EROS Data Center Research Articles

TWO METHODS FOR SELF CALIBRATION OF DIGITAL CAMERA

Abstract. Photogrammetric mapping using Commercial of the Shelf (COTS) cameras is becoming more popular. Their popularity is augmented by the increasing use of Unmanned Aerial Vehicles (UAV) as a platform for mapping. The mapping precision of these methods can be increased by using a calibrated camera. The USGS/EROS has developed an inexpensive, easy to use method, particularly for calibrating short focal length cameras. The method builds on a self-calibration procedure developed for the USGS EROS Data Center by Pictometry (and augmented by Dr. C.S Fraser), that uses a series of coded targets. These coded targets form different patterns that are imaged from nine different locations with differing camera orientations. A free network solution using collinearity equations is used to determine the calibration parameters. For the smaller focal length COTS cameras, the USGS has developed a procedure that uses a small prototype box that contains these coded targets. The design of the box is discussed, along with best practices for calibration procedure. Results of calibration parameters obtained using the box are compared with the parameters obtained using more established standard procedures.

Leaf area index of a tropical semi-deciduous forest of the southern Amazon Basin

Leaf area index (LAI) is an important ecophysiological variable because leaves are the organs responsible for gas exchange between plants and the atmosphere. This variable can be calculated from primary values of leaf area assessed by destructive or non-destructive methods, which is relatively easy when crop species are investigated, but is not the case when the focus is on natural wood plants communities. In this paper, we analyze the seasonality of LAI estimated by three different methods in the Amazonia-savannah transitional forest, located 50km north-east of Sinop city, Mato Grosso, Brazil. In the first method, we combine Monsi and Saekis' original method [Monsi M, Saeki T (1953) Jpn J Bot 14:22-52], which measures LAI using the Beer-Lambert extinction law, and the proposition of Goudriaan [Goudriaan J (1988) Agric For Meteorol 43:155-169] to estimate the extinction coefficient from solar height. The second method differed from the first only in the way in which the daily fraction of intercepted photosynthetic active radiation (FPAR) was calculated, as proposed by Charles-Edwards and Lawn (Charles-Edwards DA, Lawn RJ (1984) Plant Cell Environ 7:247-251]. In the third method, we used a remote sensing technique [MOD15_BU-collection 4, produced and distributed by EROS Data Center Distributed Active Archive Center (EDC DAAC)]. We found that the first and the second methods revealed the expected LAI dynamics, which increased during the dry-wet transition and wet season, and decreased during the wet-dry transition and dry season. From 20 randomly distributed sets in a 1.0 ha area, only 3 showed significant differences in LAI estimated from the first two methods; conversely, LAI was overestimated by the third method.

The Colorado River Delta: Regional Geomorphology and Sedimentary Processes

Surrounding the Colorado River Delta is the Sonoran sand sea to the east, delta deposits to the north, and basin and range country plus tidal salt flats to the west. Eolian sands at the western end of the sand sea form a 100-m high escarpment between the Sonoran desert–plateau and the Gulf of California. The western edge of the sand sea has a narrow zone of badland topography with well-developed dendritic drainage patterns. Where the sand sea meets the Gulf of Mexico, eolian sands predominate along the strand. Geometry of the spits indicates a net northward transport of eolian sands into the channel and shoal architecture of the delta. An array of longshore mudflats, salt flats, spits, bars, and coastal dunes dominate the shores of the Gulf.The USGS EROS data center provided standard images on CD-ROM to order. Browse images and metadata sets are easily accessible via the Internet. Included are the latest Landsat 7 thematic mapper (ETM ) images exploiting the multispectral and panchromatic imagery of this new sensor. The image size of Lansat ∼ 185 × 185 is particularly valuable in study of deltas because most will fit in a single frame. The revisit time interval of 15 d, however, falls way short of what is needed in coastal waters.

