Carbon Stock Estimation From Vegetation Biomass Using Spot-7 Imagery

https://doi.org/10.22146/ijg.78690

Iklila Rahmatika(1*), Iswari Nur Hidayati(2), R Suharyadi(3), Emilya Nurjani(4)

(1) Faculty of Geography, Universitas Gadjah Mada,Yogyakarta, Indonesia
(2) Faculty of Geography, Universitas Gadjah Mada,Yogyakarta, Indonesia
(3) Faculty of Geography, Universitas Gadjah Mada,Yogyakarta, Indonesia
(4) Faculty of Geography, Universitas Gadjah Mada,Yogyakarta, Indonesia
(*) Corresponding Author

Abstract


Vegetation absorbs carbon dioxide (CO2 ) emissions during photosynthesis. Covering more areas with trees will increase the CO2 absorption capacity more substantially than other vegetation like bushes, grasses, or rice fields. Trees convert the CO2 captured during photosynthesis into organic carbon to be stored in biomass. Woody trees account for approximately 60% of the total aboveground tree biomass, and trunks, where food reserves produced in photosynthesis are stored, have relatively large biomass compared to other parts of the tree. The biomass of a vegetation stand determines the optimization of air pollutant absorption in urban areas. Yogyakarta City is the center for tourism, education, and cultural activities in Indonesia, which is vulnerable to land-use conversion, a factor of the shrinking green space. This study aimed to estimate carbon stock from vegetation biomass in Yogyakarta City using the remote sensing product SPOT-7 imagery. To calculate the vegetation biomass, the diameter at breast height (DBH) of stands was measured in the field. Then, statistical analyses were performed to determine the correlation and regression between the actual or observed biomass and the Normalized Difference Vegetation Index (NDVI) value derived from the SPOT-7 image. The regression model used was y = 1.4277x – 0.0849. The total biomass produced in Yogyakarta City was estimated at 1,399,487.1 tonnes, which contained 643,764.1 tonnes of carbon stock.

Keywords


biomass; remote sensing; SPOT-7; carbon stock; Yogyakarta

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DOI: https://doi.org/10.22146/ijg.78690

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Copyright (c) 2023 Iklila Rahmatika, Iswari Nur Hidayati, R Suharyadi, Emilya Nurjani

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