skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Multispectral and RGB Uncrewed Aerial Vehicle imagery for several sites in interior Alaska in 2024
### Access Dataset can be accessed and downloaded from the directory via: [http://arcticdata.io/data/10.18739/A2736M42V](http://arcticdata.io/data/10.18739/A2736M42V). ### Overview This data set includes imagery collected using Uncrewed Aerial Vehicles (UAV, i.e. drones) for a series of research sites in interior Alaska with the objective of mapping the distribution of individual plants (e.g. Eriophorum vaginatum tussocks) and other similarly sized ecosystem components. Data was collected in the summer of 2024 using a DJI Mavic 3 Enterprise quadcopter with integrated multispectral and rgb sensors. The majority of the imagery focuses on study sites within the National Ecological Observatory Network (NEON) site near Healy, Alaska. The data set also includes a small amount of ground truth data on tussock dimensions for these sites. Additional images include a series of riparian corridors with beaver wetlands along the Denali and Steese Highways.  more » « less
Award ID(s):
2321530
PAR ID:
10599393
Author(s) / Creator(s):
Publisher / Repository:
NSF Arctic Data Center
Date Published:
Subject(s) / Keyword(s):
NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) ARCTIC TUNDRA BOREAL FOREST/TIAGA ECOLOGICAL DYNAMICS
Format(s):
Medium: X Other: text/xml
Sponsoring Org:
National Science Foundation
More Like this
  1. (, NSF Arctic Data Center)
    ### Access Dataset can be accessed and downloaded from the directory via: [http://arcticdata.io/data/10.18739/A2599Z39H](http://arcticdata.io/data/10.18739/A2599Z39H). ### Overview This dataset contains raw sedimentary ancient DNA (sedaDNA) sequence data and associated metadata generated from a 3-meter sediment core collected from Andy Lake, Alaska. The core was obtained during fieldwork supported by the National Science Foundation (NSF) Arctic Doctoral Dissertation Research Improvement Grant #2230019, titled Assessing the impacts of Pleistocene megaherbivores on vegetation stability and resilience in the Arctic, awarded to Principal Investigator (PI) Jacquelyn L. Gill and Co-PI Alessandro Mereghetti. The primary objective of this project is to investigate how Pleistocene megafaunal diversity influenced long-term plant community dynamics and ecosystem resilience in Arctic environments. These data contribute to understanding ecological baselines and biotic responses to past climate and extinction events, with implications for modern conservation and rewilding strategies. 
    more » « less
  2. ; ; ; ; ; ; (, NSF Arctic Data Center)
    ### Overview The SACHI (Sentinel-1/2 derived Arctic Coastal Human Impact) dataset has been developed as part of the HORIZON2020 project Nunataryuk by b.geos (www.bgeos.com). V1 covered a 100km buffer from the Arctic Coast (land area), for areas with permafrost near the coast. V2 covers additional selected areas extending the coverage to the south. It is based on Sentinel-1 and Sentinel-2 data from 2016-2020 using the algorithms described in Bartsch et al. (2020). It is a supplement to Bartsch et al. (2023). This dataset contains detected coastal infrastructure separated into seven different categories: linear transport infrastructure (asphalt), linear transport infrastructure (gravel), linear transport infrastructure (undefined), buildings (and other constructions such as bridges), other impacted area (includes gravel pads, mining sites), airstrip, and reservoir or other water body impacted by human activities. This SACHI version 2 dataset was post-processed by the Permafrost Discovery Gateway visualization pipeline. This workflow cleaned, standardized, and visualized the data as two Tile Matrix Sets per year. One Tile Matrix Set is the data in the form of GeoPackages, or staged tiles, and the other Tile Matrix Set is the staged tiles in the form of GeoTIFF tiles. The highest resolution tiles were resampled to produce GeoTIFFs for lower resolutions. This data is visualized on the Permafrost Discovery Gateway portal: https://arcticdata.io/catalog/portals/permafrost/Imagery-Viewer ### References Bartsch, A., Widhalm, B., von Baeckmann, C., Efimova, A., Tanguy, R., and Pointner, G. (2023). Sentinel-1/2 derived Arctic Coastal Human Impact dataset (SACHI) (v2.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10160636 Bartsch, A., G. Pointner, I. Nitze, A. Efimova, D. Jakober, S. Ley, E. Högström, G. Grosse, P. Schweitzer (2021): Expanding infrastructure and growing anthropogenic impacts along Arctic coasts. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ac317 Bartsch, A., Pointner, G., Ingeman-Nielsen, T. and Lu, W. (2020), ‘Towards circumpolar mapping of Arctic settlements and infrastructure based on Sentinel-1 and Sentinel-2’, Remote Sensing 12(15), 2368. ### Access Data files output from the visualization workflow are available for download at: [http://arcticdata.io/data/10.18739/A21J97929](http://arcticdata.io/data/10.18739/A21J97929) To download all files in the command line, run the following command in a terminal: `wget -r -np -nH --cut-dirs=3 -R '\?C=' -R robots.txt https://arcticdata.io/data/10.18739/A21J97929/` To download a subdirectory of the archived files, add the subdirectories to the end of the URL above. 