THE NATIONAL BASIN DELINEATION PROJECT

The National Basin Delineation Project (NBDP) was undertaken by the National Severe Storms Laboratory to define flash-flood-scale basin boundaries for the country in support of the National Weather Service (NWS) Flash Flood Monitoring and Prediction (FFMP) system. FFMP-averaged basin rainfall calculations allow NWS forecasters to monitor precipitation in flash-flood-scale basins, improving their ability to make accurate and timely flash-flood-warning decisions. The NBDP was accomplished through a partnership with the U.S. Geological Survey Earth Resources Observation Systems (EROS) Data Center (EDC). The one-arc-second (approximately 30 m)-resolution digital terrain data in the EDC's National Elevation Dataset provided the basis for derivation of the following digital maps using a geographic information system: 1) a grid of hydrologically conditioned elevation values (all grid cells have a defined flow direction), 2) a grid of flow direction indicating which of eight directions water will travel based on slope, 3) a grid of flow accumulation containing a count of the number of upstream grid cells contributing flow to each grid cell, 4) synthetic streamlines derived from the flow accumulation grid, and 5) flash-flood-scale basin boundaries. Special techniques were applied in coastal areas and closed basins (basins with no outflow) to ensure the accuracy of derived basins and streams. Codifying each basin with a unique identifier and including hydrologic connectivity information produced a versatile, seamless dataset for use in FFMP and other national applications.

Supporting users through integrated retrieval, processing, and distribution systems at the Land Processes Distributed Active Archive Center

The US Geological Survey's EROS Data Center (EDC) hosts the Land Processes Distributed Active Archive Center (LP DAAC). The LP DAAC supports NASA's Earth Observing System (EOS), which is a series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. The EOS Data and Information Systems (EOSDIS) was designed to acquire, archive, manage and distribute Earth observation data to the broadest possible user community. The LP DAAC is one of four DAACs that utilize the EOSDIS Core System (ECS) to manage and archive their data. Since the ECS was originally designed, significant changes have taken place in technology, user expectations, and user requirements. Therefore the LP DAAC has implemented additional systems to meet the evolving needs of scientific users, tailored to an integrated working environment. These systems provide a wide variety of services to improve data access and to enhance data usability through subsampling, reformatting, and reprojection. These systems also support the wide breadth of products that are handled by the LP DAAC. The LP DAAC is the primary archive for the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data; it is the only facility in the United States that archives, processes, and distributes data from the Advanced Spaceborne Thermal Emission/Reflection Radiometer (ASTER) on NASA's Terra spacecraft; and it is responsible for the archive and distribution of “land products” generated from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua satellites.

IKONOS geometric characterization

The IKONOS spacecraft acquired images on July 3, 17, and 25, and August 13, 2001 of Brookings SD, a small city in east central South Dakota, and on May 22, June 30, and July 30, 2000, of the rural area around the EROS Data Center. South Dakota State University (SDSU) evaluated the Brookings scenes and the USGS EROS Data Center (EDC) evaluated the other scenes. The images evaluated by SDSU utilized various natural objects and man-made features as identifiable targets randomly distribution throughout the scenes, while the images evaluated by EDC utilized pre-marked artificial points (panel points) to provide the best possible targets distributed in a grid pattern. Space Imaging provided products at different processing levels to each institution. For each scene, the pixel (line, sample) locations of the various targets were compared to field observed, survey-grade Global Positioning System locations. Patterns of error distribution for each product were plotted, and a variety of statistical statements of accuracy are made. The IKONOS sensor also acquired 12 pairs of stereo images of globally distributed scenes between April 2000 and April 2001. For each scene, analysts at the National Imagery and Mapping Agency (NIMA) compared derived photogrammetric coordinates to their corresponding NIMA field-surveyed ground control point (GCPs). NIMA analysts determined horizontal and vertical accuracies by averaging the differences between the derived photogrammetric points and the field-surveyed GCPs for all 12 stereo pairs. Patterns of error distribution for each scene are presented.

