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MISR Level 1B2 Terrain Data (MI1B2T_V1)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Terrain data are re-projected to the terrain altitude. In this product, surface data from all cameras will appear in the same geographic location. Thus, this product is the primary input to Level 2 aerosol/surface processing, which requires co-registration of the L1B2 imagery at the surface. Clouds will still be displaced due to their elevation above the surface, but this time with respect to the terrain rather than the ellipsoid. (The mountain location T is now assigned the geographic location at T, and the Cloud at F appears at the geographic location T.) In Level 2 aerosol/surface processing, algorithms are applied to screen out the clouds. Terrain data only exist for MISR blocks containing some land. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track).; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

NEAR IR WAVELENGTHS↗

Coordination and establishment of centralized facilities and services for the University of Alaska ERTS survey of the Alaskan environment

The author has identified the following significant results. Scene 1072-21173 of the Anaktuvuk Pass region of the Brooks Range, Alaska, was studied from the point of view of a resource survey for purposes of land use planning as part of the effort to develop ERTS data processing and interpretation techniques. Other data sources and surface observations were utilized to produce a resource survey of a remote and undeveloped region of Alaska. Three vegetative types are apparent: moist tundra, low brush, and high brush. Watersheds are easily defined on the multispectral imagery. Features related indirectly to economic minerals are discernible from ERTS-1 imagery supported by ground truth data. These include mountains, outwash plains and alluvial deposits, drainage patterns, lineaments and probable bedding planes. This region falls within present land class categories which are not inconsistent with the imperatives of the resources. These land class categories include native village withdrawals, regional deficiency area, national interest study area for possible inclusion in a national system, public interest areas, utility corridor, and state land selection.

Belon, A. E.↗

Venus volcanism - Initial analysis from Magellan data

Magellan images confirm that volcanism is widespread and has been fundamentally important in the formation and evolution of the crust of Venus. High-resolution imaging data reveal evidence for intrusion (dike formation and cryptodomes) and extrusion (a wide range of lava flows). Also observed are thousands of small shield volcanoes, larger edifices up to several hundred kilometers in diameter, massive outpourings of lavas, and local pyroclastic deposits. Although most features are consistent with basaltic compositions, a number of large pancake-like domes are morphologically similar to rhyolite-dacite domes on earth. Flows and sinuous channels with lengths of many hundreds of kilometers suggest that extremely high effusion rates or very fluid magmas (perhaps komantiites) may be present. Volcanism is evident in various tectonic settings (coronae, linear extensional and compressional zones, mountain belts, upland rises, highland plateaus, and tesserae). Volcanic resurfacing rates appear to be low (less than 2 cu km/yr) but the significance of dike formation and intrusions, and the mode of crustal formation and loss remain to be established.

Head, James W.↗

MISR Level 1B2 Terrain Data (MI1B2T_V2)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Terrain data are re-projected to the terrain altitude. In this product, surface data from all cameras will appear in the same geographic location. Thus, this product is the primary input to Level 2 aerosol/surface processing, which requires co-registration of the L1B2 imagery at the surface. Clouds will still be displaced due to their elevation above the surface, but this time with respect to the terrain rather than the ellipsoid. (The mountain location T is now assigned the geographic location at T, and the Cloud at F appears at the geographic location T.) In Level 2 aerosol/surface processing, algorithms are applied to screen out the clouds. Terrain data only exist for MISR blocks containing some land. [Location=GLOBAL LAND] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track).; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

SPECTRAL BANDS↗

MISR Level 1B2 Terrain Data (MI1B2T_V3)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Terrain data are re-projected to the terrain altitude. In this product, surface data from all cameras will appear in the same geographic location. Thus, this product is the primary input to Level 2 aerosol/surface processing, which requires co-registration of the L1B2 imagery at the surface. Clouds will still be displaced due to their elevation above the surface, but this time with respect to the terrain rather than the ellipsoid. (The mountain location T is now assigned the geographic location at T, and the Cloud at F appears at the geographic location T.) In Level 2 aerosol/surface processing, algorithms are applied to screen out the clouds. Terrain data only exist for MISR blocks containing some land. [Location=GLOBAL LAND] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track).; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

