systems and remote sensing data. The error matrix was used to evaluate the accuracy of the land cover classification results. The results showed that the manner of the spatial distribution of the land cover classes during the years 2016 and 2022 is almost identical in terms of an increase in the area of vegetation and water cover during the spring season, and a decrease during the autumn season. In contrast to both the barren lands and the salty lands, which decrease during the spring and increase during the autumn season.

Downloads

Download data is not yet available.

References

1. Navalgund, R. R., Jayaraman, V., & Roy, P. S. (2007). Remote sensing applications: An overview. current science, 1747-1766. ‏
2. Manakos, Ioannis; Braun, Matthias. Land use and land cover mapping in Europe. Springer London, 2014. ‏
3. Di Gregorio, A.; Jaffrain, Gabriel; Weber, J. L. Land cover classification for ecosystem accounting. London, UK, 2011. ‏
4. Turner, B. L. Toward integrated land-change science: Advances in 1.5 decades of sustained international research on land-use and land-cover change. In: Challenges of a Changing Earth: Proceedings of the Global Change Open Science Conference, Amsterdam, The Netherlands, 10–13 July 2001. Springer Berlin Heidelberg, 2002. p. 21-26. ‏
5. Petrescu, R., Șmuleac, A. (2019). Topographic lifting of a sewerage network in Santamaria Orlea commune, Hunedoara county. Research Journal of Agricultural Science, 51(4).
6. AlMusawi, H. M. A., & Mohsen, H. N. (2022). Study of the relationship between NDVI and LST for four months in 2021. NeuroQuantology, 20(6), 2190-2195.
7. Herbei, M.V., Sala, F. (2015). Use Landsat image to evaluate vegetation stage in sunflower crops. AgroLife Scientific Journal 4(1), pp. 79-86.
8. Aboud, J. A. & Ali, H. M. (2023). Monitoring and Detecting Land Cover Changes for Selected Areas of Al-Diwaniyah Governorate Using Remote Sensing Techniques and Geographic Information Systems. Journal of Biomechanical Science and Engineering, March 2023 – Special Issue II.
9. Saleh, N. (2000). Informatics in Agricultural Applications, General Organization of Remote Sensing, Damascus, Syria.
10. Shoko, C., Mutanga, O. (2017). Examining the strength of the newly launched Sentinel 2 MSI sensor in detecting and discriminating subtle differences between C3 and C4 grass species. ISPRS Journal of Photogrammetry and Remote Sensing 129(2017), pp. 32-40.
11. Anderson, J. R. (1976). A land use and land cover classification system for use with remote sensor data (Vol. 964). US Government Printing Office.
12. Sahar, A. A., Alhadithi, A. A., Hassan, M. A., & Jasim, A. A. (2021). Integrated remote sensing and GIS for developed new spectral index for estimating Sandy land and its potential hazards. Case study: north-east Al-Muthanna Province area, south of Iraq. Arabian Journal of Geosciences, 14(3), 1-11.
13. Anderson, G. L., Hanson, J. D., & Haas, R. H. (1993). Evaluating Landsat Thematic Mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands. Remote sensing of environment, 45(2), 165-175.
Published
2023-05-08
How to Cite
Ali, H. M., & Aboud, J. A. (2023). Use of Sentinel 2 Satellite Images in Land Cover Mapping for Selected Areas in the Diwaniyah Government. Central Asian Journal of Theoretical and Applied Science, 4(5), 36-45. https://doi.org/10.17605/OSF.IO/WB7D5
Section
Articles