Skip to main content

Organization

Deprecated[17259] Eastern Geographic Science Center

thumbnail
We identified nine study site locations, representing three mature vegetation communities [Atlantic White Cedar (desired community), tall pine pocosin (desired community), and red maple/black gum mixed (undesired community)] with typical water depth within each vegetation type. All measurements were replicated three times (3 vegetation types x 3 replicates = 9 sites total). We installed four flux chambers at each site to collect GHG fluxes from all nine sites. We measured CO2 and CH4 using a Los Gatos Research Ultra Portable Greenhouse Gas Analyzer and two-part 760 cm2 flux chambers (chamber base remained in situ; chamber top was placed on the bottom only when sampling). We checked the gas fluxes on a monthly time-table...
thumbnail
This data release contains field sampling data collected on a farm located in Talbot County. Maryland, roadside survey data from the area surrounding the farm, and WorldView-3 satellite data of the study area. Datasets include: 1) CropResidueDataset.csv: Tabular data for 174 photo sampling locations with crop residue cover ranging from 0% to 98%, as well as line-point transect residue cover measurements and lat-lon geolocations 2) Roadside_Survey_May14th2015.zip: Zipfile containing roadside survey data for 63 fields documenting percent crop residue cover, including shapefile of field boundaries 3) GroundCoverPhotographs.zip: Zipfile containing 174 nadir photographs that were the basis for ground cover calculations...
thumbnail
Datasets related to crop residue, irrigation, and shortwave infra-red (SWIR) spectral reflectance, Talbot County, MD, May 2015
This posting contains field and satellite data collected in support of the scientific manuscript "Improved crop residue cover estimates by coupling spectral indices for residue and moisture." Quemada, M., W.D. Hively, C.S. Daughtry, B.T. Lamb, and J. Shermeyer. In review by Remote Sensing of Environment. In this study, field data were collected on May 15, 2015 and paired with reflectance data collected May 14th 2015. The manuscript compares portions of agricultural fields that were irrigated the day of imagery acquisitions with portions of the same fields not yet irrigated, using the contrast to derive a moisture correction algorithm for determination of percent crop residue cover. The data publication contains...
The dataset is provided as a .zip archive containing two .csv data files. These two data files contain the results of a series of timing runs made with a suite of 28 C test programs and 20 C++ test programs using three different computers and two operating systems (Windows and Linux). All 48 test programs carry out processing of two-dimensional arrays. One of the files, "C_CppTimeTestsAllRecords.csv", contains three replicated times for each of 960 combinations of factor levels that potentially might have affected the time required to process two-dimensional arrays. The other file, "C_CppTimeTestsAverages.csv", contains the average of the three replicated times for each of the 960 combinations of factor levels....
thumbnail
Climate, crop rotation, and stream flow data used to run the SWAT model in the Tuckahoe and Greensboro subwatersheds of the Choptank River watersheds, Maryland
This posting contains the source climate and crop rotation data used to run the SWAT model in the Tuckahoe and Upper Choptank watersheds, Maryland. It also contains the monthly flow load data used for validation of model results. The data release was produced in compliance with the new 'open data' requirements as a way to make the scientific products associated with USGS research efforts and publications available to the public. It is in support of a peer reviewed journal article titled "Assessing the impacts of future climate conditions on the effectiveness of winter cover crops in reducing nitrate loads into the Chesapeake bay watershed using SWAT model." The dataset consists of the following items: 1. Greensboro...
View more...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.