Structural and Ground Pattern Analysis of Missouri and the Ozark Dome Using LANDSAT-2 Satellite Imagery
There are no author-identified significant results in this report.
Kisvarsanyi, G.↗
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Structural and ground pattern analysis of Missouri and the Ozark Dome using LANDSAT-2 satellite imagery
There are no author-identified significant results in this report.
Kisvarsanyi, G.↗
Forest land management by satellite: LANDSAT-derived information as input to a forest inventory system
The author has identified the following significant results. Analysis of LANDSAT temporal data, specifically the digitally merged winter and summer scenes, provided the best overall classification results. Comparison of temporal classification results with available ground truth reveal a 94% agreement in the delineation of hardwood categories, a 96% agreement for the combined pine category, and a greater than 50% agreement for each individual pine subcategory. For nearly 1000 acres, compared clearcut acreage estimated with LANDSAT digital data differed from company inventory records by only 3%. Through analysis of summer data, pine stands were successfully classified into subcategories based upon the extent of crown closure. Maximum spectral separability of hardwood and pine stands was obtained from the analysis of winter data.
Williams, D. L.↗
Geology of Kharga-Dakhla Oases area, western desert, Egypt, from LANDSAT-1 satellite images
There are no author-identified significant results in this report.
Elshazly, E. M.↗
Evaluation program for secondary spacecraft cells: Initial evaluation tests of General Electric Company 50.0 ampere hour nickel cadmium spacecraft cells for the LANDSAT-D satellite program
Evaluation tests of eight nickel cadmium cells are described. Although high cell pressures were observed, it is recommended that these cells be placed on a near orbit life test.
Harkness, J. D.↗
LANDSAT 2, 3, and D
The history and operational status of the LANDSAT satellites and processing of LANDSAT imagery are summarized. Multispectral band scanner (MSS) data from LANDSAT 2 are being provided by recorders placed at several foreign ground stations. Return beam vidicon data are being received from LANDSAT 3. Processing and delivery of these data is improving, with disappearance of the backlog projected for 1982. The acquisition of MSS data and data from the thematic mapper (TM) is expected from LANDSAT D, with transfer of MSS data to NOAA projected for 1983 and TM data for 1985.
Salomonson, V. V.↗
On-orbit maintenance and repair - New era in space research and industrialization
During the seventies, NASA was developing a multifunction, economical spacecraft complete with ground and spaceborne support equipment, software, and necessary documentation to facilitate a large variety of space missions on a routine and cost effective basis. In order to reduce costs and time requirements, research was conducted to identify new approaches to a reusable, low-cost spacecraft design. The result of these studies was the development of the Multimission Modular Spacecraft (MMS). Three MMS spacecraft are currently operating in orbit. These spacecraft include the two Landsat-D earth resources satellites, Landsat-4 and -5, and the Solar Maximum Mission (SMM) spacecraft. Attention is given to details regarding the MMS, the STS-41C SMM repair mission, and failure modes and component degradation.
Cepollina, F.↗
Tropical deforestation and habitat fragmentation in the Amazon - Satellite data from 1978 to 1988
Landsat satellite imagery covering the entire forested portion of the Brazilian Amazon Basin was used to measure, for 1978 and 1988, deforestation, fragmented forest, defined as areas less than 100 square kilometers surrounded by deforestation, and edge effects of 1 kilometer into forest from adjacent areas of deforestation. Tropical deforestation increased from 78,000 square kilometers in 1978 to 230,000 square kilometers in 1988 while tropical forest habitat, severely affected with respect to biological diversity, increased from 208,000 to 588,000 square kilometers. Although this rate of deforestation is lower than previous estimates, the effect on biological diversity is greater.
Skole, David↗
Digital image classification approach for estimating forest clearing and regrowth rates and trends
A technique is presented to monitor vegetation changes for a selected study area in Costa Rica. A normalized difference vegetation index was computed for three dates of Landsat satellite data and a modified parallelipiped classifier was employed to generate a multitemporal greenness image representing all three dates. A second-generation image was created by partitioning the intensity levels at each date into high, medium, and low and thereby reducing the number of classes to 21. A sampling technique was applied to describe forest and other land cover change occurring between time periods based on interpretation of aerial photography that closely matched the dates of satellite acquisition. Comparison of the Landsat-derived classes with the photo-interpreted sample areas can provide a basis for evaluating the satellite monitoring technique and the accuracy of estimating forest clearing and regrowth rates and trends.
Sader, Steven A.↗
LANDSAT-D: The new era of earth resources survey
The history of the development and utilization of LANDSAT satellites is summarized. Objectives of the LANDSAT D mission are listed and the capabilities of the 4-channel multispectral band scanner and the 7-channel radiometer (thematic mapper) to be carried on the satellite are described. Satellite components are illustrated and diagrams show the ground segment data management system, the data assessment system, and the operations control center. The flight segment of the mission and flight segment specifications are also described. Examples of digitally analyzed and enhanced imagery are included.
Source record↗
Landsat Data Continuity Mission (LDCM) Ascent and Operational Orbit Design
For the past 40-years, Landsat Satellites have collected Earth's continental data and enabled scientists to assess change in the Earth's landscape. The Landsat Data Continuity Mission (LDCM) is the next generation satellite supporting the Landsat science program. LDCM will fly a 16-day ground repeat cycle, Sun-synchronous, frozen orbit with a mean local time of the descending node ranging between 10:10 am and 10:15 am. This paper presents the preliminary ascent trajectory design from the injection orbit to its final operational orbit. The initial four burn ascent design is shown to satisfy all the LDCM mission goals and requirement and to allow for adequate flexibility in re-planning the ascent.
