Integrate Terrain Variables and Rapid Eye Satellite in Vegetation Indices, for Identifying Forest Cover Area and Density: A Case Study in Mountainous Iraqi Kurdistan Region (IKR)

Gaznayee, Heman Abdulkhaleq A.; Sabr, Halmat A,; Galalaey, Ali Mala Khedir; Shakir, Shakir Bahaddin; Omer, Farhad O.; Kareem, Shadia Hama Salih; Ababakr, Snoor H.; Mohammad, Ragheb K.; Ahmad, Fuad M.

doi:10.24271/psr.2024.192393

Integrate Terrain Variables and Rapid Eye Satellite in Vegetation Indices, for Identifying Forest Cover Area and Density: A Case Study in Mountainous Iraqi Kurdistan Region (IKR)

Authors

Heman Abdulkhaleq A. Gaznayee ¹

Halmat A, Sabr ¹

Ali Mala Khedir Galalaey ²

Shakir Bahaddin Shakir ²

Farhad O. Omer ³

Shadia Hama Salih Kareem ⁴

Snoor H. Ababakr ⁵

Ragheb K. Mohammad ¹

Fuad M. Ahmad ⁵

¹ Department of Forestry, College of Agricultural Engineering Sciences, Salahaddin University, Erbil, Iraq

² Department of Field crop and Medical plants, College of Agricultural Engineering Sciences, Salahaddin University, Erbil, Iraq

³ Erbil Polytechnic University, Erbil, Iraq

⁴ Department of Biotechnology and Crop Science, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani, Iraq

⁵ Department of Soil and water, College of Agricultural Engineering Sciences, Salahaddin University, Erbil, Iraq

10.24271/psr.2024.192393

Abstract

The Topographic Wetness Index (TWI) measures of the relative wetness or dryness of a given area of land based on its topography. This index is frequently used to evaluate hydrology and ecology studies. This study examined the association between TWI and vegetation distribution using a number of remote sensing techniques. The study was identified patterns in the data and based statistical analyses to assess the strength and significance of the relationship between TWI and vegetation statues. The result is shown this forest cover patterns are influenced by various environmental factors, including topography, and moisture levels. It is also involved comparing vegetation cover in areas with different TWI values or analyzing the relationship between TWI and other topographical variables such as slope, aspect, and elevation. A significant vegetation variation was found between slope aspects in vegetation distribution. It was revealed that (78%) of a Normalized Difference Vegetation Index (NDVI) was affected by together aspects and TWI, which may be due to a significant association between (NDVI), but this parameter was also highly influenced by slope and DEM because (17%) of the vegetation cover was obtained within these two factors.

Keywords

Density

Forest cover

Vegetation distribution

Vegetation indices

Remote sensing (RS)