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NASA NTRS2012

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.↗

NASA NTRS2016

Landsat 8: The Plans, the Reality, and the Legacy

Landsat 8, originally known as the Landsat Data Continuity Mission (LDCM), is a National Aeronautics and Space Administration (NASA)-U.S. Geological Survey (USGS) partnership that continues the legacy of continuous moderate resolution observations started in 1972. The conception of LDCM to the reality of Landsat 8 followed an arduous path extending over nearly 13 years, but the successful launch on February 11, 2013 ensures the continuity of the unparalleled Landsat record. The USGS took over mission operations on May 30, 2013 and renamed LCDM to Landsat 8. Access to Landsat 8 data was opened to users worldwide. Three years following launch we evaluate the science and applications impact of Landsat 8. With a mission objective to enable the detection and characterization of global land changes at a scale where differentiation between natural and human-induced causes of change is possible, LDCM promised incremental technical improvements in capabilities needed for Landsat scientific and applications investigations. Results show that with Landsat 8, we are acquiring more data than ever before, the radiometric and geometric quality of data are generally technically superior to data acquired by past Landsat missions, and the new measurements, e.g., the coastal aerosol and cirrus bands, are opening new opportunities. Collectively, these improvements are sparking the growth of science and applications opportunities. Equally important, with Landsat 7 still operational, we have returned to global imaging on an 8-day cycle, a capability that ended when Landsat 5 ceased operational Earth imaging in November 2011. As a result, the Landsat program is on secure footings and planning is underway to extend the record for another 20 or more years.

Loveland, Thomas R.↗

NASA NTRS1981

Estimation of irrigated land using Landsat digital data

Techniques developed by the University of California and NASA for the utilization of multitemporal Landsat digital data in estimating and mapping irrigated land are presented. Three dates of Landsat were registered to each other and to a USGS 7.5 minute quadrangle map base for approximately 1.9 million acres of land. Other data registered include county boundaries, land use stratification, and digitized ground data. To identify irrigated land, an indicator was used which consisted of the ratio of MSS Band 7 to MSS Band 5 (the 7/5 ratio). A threshold 7/5 irrigated land value was determined for each date, as actively growing land generally has a higher 7/5 ratio than other cover classes. An estimate of irrigated land was determined by Landsat classification with ground data, at a relative standard error of + or - 7.98% at the 95% confidence interval. Mapping evaluation reveals a 94% accuracy, a 7.4% omission rate, and a 6.3% commission rate. In addition, a sample unit size evaluation recommends a 1-1 1/2 square mile sample range.

Brown, C. E.↗

NASA NTRS2015

Landsat-8 Sensor Characterization and Calibration

Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI) is the reflective band sensor and the Thermal Infrared Sensor (TIRS), the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) cooperated in the development, launch and operation of the Landsat- 8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth's surface over the now 43-year record. In order to perform these analyses and avoid confusing sensor changes with Earth surface changes, a solid understanding of the sensors' performance, consistent geolocation and radiometry are essential. Particularly with the significant changes in the Landsat-8 sensors relative to previous Landsat missions, this characterization becomes all the more important.

Radiometry↗

NASA NTRS1981

Use of LANDSAT data to define soil boundaries in Carroll County, Missouri

Bands 4, 5 and 7 false color composite photographs were prepared using data from LANDSAT scenes acquired during April 1977 and April 1981 on computer compatible tapes, and these color composites were compared with band 7 black and white photographs prepared for the entire county. Delineations of soil boundaries at the soil association level were achieved using LANDSAT spectral reflectance data and slope maps for a portion of Carroll County, Missouri. Forty two spectral reflectance classes from April 1977 LANDSAT data were overlaid on digitized slope maps of nine USGS 7.5 minute series topographic quadrangle slope maps to achieve boundary delineations of the soil associations.

