Find research datasets worth reusing

NASA Web-Enabled Landsat Data Alaska 30m Composites over Annual Periods V001

WELDAKYR.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved yearly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDYR.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDYR.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDYR.032) datasets. NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. These products provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. This product includes Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDAKYR is distributed in Hierarchical Data Format 4 (HDF4).The annual products include the preceding year’s December through the current year’s November.The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.

QuikSCAT Level 2B Ocean Wind Vectors in 12.5km Slice Composites Version 3.1

This dataset contains the latest reprocessed version 3.1 of the Level 2B science-quality ocean surface wind vector retrievals from the QuikSCAT scatterometer. The retrievals are provided on a non-uniform grid within the swath at 12.5 km pixel resolution. Higher resolution is achieved through a slice composite technique in which high resolution slice measurements from L1B data are composited into a 12.5 km wind vector cell. Version 3.1 processing begins with the same L1B (time-ordered backscatter) data as used in the previous Version 3.0 processing. Version 3.1 improves upon the previous Version 3.0 processing by incorporating enhanced coastal processing using a Land Contamination Ratio (LCR) method with a fixed threshold. The 12.5 km binning resolution combined with the LCR processing enables this dataset to provide wind vector retrievals with approximately half the coastal gap as compared to the Version 3.0 12.5 km L2B dataset. The geophysical model function used to produce the wind vector cell retrievals remains unchanged between Version 3.0 and 3.1. Each L2B file corresponds to a specific orbital revolution (rev) number, which begins at the southernmost point of the ascending orbit. This is the official dataset produced by the NASA QuikSCAT Project through the SeaWinds Processing and Analysis Center (SeaPAC). More details to the processing changes and improvements are to be published in the near future, but for now can be referenced by the following presentation: https://mdc.coaps.fsu.edu/scatterometry/meeting/docs/2016/Thu_AM/coastal-poster.pdf .

GEO/LEO based cloud property composites for DSCOVR EPIC view, Version 2

In DSCOVR_EPIC_L2_composite_02, cloud property retrievals from multiple imagers on low Earth orbit (LEO) satellites (including MODIS, VIIRS, and AVHRR) and geostationary (GEO) satellites (including GOES-13 and -15, METEOSAT-7 and -10, MTSAT-2, and Himawari-8) are used to generate the composite. Based on the CERES cloud detection and retrieval system, all cloud properties were determined using a standard set of algorithms, the Satellite ClOud and Radiation Property Retrieval System (SatCORPS). Cloud properties from these LEO/GEO imagers are optimally merged to provide a seamless global composite product at 5-km resolution by using an aggregated rating that considers five parameters (nominal satellite resolution, pixel time relative to the EPIC observation time, viewing zenith angle, distance from day/night terminator, and sun glint factor) and selects the best observation at the time nearest to the EPIC measurements. About 72% of the LEO/GEO satellite overpass times are within one hour of the EPIC measurements, while 92% are within two hours of the EPIC measurements. The global composite data are then remapped into the EPIC FOV by convolving the high-resolution cloud properties with the EPIC point spread function (PSF) defined with a half-pixel accuracy to produce the EPIC composite. PSF-weighted radiances and cloud properties averages are computed separately for each cloud phase. Ancillary data (i.e., surface type, snow and ice map, skin temperature, precipitable water, etc.) needed for anisotropic factor selections are also included in the composite. These composite images are produced for each observation time of the EPIC instrument (typically 300 to 600 composites per month).

MASTER: Tropical Composition, Cloud and Climate Coupling Campaign, 2007

This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during seven flights aboard a NASA ER-2 aircraft over California, Nevada, Central America, and eastern Pacific Ocean from 2007-07-29 to 2007-08-18. This deployment supported the Tropical Composition, Cloud and Climate Coupling Campaign (TC4), which investigated the atmospheric structure, properties, and processes in the Eastern Pacific Tropics. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

Forest Canopy Composition (SNF)

The purpose of the SNF study was to improve our understanding of the relationship between remotely sensed observations and important biophysical parameters in the boreal forest. A key element of the experiment was the development of methodologies to measure forest stand characteristics to determine values of importance to both remote sensing and ecology. Parameters studied were biomass, leaf area index, above ground net primary productivity, bark area index and ground coverage by vegetation. Thirty two quaking aspen and thirty one black spruce sites were studied. Sites were chosen in uniform stands of aspen or spruce. Aspen stands were chosen to represent the full range of age and stem density of essentially pure aspen, of nearly complete canopy closure, and greater than two meters in height. Spruce stands ranged from very sparse stands on bog sites, to dense, closed stands on more productive peatlands. Within each plot, all woody stems greater than two meters in height were recorded by species and diameter breast height (dbh), height of the tree, and height of the first live branch dimensions were measured. The depth of crown was also calculated. Similar measurements were made for shrubs between one and two meters tall in the aspen sites.