Mann, Laurie M.↗
Characterization of Potential Springs in the Lower Colorado Desert of Southern California using Satellite Radar and Landsat Time Series Analysis
Renewable energy development in southern California is receiving increasing attention due to potential impacts on wildlife habitats and water sources. This study was designed to quantify and map, for the first time, sub-surface water sources from springs in the Lower Colorado Desert area of southern California using satellite radar data and 30 years of Landsat satellite image data. Synthetic Aperture Radar (SAR) data was used to identify sub-surface water sources not already documented as springs or seeps in the National Hydrography Database. Landsat imagery starting in 1985 was used to characterize vegetation growth patterns at these suspected spring locations detected from SAR analysis. Results showed a total of 104 potential spring locations across the Lower Colorado Desert study area, 19 of which were detected within Solar Energy Zone (SEZ) development boundaries, roughly evenly split between Riverside East and Imperial East, and 13 of which (both inside and outside SEZs) showed relatively high green vegetation index values over the period of 1985 to 2015 that would depend on non-precipitation water sources associated with active springs.
DRECP↗
Mapping Changes in Desert Pavement Surfaces of the Lower Colorado Desert of Southern California Using Landsat Time Series Analysis
Potential disturbance of desert soils from renewable energy development in southern California is receiving increasing attention due to potential impacts on air quality and greenhouse gas emissions. This study was designed to quantify and map, for the first time, changes in desert pavement surface area using 20 years of Landsat satellite image data across the Lower Colorado Desert. Landsat-derived maps of geomorphic surface classes from 1990 to 2014 for the Lower Colorado Desert area showed that a relatively stable area of around 1920 sq km was covered by well-developed desert pavements prior to 2014. Based on 2014 Landsat imagery, coverage of well-developed pavements within solar energy development boundaries of the Lower Colorado Desert area totaled to 421 sq km, the majority of which (>82%) were located in eastern Riverside County. If disturbed as a result of construction activities, these desert pavements could become a source of dust from exposure of the underlying fine particle layer.
Solar energy development↗
Landsat Science: 40 Years of Innovation and Opportunity
Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.
Cook, Bruce D.↗
An Operational Land Imager for the Landsat Data Continuity Mission
The National Aeronautics and Space Administration (NASA) released a request for proposals (RFP) on January 09, 2007 for an Operational Land Imager (OLI). The RFP specified the OLI as the principal sensor for the Landsat Data Continuity Mission (LDCM), the successor mission to Landsat 7. The RFP provides requirements for OLI performance, special calibration tests, and mission assurance without specifying a particular technical design. The performance specifications derive from the heritage and societal benefits of data from the previous Landsat satellites, the high standards set by the performance of the Landsat 7 Enhanced Thematic Mapper-Plus, direction from the Executive Office of the President, cognizance of current technology, and an eye to the future of land remote sensing beyond the LDCM. The specification includes nine spectral bands (four visible, one near infrared, three shortwave infrared, and one panchromatic band), spatial resolution of 30 m with the exception of a 15 m panchromatic resolution, stringent radiometric performance and absolute calibration, and accurate image geolocation with precise band-to-band and multitemporal image-to-image registration. Proposals were due on February 23, 2007 with selection and contract award anticipated by June 2007. The RFP requires delivery of a well-characterized instrument for spacecraft integration within 39 months of contract award. This schedule leads to a target LDCM launch date of July, 2011.
Irons, James R.↗
Training site statistics from Landsat and Seasat satellite imagery registered to a common map base
Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.
Clark, J.↗
On the determination of cloud cover from satellite sensors - The effect of sensor spatial resolution
The effect of sensor spatial resolution on satellite-derived estimates of cloud fractional coverage is quantified on the basis of Landsat satellite radiance data. Cloud fraction is found to depend on cloud algorithm as much as it depends on sensor spatial resolution. Even for 28.5-m spatial resolution data, large cloud fraction differences exist between algorithms. Satellite cloud retrieval algorithms depend strongly on sensor spatial resolution and/or on the optical depth of the cloud field. When present, spatial resolution effects are small (less than 0.01) for pixel diameter less than 1/4 km and are large for pixel diameter larger than 1 km. The International Satellite Cloud Climatology Project bispectral threshold gives an increase in cloud fraction of 0.11 as spatial resolution degrades from 20 m to 8 km. The spatial coherence algorithm underestimates boundary layer cloud fraction by 0.18. The use of functional box counting and an assumption of fractal scale invariance overestimates the dependence of cloud fraction for spatial scales below 1 km.
Wielicki, Bruce A.↗
Use of LANDSAT 2 data technique to estimate silverleaf sunflower infestation
The feasibility of the technique using the Earth Resources Technology Satellite (LANDSAT-2) multispectral scanner (MSS) was tested; to distinguish silverleaf sunflowers (Helianthus argophyllus Torr. and Gray) from other plant species and to estimate the hectarage percent of its infestation. Sunflowers gave high mean digital counts in all four LANDSAT MSS bands that were manifested as a pinkish image response on the LANDSAT color composite imagery. Photo- and LANDSAT-estimated hectare percentages for silverleaf sunflower within a 23,467 ha study area were 9.1 and 9.5%, respectively. The geographic occurrence of sunflower areas on the line-printer recognition map was in good agreement with their known aerial photographic locations.
Richardson, A. J.↗