Visual analytics for governance and informed decision making: an overview for land use land cover change management - Affendey, Lilly Suriani; Mustapha, Norwati; Ishak, Iskandar; Sidi, Fatimah; Hamdan, Nurul Hayat (Database Technologies and Applications Research Group (DbTA), Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 2019)
Governance describes the structures and decision-making processes that allow an organization or group of people to conduct affairs. A municipal government generally is one that provides basic city-type services to a local community, and one of the services is land use planning. Keeping track of the Land use and land cover (LULC) change information is important for planning and management activities as well as for monitoring. However, time-base geospatial data results in difficulties for analysis. Traditional static imagery can assist in analysis however the resulting visualizations are often highly specific to a particular data question and must be rebuilt to answer new questions. A solution to this problem is the creation of dynamic interfaces that use time as a mapping for the temporal component of the data. These kinds of visualizations are particularly important when the data is geospatial as well as time-dependent, since effective static visualizations of such multidimensional data are difficult to create. Visual analytics can facilitates the analysis of geospatial data on LULC changes over a period of time. Such analysis may help highlight the complexity of LULC interactions, provide better ways to communicate complex insights so that decision makers can quickly absorb the meaning of the data and take action. Various sources need to be exploited in order to assemble the LULC data which include publicly available national and international statistics and databases, land cover classification information, historical satellite imagery, and aerial photographs. Interactive visualization strategies are recommended since interaction strategies support further scalability and complexity of visual information. Using advanced visual interfaces, users may directly interact with the data analysis capabilities of the visual analytics application, allowing them to make well-informed decisions in complex situations.