IMAGERY↗

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high-biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height-normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

Jonathan A. Walter↗

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

The author has identified the following significant results. The standard error of measurement of snow covered areas in major drainage basins in the Cascade Range, Washington, using single measurements of ERTS-1 images, was found to range from 11% to 7% during a typical melt season, but was as high as 32% in midwinter. Many dangerous glacier situations in Alaska, Yukon, and British Columbia were observed on ERTS-1 imagery. Glacier dammed lakes in Alaska are being monitored by ERTS-1. Embayments in tidal glaciers show changes detectable by ERTS-1. Surges of Russell and Tweedsmuir Glaciers, now in progress, are clearly visible. The Tweedsmuir surge is likely to dam the large Alsek River by mid-November, producing major floods down-river next summer. An ERTS-1 image of the Pamir Mountains, Tadjik S.S.R., shows the surging Medvezhii (Bear) Glacier just after its surge of early summer which dammed the Abdukagor Valley creating a huge lake and later a flood in the populous Vanch River Valley. A map was compiled from an ERTS-1 image of the Lowell Glacier after its recent surge, compared with an earlier map compiled from pain-stakingly compiled from a mosaic of many aerial photographs, in a total elapsed time of 1.5 hours. This demonstrates the value of ERTS-1 for rapid mapping of large features.

Meier, M. F.↗

Alaska Crustal Deformation: Finite Element Modeling Constrained by Geologic and Very Long Baseline Interferometry Data

We compute crustal motions in Alaska by calculating the finite element solution for an elastic spherical shell problem. The method we use allows the finite element mesh to include faults and very long baseline interferometry (VLBI) baseline rates of change. Boundary conditions include Pacific-North American (PA-NA) plate motions. The solution is constrained by the oblique orientation of the Fairweather-Queen Charlotte strike-slip faults relative to the PA-NA relative motion direction and the oblique orientation from normal convergence of the eastern Aleutian trench fault systems, as well as strike-shp motion along the Denali and Totschunda fault systems. We explore the effects that a range of fault slip constraints and weighting of VLBI rates of change has on the solution. This allows us to test the motion on faults, such as the Denali fault, where there are conflicting reports on its present-day slip rate. We find a pattern of displacements which produce fault motions generally consistent with geologic observations. The motion of the continuum has the general pattern of radial movement of crust to the NE away from the Fairweather-Queen Charlotte fault systems in SE Alaska and Canada. This pattern of crustal motion is absorbed across the Mackenzie Mountains in NW Canada, with strike-slip motion constrained along the Denali and Tintina fault systems. In south central Alaska and the Alaska forearc oblique convergence at the eastern Aleutian trench and the strike-shp motion of the Denali fault system produce a counterclockwise pattern of motion which is partially absorbed along the Contact and related fault systems in southern Alaska and is partially extruded into the Bering Sea and into the forearc parallel the Aleutian trench from the Alaska Peninsula westward. Rates of motion and fault slip are small in western and northern Alaska, but the motions we compute are consistent with the senses of strike-slip motion inferred geologically along the Kaltag, Kobuk Trench, and Thompson Creek faults and with the normal faulting observed in NW Alaska near Nome. The nonrigid behavior of our finite element solution produces patterns of motion that would not have been expected from rigid block models: strike-slip faults can exist in a continuum that has motion mostly perpendicular to their strikes, and faults can exhibit along-strike differences in magnitudes and directions.

Lundgren, Paul↗

SLAR reconnaissance, Mimika-Eilanden Basin, Southern Trough of Irian Jaya

The SLAR was obtained in early April 1973 by means of an AN/APQ-97 K-band brute-force system. The flight strips are all north-look, with ground-range display, and 60% overlap. The interpretation was compiled on a 1/100,000-scale mosaic, but the actual mapping of contacts, dips, lineaments, and the like, was done on 1/100,000-scale stereo-strips. Initial regional mapping was intended as an aid in determining that part of the Southern Trough most likely to be underlain by relatively unmetamorphosed paralic Kembelangan sandstones ideally interdigitated with marine source and cape shales. SLAR reconnaissance mapping met a subsequent need to rapidly and inexpensively narrow the search to that part of the "fairway' coincident with a favorable structure. The SLAR mosaic clearly displays the Irian mountains, strongly and gently folded foothills belts, and the southern front of the fold belt south of which is a large complex of alluvial fans.

