CARBON STOCKS ESTIMATION ON URBAN VEGETATION USING UAV-SfM PHOTOGRAMMETRY METHOD

Abstract

Global warming and biodiversity loss are two critical issues currently debated among scientists and world policy makers. Forest retention and various reforestation and reforestation programs can play an important role in mitigating global climate change through sequestering atmospheric carbon. Forests are still the subject of discussion of the negotiations and exclude the contribution of vegetation outside the forest area. In fact, if trees outside the forest are not cut down, it can also reduce carbon emissions in the atmosphere. The lack of evidence regarding its potential and contribution to carbon stocks means that trees outside the forest have not been able to enter the negotiation.
 Vegetation in urban areas are an example of tree communities outside forest that have a major contribution to carbon sequestration in the atmosphere. Urban vegetation can be found in two main locations: Urban Green Open Spaces (UGS) and Road Landscapes (RL). In Bali, especially in Denpasar City, Glodokan Tiang or Polyalthia longifolia trees are planted as road shading trees or trees in green open spaces. To prove its contribution in terms of carbon sequestration, data management and a mechanism for calculating carbon stocks are needed. Generally, the calculation of tree carbon stock consumes a lot of energy and time because it is done manually (measuring tree height and DBH). Technology of Unmanned Aerial Vehicle (UAV) can be used as an alternative to efficiently calculate the estimated of carbon stock in Urban Vegetation. The calculation uses the DBH value approach using the canopy area and tree height model (CHM) obtained from UAV data processing using the Sfm method.
 UAV estimates show that the highest AGB value at Bajra Sandhi Renon Field is 201.59 kg with a stored carbon content of 94.75 kg, while on I Gusti Ngurah Rai Bypass has the highest AGB value of 215.04 kg with a stored carbon content of 101.07 kg. These results have been validated by field observations, where the results of the regression analysis at the location of Bajra Sandhi Renon and I Gusti Ngurah Rai, shows that between field observation data and estimation data with UAV there is no significant difference. While the results of the t-test: Paired Two Sample for Means at the Bajra Sandhi Renon Field and the Bypass I Gusti Ngurah Rai have a value above the significance level which proves that there is no significant difference between the carbon stock value from field observations and the carbon stock from the UAV approach.
 
 Keywords: Carbon Stock; Urban Vegetation; UAV-Sfm.