ABoVE: Vegetation Composition across Fire History Gradients on the Y-K Delta, Alaska

This dataset provides ecological field data that were collected during July 2017 and July 2018 from 43 plots spanning gradients of fire history in the upland tundra of the Yukon-Kuskokwim (Y-K) Delta, Alaska. Plot-level data include vegetation species composition and structure, leaf area index (LAI), topography, thaw-depth, and soil characteristics collected at plots burned in 1971-1972, 1985, 2006-2007, 2015, or unburned controls. Vegetation species were sampled along transects using the vegetation point-intercept (VPI) sampling approach and summarized by three metrics of vegetation cover: (1) top-hit cover, (2) any-hit cover, and (3) multi-hit cover. Each metric is the total number of hits for a species divided by the total number of sample points. The VPI any-hit cover metric data were combined with Landsat imagery to develop fractional maps of any-hit cover for four aggregated plant functional types (PFTs); bryophytes, herbs, lichen, and shrubs for the upland tundra area. Photographs of vegetation transects and soil pits are included as companion files.

NASA Web-Enabled Landsat Data CONUS 30m Composites over Weekly Periods V001

WELDUSWK.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2003 to 2012. These mosaics provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The WELD Conterminous (CONUS) United States Weekly (WELDUSWK) products include Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDUSWK is distributed in Hierarchical Data Format 4 (HDF4).WELDUSWK products are consecutive 7 day products for 2003 through 2012. Individual weeks are defined as follows: Week01: January 1 to January 7 Week02: January 8 to January 14 Week52: December 24 to December 30 (non-leap years) Week52: December 23 to December 29 (leap years) Week53: December 31 (non-leap years) Week53: December 30 to December 31 (leap years) The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.

BOREAS TGB-03 Plant Species Composition Data over the NSA Fen

The BOREAS TGB-03 team collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the NSA. This data set contains information about the composition of plant species that were within the collars used to measure NEE. The species composition was identified to understand the differences in NEE among the various plant communities in the NSA fen. The data were collected in July of 1994 and 1996.

CALIPSO Lidar Level 2 Polar Stratospheric Clouds presents, composition, and optical properties, V2-00

The Version 2 (V2) CALIPSO Lidar Level 2 Polar Stratospheric Clouds (PSC) data product ensemble describes the spatial distribution, optical properties, and composition of PSC layers observed by the CALIPSO lidar (CALIOP). The product contains profiles of PSC presence, composition, optical properties, and meteorological information on a uniform 5-km horizontal x 180-m vertical grid along CALIPSO orbit tracks. Aura Microwave Limb Sounder (MLS) measurements of the primary PSC condensable vapors HNO3 and H2O and a number of parameters from the Aura MLS V2 Derived Meteorological Products (DMPs) are also included in the V2 PSC data product ensemble.

Atmospheric Composition Ammonia Volume Mixing Ratio L3 (AIRSAC3MNH3 V3) from AIRS/AMSU on NASA Aqua at GES DISC

The mass concentration ammonia in the atmosphere, consists of products generated for the study of atmospheric ammonia. Atmospheric ammonia is an important component of the global nitrogen cycle. In the troposphere, ammonia reacts rapidly with acids such as sulfuric and nitric to form fine particulate matter. These ammonium containing aerosols affect Earth's radiative balance, both directly by scattering incoming radiation and indirectly as cloud condensation nuclei. Major sources of atmospheric ammonia involve agricultural activities including animal husbandry, especially concentrated animal feeding operations and fertilizer use. Major sinks of atmospheric ammonia involve dry deposition and wet removal by precipitation, as well as conversion to particulate ammonium by reaction with acids. Measurements of ambient NH3 are sparse, but satellites provide a means to monitor atmospheric composition globally. Using the AIRS/AMSU satellite this algorithm provides monthly measurements of derived atmospheric NH3 for September 2002 through August 2016.

