Constructing a Large-scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates

We use the landslide inventory database provided by the United States Geological Survey. USGS maintains a database of landslide reports with approximate locations and times, but no images. This is the most extensive data of its kind. We extract satellite images from Google Earth by using this inventory.<br>

Download Full-text

Analysis Ready Data: Enabling Analysis of the Landsat Archive

10.20944/preprints201808.0029.v1 ◽

2018 ◽

Cited By ~ 3

Author(s):

John Dwyer ◽

David Roy ◽

Brian Sauer ◽

Calli Jenkerson ◽

Hankui Zhang ◽

...

Keyword(s):

United States ◽

Land Cover ◽

Large Scale ◽

The United States ◽

Poor Quality ◽

Thematic Mapper ◽

United States Geological Survey ◽

Landsat 8 ◽

Landsat 7 ◽

Data Provision

Data that have been processed to allow analysis with a minimum of additional user effort are often referred to as Analysis Ready Data (ARD). The ability to perform large scale Landsat analysis relies on the ability to access observations that are geometrically and radiometrically consistent, and have had non-target features (clouds) and poor quality observations flagged so that they can be excluded. The United States Geological Survey (USGS) has processed all of the Landsat 4 and 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) archive over the conterminous United States (CONUS), Alaska, and Hawaii, into Landsat ARD. The ARD are available to significantly reduce the burden of pre-processing on users of Landsat data. Provision of pre-prepared ARD is intended to make it easier for users to produce Landsat-based maps of land cover and land-cover change and other derived geophysical and biophysical products. The ARD are provided as tiled, georegistered, top of atmosphere and atmospherically corrected products defined in a common equal area projection, accompanied by spatially explicit quality assessment information, and

Download Full-text

Multi-criteria parameter estimation for the unified land model

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-9-4417-2012 ◽

2012 ◽

Vol 9 (4) ◽

pp. 4417-4463 ◽

Cited By ~ 3

Author(s):

B. Livneh ◽

D. P. Lettenmaier

Keyword(s):

United States ◽

Remote Sensing ◽

Parameter Estimation ◽

Land Surface ◽

Large Scale ◽

The United States ◽

Limiting Factor ◽

Surface Model ◽

United States Geological Survey ◽

Skill Scores

Abstract. We describe a parameter estimation framework for the Unified Land Model (ULM) that utilizes multiple independent data sets over the Continental United States. These include a satellite-based evapotranspiration (ET) product based on MODerate resolution Imaging Spectroradiometer (MODIS) and Geostationary Operation Environmental Satellites (GOES) imagery, an atmospheric-water balance based ET estimate that utilizes North American Regional Reanalysis (NARR) atmospheric fields, terrestrial water storage content (TWSC) data from the Gravity Recovery and Climate Experiment (GRACE), and streamflow (Q) primarily from the United States Geological Survey (USGS) stream gauges. The study domain includes 10 large-scale (≥105 km2) river basins and 250 smaller-scale (<104 km2) tributary basins. ULM, which is essentially a merger of the Noah Land Surface Model and Sacramento Soil Moisture Accounting model, is the basis for these experiments. Calibrations were made using each of the criteria individually, in addition to combinations of multiple criteria, with multi-criteria skill scores computed for all cases. At large-scales calibration to Q resulted in the best overall performance, whereas certain combinations of ET and TWSC calibrations lead to large errors in other criteria. At small scales, about one-third of the basins had their highest Q performance from multi-criteria calibrations (to Q and ET) suggesting that traditional calibration to Q may benefit by supplementing observed Q with remote sensing estimates of ET. Model streamflow errors using optimized parameters were mostly due to over (under) estimation of low (high) flows. Overall, uncertainties in remote-sensing data proved to be a limiting factor in the utility of multi-criteria parameter estimation.

Download Full-text

Quality Control of Data in a Large-Scale Cancer Register Program

Methods of Information in Medicine ◽

10.1055/s-0038-1636339 ◽

1966 ◽

Vol 05 (02) ◽

pp. 67-74 ◽

Cited By ~ 5

Author(s):

W. I. Lourie ◽

W. Haenszeland

Keyword(s):

United States ◽

Quality Control ◽

Cancer Patients ◽

Large Scale ◽

The United States ◽

Newly Diagnosed ◽

Related Data ◽

Cancer Register ◽

Independent Review ◽

End Results

Quality control of data collected in the United States by the Cancer End Results Program utilizing punchcards prepared by participating registries in accordance with a Uniform Punchcard Code is discussed. Existing arrangements decentralize responsibility for editing and related data processing to the local registries with centralization of tabulating and statistical services in the End Results Section, National Cancer Institute. The most recent deck of punchcards represented over 600,000 cancer patients; approximately 50,000 newly diagnosed cases are added annually.Mechanical editing and inspection of punchcards and field audits are the principal tools for quality control. Mechanical editing of the punchcards includes testing for blank entries and detection of in-admissable or inconsistent codes. Highly improbable codes are subjected to special scrutiny. Field audits include the drawing of a 1-10 percent random sample of punchcards submitted by a registry; the charts are .then reabstracted and recoded by a NCI staff member and differences between the punchcard and the results of independent review are noted.

Download Full-text

Utopias of One

10.23943/princeton/9780691196541.001.0001 ◽

2019 ◽

Author(s):

Joshua Kotin

Keyword(s):

United States ◽

Soviet Union ◽

World War I ◽

Large Scale ◽

Jim Crow ◽

Personal Autonomy ◽

The United States ◽

Soviet Period ◽

Original Research ◽

The Soviet Union

This book is a new account of utopian writing. It examines how eight writers—Henry David Thoreau, W. E. B. Du Bois, Osip and Nadezhda Mandel'shtam, Anna Akhmatova, Wallace Stevens, Ezra Pound, and J. H. Prynne—construct utopias of one within and against modernity's two large-scale attempts to harmonize individual and collective interests: liberalism and communism. The book begins in the United States between the buildup to the Civil War and the end of Jim Crow; continues in the Soviet Union between Stalinism and the late Soviet period; and concludes in England and the United States between World War I and the end of the Cold War. In this way it captures how writers from disparate geopolitical contexts resist state and normative power to construct perfect worlds—for themselves alone. The book contributes to debates about literature and politics, presenting innovative arguments about aesthetic difficulty, personal autonomy, and complicity and dissent. It models a new approach to transnational and comparative scholarship, combining original research in English and Russian to illuminate more than a century and a half of literary and political history.

Download Full-text