These are a set of steps to produce a relevant result, whether in data processing, analysis, visualization or application of these to policies and programs. We digitized three hazard risk maps - flood, drought and landslide risk for Semarang study area. The original risk images we used to digitize were derived from Indonesian National Agency for Disaster Management (BNPB) in jpg format. Firstly, we used georeferencing to adjust the disaster images to the correct spatial location, and defined the spatial reference to these images. Here we selected projection WGS_1984_UTM_Zone_49S where the study area is located. Next, based on the existing risk images, we visually evaluated the risk levels and defined the boundaries with the similar level. Finally, we manually drew each risk polygon using a “freehand” tool on a new blank shp files. The original risk images are based on continues data ranking from 0 - 1. When we digitized the maps, we drew the risk polygons and assigned a risk level to each polygon. To be more specific, we divided the flood risk into 1 - 5 levels, and drought risk into 1- 7 levels, indicating from low to high risks. For landslide risk, we focused only on the areas faced highest landslide risk. Therefore, unlike the original continuous data across the whole area, the outputs are vector data maps illustrating risk levels using categorical numbers. By integrating the areas with similar risk values into the same level, we averaged out the detailed risk variance in each polygon. 1. In Arcmap, open the two files: one is the polygons of study area (shp file), the other is the risk image (Jpg file) which need to be adjusted to the correct location, 4. Set Projected Coordinate System and Geographic Coordinate System in the Data frame properties. We selected UTM zone 49S, where Semarang is located: 6. Update display. Now the risk image has been projected to the correct location, and overlays nicely on the study area, Source.

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Last Modified: April 23, 2016 @ 7:03 am