Forest Fire Spatio-Temporal Data Warehouse using GeoMondrian and GeoServer

Abstract

Indonesia is a country that has tremendous wealth of forests in the world. But Indonesia's forests decreases each year by deforestation amounted to 1.87 million hectares (FAO 2007). One of the main causes of deforestation in Indonesia is forest fires. Catastrophic forest fires cause major problems and need complex ways to overcome. One form of forest fire prevention is monitoring hotspots using the National Oceanic and Atmospheric Administration (NOAA) satellites. This satellite imagery capturing the form of hotspots, which could indicate the existence of forest fires based on location and time. Data obtained from these satellites have particularly large amount, causing the accumulation of data hotspot. This can be overcome by the presence spatio-temporal data warehouse technology with Spatial Online Analytical Processing (SOLAP) applications. Spatio-temporal data warehouse capabilities in integrating data into a quick and comprehensive information to assist decision-making process in terms of controlling forest fires. This study developed a geographic information system that integrates data warehousing applications spatio-temporaly with Spatial On-Line Analytical Processing (SOLAP) application using the framework Geomondrian and Geoserver as a web map server. Pre-process data such as data extraction, data transformation and loading of data, performed before the data warehouse is built in accordance with the dimensional data model (the concept of design in building a data warehouse) and integrated with Geoserver that handles the presentation of data in map form. The system was developed to visualize data of forest fires in the form of pivot tables, graphs and maps spread of hotspots in a web-based environment, so the system can support decision-making in an effort to control forest fire in Indonesia.