Remote Sensing and GIS as Counterterrorism Tools in the Afghanistan War: A Case Study of the Zhawar Kili Region*

Rocks forming the backdrop of video footage of an admitted September 11 terrorist appeared to the author to belong to the Kurram Group of eastern Afghanistan. The cultural geography and military history of the area suggested that the terrorist was in or near the Zhawar Kili cave complex. Band-ratio satellite image mapping combined with public National Imagery and Mapping Agency and United Nations databases confirmed that Zhawar Kili is on Kurram Group rocks. This information was forwarded to the U.S. government in October 2001. Military and news media reports indicate the subsequent successful elimination of a large number of terrorists and munitions at Zhawar Kili in November 2001 and January, February, and April of 2002. *The author thanks the USGS's EROS Data Center for assistance with satellite image collection and travel support to key facilities, the National Aeronautics and Space Administration's (NASA) Glenn Research Center in Cleveland, Ohio for the provision of secure processing facilities, the NASA Stennis Space Center's Science Data Purchase for high-resolution data, and TRW, Raytheon, Lockheed-Martin, Space Imaging, Kodak, and Research Systems for technical support. Howard Stafford, Robert South, Truman Hartshorn, and two unidentified reviewers provided valuable suggestions that improved this manuscript significantly. This work was supported by grants from NASA and the USGS.

Mapping from ASTER stereo image data: DEM validation and accuracy assessment

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on-board the National Aeronautics and Space Administration's (NASA's) Terra spacecraft provides along-track digital stereo image data at 15-m resolution. As part of ASTER digital elevation model (DEM) accuracy evaluation efforts by the US/Japan ASTER Science Team, stereo image data for four study sites around the world have been employed to validate prelaunch estimates of heighting accuracy. Automated stereocorrelation procedures were implemented using the Desktop Mapping System (DMS) software on a personal computer to derive DEMs with 30- to 150-m postings. Results indicate that a root-mean-square error (RMSE) in elevation between ±7 and ±15 m can be achieved with ASTER stereo image data of good quality. An evaluation of an ASTER DEM data product produced at the US Geological Survey (USGS) EROS Data Center (EDC) yielded an RMSE of ±8.6 m. Overall, the ability to extract elevations from ASTER stereopairs using stereocorrelation techniques meets expectations.

Global Forest Cover Mapping for the United Nations Food and Agriculture Organization Forest Resources Assessment 2000 Program

Abstract Many countries periodically produce national reports on the status and changes of forest resources, using statistical surveys and spatial mapping of remotely sensed data. At the global level, the Food and Agriculture Organization (FAO) of the United Nations has conducted a Forest Resources Assessment (FRA) program every 10 yr since 1980, producing statistics and analysis that give a global synopsis of forest resources in the world. For the year 2000 of the FRA program (FRA2000), a global forest cover map was produced to provide spatial context to the extensive survey. The forest cover map, produced at the U.S. Geological Survey (USGS) EROS Data Center (EDC), has five classes: closed forest, open or fragmented forest, other wooded land, other land cover, and water. The first two forested classes at the global scale were delineated using combinations of temporal compositing, modified mixture analysis, geographic stratification, and other classification techniques. The remaining three FAO classes were derived primarily from the USGS global land cover characteristics database (Loveland et al. 1999). Validated on the basis of existing reference data sets, the map is estimated to be 77% accurate for the first four classes (no reference data were available for water), and 86% accurate for the forest and nonforest classification. The final map will be published as an insert to the FAO FRA2000 report. FOR. SCI. 49(3):369–380.

Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data

Evaluation of an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image of the Mountain Pass, California area indicates that several important lithologic groups can be mapped in areas with good exposure by using spectral-matching techniques. The three visible and six near-infrared bands, which have 15-m and 30-m resolution, respectively, were calibrated by using in situ measurements of spectral reflectance. Calcitic rocks were distinguished from dolomitic rocks by using matched-filter processing in which image spectra were used as references for selected spectral categories. Skarn deposits and associated bright coarse marble were mapped in contact metamorphic zones related to intrusion of Mesozoic and Tertiary granodioritic rocks. Fe-muscovite, which is common in these intrusive rocks, was distinguished from Al-muscovite present in granitic gneisses and Mesozoic granite. Quartzose rocks were readily discriminated, and carbonate rocks were mapped as a single broad unit through analysis of the 90-m resolution, five-band surface emissivity data, which is produced as a standard product at the EROS Data Center. Three additional classes resulting from spectral-angle mapper processing ranged from (1) a broad granitic rock class (2) to predominately granodioritic rocks and (3) a more mafic class consisting mainly of mafic gneiss, amphibolite and variable mixtures of carbonate rocks and silicate rocks.

