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At least 37 records · Page 2Linked to original sources
USGS2004

The characteristics and interpretability of land surface change and implications for project design

The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

Photogrammetric Engineering and Remote Sensing↗
USGS2004

Development of a 2001 National Land Cover Database for the United States

Multi-Resolution Land Characterization 2001 (MRLC 2001) is a second-generation Federal consortium designed to create an updated pool of nation-wide Landsat 5 and 7 imagery and derive a second-generation National Land Cover Database (NLCD 2001). The objectives of this multi-layer, multi-source database are two fold: first, to provide consistent land cover for all 50 States, and second, to provide a data framework which allows flexibility in developing and applying each independent data component to a wide variety of other applications. Components in the database include the following: (1) normalized imagery for three time periods per path/row, (2) ancillary data, including a 30 m Digital Elevation Model (DEM) derived into slope, aspect and slope position, (3) perpixel estimates of percent imperviousness and percent tree canopy, (4) 29 classes of land cover data derived from the imagery, ancillary data, and derivatives, (5) classification rules, confidence estimates, and metadata from the land cover classification. This database is now being developed using a Mapping Zone approach, with 66 Zones in the continental United States and 23 Zones in Alaska. Results from three initial mapping Zones show single-pixel land cover accuracies ranging from 73 to 77 percent, imperviousness accuracies ranging from 83 to 91 percent, tree canopy accuracies ranging from 78 to 93 percent, and an estimated 50 percent increase in mapping efficiency over previous methods. The database has now entered the production phase and is being created using extensive partnering in the Federal government with planned completion by 2006.

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Photogrammetric analysis of the Mars Global Surveyor mapping data

This paper studies the photogrammetric mapping properties and capabilities of the Mars Global Surveyor (MGS) mapping data. Starting from the raw MGS data, we decompress the MOC narrow angle images, extract, and calculate their exterior orientation from the SPICE kernels, and calculate the 3D coordinates of MOLA footprints from MOLA PEDR files. A new approach is proposed that registers a MOLA profile to stereo MOC images over the same area with robust and faster convergence. Intersection is conducted to determine the 3D positions of image points measured on MOC stereo pairs. It is shown that there is a nearly constant uncertainty of one MOLA ground spacing distance (approximately 325 m) along the flight direction in MOC and MOLA registration. This is caused by the uncertainties in SPICE kernels, MOLA points, and the determination of time tags for MOC scan lines, which possibly constitutes the dominant error source for the registration. Intersection calculation reaches an optimal balance by distributing the uncertainty evenly in the two images of a stereo pair. As for the photogrammetric mapping capabilities, an uncertainty of 180.8 m in planimetric distance and 30.8 m in elevation difference is estimated. A number of numerical and graphic results over three of the selected candidate landing sites for the Mars Exploration Rover mission are presented for analysis and illustration.

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Initial results of rover localization and topographic mapping for the 2003 mars exploration rover mission

This paper presents the initial results of lander and rover localization and topographic mapping of the MER 2003 mission (by Sol 225 for Spirit and Sol 206 for Opportunity). The Spirit rover has traversed a distance of 3.2 km (actual distance traveled instead of odometry) and Opportunity at 1.2 km. We localized the landers in the Gusev Crater and on the Meridiani Planum using two-way Doppler radio positioning technology and cartographic triangulations through landmarks visible in both orbital and ground images. Additional high-resolution orbital images were taken to verify the determined lander positions. Visual odometry and bundle-adjustment technologies were applied to overcome wheel slippages, azimuthal angle drift and other navigation errors (as large as 21 percent). We generated timely topographic products including 68 orthophoto maps and 3D Digital Terrain Models, eight horizontal rover traverse maps, vertical traverse profiles up to Sol 214 for Spirit and Sol 62 for Opportunity, and five 3D crater models. A web-based landing-site Geographic Information System (GIS) has been set up at The Ohio State University to update and disseminate the daily localization and topographic information to support tactical and strategic operations of the mission. Also described in this paper are applications of the data for science operations planning, geological traverse survey, survey of wind-related features, and other science applications. The majority of the instruments onboard both rovers are healthy at this moment, and they will continue to explore the two landing sites on the Martian surface. We expect to report further localization and topographic mapping results to be achieved in the rest of the mission period and in post-mission data processing.

