Estimating carbon storage of Eucalyptus urophylla vegetation in Mutis Timau Nature Reserve, East Nusa Tenggara, Indonesia using remote sensing analysis

Abstract

Abstract. Sadono R, Wardhana W, Wirabuana PYAP. 2023. Estimating carbon storage of Eucalyptus urophylla vegetation in Mutis Timau Nature Reserve, East Nusa Tenggara, Indonesia using remote sensing analysis. Biodiversitas 24: 1946-1952. The presence of Eucalyptus urophylla S.T. Blake in Mutis Timau Nature Reserve (Cagar Alam) in Timor Island, East Nusa Tenggara Province, Indonesia plays an important role in long-term climate change mitigation. Therefore, this study aimed to investigate the carbon storage of E. urophylla in Mutis Timau Nature Reserve in varying tree densities using remote sensing analysis. Sentinel 2B satellite image acquired on 10 September 2022 was used to generate the Normalized Difference Vegetation Index (NDVI) using ArcGis 10.8. The NDVI values were then classified to generate the land cover type and density of E. urophylla. The NDVI values greater than 0.7 were assigned as the stands of E. urophylla and classified into low, moderate, and high density. The total carbon storage of each density area was calculated using the estimated area and secondary data of total carbon storage per ha for corresponding densities. The results of remote sensing analysis showed that E. urophylla vegetation was found to cover 73.82% or 9,084.56 ha of the total 12,306.43 ha estimated study area. The estimated area for moderate vegetation density of E. urophylla was 5,150.26 ha followed by low and high densities of 3,857.48 ha and 96.81 ha, respectively. The carbon storage of low, moderate, and high density was calculated to be 577,273.38, 996,655.61 and 27,467.90 tons C, respectively, totaling 1,601,396.89 tons C across the nature reserve. The findings of this study recommend that the coverage of E. urophylla vegetation needs to be expanded, specifically to become high-density to enhance carbon stock, for example through restoration.

Enhancing the estimation accuracy of above-ground carbon storage in Eucalyptus urophylla plantation on Timor Island, Indonesia, through higher spatial-resolution satellite imagery

“…Based on previous investigations, E. urophylla trees were identified using Sentinel-2B satellite imagery and an NDVI threshold value of approximately 0.7 (Sadono et al, 2023a). The Pléiades satellite imagery showed that the E. urophylla tree had an NDVI value greater than 0.699 (Sadono et al, 2023b).…”

“…According to Larekeng et al (2022), the NDVI value range for shrubs was 0.5 to 0.6, low-density forests were 0.6 to 0.65, and mediumdensity forests were 0.65 to 0.7. Furthermore, Sadono et al (2023a) classified the land cover of Mutis Timau Nature Reserve using Sentinel-2 satellite imagery with an NDVI threshold of 0.7 to differentiate eucalyptus plantations. An NDVI value equal to or above this threshold was identified and classified as a eucalyptus area.…”

“…Recently, Han and Xu (2022) found that NDVI can effectively identify trees and correlate with stand density using high-resolution remote sensing imagery. In addition to using Sentinel 2B, Sadono et al (2023a) Regardless of the specific satellite imagery used, observation had shown that higher NDVI values were associated with greater carbon storage. The correlation values ranged from moderate to strong depending on the investigated area of interest.…”

“…Apart from detecting accurate land cover, the use of NDVI with Pléiades satellite imagery can also classify the density of the investigated tree area. According to the underlying theory, a higher NDVI corresponds to denser tree cover (Sadono et al, 2023a). In cases where high precision is necessary due to the value of the species being monitored, a higher spatial resolution satellite image becomes imperative.…”