Forest cover density mapping of Zagros forests using Landsat-9 imagery and ‎hemispherical photographs

Document Type : Scientific article

Authors

1 PhD of Forestry, Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, ‎Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Brasov, Romania

2 MSc of Forestry, Faculty of Natural Resources, Urmia University, Urmia, Iran.

3 Ph.D. of Forestry, Faculty of Natural Resources, Urmia University, Urmia, Iran

4 Ph.D. student of forestry, Faculty of Natural Resources, Urmia University, Urmia, I.R. Iran‎

Abstract

The goal of this study is to see how well the forest canopy density (FCD) model and the GLAMA mobile ‎app estimate the canopy cover density of Zagros forests in Sardasht province. Landsat 9 Operational Land ‎Imager-2 (OLI-2) in 2022 was employed for this purpose. Four indices were created to run the model: 1- Advanced ‎Vegetation Index, 2- Bare Soil Index, 3- Shadow Index, and 4- Thermal Index. The Scaled Shadow Index and Vegetation Density index were then computed by integrating and synthesizing indices one and two, as well as indices three and four, and the FCD model map was created by combining these two indices. The created model was validated using GLAMA mobile app and ‎hemispherical photographs. For this purpose, 100 square sample plots in Sardasht city with varying canopy ‎cover were chosen, and photographs of the canopy cover were taken at five positions on each sample ‎plot. The overall accuracy of the FCD model generated for Sardasht Province was 76%, with a Kappa ‎coefficient of 0.697. Furthermore, the correlation results demonstrate a strong (R2‎ = 0.985) and significant ‎‎(p-value = <0.0001) correlation between the average canopy cover index values estimated by ‎hemispherical photography using GLAMA software and the values acquired by the FCD model. According ‎to the findings of this study, the FCD model developed using Landsat 9 satellite data and the GLAMA ‎mobile app performs very well in estimating forest land canopy density in Zagros forests.

Keywords

References

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Forest Research and Development
Volume 9, Issue 1
June 2023
Pages 47-65

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