Sky type discrimination using a ground-based sun photometer

A 2-year feasibility study was conducted at the USGS EROS Data Center, South Dakota (43.733°N, 96.6167°W) to assess whether a four-band, ground-based, sun photometer could be used to discriminate sky types. The results indicate that unique spectral signatures do exist between sunny skies (including clear and hazy skies) and cirrus, and cirrostratus, altocumulus or fair-weather cumulus, and thin stratocumulus or altostratus, and fog/fractostratus skies. There were insufficient data points to represent other cloud types at a statistically significant level.

The work of the US National Satellite Land Remote Sensing Data Archive Advisory Committee: 1998–2000

Earth observation data have been acquired and stored since the early 1970 s. One of the world's largest, and most important, repositories for land satellite data is the Earth Resources Observation Systems (EROS) Data Center (EDC). It is a data management, systems development and research field center for the US Geological Survey's (USGS) National Mapping Division in Sioux Falls, SD, USA. It was established in the early 1970 s and, in 1992, the US Congress established the National Satellite Land Remote Sensing Data Archive at EDC. Although data have been acquired and stored for decades, the world's remote sensing community has only recently begun to address long-term data preservation and access. One such effort was made recently by remote sensing leaders from academia, industry and government as members of a federal advisory committee from 1998 to 2000. 2 2 http://edc.usgs.gov/programs/nslrsda/advisory/index.html. This paper provides a brief account of the Committee's work product.

Distribution of crustal extension and regional basin architecture of the Albertine rift system, East Africa

By applying a kinematic and flexural model for the extensional deformation of the lithosphere, and using a recently available EROS Data Center topography DEM of Africa in conjunction with new and previous gravity data from Lakes Albert, Edward and George, we have determined the distribution, amplitude, and style of deformation responsible for the formation of the Albertine rift system, East Africa. Further, we have been able to approximate the three-dimensional architecture of the Albertine rift basin by analyzing a series of profiles across and along the rift system for which we also estimate the flexural strength of the rifted continental lithosphere and its along-strike variation. Previous modeling studies of the Lake Albert basin either overestimated the flexural strength of the extended lithosphere and/or underestimated the crustal extension. The single most important factor that compromised the success of these modeling efforts was the assumption that crustal extension was limited to the present-day distribution of the rift lakes. The style of deformation appears to have changed with time, beginning with a regionally distributed brittle deformation across the region that lead progressively to the preferential growth and development of the major border faults and antithetic/synthetic faults within the collapsed hangingwall block. Minor fault reactivation within the footwall block appears to be related to the release of bending stresses associated by the flexural uplift of the rift flank topography. By simultaneously matching the observed and modeled topography and free-air gravity across the Albertine rift system, we have determined a cumulative extension ranging from 6 to 16 km with the maximum extension occurring in the central and northern segments of the basin. Crustal extension is not constrained to the lake proper, but extends significantly to the east within the hangingwall block. Effective elastic thickness, T e, varies between 24 and 30 km and is unrelated to either the amount of extension or the maximum sediment thickness. The variation of T e relates possibly to small changes in crustal thickness, heterogeneities in crustal composition, and/or variations in radiogenic crustal heat production. Maximum sediment thickness is predicted to be 4.6 km and occurs within the central region of Lake Albert. Low bulk sediment densities, correlating with the location of major lake deltas, may be indicative of present-day sediment overpressures. Our results show that basin geometry is strongly dependent on the cumulative (and distribution) of lithospheric extension and the flexural rigidity of the lithosphere. Thus, in order to determine the total amount of extension responsible for the formation of a basin system, it is necessary to independently constrain the flexural strength of the lithosphere both during and after extension. Conversely, in order to determine the rigidity of extended lithosphere using the stratigraphy and/or geometry of rift basins and passive margins, it is necessary to independently constrain the cumulative extension of the lithosphere.

