Remote sensing technology can provide spatial information for mapping shallow water benthic habitat, a case study conducted on Sebaru Besar Island. The purpose of this study was to analyze mapping accuracy of shallow water benthic habitats usings WorldView 2 and SPOT 6 (201 imageries). The classification of multispectral images is carried out using the Depth Invariant Index (DII) transformation and by applying the Maximum Likelihood (MLH) algorithm to both satellite images. The number of benthic habitat classes produced are eight habitat classes from each image used. The results of the analysis show that the overall accuracy in Worldview 2 and SPOT 6 images is 61.29% and 51.61%. Results of Z-statistic comparison between Worldview-2 and SPOT-6 imagery was 1,04, means that the results did not differ significantly.

This study was conducted to analyze the changes in mangrove area and the density level of mangrove based on satellite imagery and field surveys in Untung Jawa Island. The image data used was Landsat image data acquired in 2000, 2005, 2010, 2015 and 2019. Apart from those, sentinel-2 data received in April 2019 were also retrieved to be compared with field data to see the density level and its accuracy. Image analysis to determine the area and density of mangroves was the Normalized Difference Vegetation Index (NDVI) model. Measurement of mangrove vegetation in the field was obtained by the line plot transect method. The results of temporal image data analysis showed the changes in mangrove area from 2000 (8.46 ha), 2005 (7.56 ha), 2010 (8.45 ha), 2015 (10.65 ha) and 2019 (6.89 ha). In 2019 the mangrove density was dense, while the result of the field survey was categorized as very dense. The level of accuracy for density using remote sensing data is 92.5%. Through the results of the field survey, the mangrove diversity was relatively low, mangrove species on the island was very uneven, and the dominant species was Rhizophora mucronata.

Research on the distribution of fish and plankton in waters that are equipped with environmental parameters is needed to obtain maximum results and increase accuracy also it provides comprehensive information. The research, which was conducted in Humbold Bay, aimed to map the fish and plankton distribution data both vertically and horizontally and combine it with environmental parameters in the bay. Fish and plankton’s data was the volume backscattering strength (Sv) value obtained using the SIMRAD EK-15 device while environmental parameter data, such as temperature, salinity, and chlorophyll obtained from marine.copernicus.eu which processed in the 5-80 m depth range. The results showed that Humbold Bay had the highest average surface temperature distribution was 30 °C, with the highest average salinity from 35.89 ppt and the highest average chlorophyll value from 0.3859 mg/m3. The horizontal distribution of plankton had an average SV value of -76.63 dB, while the fish was -56.00 dB that evenly distributed. Vertically, the Sv of plankton decreased with increasing depth as well as the Sv of fish which its’ also did not have a distribution pattern in certain environmental parameters.

This study was conducted to observe the dynamic of shoreline changes in Sangsit Region, Bali Province using multi-temporal remote sensing datasets. The remote sensing data were acquired from several Landsat images in the period of 2000-2019 (20 years) with 30-meter spatial resolution. Digital Shoreline Analysis System (DSAS) method was used to analyse data images to determine the shoreline changes. Prior to the analysis, the images were corrected by ground check data. It revealed that the shoreline changes has occur in Sangsit Region for period of 20 years (2000-2019). The results obtained indicate that there is a change in shoreline with mild accretion to less extreme abrasion categories which occurred in the Sangsit Region in that period. From 2000-2005 it shows an accretion of 221.03 m which is categorized as mild accretion and from 2005-2019 the shoreline changes that occur is only an abrasion its categorized as mild to less extreme abrasion. The highest abrasion occurred in the period of 2010-2015 which the abrasion is around 49.65 m.

Penimbangan beach is one of the tourist destinations located in Buleleng Regency, Bali Province, Indonesia. This beach is also a nesting place for one of the sea turtle species in Indonesia, which is olive ridley (Lepidochelys olivacea). The problem that exists on the island of Bali today is most of the land in coastal areas were experienced land degradation. This land degradation occurs due to human activities or natural factors, it harms the turtle nesting habitat around the coastal area of Bali Island. Conservation of nesting turtle habitat is needed through spatial analysis using Geographic Information Systems (GIS). This study uses the parameters of sand particle, beach slope, width beach, humidity, and temperature parameter to determine the suitability of the turtle nesting habitat. Penimbangan beach area which is very suitable for turtle nesting locations has an area of 163,45 m2, suitable for laying eggs 4.886,44 m2, and not suitable for laying eggs 10.201,64 m2. The map of the suitability for laying turtle eggs is dominated by areas that are not suitable because the width of the beach is not too long and the humidity is still relatively high.