Pages: 15

This chapter is intended especially to give examples of easy use of accessing, data collections, processing, and analysis of the sea surface height (SSH) data for oceanographic phenomena and marine resource studies. SSH data were collected with permission from the National Oceanic and Atmospheric Administration (NOAA) OceanWatch and AVISO database. The numerical data of SSH were processed spatially using the ER Mapper geostatistical gridding method. The chapter will give example data applications of SSH data is old ones, but this is intended to give the real data in the real event of oceanographic phenomena. These are equatorial current along the Pacific equatorial region, North Guinea Coastal Undercurrent (NGCUC), El Nino, La Nina, Tidal bore, and coastal risk and hazards of Tsunami wave and Kuroshio-Oyashio seawater mass around Japan Islands. Another possible application for marine resource studies in the future is turtle-tracking, migration, Cetacean tracking, nutrient flows and mixing, plankton distribution, and small pelagic fishes. The important new approach in this chapter is the application of geostatistical spatial interpolation of the original ASCII numerical data. Using this new method, we can increase substantially the spatial resolution from a global grid km-scale into a meter-scale resolution. Thus, we can also increase the accuracy of the object of study such as plankton abundance during a specific oceanographic phenomenon of toxic Dynoflagelates blooms or others.

Pages: 22

The chapter will lay down the very basic or fundamental concept and methods for transforming ocean station data into spatial layers for multivariate interactive ecosystem analysis. It has been so long that we can only know numerical data on each single station in the ocean. Using coordinates is the standard method for marking oceanographic field measurements. The basic approach is gathering all field measurement or sampling data in the ocean so that those can be seen visually. The method of converting points into spatial layers using the geostatistical Kriging method is known as the interpolation method. This is a controllable and corectable process both numericaly and spatially. Using this concept we can develop and analyze the spatial distribution and intercation of all kinds of measurement data in the ocean. We should understand the right concept of oceanographic variables so that we can develop on the interaction of all variables and understand the whole ecosystem. This involves obtaining key physical oceanographic variables such as seawater temperature and salinity, chemical variable such as nutrients, and biological data of phytoplankton, zooplankton, larvae, pelagic fishes, and demersal fishes. A scientificaly important example in this chapter is the ocean phenomena of seawater temperature anomaly in the event of El Nino and La Nina at the north Papua West End Pacific. This is widely known as the North Guinean Coastal Undercurrent (NGCUC), and the ocean heat flows from Peru to the west along the equator and reach north Papua.

Pages: 9

The chapter will introduce and develop the analysis of deep-water flows using both horizontal and vertical seawater temperature data for an upwelling process and its relationship to nutrient and chlorophyll-a spatial distribution. This is because such analysis using an integrative data analysis approach is very rare in Indonesia, where one can understand the whole picture and characters of oceanographic processes as an ecosystem holistically. Nitrate, phosphate, and chlorophyll-a were analyzed in 5-liter water samples from 21 stations. Nitrate, phosphate, and chlorophyll-a were analyzed using the Pearson procedure soon after each water sampling on board of RV BARUNA JAYA IV following a vacuum pump filtration and spectrophotometer method. GPS coordinates were recorded at every 6-minute interval. The survey track was designed as a “U”-shaped parallel grid track with a total length of 3375 miles. Field data were processed using the “Kriging” method in ER Mapper software (licensed user). Analysis of horizontal temperature data was performed using a multilayer analysis method developed earlier. The horizontal surface temperature of the North Papua pattern which indicates a West-North temperature flow of water mass, also known as North Guinea Coastal Undercurrent (NGCUC). A warm water mass (with temperature between 29.865 and 30.479ºC) is trapped at the coast of Cenderawasih Bay, which presumably is due to the El Nino effect. Three important phenomena can be derived from this analysis is that the thermocline layer in fact was acting as the vertical mixing barrier for vertical water mass movements, thus as well as vertical barrier for nutrient and other passive biomass. The occurrence of vertical water mass movement was a critical process to chlorophyll-a as organic or biomass production in the surface water, especially for the deep-sea ecosystem. The spatial distribution of nitrate was more affected by vertical movement of the water mass in this case by upwelling process, while spatial distribution of phosphate was more affected by relatively more dominant and strong horizontal water flows as indicated in the three-layer nitrate-phosphate-chlorophyll-a RGB-spatial model.

