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Technology to obtain bathymetric information has become necessary considering the length of the coastline and the many islands owned by Indonesia. Measurement technology using multi-beam and single-beam echo sounders is still an alternative to producing bathymetric information. In shallow water, using echo sounders has constraints and limitations, such as being time-consuming, costly and prone to equipment damage. Remote sensing technology is an alternative to obtaining bathymetric information in shallow waters. Bathymetric modelling with analytical and semi-analytic models from satellites requires attenuation coefficients. Therefore, attenuation coefficient models are essential for satellite data. Attenuation coefficient studies using inherent optical properties (IOP) parameters have not yet been studied to determine Kepulauan Seribu bathymetry, Jakarta, Indonesia. The IOP modelling is determined by absorption and backscatter parameters. Chlorophyll-a Total influences these parameters: Total Suspended Matter (TSM) and Coloured Dissolved Organic Matter (CDOM). This study was performed to determine the attenuation coefficient model using multispectral remote sensing in the Kepulauan Seribu and applied five approaches to determining the attenuation coefficient via IOP: the Gordon, Kirk, Morel, Lee and Simon models. The five models' IOP attenuation coefficient results were compared to the in-situ attenuation coefficient value and evaluated. The results of IOP attenuation coefficient modeling of multispectral remote sensing based on the condition of local water parameters is Kd(λ) = 1.4369 ((a(λ) + b(λ)) / Cos θ) + 0.072. based on the modified Gordon method, The modelling results were obtained with an accuracy of 0.98 determination coefficient (R²) and 0.029 Root Mean Square Error (RMSE). [ABSTRACT FROM AUTHOR]

Research focusing on seagrass ecosystems as carbon storage has been conducted in various Indonesian waters. However, an essential aspect that remains unexplored is the simultaneous analysis of blue carbon storage in seagrass alongside carbon dioxide (CO2) flux values, particularly within Karimunjawa waters. This study aims to assess the organic carbon stock and sea–air CO2 flux in seagrass ecosystems in Karimunjawa. Our hypothesis posits that although seagrass ecosystems release CO2 into the water, their role as blue carbon ecosystems enables them to absorb and accumulate organic carbon within seagrass biomass and sediments. This investigation took place in Karimunjawa waters, encompassing both vegetated (seagrass meadows) and unvegetated (non-seagrass meadows) areas during August 2019, 2020, and 2022. Over this period, the organic carbon stock in seagrass and sediment displayed an increase, rising from 28.90 to 35.70 gCorg m−2 in 2019 and from 37.80 to 45.25 gCorg m−2 in 2022. Notably, the expanse of seagrass meadows in Karimunjawa dwindled by 328.33 ha from 2019 to 2022, resulting in a total carbon stock reduction of the seagrass meadows of 452.39 tC to 218.78 tC. Sediment emerges as a pivotal element in the storage of blue carbon in seagrass, with sedimentary organic carbon outweighing seagrass biomass in storage capacity. The conditions in Karimunjawa, including a high A:B ratio, low dry bulk density, and elevated water content, foster a favorable environment for sediment carbon absorption and storage, facilitated by the waters' CO2 emission during the southeast monsoon season. Notably, our findings reveal that CO2 release within vegetated areas is lower compared to unvegetated areas. This outcome underscores how seagrass ecosystems can mitigate CO2 release through their adeptness at storing organic carbon within biomass and sediment. However, the presence of inorganic carbon in the form of calcium carbonate introduces a nuanced dynamic. This external source, stemming from allochthonous origins like mangroves, brown algae like Padina pavonica, and calcareous epiphytes, leads to an increase in sedimentary organic carbon stock of 53.2 ± 6.82 gCorg m−2. Moreover, it triggers the release of CO2 into the atmosphere, quantified at 83.4 ± 18.26 mmol CO2 m−2 d−1. [ABSTRACT FROM AUTHOR]

