Automated Author ProfileAlexandra D Evans
United States Geological Survey
Alexandra D Evans
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.3 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The purpose of this field data collection was to test and compare the OceanInsight HDX Mini Spectrometer as an accessible alternative against the more expensive ASD Fieldspec for collecting ground-based hyperspectral reflectance profiles for landcover analysis. The data collection took place in Dog Head Marsh and South Cape Beach within the Waquoit Bay National Estuarine Research Reserve (WBNERR). The hyperspectral profiles were collected side-by-side with both field-spectrometers using comparable sensor collection settings for various ground cover samples. The terrain and vegetation type of these sample were described as well as surveyed using Real Time Kinematic Global Positioning System. This data was collected within a 4-hour window around solar noon on October 7th, 2021. Low altitude (82 m above ground level) true-color and multispectral aerial images were collected over the marsh within the same 4-hour window surrounding solar noon to generate photogrammetric products (e.g. digital surface model (DSM), true-color and multispectral reflectance orthomosaics) for further comparison and application with the ground hyperspectral reflectance data, particularly for mapping the invasive marsh reed Phragmites australis. A 3DR SOLO uncrewed aircraft system was equipped in succession with a Ricoh GRII true-color RGB camera and a MicaSense Rededge-3 multispectral camera to collect images with sufficient overlap for photogrammetric processing. Ground control points (GCPs), black and white targets visible in the imagery, were deployed prior to imagery collection to improve the horizontal and vertical accuracy of the DEM, orthomosaic, and reflectance products. GCP locations are recorded using wifi-enabled or survey-collected RTK-GPS information. An additional landcover survey was conducted on October 8th, 2021 to record terrain and vegetation type and RTK-GPS position for randomly selected points throughout the field area to provide a ground-reference dataset for training and validation for machine learning imagery analysis. This data release includes the following data: (1) original images from the Ricoh GRII and MicaSense Rededge-3 cameras as well as (2) the GCPs needed to produce accurate photogrammetry products, (3) ground-reference data, (4) spectral reflectance profiles including GPS locations, and (5) topographic and reflectance products, including DSMs from both imagery datasets, a true-color orthomosaic and a multispectral reflectance orthomosaic.
Authors
- Jennifer M Cramer ;
- Victoria M Scholl ;
- Alexandra D Evans ;
- Seth Ackerman ;
- Elizabeth P Pendleton ;
- Sandra M Brosnahan ;
- Sydney K Nick ;
- Allyson A Boggess