Rapid-DEM: Rapid Topographic Updates through Satellite Change Detection and UAS Data Fusion

As rapid urbanization occurs in cities worldwide, the importance of maintaining updated digital elevation models (DEM) will continue to increase. However, due cost generating high-resolution DEM over large spatial extents, temporal resolution DEMs is coarse many regions. Low-cost unmanned aerial vehicles (UAS) and data fusion provide a partial solution improving but do not identify which areas require updates. We present Rapid-DEM, framework that identifies prioritizes locations with high likelihood an urban topographic change target UAS acquisition up-to-date DEM. The uses PlanetScope 3 m satellite imagery, Google Earth Engine, OpenStreetMap for land cover classification. GRASS GIS generates contextualized priority queue from outputs polygons flight planning. fly identified areas, WebODM survey data. fused existing uploaded public repository. To demonstrate Rapid-DEM case study Walnut Creek Watershed Wake County, North Carolina presented. Two classification were generated using random forests overall accuracy 89% (kappa 0.86) 91% 0.88). 109 representing 1.5% area watershed. Large forest clearings highest locations, followed by newly constructed buildings. site was 0.5 km2 clearing mapped UAS, 15 cm resampled USGS NED 1/9 arc-second Surface water flow simulated original illustrate impact on patterns highlight timely