Multi-temporal remote sensing channel mapping

Knowledge graph centered on Multi-temporal remote sensing channel mapping with 24 nodes and 84 connections. Top connected: Gothic, Crested Butte, Salix lucida subsp. lasiandra, Bacteria, East River.

Method synopsis

Integration of historical aerial photography, LiDAR data, and multispectral imagery to track channel migration and identify abandoned floodplain features using automated classification in eCognition software.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — From Grain to Floodplain: Evaluating heterogeneity of floodplain hydrostatigraphy using sedimentology, geophysics, and remote sensing. (2019), Earth Surface Processes and Landforms. Implementations in other papers (listed below) may differ.

1. Acquire historical aerial photography
   Collected historical aerial photography from U.S. Geological Survey, U.S. Department of Agriculture Forest Service, National Agricultural Imagery Project (NAIP), and historical aerial photographs of floodplain dating back to 1955. Images showed differences in NDVI and acute disparities in elevation captured in LiDAR data.
   Quantities: Historical photographs spanning 1955-2015 timeframeDuration: Data collection covered 60-year period from 1955-2015Conditions: Various historical aerial photography missions
   Equipment: archival aerial photographs from multiple agencies
2. Process multispectral imagery
   Used WorldView-2 (WV-2) 8-band multispectral data collected in 2015 to calculate Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). NDVI calculated as ratio of difference between near-infrared and red wavelength bands and sum of wavelengths. Used eCognition software by Trimble to classify regions likely occupied by former channels using vegetation signatures and physical indicators including NDVI signatures, presence of ponded water, proximity to current river channel, and elevation relative to surrounding floodplain.
   Quantities: WorldView-2 8-band multispectral imagery from 2015. Multiple spectral indices calculated.Duration: 2015 imagery acquisition and subsequent processingConditions: Clear atmospheric conditions for multispectral imaging
   WorldView-2 satellite imagery, eCognition software by Trimble

Typical Equipment

• WorldView-2 satellite imagery
• eCognition software by Trimble
• archival aerial photographs

Output Measurements

• channel migration rates
• abandoned channel locations
• NDVI time series
• elevation differences

Papers Using This Protocol (1)

Species Studied With This Protocol

Places Where Used