Preserving satellite archives

The U.S. Geological Survey's (USGS) EROS Data Center in Sioux Falls, South Dakota, presently houses one of the world's largest collections of aerial and satellite images of the Earth's land surface.Now, the Survey will also archive hundreds of thousands of additional satellite images that complement its Landsat collection and fill in gaps in Landsat coverage of low cloud cover images.

Ohioview: The Leadership Role of Libraries in Science and Technology Partnerships

The Ohioview Research Consortium was formed to improve distribution and access to data acquired from U.S. Government civilian satellites. Ohioview is a group of Ohio universities, the U.S. Geological Survey's EROS Data Center in Sioux Falls SD, the NASA Glenn Research Center in Cleveland OH, The Ohio Library and Information Network, and NREN. What is unique about this consortium is that the university library component has been called upon to play a strong leadership role. Background of the Ohioview Research Consortium is discussed, as well as challenges the group has faced. Finally the role of the Miami University Libraries in the Ohioview consortium is discussed.

New land surface digital elevation model covers the Earth

Land surface elevation around the world is reaching new heights—as far as its description and measurement goes. A new global digital elevation model (DEM) is being cited as a significant improvement in the quality of topographic data available for Earth science studies.Land surface elevation is one of the Earth's most fundamental geophysical properties, but the accuracy and detail with which it has been measured and described globally have been insufficient for many large‐area studies. The new model, developed at the U.S. Geological Survey's (USGS) EROS Data Center (EDC), has changed all that.

Landsat MSS-derived land-cover map of northern Alaska: Extrapolation methods and a comparison with photo-interpreted and AVHRR-derived maps

Vegetation maps of Arctic areas are needed for a variety of tundra ecosystem and climate change studies and for extrapolating from relatively small, well-known sites to broader regions. We made a preliminary land-cover map of northern Alaska by extrapolating a Landsat Multi-Spectral Scanner (MSS) derived classification of the Kuparuk River Region (KRR) to all of northern Alaska. We used a 26-scene mosaic that was previously made by the EROS Data Center, and a K-means unsupervised classification algorithm to produce eight broad land-cover categories. The northern Alaska-MSS map (NA-MSS) has the following land-cover categories and respective percentage coverage within the 200000km2 Arctic Slope: Dry Prostrate-shrub Tundra and Barrens, 8%; Moist Graminoid, Prostrate-shrub Tundra, 22%; Moist Tussock-graminoid, Dwarf-shrub Tundra, 4%; Moist Dwarf-shrub, Tussock-graminoid, Tundra, 28%; Moist Lowshrub Tundra and other Shrublands, 19%; Wet Graminoid Tundra, 9%; Water, 6%; Clouds and ice, <1%; Shadows, 4%. Ancillary data were used to improve the classification for a region of sandy tundra not encountered in the KRR and to separate shadows in the mountains from water and wetlands elsewhere. The NA-MSS map helps to define the distribution of a recently described moist nonacidic (calcareous) tundra and areas of shrublands that are of broad interest to the tundra- and climate-change modelling communities. A boundary separating moist acidic tundra from moist nonacidic tundra stretches across all of northern Alaska (about 850km). Shrub-dominated tundra is prevalent in the southern and western (warmer, wetter) portions of the map. We created difference maps for comparing the northern Alaska-MSS (NA-MSS) map to the Major Ecosystems of Alaska (MEA) map and a map derived from a time series of Advanced Very High Resolution Radiometer images (NA-AVHRR). Compared to the other maps, the NA-MSS map provides more detailed information for moist tundra areas and shows more shrub-dominated vegetation with different spatial distributions than the other two maps. An accuracy assessment of the map will be performed in 1999.

