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Applications of Google Earth Engine in fluvial geomorphology for detecting river channel change

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Abstract Cloud‐based computing, access to big geospatial data, and virtualization, whereby users are freed from computational hardware and data management logistics, could revolutionize remote sensing applications in fluvial geomorphology. Analysis of multitemporal, multispectral satellite imagery has provided fundamental geomorphic insight into the planimetric form and dynamics of large river systems, but information derived from these applications has largely been used to test existing concepts in fluvial geomorphology, rather than for generating new concepts or theories. Traditional approaches (i.e., desktop computing) have restricted the spatial scales and temporal resolutions of planimetric river channel change analyses. Google Earth Engine (GEE), a cloud‐based computing platform for planetary‐scale geospatial analyses, offers the opportunity to relieve these spatiotemporal restrictions. We summarize the big geospatial data flows available to fluvial geomorphologists within the GEE data catalog, focus on approaches to look beyond mapping wet channel extents and instead map the wider riverscape (i.e., water, sediment, vegetation) and its dynamics, and explore the unprecedented spatiotemporal scales over which GEE analyses can be applied. We share a demonstration workflow to extract active river channel masks from a section of the Cagayan River (Luzon, Philippines) then quantify centerline migration rates from multitemporal data. By enabling fluvial geomorphologists to take their algorithms to petabytes worth of data, GEE is transformative in enabling deterministic science at scales defined by the user and determined by the phenomena of interest. Equally as important, GEE offers a mechanism for promoting a cultural shift toward open science, through the democratization of access and sharing of reproducible code. This article is categorized under: Science of Water
Example of three available Google Earth Engine (GEE) data catalog products for the Cagayan‐Ilagan River confluence (Luzon, Philippines; 17°11′37.4″N, 121°52′32.2″E), all acquired within ±4 days in February 2019: (a) false‐color Landsat 8 imagery (bands B6, B5, B4), (b) false‐color Sentinel‐2 imagery (bands B11, B8, B4), and (c) Sentinel‐1 SAR ground range detected (GRD): C‐band (VV polarization). Flow direction is from south to north
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Active channel centerline change for the Cagayan River near Iguig (Luzon, Philippines—17°44′17.3″N, 121°42′51.2″E). Spatially heterogenous shifts in the active channel centerline are shown, with meander expansion (erosion and accretion) and cutoff processes recorded. Base map is an annual temporal composite (2019–2020) using Sentinel‐2 imagery (bands B11, B8, B4)
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Visual workflow example for extracting the active channel from a series of Landsat satellite images in Google Earth Engine. Region of interest (ROI) refers to the region of interest. Time filter was set to January 01, 2019 to January 01, 2020. Wetted channel classification followed Zou et al. (2018), alluvial deposits were classified using a relational operator where modified normalized difference water index (MNDWI) ≥ −0.4 and normalized difference vegetation index (NDVI) ≤0.2
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Spatial–temporal domain trajectories of remotely sensed data typically used in fluvial geomorphology applications. The trajectories are plotted along the conjectural division of characteristic spatiotemporal domains of four modes of theory construction suggested by Church (1996). Analysis scale refers to the typical scale of analysis achievable. Pixel scale refers to the nominal characteristics of a single pixel. Dashed blue box indicates the typical spatiotemporal domain for GEE analyses. Analysis scale abbreviations: AA1, aerial photography (5‐year temporal resolution, 100 km coverage); HA1, historical maps (25‐year temporal resolution, 250 km coverage); LA1, Landsat 8 (10‐year temporal resolution, 175 km coverage); LA2, Landsat 8 (1‐year temporal resolution, 175 km coverage); LA3, Landsat 8 (16‐day temporal resolution, 175 km coverage); LA4, Landsat 8 (16‐day temporal resolution, >1,500 km coverage); SA1, Sentinel‐2 (1‐year temporal resolution, 100 km coverage); SA2, Sentinel‐2 (10‐day temporal resolution, 100 km coverage); SA3, Sentinel‐2 (10‐day temporal resolution, >500 km coverage). Pixel scale abbreviations: AP1, aerial photography (20 m spatial resolution); HP1, historical maps (100 m spatial resolution); LP1–LP3, Landsat 8 (30 m spatial resolution), SP1–SP2, Sentinel‐2 (10 m spatial resolution)
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Sensitivity of planimetric interpretations with changes in river stage for the Abra River (Luzon, Philippines). False‐color Sentinel‐2 imagery (bands B11, B8, B4) acquired January 06, 2018 (dry season) and September 18, 2018 (wet season) for the Abra River between (a) Bucay and Carsuan (17°36′22.9″N, 120°40′12.1″E) and (b) Luba and Bucay (17°26′35.0″N, 120°42′47.3″E). Flow direction is east to west in (a) and south to north in (b)
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