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  2. EOSDIS Data News: July 20, 2018

EOSDIS Data News: July 20, 2018

GHRC DAAC

NASA's Global Hydrology Resource Center Distributed Active Archive Center (GHRC DAAC) published new versions (p0.2) of four different datasets from the Lightning Imaging Sensor onboard the International Space Station - LIS (ISS): near real-time (NRT) LIS (ISS) Provisional Science Data, NRT LIS (ISS) Provisional Backgrounds, Non-Quality Controlled LIS (ISS) Provisional Science Data, and Non-Quality Controlled LIS (ISS) Provisional Backgrounds. This data collection is useful for severe storm detection and analysis, as well as for lightning-atmosphere interaction studies. The LIS instrument makes measurements during both day and night with high detection efficiency. This new version contains improved geolocation and time changes. The data are available in both HDF-4 and netCDF-4 formats, with corresponding browse images in GIF format. Please note that these LIS (ISS) data are provisional files indicating that the algorithm is still under development and the data may contain errors. Use the data with caution and do not use for research leading to publications or presentations without consent of the data provider. Please give feedback directly to the data provider. Quality controlled data are currently unavailable, but will be available later this year.

NSIDC DAAC

NASA's National Snow and Ice Data Center DAAC (NSIDC DAAC) has published data through May 2018 for the dataset Making Earth System Data Records for Use in Research Environments (MEaSUREs) Greenland Image Mosaics from Sentinel-1A and -1B, Version 2. This dataset, part of the MEaSUREs Program, provides 6 and 12-day 50 m resolution image mosaics of the Greenland coastline and ice sheet periphery beginning in January 2015. The mosaics are derived from C-band Synthetic Aperture Radar (C-SAR) acquired by the Copernicus Sentinel-1A and -1B imaging satellites.

NSIDC DAAC has published Version 3.1 of the dataset Bootstrap Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I)-Special Sensor Microwave Imager Sounder (SSMIS). In this minor version release, the sea ice concentration field derived from the Bootstrap algorithm uses an “open water” identifier that is calculated daily in May and October. In Version 3.0, this value was calculated using a single monthly value for May and a single monthly value for October. The difference in total Arctic sea ice area and sea ice extent between the two versions is typically small (less than ± 0.5%), except in the second half of May when daily sea ice areas are often 0.5-1.5% higher and extents are 1-3% higher in Version 3.1 than in Version 3.0.

NSIDC DAAC has published the dataset MEaSUREs Moderate Resolution Imaging Spectroradiometer (MODIS) Mosaic of Antarctica 2013-2014 (MOA2014) Image Map, Version 1. This dataset, part of the NASA MEaSUREs Program, includes two image maps produced from composited image swath data acquired by MODIS over Antarctica for the 2013-2014 austral summer season. The two image maps, a snow grain size map and a surface morphology map, are both provided at two different grid scales of 125 m and 750 m resolution. These data are a follow on to the MOA2004 and MOA2009 datasets.

ORNL DAAC

NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC) published the North American Carbon Program (NACP) dataset Mean Annual Fluxes of Carbon in Coastal Ecosystems of Eastern North America. This dataset contains best estimates and uncertainties for mean annual fluxes of inorganic, organic, and total (organic and inorganic) carbon in tidal wetlands, estuaries and shelf waters of eastern North America, which is defined by the coastline running between the tip of the Scotian Peninsula (Canada) and the southern tip of Florida (USA). The data are provided on a per-unit-area basis and as spatially integrated values for each of the three ecosystem types (tidal wetlands, estuaries, and shelf waters) and the entire coastal ecosystem (tidal wetlands + estuaries + shelf waters) as well as for three geographic subregions (the Gulf of Maine, the Mid-Atlantic Bight, and the South Atlantic Bight) and the entire Eastern North America domain (Gulf of Maine and Mid-Atlantic Bight and South Atlantic Bight). The data include the net uptake from the atmosphere by the three ecosystems; burial in tidal wetland soils, estuarine sediments, and continental shelf sediments; riverine input from land to estuaries; and the net lateral advective transports from ecosystem to ecosystem. In addition, heterotrophic respiration (HR), net primary production (NPP), and net ecosystem production (NEP) estimates were computed for each ecosystem. The fluxes were derived using a variety of sources and are estimates for average conditions over the past decades from data covering roughly the period 1976-01-01 to 2017-12-31.

ORNL DAAC published the Arctic-Boreal Vulnerability Experiment (ABoVE) dataset ABoVE: Landsat-derived Burn Scar dNBR across Alaska and Canada, 1985-2015. This dataset contains differenced Normalized Burned Ratio (dNBR) at 30-m resolution calculated for burn scars from fires that occurred within the ABoVE Project domain in Alaska and Canada during 1985-2015. The fire perimeters were obtained from the Alaskan Interagency Coordination Center (AICC) and the Natural Resources Canada (NRC) fire occurrence datasets. Only burns with an area larger than 200-ha were included. The dNBR for each burn scar at 30-m pixel resolution was derived from pre- and post-burn Landsat 5, 7, and 8 scenes within a 5-km buffered area surrounding each burn scar using Landsat LEDAPS surface reflection image pairs.

ORNL DAAC published the ABoVE dataset A Concise Experiment Plan for ABoVE. This document presents the Concise Experiment Plan for NASA's ABoVE to serve as a guide to the Program as it identifies the research to be conducted under this study. Research for ABoVE will link field-based, process-level studies with geospatial data products derived from airborne and satellite remote sensing, providing a foundation for improving the analysis and modeling capabilities needed to understand and predict ecosystem responses and societal implications. The ABoVE Concise Experiment Plan (ACEP) outlines the conceptual basis for the Field Campaign and expresses the compelling rationale explaining the scientific and societal importance of the study. It presents both the science questions driving ABoVE research as well as the top-level requirements for a study design to address them.

ORNL DAAC published the Carbon Monitoring System (CMS) dataset LiDAR-Derived Aboveground Biomass and Uncertainty for California Forests, 2005-2014. This dataset provides estimates of aboveground biomass and spatially explicit uncertainty from 53 airborne LiDAR surveys of locations throughout California between 2005 and 2014. Aboveground biomass was estimated by performing individual tree crown detection and applying a customized "remote sensing aware" allometric equation to these individual trees. Aboveground biomass estimates and their uncertainties for each study area are provided in per-tree and gridded format. The canopy height models used for the tree detection and biomass estimation are also provided.

ORNL DAAC published the Carbon Monitoring System dataset LiDAR-Derived Aboveground Biomass and Uncertainty for California Forests, 2005-2014. This dataset provides estimates of aboveground biomass and spatially explicit uncertainty from 53 airborne LiDAR surveys of locations throughout California between 2005 and 2014. Aboveground biomass was estimated by performing individual tree crown detection and applying a customized "remote sensing aware" allometric equation to these individual trees. Aboveground biomass estimates and their uncertainties for each study area are provided in per-tree and gridded format. The canopy height models used for the tree detection and biomass estimation are also provided.


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Last Updated: Aug 6, 2019 at 12:07 PM EDT