Water is the limiting factor in many ecologic systems, and changes in water regimes affect various natural resources. One critical aspect of water resources monitoring is the study of surface hydrologic processes involving ephemeral streams — their flow conveyance, sediment transport, and groundwater recharge. In arid environments, knowledge about ephemeral streams is vital for understanding the hydrologic cycle, local ecosystems, and water availability for human use. However, quantifying surface hydrologic processes is extremely challenging, because runoff events in arid landscapes are episodic, and established methods for accurately mapping ephemeral stream networks and characterizing their functionality have been lacking.
Remote sensing technologies permit spatially contiguous data collection over large areas, automated processing, and streamlined data analysis. Remote sensing has been applied to identify stream channels across various landscapes. However, previous methods were inadequate for reliably mapping ephemeral stream channels and their properties, because of the complexity of channel networks, the absence of flow, and the small topographic gradient of desert drainage systems.
By applying knowledge about desert landscapes and multispectral imagery at very high resolution, EVS scientists have developed a new algorithm for mapping ephemeral channel networks and their properties. The Argonne algorithm combines a series of spectral transformations and spatial statistical operations with expert knowledge to generate spatially explicit, spatially contiguous data that represent desert vegetation and the ground surface. From the patterns of vegetation occurrence and density, as well as surface brightness and its spatial heterogeneity, the algorithm detects stream channels, extracts channel centerlines, and calculates channel length and width.
The Argonne knowledge-based algorithm extracts well-defined single channels, complex braided streams, and small tributaries across a large heterogeneous desert landscape and generates a highly detailed map of dry stream networks and their geometry. The algorithm could contribute significantly to advancing hydrologic modeling and could facilitate the development of cost-effective monitoring strategies for water resource management in desert regions.
- Mapping Ephemeral Streams Using Aerial Very High Resolution Remote Sensing & Knowledge-Based Feature Extraction Algorithm (Poster) (346 KB)
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