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At least 73 records · Page 4Linked to original sources
USGS2017

Aerodynamic roughness length estimation with lidar and imaging spectroscopy in a shrub-dominated dryland

The aerodynamic roughness length (Z 0 m ) serves an important role in the flux exchange between the land surface and atmosphere. In this study, airborne lidar ( ALS ), terrestrial lidar ( TLS ), and imaging spectroscopy data were integrated to develop and test two approaches to estimate Z 0 m over a shrub dominated dryland study area in south-central Idaho, USA. Sensitivity of the two parameterization methods to estimate Z 0 m was analyzed. The comparison of eddy covariance-derived Z 0 m and remote sensing-derived Z 0 m showed that the accuracy of the estimated Z 0 m heavily depends on the estimation model and the representation of shrub (e.g., Artemisia tridentata subsp. wyomingensis) height in the models. The geometrical method (RA1994) led to 9 percent (~0.5 cm) and 25% (~1.1 cm) errors at site 1 and site 2, respectively, which performed better than the height variability-based method (MR1994) with bias error of 20 percent and 48 percent at site 1 and site 2, respectively. The RA1994 model resulted in a larger range of Z 0 m than the MR1994 method. We also found that the mean, median and 75th percentiles of heights (H75) from ALS provides the best Z 0 m estimates in the MR1994 model, while the mean, median, and MLD (Median Absolute Deviation from Median Height), as well as AAD (Mean Absolute Deviation from Mean Height) heights from ALS provides the best Z 0 m estimates in the RA1994 model. In addition, the fractional cover of shrub and grass, distinguished with ALS and imaging spectroscopy data, provided the opportunity to estimate the frontal area index at the pixel-level to assess the influence of grass and shrub on Z 0 m estimates in the RA1994 method. Results indicate that grass had little effect on Z 0 m in the RA1994 method. The Z 0 m estimations were tightly coupled with vegetation height and its local variance for the shrubs. Overall, the results demonstrate that the use of height and fractional cover from remote sensing data are promising for estimating Z 0 m , and thus refining land surface models at regional scales in semiarid shrublands.

Photogrammetric Engineering and Remote Sensing↗
USGS2018

Crisis remote sensing during the 2018 lower East Rift Zone eruption of Kīlauea Volcano

Kīlauea Volcano, Hawai‘i, is renowned as one of the most active and closely monitored volcanoes on Earth. Scores of seismometers and deformation sensors form an array across the volcano to detect subsurface magmatic activity, and ground observers track eruptions on the surface. In addition to this dense ground-based monitoring, remote sensing – both airborne and spaceborne – has become a backbone tool at the U.S. Geological Survey’s (USGS) Hawaiian Volcano Observatory (HVO) for mapping activity and forecasting volcanic hazards. Remote observations were critical components of HVO’s response to the historically unprecedented 2018 eruption from Kīlauea’s lower East Rift Zone (ERZ); here we describe some of the many types of remote sensing tools that were utilized, and the specific monitoring roles they filled.

Hawaii↗
USGS2018

Removing rural roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011

Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database ( NLCD ) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km 2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.

Photogrammetric Engineering and Remote Sensing↗
USGS2021

Hyperspectral narrowband data propel gigantic leap in the earth remote sensing

Hyperspectral narrowbands (HNBs) capture data as nearly continuous “spectral signatures” rather than a “few spectral data points” along the electromagnetic spectrum as with multispectral broadbands (MBBs). Almost all of satellite remote sensing of the Earth in the twentieth century was conducted using MBB data from sensors such as the Landsat-series, Advanced Very High-Resolution Radiometer (AVHRR), SPOT (Système Pour l’Observation de la Terre), and the Indian Remote Sensing (IRS) satellites. These systems typically provide 4 to 9 broad spectral wavebands spread from 400 to 2500 nm, often with one or two additional bands in the thermal range. Significant advances in the study of the Earth have been made based on these data [Thenkabail et al., 2018a,b,c,d; Thenkabail et al., 2015a,b,c]. Possibilities of great advances that can be made using HNB data over MBB data are well established based on studies conducted using hyperspectral sensors such as the hand-held spectroradiometers, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and spaceborne Earth Observing -1 (EO-1) Hyperion [Thenkabail 2018a,b,c,d]. The twenty-first century is already seeing the dawn of hyperspectral imaging data from sensors such as the German Aerospace Center’s (DLR’s) DESIS (DLR Earth Sensing Imaging Spectrometer) onboard the MUSES (Multi-User System for Earth Sensing) platform on the International Space Station (ISS), the polar-orbiting Italian Space Agency’s (ASI) PRISMA (PRecursore IperSpettrale della Missione Applicativa), and many other upcoming sensors such as the NASA Surface Biology and Geology (SBG) [Thenkabail et al., 2018a,b,c,d]. These satellites acquire data in hundreds of narrow spectral bands of 1 to 10 nm width, typically between 400 to 2500 nm; also future planned missions will be extending HNBs to the thermal (9,000 to 14,000 nm) electromagnetic spectrum. This expansion creates a quantum leap in new data, new information, and myriad possible new applications in the study of the Earth in addition to great advances in existing applications. Given the above, the objective of this article is to provide insights on the gigantic leap in our understanding, modeling, mapping, and monitoring of the Earth that can be made using HNB relative to MBB by focusing on agricultural and vegetation applications. We will address this in four aspects: 1. Comparison between HNB and MBB data; 2. Spectral libraries of agricultural crops; 3. HNB data analysis in general; and 4. HNB analysis using machine learning (ML) and cloud computing.