Wing, R. S.↗

Characterizing the Vertical Processes of Ozone in Colorado's Front Range Using the GSFC Ozone Dial

Although characterizing the interactions of ozone throughout the entire troposphere are important for health and climate processes, there is a lack of routine measurements of vertical profiles within the United States. In order to monitor this lower ozone more effectively, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZDIAL) has been developed and validated within the Tropospheric Ozone Lidar Network (TOLNet). Two scientifically interesting ozone episodes are presented that were observed during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER AQ) campaign at Ft. Collins,Colorado.The first case study, occurring between 22-23 July 2014, indicates enhanced concentrations of ozone at Ft. Collins during nighttime hours, which was due to the complex recirculation of ozone within the foothills of the Rocky Mountain region. Although quantifying the ozone increase a loft during recirculation episodes has been historically difficult, results indicate that an increase of 20 -30 ppbv of ozone at the Ft. Collins site has been attributed to this recirculation. The second case, occurring between Aug 4-8th 2014, characterizes a dynamical exchange of ozone between the stratosphere and the troposphere. This case, along with seasonal model parameters from previous years, is used to estimate the stratospheric contribution to the Rocky Mountain region. Results suggest that a large amount of stratospheric air is residing in the troposphere in the summertime near Ft. Collins, CO. The results also indicate that warmer tropopauses are correlated with an increase in stratospheric air below the tropopause in the Rocky Mountain Region.

Sullivan, John T.↗

Modeling Snow Ablation over the Western United States Mountains: Patterns and Controlling Factors

When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.

Snow↗

Lidar

Lidar is an optical radar technique employing laser energy. Variations in signal intensity as a function of range provide information on atmospheric constituents, even when these are too tenuous to be normally visible. The theoretical and technical basis of the technique is described and typical values of the atmospheric optical parameters given. The significance of these parameters to atmospheric and meteorological problems is discussed. While the basic technique can provide valuable information about clouds and other material in the atmosphere, it is not possible to determine particle size and number concentrations precisely. There are also inherent difficulties in evaluating lidar observations. Nevertheless, lidar can provide much useful information as is shown by illustrations. These include lidar observations of: cirrus cloud, showing mountain wave motions; stratification in clear air due to the thermal profile near the ground; determinations of low cloud and visibility along an air-field approach path; and finally the motion and internal structure of clouds of tracer materials (insecticide spray and explosion-caused dust) which demonstrate the use of lidar for studying transport and diffusion processes.

Collis, R. T. H.↗

Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous and mountainous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

Manuel Helbig↗

Aerosol optical depth retrievals over the Konza Prairie

The aerosol optical depth over the Konza Prairie, near Manhattan, Kansas, was recorded at various locations by five separate teams. These measurements were made in support of the First ISLSCP Field Experiment (FIFE) and used to correct imagery from a variety of satellite and aircraft sensors for the effects of atmospheric scattering and absorption. The results from one instrument are reported here for 26 days in 1987 and for 7 in 1989. Daily averages span a range of 0.05 to 0.28 in the midvisible wavelengths. In addition, diurnal variations are noted in which the afternoon optical depths are greater than those of the morning by as much as 0.07. A comparison between instruments and processing techniques used to determine these aerosol optical depths is provided. The first comparisons are made using summer 1987 data. Differences of as much as 0.05 (midvisible) are observed. Although these data allow reasonable surface reflectance retrievals, they do not agree to within the performance limits typically associated with these types of instruments. With an accuracy goal of 0.02 a preseason calibration/comparison experiment was conducted at a mountain site prior to the final field campaign in 1989. Good calibration data were obtained, and good agreement (0.01, midvisible) was observed in the retrieved optical depth acquired over the Konza. By comparing data from the surface instruments at different locations, spatial inhomogeneities are determined. Then, data from the airborne tracking sunphotometer allow one to determine variations as a function of altitude. Finally, a technique is proposed for using the in situ data to establish an instrument calibration.

