|  e-ISSN: 2791-7169

Original article | Journal of Biometry Studies 2022, Vol. 2(2) 78-86

Estimation of aboveground carbon storage based on remote sensing and inventory data: A case study from Türkiye

Fatih SİVRİKAYA, Döndü DEMİREL

pp. 78 - 86   |  DOI: https://doi.org/10.29329/JofBS.2022.445.05   |  Manu. Number: MANU-2212-21-0002.R1

Published online: December 29, 2022  |   Number of Views: 7  |  Number of Download: 54


Abstract

Forest ecosystems are one of  the most important systems in capturing atmospheric carbon dioxide (CO2) and play an essential role in mitigating climate change. Forest ecosystems provide biodiversity, soil conservation, recreation areas, wildlife habitat, nutrient cycling, carbon storage and oxygen production. According to the Climate Change Framework Convention, determining and reporting the amount of carbon accumulation in forest ecosystem is of great importance. Different methods such as allometric equations, carbon expansion factor and remote sensing methods are used to determine aboveground carbon (AGC) storage. Especially with the developing technology, remote sensing techniques are used intensively to determine AGC storage. Normalized Difference Vegetation Index (NDVI) are commonly used, especially in determining the amount of AGC storage. The aim of this study is to estimate AGC storage according to different methods and to investigate whether there are statistical differences in AGC storage estimation of these approaches. The research was carried out in pure Calabrian pine (Pinus brutia Ten.) stands in the Burmahanyayla planning unit in Antalya province in the Mediterranean region of Türkiye. Within the scope of the study, the amount of AGC storage was calculated by using the inventory study conducted in 2022 and the Landsat 9 satellite data. A paired sample t-test was used to statistically examine the difference in the quantity of AGC storage based on inventory data and remote sensing data using SPSS 23.0. The results reveal that there was no statistically significant difference in the AGC storage values between the two approaches in all sample plots.

Keywords: Allometric equations, Aboveground carbon storage, NDVI, Remote sensing


How to Cite this Article?

APA 6th edition
SIVRIKAYA, F. & DEMIREL, D. (2022). Estimation of aboveground carbon storage based on remote sensing and inventory data: A case study from Türkiye . Journal of Biometry Studies, 2(2), 78-86. doi: 10.29329/JofBS.2022.445.05

Harvard
SIVRIKAYA, F. and DEMIREL, D. (2022). Estimation of aboveground carbon storage based on remote sensing and inventory data: A case study from Türkiye . Journal of Biometry Studies, 2(2), pp. 78-86.

Chicago 16th edition
SIVRIKAYA, Fatih and Dondu DEMIREL (2022). "Estimation of aboveground carbon storage based on remote sensing and inventory data: A case study from Türkiye ". Journal of Biometry Studies 2 (2):78-86. doi:10.29329/JofBS.2022.445.05.

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