Pages: 12

The chapter is dedicated to discover the uniqueness of plankton diversity, density, and spatial distribution in the West End Pacific deep seawater at the North Papua seawaters. The areas are often least studied and scarce in information despite their uniqueness and importance to scientific development. The chapter is part of a holistic ecosystem study to understand the whole ecosystem characters and its interactions, including water movement, nutrients, chlorophyll-a, phytoplankton, zooplankton, and fish biomass spatial pattern off the north of Papua, which had been published in a series of different manuscripts. The plankton samples survey track was designed as a “U”-shaped parallel grid track with a total length of 3375 miles and ranging from 120 to 240 miles off the North Papua, with 60-mile intervals between main legs. All field data of chlorophyll-a (mg.m-3), phytoplankton (cells.m-3), zooplankton (individu.m-3) were then processed spatially using the geostatistical Kriging method. From the findings of the study, firstly, the green-pigmented phytoplankton, considered edible, was found in the corridor of Halmahera and Papua waters. A spatial interaction analysis indicates the occurrence of spatial overlapping of zooplankton over phytoplankton and this ecological phenomenon is referred to as a “grazing zone.” Secondly, the dominant plankton in this area was in fact a non-chlorophyll pigment genera or species such as Radiolarian and with dominant silica cell content. Evidence based on the actual field samples of phytoplankton explain that not all phytoplankton genera found in this specific area of North Papua waters consist of green pigment chlorophyll-a or the edible plankton genera for fish communities. Instead, there were other genera such as the spiny-siliceous genera of Radiolarian which are a non-green pigment and regarded as a non-edible genus. These non-pigment phytoplankton genera were assumed as the specific genera for this extreme oceanic and deep seawater ecosystem and considered as the ecological response to the seawater temperature anomaly condition caused by the El Nino event in 1997.

Pages: 8

The increasing need to introduce and highlight the analysis of deep seawater temperature (both horizontal and vertical) profiles for an upwelling process and its relationship to fish biomass spatial distribution was inevitable. This is especially to avoid the misleading interpretation of using only surface water temperature data for deep seawater fish biomass analysis. The chapter analyzed and revealed the fate or occurrence of upwelling zones adjacent to Halmahera island through the analysis of both multilayer horizontal and vertical temperature data. Further analysis on the temperature and fish biomass data revealed the close relationship of the horizontal temperature pattern, especially at a depth of 80 m, with the spatial distribution of total fish biomass based on acoustic numerical data: converted fish biomass from the dB unit to ton/mile square), representing fish assemblages with a total length of above 30 cm.

Pages: 13

Coastal seawater ecosystems represent a significant importance with regard to regional and local economic fisheries including marine culture, tourism, and other activities. Measuring their typical spatial distribution patterns, however, has proved challenging since the real coastal water parameters as a part of a whole ecosystem and their interactions had never been revealed so far. A GPS-guided sampling and in situ measurement of the field data, digital, and image processing analysis were applied to ensure that the simulated coastal water ecology model displayed high levels of spatial, geodetic, and real-data accuracy. The newly developed techniques could ultimately provide coastal managers and decision-makers with ecologically truthful and cost-effective means to determine and assess the right zone for fisheries and other coastal water activities based on both temporal and spatial changes.

Pages: 26

Oil spills are a major source of marine pollution, particularly in the Bintan Waters located along Indonesia’s Archipelagic Sea Lane (ALKI-I), where intensive shipping activities occur. This activity increases the risk of marine pollution, including oil spills, which can be detected through Sentinel-1A SAR (Synthetic Aperture Radar) radar imagery. This chapter aims to analyze the distribution of oil spills, trajectory spatial model or movement of oil spills using GNOME software, calculate the area and volume of oil spills, and evaluate their impact on chlorophyll-a concentration. The analysis was conducted using SNAP, QGIS, WebGNOME, and ArcMap software. The study case of this chapter is oil spills incident on March 23, 2023. The results obtained include the location of oil spill distribution, types of oil spills, such as diesel, light crude, and medium crude, trajectory models, and correlations with chlorophyll-a concentration in the waters of the study area.

