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Dataset results
6 results for “LandCover Map”
Landcover change analysis of the McKenzie Basin for the Maps and Locals (MALS) project.
This dataset was developed for use in an analysis of landcover change in the McKenzie Basin for the Maps and Locals (MALS) project. MALs is funded by LTER Social Science Supplement grants of the National Science Foundation.
1989 General Landcover Map of the Eastern Shore of Virginia
This generalized landcover classification of the Eastern Shore of Virginia focuses on major landforms and habitats of the Virginia Coast Reserve LTER. The classification is based on a Landsat 5 Thematic Mapper (TM) satellite image taken on July 25, 1989 at 15:14 GMT (11:14 EDT), which is roughly concurrent with mid-tide water levels as predicted for Wachapreague, VA (L=8:25, H=14:52 EDT). The classification divides the landscape into three components: water (code 1); salt marsh (code 2); and upland/mainland areas (code 3). The primary purpose of this dataset is to provide a background map layer over which VCRLTER researchers and students can plot individual research site locations for figures intended for publications and presentations.
Landcover map for the central region of the Yukon-Kuskokwim Delta, Alaska
<p>Climate change is causing an intensification in tundra fires across the Arctic, including the unprecedented 2015 fires in the Yukon-Kuskokwim (YK) Delta. The YK Delta contains extensive surface waters (∼33% cover) and significant quantities of organic carbon, much of which is stored in vulnerable permafrost. Inland aquatic ecosystems act as hot-spots for landscape CO<sub>2</sub> and CH<sub>4</sub> emissions and likely represent a significant component of the Arctic carbon balance, yet aquatic fluxes of CO<sub>2</sub> and CH<sub>4</sub> are also some of the most uncertain. We measured dissolved CH<sub>4 </sub>and CO<sub>2</sub> concentrations (n = 364), in surface waters from different types of waterbodies during summers from 2016 to 2019. We used Sentinel-2 multispectral imagery to classify landcover types and area burned in contributing watersheds. We develop a model using machine learning to assess how waterbody properties (size, shape, and landscape properties), environmental conditions (O<sub>2</sub>, temperature), and surface water chemistry (dissolved organic carbon composition, nutrient concentrations) help predict in situ observations of CH<sub>4 </sub>and CO<sub>2</sub> concentrations across deltaic waterbodies. CO<sub>2</sub> concentrations were negatively related to waterbody size and positively related to waterbody edge effects. CH<sub>4</sub> concentrations were primarily related to organic matter quantity and composition. Waterbodies in burned watersheds appeared to be less carbon limited and had longer soil water residence times than in unburned watersheds. Our results illustrate the importance of small lakes for regional carbon emissions and demonstrate the need for a mechanistic understanding of the drivers of greenhouse gasses in small waterbodies.</p>
Landcover map for the central region of the Yukon-Kuskokwim Delta, Alaska
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NACP Peatland Landcover Type and Wildfire Burn Severity Maps, Alberta, Canada
This data set provides landcover maps of (1) peatland type (bog, fen, marsh, swamp) with levels of biomass (open, forested) and (2) Burn Severity Index (BSI) (Dyrness and Norum, 1983) for four wildfire areas in northern Alberta, Canada. The four wildfire sites include the Utikuma fire site of 2011, Kidney Lake fire site of 2011, Fort McMurray west fire site of 2009, and Fort McMurray east fire site of 2009. The peatland classification at 12.5-m resolution (fen vs. bog including treed vs. open vs. shrubby) at each wildfire site was based on a pre-burn 2007 multi-date, multi-sensor fusion (Optical-IR, C-band and L-band SAR) approach. Over 350 field locations were sampled in central Alberta to train and validate the peatland type maps. The additional site, Wabasca, was an unburned site. Burn severity was measured in the field using the Burn Severity Index (BSI) (Dyrness and Norum 1987), a qualitative assessment of burnt moss that uses a 1-5 scale, with 1 being unburnt and 5 being severely burnt. The field data of ground consumption were correlated with Landsat pre- and post-burn imagery, specific to peatlands, to develop multivariate models for calculating burn severity and %-not-sphagnum-moss. These models were used to generate the Burn Severity Maps at 30-m resolution (percent unburned moss, and the burn severity index (BSI)). All sites were visited in 2013 for field measurements and the Utikuma site was also visited in 2012 for field measurements. Additional biophysical data for the various peatlands (aboveground biomass – tree and shrub, plant heights, density, etc. were collected and will be provided in another data set.
BOREAS RSS-15 SIR-C and TM Biomass and Landcover Maps of the NSA and SSA
As part of BOREAS, the RSS-15 team conducted an investigation using SIR-C , X-SAR and Landsat TM data for estimating total above-ground dry biomass for the SSA and NSA modeling grids and component biomass for the SSA. Relationships of backscatter to total biomass and total biomass to foliage, branch, and bole biomass were used to estimate biomass density across the landscape. The procedure involved image classification with SAR and Landsat TM data and development of simple mapping techniques using combinations of SAR channels. For the SSA, the SIR-C data used were acquired on 06-Oct-1994, and the Landsat TM data used were acquired on September 2, 1995. The maps of the NSA were developed from SIR-C data acquired on 13-Apr-1994.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.