Photogrammetric Engineering and Remote Sensing↗
USGS2005

HRSC on Mars Express: Photogrammetric and cartographic research

The High Resolution Stereo Camera (HRSC) on the European spacecraft Mars Express is the first camera on a planetary mission especially designed for photogrammetric and cartographic purposes. Since January 2004 the camera has been taking image data from the Martian surface, characterized by high-resolution, stereo capability and color. These data provide an enormous potential for the generation of 3D surface models, color orthoimages, topographic and thematic maps, and additional products. The image data acquired undergo calibration and systematic processing to orthoimages and 3D data products. Within the international HRSC Science Team the members of the Photogrammetric/Cartographic Working Group are concerned with further refinements in order to achieve highest quality data products. These activities comprise improvements of the exterior orientation of the camera, various approaches to enhance DTM quality, and the generation of maps in the standard scale of 1:200 000 and larger scales as well. The paper reports on these activities and the results achieved so far .

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Joint analysis of visible and infrared images

Analysis of data combining daytime visible reflected, daytime IR emitted, and nighttime IR emitted images allows us to isolate the physical effects of topography, albedo, and thermal inertia. To a good approximation, these physical influences interact linearly so that maps showing topographic shading, albedo, and relative thermal inertia can be produced by simple algebraic manipulation of the co-registered images. The shading map resembles an airbrush, shaded relief portrayal of the surface, and can be used as the input for quantitative reconstruction of topography by photoclinometry (shape-fromshading). We demonstrate the method with imagery from the NASA 2001 Mars Odyssey Thermal Emission Imaging System (THEMIS), a dataset that could support mapping most of Mars in this way at 100 m resolution .

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Utility of Viking Orbiter images and products for Mars mapping

This paper reports on mapping procedures developed by the U.S. Geological Survey that use Viking Orbiter imagery and Mars Orbiter Laser Altimeter (MOLA) derived radii to produce topographic data. The use of Mosaiced Digital Image Models (MDIMs), created from Viking Orbiter images, and MOLA data to provide horizontal and vertical control is reviewed. We describe procedures to adapt a commercial digital photogrammetric workstation to work with planetary data.

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Leaf optical property changes associated with the occurrence of Spartina alterniflora dieback in Coastal Louisiana related to remote sensing mapping

In order to provide a remote sensing solution that would detect both the initial onset and monitor the early, as well as, the later stages of impact progression, changes in live leaf optical properties were compared along transects spanning impacted coastal Louisiana marsh sites. Green and red edge reflectance trends generally represented the early stages and fairly well the later stages of dieback progression, while blue and red reflectance and absorption trends represented the later stages of marsh impact that were most closely related to visible signs of marsh impact. Leaf reflectance in the near infrared (NIR) was not compatible with visual reflectance trends and did not co-vary with derived indicators of leaf water content, and thereby, water stress. Predicted from reflectance ratios, carotene tended to remain constant or increase relative to chlorophyll following noted changes in stressed plants at the two least impacted sites, while the pigments co-varied at the two most impacted sites. As an operational solution most amenable for satellite remote sensing, the NIR /red ratio followed blue and red reflectance trends while the NIR /green ratio mimicked the green and red edge reflectance trends indicating impact onset and progression, as well as, generally portraying blue and red reflectance trends indicating later stages of impact. The NIR/ green ratio magnitude and range generally increased from the most to least impacted site providing a convenient method to detect dieback onset and monitor dieback progression. This research demonstrated that remote sensing mapping at these sites could offer a more accurate perception of dieback severity distribution than offered by determinations relying on visible indicators of marsh changes.