Davidson, S. E.↗

NASA NTRS2004

Status of the Landsat Data Continuity Mission

Efforts to begin implementing a successor mission to Landsat 7, called the Landsat Data Continuity Mission (LDCM), suffered a set back in 2003. NASA and the Department of Interior (DOI)/U.S. Geological Survey (USGS) currently manage the Landsat Program as an interagency partnership. The two agencies had planned to purchase data meeting LDCM specifications from a privately owned and commercially operated satellite system beginning in March, 2007. This approach represented a departure from the traditional procurement of a government owned and operated satellite system. NASA, however, cancelled a Request-for-Proposals (RFP) for providing the required data after an evaluation of proposals received from private industry. NASA concluded that the proposals failed to meet a key objective and expectation of the RFP, namely, to form a fair and equitable partnership between the Government and private industry. Alternative strategies for implementing an LDCM are now under consideration. The Executive Office of the President formed an interagency working group on the LDCM following the RFP cancellation. The working group is considering other options for implementing a successor system to Landsat 7 consistent with the Land Remote Sensing Policy Act of 1992 (Public Law 102-555). This Act lists four management options for consideration: 1) private sector funding and management; 2) an international consortium; 3) funding and management by the U.S. Government; and 4) a cooperative effort between the US. Government and the private sector. The working group is currently attempting to minimize the risk of a Landsat data gap through development of a strategy that leads to a Landsat 7 successor mission. The selected strategy and the status of the mission will be presented at the Symposium.

Irons, James R.↗

NASA NTRS1993

Pargo Chasma and its relationship to global tectonics

Pargo Chasma was first identified on Pioneer Venus data as a 10,000 km long lineation extending from Atla Regio in the north terminating in the plains south of Phoebe Regio. More recent Magellan data have revealed this feature to be one of the longest chains of coronae so far identified on the planet. Stofan et al have identified 60 coronae and 2 related features associated with this chain; other estimates differ according to the classification scheme adopted, for example Head et al. identify only 29 coronae but 43 arachnoids in the same region. This highlights one of the major problems associated with the preliminary mapping of the Magellan data: there has been an emphasis on identifying particular features on Venus without a universally accepted scheme to classify those features. Nevertheless, Pargo Chasma is clearly identified as a major tectonic belt of global significance. Together with the Artemis-Atla-Beta tectonic zone and the Beta-Phoebe rift belt, Pargo Chasma defines a region on Venus with an unusually high concentration of tectonic and volcanic features. Thus, an understanding of the processes involved in the formation of Pargo Chasma may lend significant insight into the evolution of the region and the planet as a whole. I have produced a detailed 1 to 10 million scale map of Pargo Chasma and the surrounding area from preliminary USGS controlled mosaiced image maps of Venus constructed from Magellan data. In view of the problems highlighted above in relation the efforts already made at identifying a particular set of features I have mapped the region purely on the basis of the geomorphology visible in the magellan data without any attempt at identifying a particular set or class of features. Thus, the map produced distinguishes between areas of different brightness and texture. This has the advantage of highlighting the tectonic fabric of Pargo Chasma and clearly illustrates the close inter-relationship between individual coronae and the surrounding tectonic belts.

Ghail, R. C.↗

NASA NTRS1973

Evaluation of land use mapping from ERTS in the shore zone of CARETS

Imagery of the Atlantic shoreline zone of the Central Atlantic Regional Ecological Test Site (CARETS) was evaluated for classifying land use and land cover, employing the USGS Geographic Application Program's land use classification system. ERTS data can provide a basis for land cover and land use mapping within the shoreline zone, however because of the dynamic nature of this environment, two additional terms are considered: vulnerability of classes to storms and progressive erosion, and sensitivity of the classes to man's activities.

Dolan, R.↗

NASA NTRS1987

Refining image segmentation by polygon skeletonization

A skeletonization algorithm was encoded and applied to a test data set of land-use polygons taken from a USGS digital land use dataset at 1:250,000. The distance transform produced by this method was instrumental in the description of the shape, size, and level of generalization of the outlines of the polygons. A comparison of the topology of skeletons for forested wetlands and lakes indicated that some distinction based solely upon the shape properties of the areas is possible, and may be of use in an intelligent automated land cover classification system.

Clarke, Keith C.↗

NASA NTRS2012

The Landsat Data Continuity Mission Operational Land Imager (OLI) Sensor

The Landsat Data Continuity Mission (LDCM) is being developed by NASA and USGS and is currently planned for launch in January 2013 [1]. Once on-orbit and checked out, it will be operated by USGS and officially named Landsat-8. Two sensors will be on LDCM: the Operational Land Imager (OLI), which has been built and delivered by Ball Aerospace & Technology Corp (BATC) and the Thermal Infrared Sensor (TIRS)[2], currently being built and tested at Goddard Space Flight Center (GSFC) with a planned delivery of Winter 2012. The OLI covers the Visible, Near-IR (NIR) and Short-Wave Infrared (SWIR) parts of the spectrum; TIRS covers the Thermal Infrared (TIR). This paper discusses only the OLI instrument and its pre-launch characterization; a companion paper covers TIRS.

