Seagrass is one of the marine resources that considerably potential as a CO2 absorbent and functioned as carbon sinks in the oceans known as blue carbon. The result of carbon sequestration from the process of photosynthesis is stored as carbon stocks on seagrass tissue, or streamed to multiple compartments, such as sediment, herbivores and other ecosystems. This study aims to assess the potential for carbon stock storage in biomass on a tissue of seagrass in Sanur Beach coastal area. The observations of seagrass are included the seagrass type, seagrass stands, and measurement of environmental parameters. Then the sampling was conducted to obtain the value of seagrass biomass. The carbon stocks obtained through the conversion of biomass by using carbon concentration analysis of seagrass tissue and then carried a spatial distribution of carbon stocks. Types of seagrass found in Sanur Beach coastal area consist of eight species that are Enhalus acroides, Thalassia hemprichii, Halophila ovalis, Syringodium isoetifolium, Cymodocea serrulata, Cymodocea rotundata, Halodule uninervis and Halodule pinifolia. The result of the carbon stock seagrass in the bottom substrate is 60% greater than the carbon stock in the top substrate which is 40%. Seagrass covering 322 ha of Sanur Beach coastal area with a total potential carbon storage of 66.60 tons or 0.21 tons / ha. Seagrass key role as a carbon storage is on the bottom substrate tissue, and Enhalus acroides is a seagrass species that contributes the most to the carbon storage.

The mangrove forest of TAHURA Ngurah Rai is one of the mangrove ecosystems in Bali that suffered damages and density changes due to natural factors and human activities. Remote sensing is one of the technology that can be used to estimate the density of mangrove canopy in TAHURA Ngurah Rai. The purpose of this study was to find the best vegetation index for estimating mangrove canopy density out and map it spatially using Sentinel-2A image. The method of this research is using vegetation index NDVI, EVI and mRE-SR to estimate mangrove canopy density. Field data was collected using Stratified Random and Proportional Sampling method by taking photo of the density of canopy using camera with Fish Eye lens on 34 plot. The results of this study show the satistic test of the linear model of the vegetation index with the mangrove canopy density value on the NDVI index (r = 0.8165, R2 = 0.6667, RMSE = ± 8.1508), EVI (r = 0.8597, R2 = 0.7390, RMSE = ± 7.8117), and mRE-SR (r = 0.9277, R2 = 0.8607, RMSE = ± 4.9571). The conclusion of this research is mRE-SR vegetation index able to map mangrove canopy density better than NDVI and EVI vegetation index with 86.07% accuracy. The mangrove spatial distribution generated from the mRE-SR model is 1002.22 Ha with 3.24 Ha categorized as very high density, 94.82 Ha categorized as high density, 333 Ha categorized as medium density, 402.38 Ha categorized as low density, and categorized as very low density is up to 168.76 Ha.

Abstract. Sugiana IP, Andiani AAE, Dewi IGAIP, Karang IWGA, As-Syakur AR, Fharmawan IWE. 2022. Spatial distribution of mangrove health index on three genera dominated zones in Benoa Bay, Bali, Indonesia. Biodiversitas 23: 3407-3418. A study of mangrove forest stratification was conducted in Benoa Bay which experienced high coastal development pressures during the last decade. The study aimed to determine mangrove health index distribution (MHI) and forest community structures along three genera-dominated zones which were Sonneratia, Rhizophora and Bruguiera. Random forest method was applied to classify the areas of distributed genera along the bay. Forest structure was assessed with 54 plots. The forest was mainly composed of Rhizophora and Sonneratia-dominated zones in a respective forest area proportion at approximately 51% and 45%. Those zones were dominated by R. mucronata and S. alba with an importance value index (IVI) at 266.35% and 145.57%, respectively. A narrow Bruguiera zone composed of B. gymnorrhiza domination was found in the most landward area, only covering 4% of the mangrove area. Overall accuracy and a kappa coefficient indicated high accuracy of forest classification at 97% and 0.94 respectively. We found that 47.44% of mangrove areas could be classified into the highest healthiness category indicating that the mangrove forest in Benoa Bay is in excellent condition. The Rhizophora zone made a significant contribution to the entire forest state since the excellent category coverage in this zone was approximately 73.80%.

The seagrass ecosystem has great potential in absorbing of CO2 concentration in atmosphere, results of the process photosynthesis will be stored in form of biomass during seagrass still alive. The research purpose was to know carbon storage from the seagrass ecosystem at the top substrate (leaves) and bottom substrates (rhizome and roots) in Nusa Lembongan coastal area, Bali. The research location is divided into three stations with 27 points. Carbon stock was analyzed by using invasion method consisting of calculating the value of ash content, organic matter content and carbon content. The results found three seagrass species in the Nusa Lembongan coastal area: Thalassia hemprichii, Cymodocea rotundata and Enhalus acoroides. The most dominant spesies is the Thalassia hemprichii. The carbon stored at the top substrate (leaf) is 21.08 gC/m2 and the bottom substrates (rhizome and root) are 52.67 gC/m2. The total estimated carbon deposits in the Nusa Lembongan coastal area is 65.98 tonnes with carbon deposits in the bottom substrate are larger than the top substrate, which is 71% or 47.12 tons on the bottom substrate while 29% or 18.86 tons on the top substrate.

Landsat  8,  Landsat  Data  Continuity  Mission  (LDCM)  satellite,  was  launched  on  11 February 2013 with Operation Land Imager (OLI) sensors. Tis sensor has better radiometric performance than the previous mission, which is quantized in the 12-bit dynamic range due to an increase in the signal-to-noise (SNR) ratio. In this analysis, the spatio-temporal distribution of the propagation of the internal solitary wave (ISW) in the Lombok Strait was extracted from the Landsat 8 images described for the first time.  Tere were 14 ISW events studied for period 2014  -  2015  using  Landsat  8.  Te  manifestations  of  ISW  recorded  on  Landsat  8  images  were then extracted using digitization method to investigate and measure several parameters and ISW distribution in the Lombok Strait. Te estimation results of the average ISW phase velocity in this study are 2.05 ms-1 with the direction of propagation heading north at an average angle of 19.08°. Tis study has shown that Landsat 8 can be used to monitor and analyze several internal wave parameters in the ocean.