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Computational Ecology and Software, 2022, 12(2): 67-79
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Estimating and mapping woodland biomass and carbon using Landsat 8 vegetation index: A case study in Dirmaga Watershed, Ethiopia

M. Adamsew Marelign, D. Temesgen Mekonen
Department of Natural Resource Management, College of Agriculture and Environmental Sciences, University of Gondar, P.O . Box 196, Gondar, Ethiopia

Received 19 February 2022;Accepted 11 March 2022;Published 1 June 2022
IAEES

Abstract
This study was conducted to estimate the above and below ground carbon storage in the Woodlands of Dirmaga Watershed, North Western Ethiopia. The field data were collected through systematic random sampling techniques of 40 sample plots. The above-ground biomass and below-ground biomass of the study area was collected from 20 m by 20 m area of the main plot. The biomass and carbon stock of the woodland was estimated using site-specific allometric models and Landsat 8 NDVI and analyzed by ArcGIS. The result showed that the mean carbon stock of above-ground carbon and below-ground carbon were accounted for about 291.47 t/ha and 24.81 t/ha, respectively. The relationship between AGC and NDVI was strong with correlation coefficient of 0.86 and R2 value of 0.745. Tree species of Anogeissus leiocarrpa, Adansonia digitata and Diospyros mespiliformis sequestered the largest portion of the carbon stockwhile, Ficus sycomorus L., Rhus glutinosa and Securinega virosa were the least contributor of carbon stock. The woodland has a great potential for carbon sequestration and biodiversity conservation and the concerned body should conserve and manage the resource properly.

Keywords carbon stock;woodland;allometric equation;NDVI;regression;correlation.

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