Pages: 16

Sharks-ray guitarfish is included in the category of cartilaginous fishes (Elasmobranchii). Shark is demersal fish so that we need to know the depth of the waters to find out the habitat of shark. The depth variations can be analyzed using numerical spatial data. Remote sensing is a method of observing objects without touching them directly. The purpose of this chapter is to develop a shark-ray catch spatial database system, also known as “fishing-ground” spatial model and its more detail derivative spatial analysis such as its intercorrelations with oceanographic variables such as depth variation in the Java Sea or its relationship among other shark catches. It also performs retrieval exploration on the analysis of fish-catch to the depth data at Java Sea. Main data are coordinates of fishing operation collected from fishermen’s log books. Shark-ray data catch is also supported with data available at the Kejawanan Cirebon Fishing Port for the period of 2011–2012 for two major species of Junjunan shark (Rhynchobatus djiddensis) and Depo shark (Rhinobatos schegelii). The highest catch for the Junjunan shark was recorded during the west monsoon in 2011, with total catches reaching 7,440 kg, and the highest catch for the Depo shark was recorded during the east monsoon in 2011, with total catches reaching 7,383 kg. Another catch data gives example of 2019–2022 four species of shark-ray: Rhyncobatus australiae, Rhyncobatus leavis, Rhyncobatus springeri, and Rhina ancylostoma. The average depth fishing ground of shark-rays at the Java Sea is 50 m. This indicates the association of shark-rays with its depth preference in the Java Sea.

Pages: 28

This chapter explores and gives examples of the new paradigms and how to develop the degree of association with data of sub-surface temperature. Tuna (Thunnus sp.) is a large pelagic fish that has its own sub-surface seawater temperature preference. Tuna are known as a “thermo-conformers” species, which could not adjust their body temperature to their surrounding seawater temperature and thus actively swim in their preferred sub-surface temperature.

Pages: 10

Specific coastal risk hazards that occurred in Semarang city are coastal land subsidence and tidal flat. This chapter gives a series of data, which includes field measurements, land contours, land height, and coordinate positioning via Geodetic-GPS for the 60 benchmark positions in Semarang, that would be held by the Indonesian Geospatial Information Agency (previously BIG Bakosurtanal). The collected Geodetic data were transformed into numerical data and then processed into spatial layer using the geostatistical Kriging method in ER Mapper 6.4 software. Another spatial data used are Space shuttle Radar for Terrain Model (SRTM) on Semarang city for 3D-image analysis and Landsat-ETM. A spatial coastal land-subsidence model was built based on field measurement data. Spatial coastal land Subsidence Vulnerability Index (SVI) was developed based on variables of distance from coastal line, land-slope, and the distance from the river. Field data measurement and a series of spatial plots revealed that subsidence rates in Semarang city ranged from 1 to 9 cm/year. The SVI model was then validated using the field (actual) land subsidence. As a consequence of the phenomena, the need for re-mapping and periodic evaluation of the city on spatial zoning is inevitable.

Pages: 40

This chapter is intended to discuss the global-scale tsunami of Aceh from the point of view of geomatic science and for the benefit of people through some textural, slope, and height algorithm of three-dimensional satellite data of space shuttle contour data capable of distinguishing among flat, hilly, and mountainous zones of the affected area and hyperspectral of IKONOS data to the coastal environmental changes. That is to analyze the effect of tsunami to the change of the earth surface such as vegetation, topsoil, and infrastructure such as road network, buildings, housing area, fishermen villages, energy supply network, and telecommunication system. Geomatic mapping creates tsunami inundation models (e.g., 10 m and 20 m height) to identify high-risk zones for mitigation and prevention of destructive effects. Lesson learned of Aceh tsunami: three-dimensional data analysis (based on slope algorithm) for coastal zone rehabilitation, town-planning, escape zone, other coastal area thematic spatial database system, and management. To the near future, the objective of the chapter is to introduce socialization of “Potential Risk and Hazard Coastal Area by Tsunami Wave” to society and establish some broad knowledge and principles for planner Bappeda (Badan Perencanaan Daerah – Province Planning Office) and Bappenas (Badan Perencanaan Nasional – National Planning Office) and for coastal managers to shift towards a new holistic paradigm for anticipating all possible risks and hazards of coastal areas, with more emphasis on the local character of nearby coastal areas, geomorphology, and the way of life of local inhabitants.

