Thomas Loveland (Former Employee)
Science and Products
Filter Total Items: 142
A conceptual method for monitoring locust habitat
A procedure to map and monitor vegetation conditions in near-real time was developed at the United States Geological Survey;s Earth Resources Observation Systems Data Center for use in locust control efforts. Meteorological satellite dat were acquired daily for 3 weeks in October and November 1986 over a 1.4-million-square-kilometer study area centered on Botswana in southern Africa. Advanced Ve
Authors
Stephen M. Howard, Thomas R. Loveland, Donald O. Ohlen, Donald G. Moore, Kevin P. Gallo, Jonathon Olsson
Producing Alaska interim land cover maps from Landsat digital and ancillary data
In 1985, the U.S. Geological Survey initiated a research program to produce 1:250,000-scale land cover maps of Alaska using digital Landsat multispectral scanner data and ancillary data and to evaluate the potential of establishing a statewide land cover mapping program using this approach. The geometrically corrected and resampled Landsat pixel data are registered to a Universal Transverse Merca
Authors
Katherine Fitzpatrick-Lins, Eileen Flanagan Doughty, Mark Shasby, Thomas R. Loveland, Susan Benjamin
Applications of U.S. Geological Survey digital cartographic products, 1979-1983
The U.S. Geological Survey prepares and distributes fundamental, multipurpose cartographic data to a wide range of users throughout the United States. Recognizing that traditional cartographic procedures will eventually be replaced by digital techniques, the USGS is now actively developing computer-based methods to produce digital cartographic products. The digital cartographic products currently
Authors
Thomas R. Loveland, Benjamin S. Ramey
The role of remotely sensed and other special data for predictive modeling: the Umatilla, Oregon example
Landsat data and 1:24 000-scale aerial photographs were initially used to map the expansion of irrigation from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a
Authors
Thomas R. Loveland, Gary E. Johnson
Evaluation of AMOEBA: a spectral-spatial classification method
Muitispectral remotely sensed images have been treated as arbitrary multivariate spectral data for purposes of clustering and classifying. However, the spatial properties of image data can also be exploited. AMOEBA is a clustering and classification method that is based on a spatially derived model for image data. In an evaluation test, Landsat data were classified with both AMOEBA and a widely us
Authors
Susan K. Jenson, Thomas R. Loveland, J. Bryant
Remote sensing applied to irrigation engineering
No abstract available.
Authors
Gary E. Johnson, Robert F. Vining, Thomas Loveland
The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example
The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were
Authors
Thomas R. Loveland, Gary E. Johnson
The Columbia River and tributaries irrigation withdrawals analysis project—Feasibility analysis and future plans
No abstract available.
Authors
Gary E. Johnson, Thomas Loveland
A selected bibliography of remote sensing applications to soil science
The bibliography contains approximately 200 references dealing with the application of remote sensing technology to the identification and analysis of soils. The scientific papers and reports listed describe procedures and methods used in data collection and include specific applications of those data to soil studies. Most citations discuss current work from 1970 to 1978 and all references are cat
Authors
Thomas R. Loveland, Daniel B. Carter, William C. Draeger
Land capability studies of the South Dakota Automated Geographic Information System (AGIS)
No abstract available.
Authors
J. Schlesinger, B. Ripple, Thomas R. Loveland
Science and Products
Filter Total Items: 142
A conceptual method for monitoring locust habitat
A procedure to map and monitor vegetation conditions in near-real time was developed at the United States Geological Survey;s Earth Resources Observation Systems Data Center for use in locust control efforts. Meteorological satellite dat were acquired daily for 3 weeks in October and November 1986 over a 1.4-million-square-kilometer study area centered on Botswana in southern Africa. Advanced Ve
Authors
Stephen M. Howard, Thomas R. Loveland, Donald O. Ohlen, Donald G. Moore, Kevin P. Gallo, Jonathon Olsson
Producing Alaska interim land cover maps from Landsat digital and ancillary data
In 1985, the U.S. Geological Survey initiated a research program to produce 1:250,000-scale land cover maps of Alaska using digital Landsat multispectral scanner data and ancillary data and to evaluate the potential of establishing a statewide land cover mapping program using this approach. The geometrically corrected and resampled Landsat pixel data are registered to a Universal Transverse Merca
Authors
Katherine Fitzpatrick-Lins, Eileen Flanagan Doughty, Mark Shasby, Thomas R. Loveland, Susan Benjamin
Applications of U.S. Geological Survey digital cartographic products, 1979-1983
The U.S. Geological Survey prepares and distributes fundamental, multipurpose cartographic data to a wide range of users throughout the United States. Recognizing that traditional cartographic procedures will eventually be replaced by digital techniques, the USGS is now actively developing computer-based methods to produce digital cartographic products. The digital cartographic products currently
Authors
Thomas R. Loveland, Benjamin S. Ramey
The role of remotely sensed and other special data for predictive modeling: the Umatilla, Oregon example
Landsat data and 1:24 000-scale aerial photographs were initially used to map the expansion of irrigation from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a
Authors
Thomas R. Loveland, Gary E. Johnson
Evaluation of AMOEBA: a spectral-spatial classification method
Muitispectral remotely sensed images have been treated as arbitrary multivariate spectral data for purposes of clustering and classifying. However, the spatial properties of image data can also be exploited. AMOEBA is a clustering and classification method that is based on a spatially derived model for image data. In an evaluation test, Landsat data were classified with both AMOEBA and a widely us
Authors
Susan K. Jenson, Thomas R. Loveland, J. Bryant
Remote sensing applied to irrigation engineering
No abstract available.
Authors
Gary E. Johnson, Robert F. Vining, Thomas Loveland
The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example
The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were
Authors
Thomas R. Loveland, Gary E. Johnson
The Columbia River and tributaries irrigation withdrawals analysis project—Feasibility analysis and future plans
No abstract available.
Authors
Gary E. Johnson, Thomas Loveland
A selected bibliography of remote sensing applications to soil science
The bibliography contains approximately 200 references dealing with the application of remote sensing technology to the identification and analysis of soils. The scientific papers and reports listed describe procedures and methods used in data collection and include specific applications of those data to soil studies. Most citations discuss current work from 1970 to 1978 and all references are cat
Authors
Thomas R. Loveland, Daniel B. Carter, William C. Draeger
Land capability studies of the South Dakota Automated Geographic Information System (AGIS)
No abstract available.
Authors
J. Schlesinger, B. Ripple, Thomas R. Loveland