Louisiana↗
USGS2005

Field determination of optimal dates for the discrimination of invasive wetland plant species using derivative spectral analysis

Mapping invasive plant species in aquatic and terrestrial ecosystems helps to understand the causes of their progression, manage some of their negative consequences, and control them. In recent years, a variety of new remote-sensing techniques, like Derivative Spectral Analysis (DSA) of hyperspectral data, have been developed to facilitate this mapping. A number of questions related to these techniques remain to be addressed. This article attempts to answer one of these questions: Is the application of DSA optimal at certain times of the year? Field radiometric data gathered weekly during the summer of 1999 at selected field sites in upstate New York, populated with purple loosestrife ( Lythrum salicaria L.), common reed ( Phragmites australis (Cav.)) and cattail ( Typha L.) are analyzed using DSA to differentiate among plant community types. First, second and higher-order derivatives of the reflectance spectra of nine field plots, varying in plant composition, are calculated and analyzed in detail to identify spectral ranges in which one or more community types have distinguishing features. On the basis of the occurrence and extent of these spectral ranges, experimental observations suggest that a satisfactory differentiation among community types was feasible on 30 August, when plants experienced characteristic phenological changes (transition from flowers to seed heads). Generally, dates in August appear optimal from the point of view of species differentiability and could be selected for image acquisitions. This observation, as well as the methodology adopted in this article, should provide a firm basis for the acquisition of hyperspectral imagery and for mapping the targeted species over a broad range of spatial scales.

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Characteristics of seasonal vegetation cover in the conterminous USA

A data set of the fractional green vegetation cover (FGREEN) for the Conterminous USA was evaluated for regional and seasonal variation. The value of FGREEN was derived monthly for the three most dominant land cover classes per 20 km by 20 km grid cell within the study area. At this grid cell resolution (comprised of 400 1-km pixels), 97 percent of the grid cells included three or fewer land cover classes. FGREEN was found to vary regionally due to local land cover and climate variations. FGREEN was found significantly different between one or more of the land cover classes, for one or more months, in 58 percent of the grid cells included in the study. Monthly FGREEN values for the land cover classes vary sufficiently between the land cover classes to warrant monthly FGREEN data for each of the one to three most dominant land cover classes per grid cell .

Photogrammetric Engineering and Remote Sensing↗
USGS2005

Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation

Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R 2 values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.

Photogrammetric Engineering and Remote Sensing↗
USGS2006

Landsat-7 long-term acquisition plan radiometry - evolution over time

The Landsat-7 Enhanced Thematic Mapper Plus instrument has two selectable gains for each spectral band. In the acquisition plan, the gains were initially set to maximize the entropy in each scene. One unintended consequence of this strategy was that, at times, dense vegetation saturated band 4 and deserts saturated all bands. A revised strategy, based on a land-cover classification and sun angle thresholds, reduced saturation, but resulted in gain changes occurring within the same scene on multiple overpasses. As the gain changes cause some loss of data and difficulties for some ground processing systems, a procedure was devised to shift the gain changes to the nearest predicted cloudy scenes. The results are still not totally satisfactory as gain changes still impact some scenes and saturation still occurs, particularly in ephemerally snow-covered regions. A primary conclusion of our experience with variable gain on Landsat-7 is that such an approach should not be employed on future global monitoring missions.

Photogrammetric Engineering and Remote Sensing↗
USGS2006

Historical record of Landsat global coverage

The long-term, 34+ year record of global Landsat remote sensing data is a critical resource to study the Earth system and human impacts on this system. The National Satellite Land Remote Sensing Data Archive (NSLRSDA) is charged by public law to: “maintain a permanent, comprehensive Government archive of global Landsat and other land remote sensing data for long-term monitoring and study of the changing global environment” (U.S. Congress, 1992). The advisory committee for NSLRSDA requested a detailed analysis of observation coverage within the U.S. Landsat holdings, as well as that acquired and held by International Cooperator (IC) stations. Our analyses, to date, have found gaps of varying magnitude in U.S. holdings of Landsat global coverage data, which appear to reflect technical or administrative variations in mission operations. In many cases it may be possible to partially fill these gaps in U.S. holdings through observations that were acquired and are now being held at International Cooperator stations.

