Dasymetric Mapping of 2016 Population of Washington, D.C. Using Hyperspectral Imagery

Keywords: dasymetric, hyperspectral, population
Session Type: Virtual Poster
Day: Saturday
Session Start / End Time: 4/10/2021 03:05 PM (Pacific Time (US & Canada)) - 4/10/2021 04:20 PM (Pacific Time (US & Canada))
Room: Virtual 52

Abstract

Dasymetric mapping has been utilized since the early nineteenth century for thematic cartography. As one of the most popular methods of thematic cartography, Choropleth mapping is often used to map to display statistical data, like demographic information. Compared to choropleth mapping, dasymetric mapping is a more accurate representation for displaying population data (Holt et al. 2004). This project aimed to use dasymetric mapping methods to display the 2016 population of Washington, DC using a very high-resolution hyperspectral sensor. The sensor, E0-1 Hyperion, collects 220 unique spectral channels ranging from 0.357 to 2.576 micrometers with a 10-nm bandwidth. ENVI was used to classify the hyperspectral image of the study area using the Spectral Angle Mapper (SAM) classification method. ArcGIS was utilized to overlay the classification with census data to model the distribution of the data. The overall classification accuracy was 83.08%.