The research focuses on the application of remote sensing techniques in studying the components and characteristics of the Earth’s surface in a new two- axis way. The first is the use of the French Sentinel 2 satellite, which is characterized by more discriminatory accuracy than the Landsat8 satellite, which reaches (10) m, while the accuracy of the latter is (30)) M. As for the second axis, it is the study of spectral indicators, as it depends on algorithms and equations whose results are for parts of the earth’s surface, whether at the level of vegetation, water, or what is related to them. Among these modern indicators issued by the USGS survey are (GNDVI, EVI, SAVI, NDMI, NBRI, BSI, NDWI), as these indicators refer to the study of a specific type of land cover that depends on the spectral regions provided by the satellite. And on the date of picking up 3/21/2021, due to the appearance of the plant in its best condition, in addition to the fact that the ground cover is characterized by diversity at this time. The research aims to build tools within the ARC GIS program using the Model Builder in the form of tools in advisory and environmental studies, and the algorithms of each indicator are decoded using Map Algebra. The Sarkaran region was chosen because it is characterized by the diversity of its surface components, from trough areas to plains, and between barren lands to plain areas with high vegetation density.
Jassim, Saad Mohammed; Salah, Mohammed Attia; and Mohammed, Kaiser Ali
"Building digital models for spectral indicators expressing the land cover in Sarkaran district using Sentinel 2 satellite data.,"
Journal of STEPS for Humanities and Social Sciences: Vol. 1
, Article 13.
Available at: https://doi.org/10.55384/2790-4237.1075
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.