Photogrammetric Engineering and Remote Sensing.↗
USGS2021

Semi-centennial of Landsat observations and pending Landsat 9 launch

The first Landsat was placed in orbit on 23 July 1972, followed by a series of missions that have provided nearly continuous, two-satellite 8-day repeat image coverage of the Earth’s land areas for the last half-century. These observations have substantially enhanced our understanding of the Earth’s terrestrial dynamics, both as a major element of the Earth’s physical system, the primary home of humans, and the major source of natural resources that support them. The history of Landsat is complex, reflective of the human systems that sustain it. Despite the conflicted perspectives surrounding the continuation of the program, Landsat has survived based on worldwide recognition of its critical contributions to understanding land dynamics, management of natural resources and Earth system science. Launch of Landsat 9 is anticipated in Fall 2021, and current planning for the next generation, Landsat Next is well underway. The community of Landsat data users is looking forward to another 50 years of the Landsat program.

Photogrammetric Engineering and Remote Sensing (PE↗
USGS1981

Use of 35-mm color aerial photography to acquire mallard sex ratio data

A conventional 35-mm camera equipped with an f2.8 135-mm lens and ASA 64 color film was used to acquire sex ratio data on mallards ( Anas platyrhynchos ) wintering in the Platte River Valley of south-central Nebraska. Prelight focusing for a distance of 30.5 metres and setting of shutter speed at 1/2000 of a second eliminated focusing and reduced image motion problems and resulted in high-resolution, large-scale aerial photography of small targets. This technique has broad application to the problem of determining sex ratios of various species of waterfowl concentrated on wintering and staging areas. The aerial photographic method was cheaper than the ground ocular method when costs were compared on a per-100 bird basis.

Nebraska↗
USGS1976

Utilization of satellite data for inventorying prairie ponds and lakes

By using data acquired by LANDSAT-1 (formerly ERTS- 1), studies were conducted in extracting information necessary for formulating management decisions relating to migratory waterfowl. Management decisions are based in part on an assessment ofhabitat characteristics, specifically numbers, distribution, and quality of ponds and lakes in the prime breeding range. This paper reports on a study concerned with mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single nearinfrared waveband. The results of this recognition were thematic maps and statistics relating to open surface water. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

Photogrammetric Engineering and Remote Sensing↗
USGS2000

Accuracy assessment for the U.S. Geological Survey Regional Land-Cover Mapping Program: New York and New Jersey Region

The U.S. Geological Survey, in cooperation with other government and private organizations, is producing a conterminous U.S. land-cover map using Landsat Thematic Mapper 30-meter data for the Federal regions designated by the U.S. Environmental Protection Agency. Accuracy assessment is to be conducted for each Federal region to estimate overall and class-specific accuracies. In Region 2, consisting of New York and New Jersey, the accuracy assessment was completed for 15 land-cover and land-use classes, using interpreted 1:40,000-scale aerial photographs as reference data. The methodology used for Region 2 features a two-stage, geographically stratified approach, with a general sample of all classes (1,033 sample sites), and a separate sample for rare classes (294 sample sites). A confidence index was recorded for each land-cover interpretation on the 1:40,000-scale aerial photography The estimated overall accuracy for Region 2 was 63 percent (standard error 1.4 percent) using all sample sites, and 75.2 percent (standard error 1.5 percent) using only reference sites with a high-confidence index. User's and producer's accuracies for the general sample and user's accuracy for the sample of rare classes, as well as variance for the estimated accuracy parameters, were also reported. Narrowly defined land-use classes and heterogeneous conditions of land cover are the major causes of misclassification errors. Recommendations for modifying the accuracy assessment methodology for use in the other nine Federal regions are provided.