NASA Web-Enabled Landsat Data Alaska 30m Composites over Monthly Periods V001

WELDAKMO.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. These mosaics provide consistent data for deriving land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The Alaska Monthly products are defined with respect to each calendar year by the days in each month. This product includes Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. These products are distributed in Hierarchical Data Format 4 (HDF4).The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.

QuikSCAT Level 2B Ocean Wind Vectors in 12.5km Slice Composites Version 3

This dataset contains the latest reprocessed version 3 of the Level 2B science-quality ocean surface wind vector retrievals from the QuikSCAT scatterometer. The retrievals are provided on a non-uniform grid within the swath at 12.5 km pixel resolution. Higher resolution is achieved through a slice composite technique in which high resolution slice measurements from L1B data are composited into a 12.5 km wind vector cell. Version 3 processing begins with the same L1B (time-ordered backscatter) data as used in the previous processing. Version 3 has several improvements over the previous JPL processing of the QuikSCAT L2B winds: 1) changes to measurement binning, which was done in order to decrease noise and reduce gaps in the 12.5 km L2B wind retrievals, 2) an improved geophysical model function (GMF) to model the effect of wind on backscatter, 3) a neural network approach to correct rain contaminated winds speeds, 4) cross-track dependent wind speed biases were estimated and removed from the wind retrievals. The 12.5 km binning resolution enables users to obtain wind vector retrievals 10 km closer to shore when compared to the 25 km L2B dataset (only available in versions 1 and 2). More details to the processing changes and improvements are noted by Fore et al. (2014): PO.DAAC Drive at https://podaac-tools.jpl.nasa.gov/drive/files/allData/quikscat/L2B12/docs/fore_et_al_ieee_2014.pdf . Each L2B file corresponds to a specific orbital revolution (rev) number, which begins at the southernmost point of the ascending orbit. This is the official dataset produced by the QuikSCAT Project through the SeaWinds Processing and Analysis Center (SeaPAC). The Version 3 User Guide document is accessible from https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/quikscat/open/L2B12/docs/qscat_l2b_v3_ug_v1_0.pdf.

NASA Web-Enabled Landsat Data CONUS 30m Composite Pixel Center Lat/Longs V001

WELDUSLL.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets. NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. These mosaics provide consistent data to derive land cover as well as geophysical and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The Conterminous (CONUS) United States Latitude/Longitude (WELDUSLL) products provide the geographic latitude and longitude for the center of each 30 meter (m) pixel within a tile of WELD data. WELDUSLL is distributed in Hierarchical Data Format 4 (HDF4).The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.

CAR ARCTAS Arctic Research of the Composition of the Troposphere from Aircraft and Satellites L1 V1 (CAR_ARCTAS_L1C) at GES DISC

ARCTAS focuses on advancing understanding of the factors driving current changes in the Arctic region including transport of mid-latitude pollution, boreal forest fires, aerosol radiative forcing, and chemical processes. ARCTAS aimed to use detailed observations from aircraft to provide the validation, retrieval constraints, correlative data, and process information needed to better achieve the potential of satellites for Arctic research. The plan is for the combination of satellite and aircraft data to provide together powerful information for constraining and evaluating models of Arctic atmospheric composition and climate, and thus improve model projections of future change.

NASA Web-Enabled Landsat Data Alaska 30m Composites over Seasonal Periods V001

WELDAKSE.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. The mosaics provide consistent data for deriving land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. This product includes Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDAKSE is distributed in Hierarchical Data Format 4 (HDF4).In the Alaska seasonal products, seasons are defined as follows: Winter: December, January, February Spring: March, April, May Summer: June, July, August Autumn: September, October, NovemberThe WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.

LBA-ECO CD-06 Isotopic Composition of Carbon Fractions, Amazon Basin River Water

This data set includes measurements of standard geochemical variables, dissolved CO2, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), fine particulate organic carbon (FPOC), and coarse particulate organic carbon (CPOC) in samples taken from 60 Amazonian river locations across the Amazon Basin from 1991 to 2003 (Mayorga et al., 2005). The 14C and 13C isotopic composition of DIC was measured on samples collected between 1991 and 2003. The 14C composition of organic carbon fractions was measured on samples collected from 1995 through 1996. There are four comma-delimited data files with this data set. Note that site descriptions include a categorization of each site by topography according to the percentage of the drainage area above 1,000 m elevation (Mayorga et al., 2005). Only means of geochemical and carbon-fraction results are provided. Both individual 13C and 14C measurements and mean results are provided.