Pages: 17

This chapter explores and discusses the importance of coastal zone ecosystems such as estuarine and deltas which can be grouped into two categories: shallow and deep sea. Shallow coastal estuarine and delta is characterized by a very shallow coastal plain, usually very turbid water and high sedimentation rate. Deep water coastal estuarine and delta is characterized by a very steep coastal feature and low sedimentation rate. The morphology of both categories of delta had been explored to measure some ecosystem parameters, especially salinity, sediment, or substrate of delta and to study their specific oceanographic phenomena. The field work will give some samples and identify its endemic organism and important fish resources. This chapter gives some examples of Landsat-TM time series delta analysis, old delta reconstruction based on DEM analysis of SRTM data and the built spatial database system. This chapter gives some important new scientific facts such as the fate and occurrence of specific hydro-oceanographic phenomena based on the important seawater indicator parameter such as water salinity in the “fresh-water dominated Mahakam delta, seawater intrusion in the Demak delta, extreme tidal range in Bagan Siapi Api, Dumai, Panipahan, Siak, and non-mixing of two water mass in Batang Gasan and Batang Kataping delta, Sumatra. Endemic organisms found are “mimi” (Limulus sp), fresh-water burrowing crab and “tiger-snail escargot” (Babylonia sp.).

Pages: 13

The Indonesian Islands formation began in the era of Oligocene (50–30 million years ago), with the collision of the three tectonic plates of Sumatra, Java, and Borneo (Kalimantan) Islands of Eurasia plate, and the south Sulawesi (Celebes), Mollucas Islands, and south Palua of the Australian plate, and north Sulawesi and north of Papua Island of the Pacific plates. The research aims to reconstruct this based on the concept of ancient Muria Strait and Grobogan seawater trap and Sangiran deep sea. DEM data were used to reconstruct and analyze the phase of sedimentation, geological uplift processes, and marine palaentological samples of the ancient coastal line to the unification of the ancient seas to become the existing Java condition. This chapter gives examples of three phases. Phase-1 in the Pliocene Era (2 million years ago) showed the uplift of South Java leading to the formation of Sangiran dome and back-swamp paleo-ecology zone. Field validation had found a variety of massive marine mollusc fossils such as Turritella sp., Strobus sp., Murex sp., Ostrea sp., Orthaulax sp., Natica vitellus, and the “Bukuran village” (“bukur” in Javanese means gastropods). The mollusc dome was characterized by a dark high organic clay sediment. Phase-2 aims to discover the “fringing-reef” and mollusc fossils found at Bendung Klambu and continued to the ‘trapped ancient seawater’ locally known as ‘Bleduk-Kuwu’ where a mud-blow, salt, and mollusc fossils are found. This zone is known as “the north Kendeng lime-stone mountain” or “the front-arch formation” that was assumed as the ancient coastal line of the “Muria strait” and recognized as a marine-palaentological zone. Phase-3, Patiayam dome in Kudus uncovered the vertical eco-geological layers of freshwater and marine mollusc fossils such as Tridacna sp., Cassis tuberosa, Tonna allium, and Haliotis asinine and high organic freshwater and coraline marine sediment.

Pages: 17

Most of recent approaches by authorities for designing any conservation programs prioritize broad spatial targets rather than the specific needs of endemic species within those areas. The old zonation method used is usually not based on ecological delineation but mostly relies on island physical boundaries and lacks a rehabilitation zone. In the conservation zone such as Taka Bonerate marine park, there could be a limited-use zone based on the traditional use and not on an intensive use activity. This chapter develops a new ecosystem and endemic organism-based spatial scoring to build a new spatial zonation model which is specifically dedicated to any conservation zone or a marine park that would be used for a management plan and further action plan. A spatial-based approach analysis with reliable details and adequate accuracy was needed as a guide in zonation processes for the management of coastal or marine protected area. The spatial modeling was a combination of satellite and field data analysis. This spatial modeling analysis was also called cell-based modeling based on raster/spatial data and “spatial-scoring” method that emphasized the specific ecosystem and endemic organism valuation and weight approach. This new concept and paradigm on the “specific ecosystem and endemic organism based spatial-scoring for a new spatial model” and targeted existing knowledge for a beyond “the usual-goals” for Marine Protected Area (MPA). The idea of preserving and conserving “marine living fossils” such as Nautilus pompilus in Taka Bonerate, Latimeria menadoensis in north Sulawesi waters, and Limulus sp. in Java and Kangean seawater is proposed as a “new concept of MPA-Plus.” Deep-sea vulnerable reefs and atolls and a sand dune (“bungin”) ecosystem are crucial habitats for reef fishes like the endangered Napoleon wrasse (Cheilinus undulatus), flying fish (Cypsilurus sp.), and others.