| Abstrak/Abstract |
In recent years, geolocation data sets have become more abundant concerning human movement and quantitatively studied individual and collective / population mobility patterns. The study of human mobility is essential for applications such as estimating migration flows, traffic forecasting, urban planning, and epidemic modelling. This study examines location data from mobile phones and other geographic big data sources such as data from geoportal, open/shared data, and global data to understand the spatiotemporal patterns of people's mobility Covid-19 pandemic in coastal wetlands. Coastal wetlands have important functions and benefits in the ecosystem. They must be conserved because they are the most productive ecosystem environment globally and provide habitat for various biodiversity (flora and fauna), including cleaning water and storing germplasm. Spatiotemporal mobility patterns of people in coastal wetlands are understood by analyzing the geolocation data population of cellular phones, clustering using DBSCAN, Kernel Density Estimation (KDE), and Space-Time Pattern Mining (Hot and Cold Spot Analysis). People's mobility pattern is also understood during weekdays, weekends, day, and night, so that the patterns of collective mobility/population of coastal wetlands can be understood spatially and temporally. |