The coral reef ecosystem plays an important role as a provider of ecosystem services and has various economic benefits to the coastal community. However, the coral reefs ecosystem continues to degrade by 19% globally. This degradation caused some coastal and archipelagic countries have developed methods of calculating coral reef health index, including Indonesia. However, some literature shows that there is no common standard method for coral reef health index as the analysis depends on the data availability and the purpose of the study. Remote sensing technology that currently provides much open-source data is a potential method/tool to calculate the health index of coral reefs if the required parameters are met. This article review aims to identify remote sensing data used in the existing coral health indexes and then analyze the integration of all spatial data for coral reef health index calculation. Reference searches are sourced from the SCOPUS database combined with search engines Harzing and Mendeley. There are five coral reef health index calculation models from 25 references consisting of 19 publications and six reports out of 209 filtered references using keywords of Coral Reef Health Index. As a result, coral reef cover and algae are commonly used data obtained from remote sensing imagery. However, remote sensing technology cannot estimate other important parameters such as fish biomass. In addition, physical information of the waters, such as sea surface temperature (SST) and water clarity indicators (turbidity and diffused attenuation coefficient), are parameters contained in the five indexes that can be obtained from remote sensing data. In general, the literature review shows that coral reef health indicators (e.g. index or individual benthic cover) are significantly related to the various parameters affecting coral reef degradation such as algae cover, rubble cover, SST and river plump either as an individual or multivariate factors. [ABSTRACT FROM AUTHOR]

The Java Sea acts as a carbon source that contributes to the release of carbon dioxide into the atmosphere. The blue carbon ecosystems in the Karimunjawa Islands may absorb and store the carbon released from the Java Sea. The carbon stock in Kemujan Island (Karimunjawa Islands), one of these blue carbon ecosystems, was previously estimated using a remote sensing approach. In the present study, we investigated the carbon stock in the seagrass bed at Kemujan Island by conducting field observations and laboratory analysis. The result shows that there are only two seagrass species in the study area--'Enhalus acoroides' and 'Thalassia hemprichii'--which are categorized as nearly dense and very dense, respectively. Regarding the carbon biomass, the carbon stock below the substrate is more than that above the substrate. However, the carbon stock in the seagrass biomass is less than in the sediment. The average carbon stock in the seagrass bed at Kemujan Island is 4901.91 g C/m2, which is much more than the amount estimated by means of remote sensing. Furthermore, this amount is much larger compared with the average carbon stock of other areas in the Karimunjawa Islands. The large amount of carbon stock stored in the seagrass bed at Kemujan Island denotes the role of this seagrass bed as a carbon sink area. [ABSTRACT FROM AUTHOR]

Seagrass data support conservation areas, carbon budget, natural resource assessment, and other national interests in Indonesia. However, to what extent seagrass-related data are available and how the data are managed are still unknown. In this study, we assess the status of data availability and the roles of stakeholders in seagrass-related data provisioning at a national level in Indonesia. Data were collected in August and September 2022 through Focus Group Discussion (FGD) and a questionnaire. The participants comprised representatives from the central governments (planning, ministerial, research, geospatial agencies), local governments, universities, and non-governmental organizations (NGOs) working in the fields related to the coastal ecosystem. Stakeholders' roles were analyzed using Stakeholders' Analysis (SA), while their relationships were examined with Social Network Analysis (SNA). The results showed that the seagrass areal extent (61.7%) was the most crucial data needed, followed by the percent cover (12.77%). Using seagrass data as coastal management was the highest priority among stakeholders. There were overlapping roles between stakeholders related to seagrass data, as producers or users, due to their urgent needs. Almost all stakeholders were key players, and there was a lack of coordination among them relating to seagrass data provisioning. There was an urgent need to strengthen seagrass data governance. The results of this work form an important pathway for Indonesia to develop approaches to map the seagrass areal extent and share knowledge. • Seagrass data is an urgent need for various stakeholders in Indonesia. • However, data is still scattered among stakeholders and needs to be managed. • Therefore, it is necessary to identify the role of stakeholders clearly. • Stakeholder and Social Network Analysis examined the roles, overlaps, and central actors in providing seagrass data. [ABSTRACT FROM AUTHOR]