CARVE: Fire-Related Aerosol and Soil Elemental and Isotopic Composition, Alaska, 2013

This data set provides measurements of the isotopic composition of black carbon and organic carbon aerosols collected at two locations in interior Alaska during the summer of 2013, as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The delta14C end member of fire aerosol was derived and linked to soil elemental and isotopic composition in Alaskan boreal forests. Soil and aerosol measurements were used to estimate average depth of burn in Alaska during the summer of 2013.

LBA-ECO LC-09 Soil Composition and Structure in the Brazilian Amazon: 1992-1995

This data set reports basic soil structure and composition information for five Amazonian research sites: Altamira, Bragantina, Tome-Acu, and Ponta de Pedras, all four in the state of Para, Brazil; and one site in Yapu, Colombia. Soil characteristics reported for all five study sites include cation information (e.g., H, Al, Mg, K, Na, S), percent of soil C, N, and organic matter, soil texture/composition and color, pH, and land use history. Soil bulk density and tons of carbon/ha are reported for only three of the study sites: Altamira, Bragantina, and Tome-Acu. All of the data are provided in one comma-separated data file.The five study areas represent characteristic differences in soil fertility and a range of land uses typical of the Amazon region. One of these areas, Altamira, is characterized by above average pH, nutrients, and texture. The other four areas are more typical of the 75 percent of the Amazon that is characterized by Oxisols and Ultisols, with well-drained but low pH and low levels of nutrients. Ponta de Pedras in Marajo Island, located in the estuary, is composed of upland Oxisols and floodplain alluvial soils. Igarape-Acu in the Bragantina region is characterized by both nutrient-poor Spodosols and Oxisols. Tome-Acu, south of Igarape-Acu, represents a mosaic of Oxisols and Ultisols. Yapu, in the Colombian Vaupes, is composed of patches of Spodosols and Oxisols. Three of the areas are colonization regions at various degrees of development: Altamira is a colonization front that opened up in 1971, whereas Tome-Acu was settled by a Japanese population in the 1930s, and Bragantina was settled in the early part of the twentieth century. Marajo (Ponta de Pedras) is the home of caboclos, whereas Yapu is home to Tukanoan Native American populations. In these study areas slash-and-burn cultivation as well as plantation agriculture and mechanized agriculture are employed. Length of fallows vary in these communities. The two indigenous areas leave their land in longer fallow than do the three colonization areas, and the proportion of land prepared from secondary forests increases with length of settlement as the stock of mature forest declines over time.

GPM GROUND VALIDATION COMPOSITE SATELLITE OVERPASSES GCPEX V1

The GPM Ground Validation Composite Satellite Overpasses GCPEx dataset provides satellite overpasses from the Special Sensor Microwave Imager/Sounder (SSMIS) satellites (F-16, 17, 18) during the GPM Cold-season Precipitation Experiment (GCPEx) which took place in Ontario, Canada, January 17, 2012 through February 29, 2012. The radiometric data was matched up with other datasets necessary to carry out land surface emissivity studies. These other datasets include the NEXRAD National Mosaic and Multi-Sensor QPE (NMQ) radar mosaic for knowledge of rain structure and intensity at the time of the overpass, as well as the previous accumulated precipitation prior to the satellite overpass time, the NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) snow mapping system (to identify surface snow or ice cover), and the NASA/GMAO Modern-Era Retrospective Analysis for Research (MERRA) land and atmospheric reanalysis (for background land and atmospheric state needed for microwave radiative transfer calculations). The identified SSMIS satellite overpasses passed within 700-km of the central field site.

NASA Web-Enabled Landsat Data CONUS 30m Composites over Monthly Periods V001

WELDUSMO.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. These mosaics provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The WELD Conterminous (CONUS) United States Monthly products include Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. These products are distributed in Hierarchical Data Format 4 (HDF4).WELDUSMO products are defined by a calendar month (e.g. January, February, March, etc.) for December 2002 through November 2012.The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.