Bruegge, Carol J.↗

The First Six Months of Iapetus Observations by the Cassini ISS Camera

Since Saturn arrival in June 2004, Iapetus has been studied intensively by the Cassini ISS camera [1] at various ranges. The first of two relatively close flybys in the primary mission occurred on Dec 31, 2004 at an altitude of approx.123,400 km over the northern leading hemisphere, resulting in images with a minimum pixel scale of 740 m. Detailed results of this flyby are given in [2], while this abstract covers the observations obtained earlier. Among the most important discoveries are: (a) Four giant impact basins with diameters between 390 and 550 km were detected, three of them are located in the dark terrain [3]. (b) Data revealed a >1300 km long ridge that marks exactly Iapetus' equator within the dark terrain. Individual mountains within the western part of the ridge reach heights of approx.20 km over surrounding terrain [3]. (c) Impact craters were confirmed to be the main geological feature within the dark terrain and at high southern latitudes. (d) There are numerous craters with dark walls roughly facing towards the central parts of the dark hemisphere [3]. (e) Almost all parts of Iapetus have been imaged at least at low resolution (< 60 km/pxl).

Denk, T.↗

A reconnaissance space sensing investigation of crustal structure for a strip from the eastern Sierra Nevada to the Colorado Plateau

The author has identified the following significant results. An operational technique for producing high resolution false color composites of ERTS-1 MSS imagery has been developed. The technique uses standard NASA (NDPF) or EROS black/white data products, and permits a broad range of control on composite color balance and contrast range. The use of an additive color viewer has proven valuable for determining the optimum color balance of composites for effective interpretation. The compositing technique is adaptable for effective interpretation. The technique is adaptable to data from a variety of multispectral imaging systems, including multi-seasonal and multipolarization data. A 50 mile north-trending linear anomaly recognized in ERTS-1 MSS imagery west of Goldfield, Nevada has been confirmed as a steeply west-dipping normal fault, here termed the Paymaster Fault. This structure trends southward from the General Thomas Hills along Paymaster Valley and the east side of Clayton Valley into the Palmetto Mountains. There, it terminates against a less pronounced east-trending transverse anomaly which is also believed to be fault controlled. The Paymaster Fault is the most prominent of several large normal faults which terminate southward against this transverse anomaly.

Liggett, M. A.↗

MISR Level 1B2 Ellipsoid Data (MI1B2E_V1)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Ellipsoid product is referenced to the World Geodetic System 1984 (WGS84) ellipsoid, which approximates the Earth's shape at sea level. In this product, the radiances and associated altitudes are projected to the ellipsoid, so that higher elevation data appear displaced from their true location for non-nadir camera views, much as they are seen by the instrument. (A cloud at location F, or a mountain top at location T in the image below appears as if it is at location E.) The more oblique the camera view, or the higher in altitude the feature, the more displaced the elevated data will appear. This displacement is used to advantage in MISR stereo retrievals, and this product is the primary input to Level 2 top-of-atmosphere/cloud processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track); Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

EOSDIS↗

MISR Level 1B2 Ellipsoid Data (MI1B2E_V2)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Ellipsoid product is referenced to the World Geodetic System 1984 (WGS84) ellipsoid, which approximates the Earth's shape at sea level. In this product, the radiances and associated altitudes are projected to the ellipsoid, so that higher elevation data appear displaced from their true location for non-nadir camera views, much as they are seen by the instrument. (A cloud at location F, or a mountain top at location T in the image below appears as if it is at location E.) The more oblique the camera view, or the higher in altitude the feature, the more displaced the elevated data will appear. This displacement is used to advantage in MISR stereo retrievals, and this product is the primary input to Level 2 top-of-atmosphere/cloud processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track); Horizontal_Resolution_Range=500 meters - < 1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

EOSDIS↗