    more » « less
  3. ; ; ; ; ; ; ; (, NSF Arctic Data Center)
    ### Overview This data release includes surface nuclear magnetic resonance (sNMR) data collected as part of the SUN-SPEARS project. The project is funded by the National Science Foundation (Award number 2015329) and is concerned with studying soil evolution in high Arctic environments post glacial retreat. Within SUN-SPEARS, data are collected on a chronosequence from very recently deglaciated to older locations which have been exposed for decades to centuries. In this data release, sNMR data from two sites are included: site 1 which was collected approximately 15 meters (m) from the snout of the glacier, and site 2 which was located approximately 1000 m from the snout of the glacier, Global Positioning System (GPS) coordinates are included for more precise locations. ### Access Data files can be accessed via: [https://arcticdata.io/data/10.18739/A23X83N25](https://arcticdata.io/data/10.18739/A23X83N25) 
    more » « less
  4. (, NSF Arctic Data Center)
    ### Access GPS, photo, and position data can be accessed and downloaded from the directory via: [http://arcticdata.io/data/10.18739/A2MS3K37K](http://arcticdata.io/data/10.18739/A2MS3K37K). ### Overview The following files gather Surface Mass Balance stakes, timelapse camera photos, Hobo TidBits temperature sensors data, Global Positioning System (GPS) measurements, and debris thickness measurements on the surface of Malaspina Glacier, specifically in its lobe. The data was collected in Summer 2021. The glacier is located on the southwestern coast of Alaska, in the Wrangell St-Elias National Park. The study was mostly focused on the lobe of this piedmont glacier. The goal of the study was to measure several glaciological variables to be later compared to satellite-derived datasets, and incorporated into an ice flow model. The research topic was the retreat of Malaspina glacier over the next decades. We identified regions of interests within the glacier's lobe, that could potentially be markers of a starting retreat. The data gathered was used for publications currently in preparation as of October 2025. This study was led under the NSF grant number #1929566. 
    more » « less
  5. (, NSF Arctic Data Center)
    ### Access All files can be accessed and downloaded from the directory via: [http://arcticdata.io/data/10.18739/A2MW28G9D](http://arcticdata.io/data/10.18739/A2MW28G9D). ### Overview Storm surge extremes are intensifying across Arctic coastlines, yet limited observational records hamper detailed spatial and temporal characterization of these events. To address that, this data is a 45-year hydrodynamic hindcast of storm-driven water levels across Northern and Western Alaska. We utilize ADCIRC+SWAN to simulate interactions between the ocean, land, sea ice, and atmosphere, focusing on the period from 1979 to 2024 for Western to Northern Alaska coasts. Data from the European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA5), including sea ice concentration and atmospheric forcing were utilized to support these simulations, which investigate annual conditions in the Alaskan Arctic. The Processed_DATA dataset contains extracted parameters for communities located in western to northern Alaska. For other areas in the state not included here, please refer to the Raw_DATA file. ### Goal The goal of this study's data is to attribute long-term changes in Arctic storm surge extremes to evolving physical drivers—primarily the transition from sea-ice-dominated to wind-driven surge regimes. Furthermore, to fill in the gap in observed water levels and wave conditions throughout Alaska. ### Methods This study’s hindcast model framework is to evaluate the storm driven water levels from 1979 to 2024. The framework integrates a coupled hydrodynamic–wave model driven by time-varying boundary inputs representing atmospheric, oceanic, tidal, and sea ice conditions. We used the coupled Advanced CIRCulation and Simulating WAves Nearshore model (ADCIRC+SWAN) to simulate water levels and wave conditions. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email