An inventory of topographic surface changes: the value of multi-temporal elevation data for change analysis and monitoring
- U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, USA
Keywords: DEM/DTM, Geomorphology, Change Detection, SAR, Multitemporal, Monitoring, Accuracy, Error
Abstract. Landscape change resulting from human activities continues to be a primary topic in geographic research. Many studies have focused upon human-induced changes in two dimensions, namely in land cover. However, those changes may include a corresponding transformation of the third dimension, or vertical component, of the landscape as expressed in the local surface topography. Some previous studies have estimated the total effects of human activity on the landforms and shape of the Earth’s surface, but these studies have not emphasized the spatial component of the changes. The primary issue addressed by the research reported here is the need for more comprehensive information on the nature and extent of recent human geomorphic activity. The elevation information from the Shuttle Radar Topography Mission (SRTM) paired with the historical topographic data in the U.S. Geological Survey's National Elevation Dataset (NED) allow for mapping and assessment of significant changes to the shape of the land surface across the conterminous United States. The NED supplied the historical elevation information that was subtracted from the more recently collected SRTM data to create an elevation difference grid that provided information about where topographic changes have taken place. The elevation difference information was filtered and refined to complete a national inventory of vertical landscape changes, and it represents a first ever accounting of topographic change across the United States. The inventory serves as a useful foundation for ongoing monitoring of topographic changes using recently collected high-resolution elevation data, including current work with airborne interferometric synthetic aperture radar data.