Photogrammetric Engineering and Remote Sensing↗
USGS1983

Objective procedures for lineament enhancement and extraction

A longterm research goal at EROS Data Center is to develop automated, objective procedures for lineament mapping. In support of this goal, a five-step digital convolution procedure has been used to produce directionally enhanced images, which contain few artifacts and little noise. The main limitation of this procedure is that little enhancement of lineaments occurs in dissected terrain, in shadowed areas, and in flat areas with a uniform land cover. The directional enhancement procedure can be modified to extract edge and line segments from an image. Any of various decision rules can then be used to connect the line segments and to produce a final lineament map. The result is an interpretive map, but one that is based on an objective extraction of lineament components by digital processing. -from Authors

Photogrammetric Engineering and Remote Sensing↗
USGS1982

Computation with physical values from Landsat digital data

Landsat digital images are commonly analyzed by using the digital numbers for each pixel recorded on a computer-compatible magnetic tape. Although this procedure may be satisfactory when only a single, internally consistent image is used, the procedure may produce incorrect results if more than one image is used for analysis as in mosaics or temporal overlays. The digital numbers for each pixel should be converted to their dimensioned equivalents such as radiance, as measured at the satellite, in milliwatts per square centimetre per steradian, or reflectance.-from Author

Photogrammetric Engineering and Remote Sensing↗
USGS1982

Sample design for estimating change in land use and land cover ( Pennsylvania).

The methodology of sample design which is applied to estimating change in land use and land cover is general and extendable to determination of change in any type of thematic mapping that is time variant. Land-use maps of the State of Pennsylvania at a scale of 1:250,000 were compiled circa 1958 with land use classified into six categories. The more detailed land-use and land-cover mapping of the State of Pennsylvania at a scale of 1:250,000 was completed by the U.S. Geological Survey circa 1977. With some rearrangement of these categories, the recent maps are very nearly compatible with a combination of five categories of the earlier maps. -from Author

Photogrammetric Engineering and Remote Sensing↗
USGS1983

Generalized adjustment by least squares ( GALS).

The least-squares principle is universally accepted as the basis for adjustment procedures in the allied fields of geodesy, photogrammetry and surveying. A prototype software package for Generalized Adjustment by Least Squares (GALS) is described. The package is designed to perform all least-squares-related functions in a typical adjustment program. GALS is capable of supporting development of adjustment programs of any size or degree of complexity. -Author

Photogrammetric Engineering and Remote Sensing↗
USGS1982

Photogrammetry of the Viking-Lander imagery.

We have solved the problem of photogrammetric mapping from the Viking Lander photography in two ways: 1) by converting the azimuth and elevation scanning imagery to the equivalent of a frame picture by means of computerized rectification; and 2) by interfacing a high-speed, general-purpose computer to the AS-11A analytical plotter so that all computations of corrections can be performed in real time during the process of model orientation and map compilation. Examples are presented of photographs and maps of Earth and Mars. -from Authors

Photogrammetric Engineering and Remote Sensing↗
USGS1982

Geometry of a mapping satellite.

The proposed mapping satellite Mapsat is to consist of fixed fore, vertical, and aft linear detector arrays, any two of which may be used simultaneously to obtain digital images for one- dimensional stereo correlation. The satellite attitude may be varied according to Fourier series to enable a given detector on one array to follow closely the groundtrack sensed by the corresponding detector on another array throughout the orbit. These tracking errors are negligible for a satellite stable within anticipated ranges. The required computations have been programmed in FORTRAN IV. -Author

Photogrammetric Engineering and Remote Sensing↗
USGS1982

USGS aerial resolution targets.

It is necessary to measure the achievable resolution of any airborne sensor that is to be used for metric purposes. Laboratory calibration facilities may be inadequate or inappropriate for determining the resolution of non-photographic sensors such as optical-mechanical scanners, television imaging tubes, and linear arrays. However, large target arrays imaged in the field can be used in testing such systems. The USGS has constructed an array of resolution targets in order to permit field testing of a variety of airborne sensing systems. The target array permits any interested organization with an airborne sensing system to accurately determine the operational resolution of its system. -from Author

Photogrammetric Engineering and Remote Sensing↗
USGS1981

Analysis of variance of thematic mapping experiment data.

As an example of the methodology, data from an experiment using three scales of land-use and land-cover mapping have been analyzed. The binomial proportions of correct interpretations have been analyzed untransformed and transformed by both the arcsine and the logit transformations. A weighted analysis of variance adjustment has been used. There is evidence of a significant difference among the three scales of mapping (1:24 000, 1:100 000 and 1:250 000) using the transformed data. Multiple range tests showed that all three scales are different for the arcsine transformed data. - from Author

Photogrammetric Engineering and Remote Sensing↗
USGS1983

The relationship of acquisition systems to automated stereo correlation.

Today a concerted effort is being made to expedite the mapping process through automated correlation of stereo data. Stereo correlation involves the comparison of radiance (brightness) signals or patterns recorded by sensors. Conventionally, two-dimensional area correlation is utilized but this is a rather slow and cumbersome procedure. Digital correlation can be performed in only one dimension where suitable signal patterns exist, and the one-dimensional mode is much faster. Electro-optical (EO) systems, suitable for space use, also have much greater flexibility than film systems. Thus, an EO space system can be designed which will optimize one-dimensional stereo correlation and lead toward the automation of topographic mapping.-from Author

Photogrammetric Engineering and Remote Sensing↗