The drivers for coastal flooding may vary from extremely high intensity and persistent rainfall, morphological factors of the coastal area, to extreme waves from the ocean. This means that the flood vulnerability of a coastal area does not solely depend on a single driver but can be a combination with others. A national standard for coastal flooding based on rainfall drivers has been developed. As an evaluation, this study aimed to develop a method for coastal flood-prone mapping by combining rainfall with tidal waves. The steps included the assessment of the coastal flood-prone areas driven by rainfall (CFR) and the coastal flood-prone areas by combined drivers (CFC), which was developed by employing the analytic hierarchy process (AHP), spatial-overlaid, weighted-scored, and logical tests. The coastal area of Mataram City on the Island of Lombok in Indonesia was selected as the study area, since it is frequently affected by flooding. The findings determined the essentiality of the CFC method for identifying flood vulnerability areas. Thus, the minimum standard for CFC parameters can be defined with climatic and land characteristic factors. Further, the findings also identified the need for expert judgment in the development of the CFC weighted score-based method.

Balancing water supply demand is vital for sustaining livelihoods. Spatial mapping and calculating water yield dynamics due to land use changes over decades are needed to manage land resources and formulate ecological protection policies. This study mapped the supply, demand, and matching status of water product service using the Integrated Valuation of Ecosystem Service and Tradeoff (InVEST) biophysical models in the Citarum Watershed (CW) in 2000, 2010, and 2020. Moreover, this study used Exploratory Spatial Data Analysis (ESDA) and Geographic Information System (GIS) techniques to study the agglomeration characteristics and evolutionary trajectories of supply–demand over two decades. The results showed that between 2000–2010 and 2010–2020, the water supply decreased by 19.01 × 10⁸ m³ (18.28%) and 12.97 × 10⁸ m³ (15.27%), respectively. However, the water demand in the same period increased by 6.17 × 10⁸ m³ (23%) and 15.74 × 10⁸ m³ (47%), respectively. Over the decades, the contribution of land use land cover (LULC) changes to variations in water supply has yielded values ranging from 2.87% to 6.37%. The analysis of the water supply–demand imbalance indicated that the entire CW experienced water shortage, and the type of spatial matching for supply and demand is dominated by a high supply and high demand class (16.09% of the total area). Based on the level of water deficit calculation, the upstream and downstream areas were identified as zones that require ecological conservation, while the middle CW area requires ecological restoration or ecological improvement.

Sustainable coastal management is playing an important role in coastal resources conservation, particularly on small islands. Karimata archipelago has unique characteristics and great potential to be developed as a tourism object, one of which is Karimata Island as the largest island and also reserve area. The concept of ecotourism focuses on the ecology conservation, economic benefits, and social life. Ecotourism aims to build sustainable tourism that provides economically viable and social benefits to the community. This study aims to develop coastal management strategy based on ecotourism at Karimata Island. Spatial approaching through coastal type was done. Qualitative descriptive analysis and SWOT are used to develop sustainable management strategies for the coast of Karimata Island, where the opportunities and challenges to the development of coastal ecotourism Karimata Island also included. If this potential is optimally utilized, it can be relied as an economic opportunity for local communities. Structurally shaped coast, marine depositional coast and coast build by organism are several of coastal types found at Karimata Island. Coastal ecosystems inhabited Karimata Island are mangroves, coral reefs, and macro-algae. Karimata Island have not been optimally utilized for tourist destinations. The biggest obstacle encountered is the accessibility from Kalimantan or other island at Karimata islands. Several problems related to the utilization of coastal resources were found such as mangrove and coral reef damage, also regulation that less supportive. The results of this study are expected to provide an overview of solutions for the development of coastal tourism potentials in Karimata Island.

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.

Numerous approaches for deriving benthic habitat mapping from visible spectrums of remotely-sensed imagery have been widely used, but image classification without training data for remote benthic habitat remains a few. In many cases, the collection of the needed ground-truth data is often prohibitively expensive or logistically infeasible. This will prevent us from providing training data for image classification purposes. In this paper, we evaluated the accuracy of the classification of benthic habitat from Sentinel 2A imagery in an absence of training data in the optically shallow water of Pari Island, Kepulauan Seribu, Indonesia. Benthic Habitat map was produced from geometrically, radiometrically, and water column corrected Sentinel 2A images. For water column correction, we performed Depth Invariant Index (DII) transformation. It was followed by the classification of Sentinel 2A imagery by applying unsupervised classification, such as IsoData and K-means algorithm. From the experiment, we produced four habitat classes. The analyses result for each unsupervised classification shows that the overall accuracy of IsoData and K-Means was 47.98% and 55.64%. However, the results of the Kappa coefficient show that the IsoData algorithm has slightly better accuracy of benthic habitat mapping (0.39) rather than K-Means (0.30).

The availability of updated and easy access to geospatial data and information is the main thing in disaster mitigation and sustainable spatial planning. This needs to be supported by the rapid development of technology in the aspect of spreading data and spatial information via the internet. The Spatial Data Infrastructure (SDI) is realized as an implementation of spatial data distribution. SDI is an integrated mechanism to make it easier for spatial data users to access, search, share, and use spatial data and information. Built upon the background statements, the research does intend to develop a web-app which is functioned as a data repository, viewer, and also simple processing (web GIS). To design and develop a disaster geospatial online application web-app that has an integrated function (repository-web GIS) following the directions and input from user feedback becomes the fold of the research. . The importance of putting the user needs in building a web-app to be used by anyone universally is more realistic and practical. The user interface is very essential in bridging communication between users and web mapping systems. User-centred design (UCD) implemented by gathering input and feedback from users. UCD describes the process of ensuring interface success throughout the design and development of the interface. GeoNode has chosen as the platform since it is open-sourced, and commonly used for managing and publishing geospatial data. Based on respondents' assessment of the quality of content/information that important to be developed in a disaster website, it is recognized that providing reliable and up-to-date data and information (69%) and the accuracy of data and information (74%) are the most important things to develop in the InDITA application. the most important features to respondents are the spatial data display feature/map viewer (89%). The design of InDITA was built interactive and user-friendly which designed as an application that accommodates simple viewer, data repository, and web GIS functions. The interactive design emerged as the demand for app users.