by Amy Kracker Selzer, College of William and Mary
Building on Sainan's "Digitize a JPG Picture" post below, this post discusses the creation of a village-level risk hazard index. In her post, Sainan described a process for creating polygons that show risk for exposure to flooding, drought, and landslides. In addition to having an overall assessment of the geography of risk, we also wanted to know more about the demographics of those communities exposed to certain levels of risk. Specifically, we wanted to better understand the levels of vulnerability ofcommunities. Those communities with a high proportion of impermanent dwellings, a reliance on an agricultural economy, and a high population density are likely to be more vulnerable to these risks. Additionally, the capacity of communities to adapt to the consequences of these hazards is correlated to characteristics such as income, education, and migration status. Because of these relationships between population dynamics and environmental hazards, we wanted to compare the geography of risk to the spatial distribution of population characteristics. The demographic information we used comes from village-level data from the Indonesian census.
To examine the relationship between levels of risk and demographic characteristics, we needed to calculate village-level measurements of risk from the hazard polygons Sainan had created. Because of the shape of the hazard files, there were some areas that had no risk values because they were not in risk zones. The first thing I did was assign those areas the lowest value of 1. Also, because the scales used for each risk factor (landslide, flood, and drought) were different, I rescaled each hazard to a 1-7 risk scale to allow greater comparability. I then converted these polygons to raster files. Each of these raster files was then overlaid on a polygon file containing the village boundaries within the study area of Semarang, Indonesia. The average level of risk for each type of hazard was then calculated for each village using zonal statistics. Finally, an overall risk index was calculated by overlaying each of the three hazard raster layers (landslide, flood, and drought) and summing risk values across the layers. Based on the resulting values, an indexed average risk value was again calculated for each village using zonal statistics.
Below is an image of the distribution of the overall risk index in the study area.
/methods/upload_files?prefix=20171213075816/components/com_communityanswers/assets/uploader/plupload.flash.swf/components/com_communityanswers/assets/uploader/plupload.silverlight.xappdf,doc,docx,xls,xlsx,odt,rtf,txt,odf,csv,dbf,odp,uop,pptx,ppt,pps,ppsx,eps,gif,jpg,jpeg,jpe,png,ps,svg,tif,tiff,bmp,cdfClick here/methods/verify_captchaContribute Your ResponseCancelYesNoError!ConfirmSuccess!Click here/methods/subscribe_qn/36-creating-a-village-risk-hazard-index/methods/unsubscribe_qn/36-creating-a-village-risk-hazard-indexYou have successfully subscribed to this topic. You should now receive emails when new respones are posted.You have successfully unsubscribed to this topic.Subscribe To TopicUnsubscribe From Topic/methods/get_answerReport ThisSubmitInformation!