Markham, Brian L.↗

NASA NTRS2019

Monitoring Volcanic Eruptions by OMI/OMPS, ASTER, and MERRA-2

Volcanic lava flows and/or the gas eruptions are the most common characteristics that can be remotely monitored with satellite technology in the global perspective and on different timescales. Atmospheric Sulfur Dioxide (SO2), one of the most abundant gases from volcanic eruptions apart from atmospheric common gases Carbon Dioxide and water vapor, can be directly detected by space-based sensors on satellites. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of the 12 Distributed Active Archive Centers (DAACs) within NASA's Earth Observing System Data and Information System (EOSDIS), which archives SO2 data sets from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) in 1978, till the ongoing Ozone Monitoring Instrument (OMI) on NASA's EOS-Aura satellite, the Ozone Mapping Profiler Suite (OMPS) Nadir Mapper (NM) on both the Suomi National Polar-Orbiting Partnership (Suomi-NPP or SNPP) and the Joint Polar-orbiting Satellite System-1 (JPSS-1) satellites, into the future JPSS missions. In addition to the standard OMI/Aura and OMPS/S-NPP SO2 products, SO2 products created under the charter of the Making Earth System Data Records for Use in Research Environments (MEaSUREs) project, are also archived at GES DISC, through which NASA enacts to expand understanding the Earth system using consistent data records. The Land Processes Distributed Active Archive Center (LP DAAC) is another EOSDIS's DAAC that provides land data products and operates as a partnership with the U.S. Geological Survey (USGS). The LP DAAC has been archiving the satellite imagery from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard NASA's EOS-Terra satellite, a high spatial resolution (15 meters) and 14 band multispectral instrument. The ASTER imagery is one of the land products contributing to the application for monitoring hot spots and land terrain changes caused by volcanic eruption events. The data potential in GES DISC and LP DAAC to monitor volcanic sources of SO2 and the influence of wind fields on the gas plume spread will be demonstrated with the most recent 2018 May-July Kilauea Volcano eruption.

Zeng, Jian↗

NASA NTRS2011

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Spruce, Joseph P.↗

NASA NTRS1983

Geometric accuracy of LANDSAT-4 MSS image data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CCT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 x 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSATS -1, -2 and -3.

Welch, R.↗

NASA NTRS1984

Geometric Accuracy of LANDSAT-4 MSS Image Data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CTT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 by 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSAT-1, -2 AND -3.

Welch, R.↗

NASA NTRS2006

Spatial Resolution Characterization for Aerial Digital Imagery

The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration have jointly conducted characterizations of aerial digital imagery from commercial data providers. In a typical scenario, a vendor acquired imagery over the Stennis Space Center test range and provided a common data package to SSC. SSC personnel analyzed the geopositional accuracy and spatial resolution of the images, then documented the characterization results in a report and delivered the report to the USGS. Spatial resolution characterization was based on edge response measurements using one of the SSC edge targets and the tilted-edge technique. Relative Edge Response (RER) has been estimated for aerial digital imagery from several commercial data providers. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale.

Blonski, Slawomir↗

NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗

NASA NTRS2012

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Spruce, Joseph P.↗

NASA NTRS2013

Planetary Data Systems (PDS) Imaging Node Atlas II

The Planetary Image Atlas (PIA) is a Rich Internet Application (RIA) that serves planetary imaging data to the science community and the general public. PIA also utilizes the USGS Unified Planetary Coordinate system (UPC) and the on-Mars map server. The Atlas was designed to provide the ability to search and filter through greater than 8 million planetary image files. This software is a three-tier Web application that contains a search engine backend (MySQL, JAVA), Web service interface (SOAP) between server and client, and a GWT Google Maps API client front end. This application allows for the search, retrieval, and download of planetary images and associated meta-data from the following missions: 2001 Mars Odyssey, Cassini, Galileo, LCROSS, Lunar Reconnaissance Orbiter, Mars Exploration Rover, Mars Express, Magellan, Mars Global Surveyor, Mars Pathfinder, Mars Reconnaissance Orbiter, MESSENGER, Phoe nix, Viking Lander, Viking Orbiter, and Voyager. The Atlas utilizes the UPC to translate mission-specific coordinate systems into a unified coordinate system, allowing the end user to query across missions of similar targets. If desired, the end user can also use a mission-specific view of the Atlas. The mission-specific views rely on the same code base. This application is a major improvement over the initial version of the Planetary Image Atlas. It is a multi-mission search engine. This tool includes both basic and advanced search capabilities, providing a product search tool to interrogate the collection of planetary images. This tool lets the end user query information about each image, and ignores the data that the user has no interest in. Users can reduce the number of images to look at by defining an area of interest with latitude and longitude ranges.

Stanboli, Alice↗