Changes in climate and land use land cover (LULC) are important factors that affect water yield (WY). This study explores which factors have more significant impact on changes in WY, spatially and temporally, within the Citarum River Basin Unit (RBU), West Java Province, Indonesia with an area of ±11.317 km². The climate in the area of Citarum RBU belongs to the Am climate type, which is characterized by the presence of one or more dry months. The objectives of the study were: (1) To estimate a water yield model using integrated valuation of ecosystem services and tradeoffs (InVEST), and (2) to test the sensitivity of water yield (WY) to changes in climate variables (rainfall and evapotranspiration) and in LULC. The integration of remote sensing (RS), geographic information system (GIS), and the integrated valuation of ecosystem services and tradeoffs (InVEST) approach were used in this study. InVEST is a suite of models used to map and value the goods and services from nature that sustain and fulfill human life. The parameters used for determining the WY are LULC, precipitation, average annual potential evapotranspiration, soil depth, and plant available water content (PAWC). The results showed that the WY within the territory of Citarum RBU was 12.17 billion m3/year, with mean WY (MWY) of 935.26 mm/year. The results also show that the magnitude of MWY in Citarum RBU is lower than the results obtained in Lake Rawa Pening Catchment Areas, Semarang Regency and Salatiga City, Central Java (1.137 mm/year) and in the Patuha Mountain region, Bandung Regency, West Java (2.163 mm/year), which have the same climatic conditions. The WY volume decreased from 2006, to 2012, and 2018. Based on the results of the simulation, climatic parameters played a major role affecting WY compared to changes in LULC in the Citarum RBU. This model also shows that the effect of changes in rainfall (14.06–27.53%) is more dominant followed by the effect of evapotranspiration (10.97–23.86%) and LULC (10.29–12.96%). The InVEST model is very effective and robust for estimating WY in Citarum RBU, which was indicated by high coefficient of determination (R²) 0.9942 and the RSME value of 0.70.

With 25% confirmed cases of the country’s total number of coronavirus disease 2019 (COVID-19) on 31 January 2021, Jakarta has the highest confirmed cases of in Indonesia. The city holds a significant role as the centre of government and national economic activity for which pandemic have had a huge impact. Spatiotemporal analysis was employed to identify the current condition of disease transmission and to provide comprehensive information on the COVID-19 outbreak in Jakarta. We applied space-time analysis to visualise the pattern of COVID-19 hotspots in each time series. We also mapped area capacity of the referral hospitals covering the entire area of Jakarta to understand the hospital service range. This research was conducted in 4 stages: i) disease mapping; ii) spatial autocorrelation analysis; iii) space-time pattern analysis; and iv) areal capacity mapping. The analysis resulted in 144 sub-districts categorised as high vulnerability. Autocorrelation studies by Moran’s I identified cluster patterns and the emerging hotspot results indicated successful interventions as the number of hotspots fell in the first period of social restrictions. The results presented should be beneficial for policy makers.

Semarang City is one of the most influential coastal cities in Java Island. The city is facing increasingly-high water demand due to its development and water problems due to climate change. The spatial physiography and landscape of Semarang City are also exposed the city to water security problem. Hence, rainwater harvesting treatment is an urgent effort to meet the city's water needs. However, planning, implementation and management of rainwater harvesting are highly depended on multitemporal rainfall data. It has not yet been fully compiled due to limited rain stations. This study aims to examine the extent to which CHIRPS satellite data can be utilized in estimating volume of rainwater harvesting 16 sub-districts in Semarang and determine the water security status. This study uses descriptive statistical method based on spatial analyses. Such method was developed through spatial modeling for rainfall using isohyetal model. The parameters used are rainfall, residential rooftop area, administrative area, population, physiographic and altitude units. Validation is carried out by using monthly 10 rain stations data. The results show level of validity by utilizing CHIRPS Satellite data and mapping rainfall distribution. This study also produces a potential map of distribution rainfall volume that can be harvested in 16 sub-districts of Semarang.

Low carbon development has become a trendsetter in this millennial era. The social and economic factors of the community are commonly used variables in assessing linear functions of the level of social welfare. The level of social welfare is then thought to be one of the main drivers of anthropogenic pressure on the environment. We examine the extent to which social and economic aspects of capture fisheries activities influence the dynamics of CO₂ emissions generated from capture fisheries activities in all coastal areas in West Java Province during the 2007-2016 period. Based on the results of geographic information system and statistical analysis, we find that the increasing economic factor can reduce the ghg emission while the increasing of social factor on the contrary can increase the ghg emission. The GIS analysis also show that the level of CO₂ emissions was found to be lower in districts that had relatively high levels of social index. It is estimated, the higher level of education and social welfare has a real positive correlation with increasing public awareness in conducting fishing activities that are environmentally friendly and carbon friendly.

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.

Natural disasters that often occur in coastal areas are tidal floods and river floods. Flood vulnerability management of coastal areas has become increasingly important to mitigate and prevent floods. The purpose of the study was to analyze the socio-economic vulnerability of the Mataram City coast. The spatial-DPSIR approach was employed to study the socio-economic and ecological framework. The socio-economic vulnerability was analyzed using the following parameters: population density, poverty level, livelihoods, land ownership, awareness of disasters, the presence of business areas and trade areas, and physical damage to buildings. The analysis result of the coastal flood socio-economic vulnerability showed that most of the Mataram coast were classified as intermediate. The results of this study are expected to become a reference for development and management, especially in spatial planning policies for a disaster-secure coastal area.