Carbon Stock Estimation of Mangrove Vegetation Using Remote Sensing in Perancak Estuary, Jembrana District, Bali

Hastuti, Amandangi Wahyuning; Suniada, Komang Iwan; Islamy, Fikrul

doi:10.30536/j.ijreses.2017.v14.a2841

Cited by 8 publications

(4 citation statements)

References 29 publications

(40 reference statements)

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“…Mangroves that receive circulatory water input will grow better because they are supplied with sufficient water, accelerating vegetation growth. That carbon stocks in natural mangrove vegetation were higher than mangrove vegetation replanted in former ponds [21]. Not only that, but it also relates to the backscattering value generated by HV polarization.…”

Section: Resultsmentioning

confidence: 84%

Carbon stock estimation and mapping of mangrove forest using ALOS-2 PALSAR-2 in Benoa Bay Bali, Indonesia

Mahasani

Osawa

Adnyana

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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Mangrove forests in tropics coastlines area play an essential role in carbon fixation and carbon storage. Mangrove forests in coastal areas are very effective and efficient in reducing the concentration of carbon dioxide (CO2) in the atmosphere because mangroves can absorb CO2 through photosynthesis by diffusion through stomata and then store carbon in the form of biomass. With the lack of efforts to manage mangrove forests, it needs to be developed so that forest functions can be utilized sustainably. This paper describes examining the use of remote sensing data, particularly dual-polarization ALOS-2 PALSAR-2 data, with the primary objective to estimate the carbon stock of mangrove forests in Benoa Bay, Bali. The carbon stock was estimated by analyzing HV Polarization, Above Ground Biomass (AGB), and ground biomass (BGB). The total carbon stock was obtained by multiplying the total biomass with the organic carbon value of 0.47. The potential carbon stock in the mangrove Benoa Bay area is 209,027.28 ton C to absorb carbon dioxide (CO2) of 767,130.11 ton CO2 Sequestration same with 3.87 X 1011 bottles in 2015 and 204.422,59 ton C to absorb carbon dioxide (CO2) of 750.230,93 ton CO2 Sequestration same with 3.79 x 1011 bottles in 2020.

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Section: Resultsmentioning

confidence: 84%

Carbon stock estimation and mapping of mangrove forest using ALOS-2 PALSAR-2 in Benoa Bay Bali, Indonesia

Mahasani

Osawa

Adnyana

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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“…Vegetation indices (VIs) are used to determine the plant density from remote sensing images. In this research, correlation and regression analysis was used to exploit the association between the values of the NDVI and the carbon information from the existing assessment to estimate the mangroves' aboveground carbon (Hastuti et al, 2017). NDVI is one of the most corresponding vegetation indices for a related purpose (Bindu et al, 2020).…”

Section: Vegetation Indexmentioning

confidence: 99%

Utilization of Sentinel-2 Imagery in Mapping the Distribution and Estimation of Mangroves' Carbon Stocks in Bengkulu City

Sugara

Lukman²,

Rudiastuti³

et al. 2022

Geos. Ind.

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The mangroves' aboveground biomass significantly contributes to the global carbon cycle or economic and ecological values. This makes knowledge about the spatial extent of the mangroves indispensable for policymakers. The sequence of mangroves’ condition range also requires remote sensing data to update the geographical information and synthesize carbon stock in Bengkulu. Therefore, this study aims to create a spatial distrribution of mangroves and evaluate their carbon stock in Bengkulu City using Sentinel-2 imagery. The semi-empirical method uses Sentinel-2 imagery through NDVI to appraise and picture the mangroves' aboveground carbon stock. An allometric equation was used to compute the mangroves' aboveground carbon stock from field measurements. Non-linear regression was used to establish a connection between the NDVI calculated from the Sentinel-2 imagery and the mangroves' aboveground biomass measured in the field, which was subsequently used for aboveground carbon estimation. The results showed that mangroves mapping could derive overall accuracy of 89.09%, where the high-density class existed in 135.12 Ha of total area. It was also discovered that Sentinel-2 imagery could estimate mangroves carbon stock up to 61%. The carbon stock estimation based on the imagery has a value of 16.3992 – 115.134 t C/ha, while that of field survey data ranges from 19.69 to 326.06 t C/ha. These results showed that Sentinel-2B spectral data is functional and has a good chance of being able to predict carbon stock. Keywords : Carbon; mangroves; NDVI; remote sensing; sentinel-2B Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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“…Selain akurasi tinggi, monitoring luasan hutan mangrove dengan menggunakan data satelit penginderaan jauh dapat dilakukan secara berkala dengan lebih cepat dan biaya yang tidak terlalu mahal. Beberapa kajian mangrove yang memanfaatkan data satelit penginderaan jauh diantaranya adalah untuk mengetahui perubahan luasan hutan mangrove dengan menggunakan dua data pada lokasi yang sama dengan rentang waktu yang berbeda (Haryani, 2013); kajian untuk memetakan sebaran dan kerapatan mangrove di Segara Anakan, Cilacap (Purwanto et al, 2014); serta kajian pendahuluan untuk menghitung stok karbon (above ground dan below ground carbon stock) di kawasan estuary Perancak dengan menggunakan data citra satelit Landsat (Hastuti et al, 2017).…”

Section: Pendahuluanunclassified

Pengaruh Perubahan Luas Hutan Mangrove Terhadap Konsentrasi Total Suspended Matter (Tsm) Di Muara Perancak, Jembrana – Bali

Suniada¹

2019

Jurnal Kelautan Nasional

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Study of the function of mangrove forests as a sediment trap has been largely undertaken using field measurement methods, but only a few researches that fully utilize remote sensing data to find out the influence of mangrove forest’s area changes against the Total Suspended Matter (TSM) making this study very interesting and important to do. This research was conducted in Perancak estuary area which is one of mangrove ecosystem area in Bali besides West Bali National Park, Benoa Forest Park and Nusa Lembongan. The data used to generate TSM information and change of mangrove forest area in this research is medium resolution satellite image data, Landsat. Tidal data and rainfall data were used as a supporting data. The information of TSM concentration obtained by using Budhiman (2004) algorithm, shows that along with the increasing of mangrove forest area has caused the decreasing of TSM concentration at mouth Perancak river. The decline was caused by sediments trapped and settled around trees or mangrove roots, especially the Rhizophora mangroves. In addition to the increasing of mangrove forest area, the tidal oceanography factor also greatly influences the TSM fluctuation around Perancak river mouth.

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Carbon Stock Estimation of Mangrove Vegetation Using Remote Sensing in Perancak Estuary, Jembrana District, Bali

Cited by 8 publications

References 29 publications

Carbon stock estimation and mapping of mangrove forest using ALOS-2 PALSAR-2 in Benoa Bay Bali, Indonesia

Carbon stock estimation and mapping of mangrove forest using ALOS-2 PALSAR-2 in Benoa Bay Bali, Indonesia

Utilization of Sentinel-2 Imagery in Mapping the Distribution and Estimation of Mangroves' Carbon Stocks in Bengkulu City

Pengaruh Perubahan Luas Hutan Mangrove Terhadap Konsentrasi Total Suspended Matter (Tsm) Di Muara Perancak, Jembrana – Bali

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