Authors: Michael P. Bishop*, Texas A & M University, Brennan W. Young, Texas A & M University, Da Huo, Texas A & M University
Topics: Geomorphology, Geographic Information Science and Systems, Remote Sensing
Keywords: DEM, Geomorphometry, Landform Mapping, Spatial Analysis, Spatial Concepts
Session Type: Paper
Presentation File: No File Uploaded
Advances in remote sensing technologies and geospatial data science provide new opportunities to study landforms, surface processes and system couplings through the use of high-resolution digital elevation models and innovative spatial analysis and modeling approaches. Nevertheless, this requires accurate quantitative characterization of topography and landform properties, and an ability to utilize the concept of process-form relationships as a basis for diagnostic landform and process-regime mapping. Such capabilities are notoriously difficult to accomplish due to issues associated with mathematical formalization of key concepts such as scale, anisotropy, semantic modeling, indeterminate boundaries, mass distribution and spatial topology among others. Addressing these issues requires concept formalization through semantic modeling and the development of geospatial analysis solutions. Consequently, we address various concepts and issues that are required to advance geomorphometric characterization of landforms, and examine the topography from a systems perspective to permit diagnostic landform and process-regime mapping. Specifically, we provide analytical examples of concept formalization that provide insight into the processes that are responsible for landform formation and evolution. Examples include glacier characterization and mapping that permit evaluation of glacier state and ablation dynamics, and fully automated sand dune characterization and mapping using various spatial analysis approaches. Collectively our results demonstrate the importance of formalizing spatial concepts and addressing the multi-faceted concept of uncertainty.