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USGS2018

AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data

In this work we describe the AutoCNet library, written in Python, to support the application of Computer Vision techniques for n-image correspondence identication in remotely sensed planetary images and subsequent bundle adjustment. The library is designed to support exploratory data analysis, algorithm and processing pipeline development, and application at scale in High Performance Computing (HPC) environments for processing large data sets and generating foundational data products. We also present a brief case study illustrating high level usage for the Apollo 15 Metric camera.

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USGS2020

OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features

The National Hydrography Dataset (NHD) is a foundational geospatial data source in the United States that enables extensive and diverse environmental research and supports decision-making in numerous contexts. However, the NHD requires regular validation and update given possible inconsistent initial collection and hydrographic changes. Furthermore, systems or tools that use NHD data must manage regular updates that occur within the high-resolution version of the NHD (NHD HR). This research contributes to filling this gap by establishing an open-source software tool named OpenCLC, which automatically identifies matching and mismatching line features between two sets of hydrographic flowlines. Aside from identifying differences among two version of NHD lines, results can be applied to improve the quality of NHD HR content. OpenCLC significantly outperforms the best available commercial off-the-shelf software in computational scalability, and it is made widely available as part of the CyberGIS Toolkit to benefit broad environmental and geospatial science communities.

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USGS2020

SurfRCaT: A tool for remote calibration of pre-existing coastal cameras to enable their use as quantitative coastal monitoring tools

The Surf-camera Remote Calibration Tool (SurfRCaT) is a Python-based software application to calibrate and rectify images from pre-existing video cameras that are operating at coastal sites in the United States. The software enables remote camera calibration and subsequent image rectification by facilitating the remote-extraction of ground control points using airborne lidar observations, and guides the user through the entire process. No programming or code interaction are necessary to use the software. Calibration parameters and subsequent rectified image products derived from the software are saved locally. Users can apply SurfRCaT to any camera imagery that has stationary structures within the camera’s field of view. Given current recreational camera infrastructure, SurfRCaT could increase the number of potential quantitative coastal video monitoring stations in the United States by an order of magnitude.

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USGS2022

CoastalImageLib: An open-source Python package for creating common coastal image products

CoastalImageLib is a Python library that produces common coastal image products intended for quantitative analysis of coastal environments. This library contains functions to georectify and merge multiple oblique camera views, produce statistical image products for a given set of images, and create subsampled pixel instruments for use in bathymetric inversion, surface current estimation, run-up calculations, and other quantitative analyses. This package intends to be an open-source broadly generalizable front end to future coastal imaging applications, ultimately expanding user accessibility to optical remote sensing of coastal environments. This package was developed and tested on data collected from the Argus Tower, a 43 m tall observation structure in Duck, North Carolina at the US Army Engineer Research and Development Center’s Field Research Facility that holds six stationary cameras which collect twice-hourly coastal image products. Thus, CoastalImageLib also contains functions designed to interface with the file storage and collection system implemented at the Argus Tower.

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USGS2023

iBluff: An open-source R package for geomorphic analysis of coastal bluffs/cliffs

The R package iBluff is designed for coastal bluffs/bluffs morphological analysis and offers an automatic and reproducible alternative to identify bluff edges using a bare earth digital elevation model (DEM) instead of hand digitizing. This package extracts elevation profiles along automatically identified transects on the bluff-face, bluff top, toe, secondary inflections, relative concavity/convexity of bluff-face, and beach dunes (crests and troughs). The package requires at a minimum a bare earth DEM as a raster and a generalized line shapefile (shoreline) approximately parallel with the bluff-face. Both files should be in the same projected coordinate system. The iBluff package was developed to expand and generalize studies of high-relief coastal areas, investigate erosion and seasonality, and could be extended to use three-dimensional (3D) point-cloud data instead of a DEM.

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