ASTER as a source for topographic data in the late 1990s

Topography is a fundamental Earth characteristic that can be measured for studies of the land surface. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard the EOS-AM1 platform will acquire along-track stereo data for topographic mapping. ASTER is capable of recording 771 digital stereo pairs per day, each covering 60/spl times/60 km on the ground, at 15-m resolution, with a base-to-height ratio of 0.6. According to present plans, approximately 30 digital elevation models (DEMs), accurate to within /spl plusmn/7 to /spl plusmn/50 m (RMSE/sub z/) will be produced daily by processing facilities in Japan and the United States. The Land Processes Distributed Active Archive Center (LP-DAAC) at the United States Geological Survey's (USGS's) EROS Data Center (EDC) will emphasize the use of automated stereocorrelation procedures to produce absolute DEMs tied to ground control. During the six-year mission, ASTER has the potential to provide a coherent, digital stereo data set covering all of the Earth's land surface. At minimum, ASTER DEMs will augment topographic data from other sources. Results of simulations of ASTER stereo data using existing satellite and aircraft data over validation sites in Huntsville, AL, and Iguala, Mexico, illustrate the value of high-resolution ASTER DEMs and how actual ASTER DEMs will be validated.

North American landscape characterization project: The production of a continental scale three‐decade Landsat data set

The North American Landscape Characterization (NALC) project is a component of the National Aeronautics and Space Administration (NASA) Landsat Pathfinder program. Pathfinder projects are focused on the investigation of global change utilizing current remote sensing technologies. The NALC project is a cooperative effort between the U. S. Environmental Protection Agency (EPA), the U.S. Geological Survey (USGS), and NASA to make Landsat data available to the widest possible user community for scientific research and general public interest. The NALC project is principally funded by the EPA Office of Research and Development and the USGS's Earth Resources Observation Systems (EROS) Data Center (EDC). The objectives of the NALC project are to produce standardized remote sensing data sets, develop standardized analysis methods, and derive standardized land cover change products for a large portion of the North American continent (the conterminous United States and Mexico) (Lunetta and Sturdevant, 1993). The standard product is the NALC “triplicate”;, consisting of co‐registered Landsat multispectral scanner data for the years 1973, 1986, and 1991 (plus or minus one year), plus co‐registered 3 arcsecond digital terrain elevation data. Processing began with the 1986 scene, which was precision corrected (with full terrain correction) to a 60 meter Universal Transverse Mercator base. Automated cross‐correlation procedures were used to co‐register the 1970's and 1990's data to the 1980's base, and independent verifications of registration quality were performed on all triplicate components. The pertinent metadata were compiled in a relational database, which includes WRS2 path/rows, scene ID's, image dates, solar azimuth and elevation, verification RMSE's, and the number of verification control points. NALC triplicate data sets are being used for a number of applications, including the analysis of urbanization patterns, dynamics of climatic fluctuations, deforestation studies, and vegetation classification and mapping. These data are being distributed through the Earth Observing System Data and Information System (EOSDIS) Information Management System (IMS) at a cost of $15(U.S.) for each triplicate.

A summary of Asian vegetation using annual vegetation dynamic indicators

Time series Advanced Very High Resolution Radiometer (AVHRR) data of eastern Asia for the period April to October 1992 have been analyzed to produce statistically independent annual indicators of vegetation development. Monthly AVHRR data composites used in the analysis were generated by USGS EROS Data Center using the maximum Normalized Difference Vegetation Index (NDVI) approach to produce a cloud free representation of eastern Asia. The time series data were analyzed to determine whether a phenologically based transformation could assist analysis of vegetation dynamics and understanding of landscape features. The reflective channels of each monthly composite were transformed to Tasseled Cap greenness and brightness. Comparison of the sun angle corrected greenness feature to NDVI favored use of greenness in the analysis. Using principal components methods, a linear transformation of the lime series greenness was discovered. The transformation describes ninety percent of scene greenness variation in four variables. These variables include cumulative greenness (the sum of greenness for each date), summer greenness flux (the contrast of summer biomass productivity to the rest of the year), early season greenness flux (a measure of early season biomass productivity), and periodic greenness flux (biomass productivity attributable to multiple cropping). The transformation enables effective visualization of vegetation dynamics in a single image, capturing dominant biological patterns. Imagery formed using annual vegetation dynamic indicators illustrates the potential of employing the transformation to interpret land cover, and identify natural temporal dynamics as well as those that are a result of human intervention, like multiple cropping.