Photogrammetric Engineering and Remote Sensing↗
USGS2006

Evaluating a small footprint, waveform-resolving lidar over coastal vegetation communities

NASA’s Experimental Advanced Airborne Research Lidar (EAARL) is a raster-scanning, waveform-resolving, green-wavelength (532 nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor records the time history of the return waveform within a small footprint (20 cm diameter) for each laser pulse, enabling characterization of vegetation canopy structure and “bare earth” topography under a variety of vegetation types. A collection of individual waveforms combined within a synthesized large footprint was used to define three metrics: canopy height (CH), canopy reflection ratio (CRR), and height of median energy (HOME). Bare Earth Elevation (BEE) metric was derived using the individual small-footprint waveforms. All four metrics were tested for reproducibility, which resulted in an average of 95 percent correspondence within two standard deviations of the mean. CH and BEE values were also tested for accuracy using ground-truth data. The results presented in this paper show that combining several individual small-footprint laser pulses to define a composite “large-footprint” waveform is a possible method to depict the vertical structure of a vegetation canopy .

Photogrammetric Engineering and Remote Sensing↗
USGS2006

Canopy reflectance related to marsh dieback onset and progression in Coastal Louisiana

In this study, we extended previous work linking leaf spectral changes, dieback onset, and progression of Spartina alterniflora marshes to changes in site-specific canopy reflectance spectra. First, we obtained canopy reflectance spectra (approximately 20 m ground resolution) from the marsh sites occupied during the leaf spectral analyses and from additional sites exhibiting visual signs of dieback. Subsequently, the canopy spectra were analyzed at two spectral scales: the first scale corresponded to whole-spectra sensors, such as the NASA Earth Observing-1 (EO-1) Hyperion, and the second scale corresponded to broadband spectral sensors, such as the EO-1 Advanced Land Imager and the Landsat Enhanced Thematic Mapper. In the whole-spectra analysis, spectral indicators were generated from the whole canopy spectra (about 400 nm to 1,000 nm) by extracting typical dead and healthy marsh spectra, and subsequently using them to determine the percent composition of all canopy reflectance spectra. Percent compositions were then used to classify canopy spectra at each field site into groups exhibiting similar levels of dieback progression ranging from relatively healthy to completely dead. In the broadband reflectance analysis, blue, green, red, red-edge, and near infrared (NIR) spectral bands and NIR/green and NIR/red transforms were extracted from the canopy spectra. Spectral band and band transform indicators of marsh dieback and progression were generated by relating them to marsh status indicators derived from classifications of the 35 mm slides collected at the same time as the canopy reflectance recordings. The whole spectra and broadband spectral indicators were both able to distinguish (a) healthy marsh, (b) live marsh impacted by dieback, and (c) dead marsh, and they both provided some discrimination of dieback progression. Whole-spectra resolution sensors like the EO-1 Hyperion, however, offered an enhanced ability to categorize dieback progression.

Louisiana↗
USGS2006

Evaluation of eelgrass beds mapping using a high-resolution airborne multispectral scanner

Eelgrass ( Zostera marina ) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions.

Photogrammetric Engineering and Remote Sensing↗
USGS2006

An agreement coefficient for image comparison

Combination of datasets acquired from different sensor systems is necessary to construct a long time-series dataset for remotely sensed land-surface variables. Assessment of the agreement of the data derived from various sources is an important issue in understanding the data continuity through the time-series. Some traditional measures, including correlation coefficient, coefficient of determination, mean absolute error, and root mean square error, are not always optimal for evaluating the data agreement. For this reason, we developed a new agreement coefficient for comparing two different images. The agreement coefficient has the following properties: non-dimensional, bounded, symmetric, and distinguishable between systematic and unsystematic differences. The paper provides examples of agreement analyses for hypothetical data and actual remotely sensed data. The results demonstrate that the agreement coefficient does include the above properties, and therefore is a useful tool for image comparison.

Photogrammetric Engineering and Remote Sensing↗
USGS2006

A 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska

The U.S. Geological Survey (USGS) has developed a 16-year time series of vegetation condition information for the conterminous United States and Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometric measurements obtained from wide field-of-view observations, and the geometric registration accuracy. The conterminous United States and Alaska data sets have an atmospheric correction for water vapor, ozone, and Rayleigh scattering and include a cloud mask derived using the Clouds from AVHRR (CLAVR) algorithm. In comparison with other AVHRR time series data sets, the conterminous United States and Alaska data are processed using similar techniques. The primary difference is that the conterminous United States and Alaska data are at 1 km resolution, while others are at 8 km resolution. The time series consists of weekly and biweekly maximum normalized difference vegetation index (NDVI) composites.

Photogrammetric Engineering and Remote Sensing↗