Automated recognition of oceanic cloud patterns. II - Detection of air temperature and humidity anomalies above the ocean surface from satellite imagery
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Garand, Louis↗
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Application of dynamical systems theory to global weather phenomena revealed by satellite imagery
Theoretical studies of low frequency and seasonal weather variability; dynamical properties of observational and general circulation model (GCM)-generated records; effects of the hydrologic cycle and latent heat release on extratropical weather; and Earth-system science studies are summarized.
Saltzman, Barry↗
Variability of the Columbia River plume observed in visible and infrared satellite imagery
Advanced Very High Resolution Radiometer and Coastal Zone Color Scanner (CZCS) data were used to derive images of sea surface temperature and phytoplankton pigment images. Observations were made in coastal waters off the Northwestern United States from 1979-1985 and showed that orientation, shape, intensity and relative temperature of the plume varied in response to coastal winds and wind-driven surface currents. CZCS images illustrating changes in the river plume during spring transition in 1982, changes due to reversal of the summer prevailing winds, during a strong summer upwelling, and during peak river flow in the early summer are presented and analyzed. It is noted that remote sensing of the Columbia River plume provides information for oceanographic studies and fisheries management in the region.
Fiedler, Paul C.↗
Normalization of satellite imagery
Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.
Kim, Hongsuk H.↗
An investigation of the detection of tornadic thunderstorms by observing storm top features using geosynchronous satellite imagery
The number of tornado outbreak cases studied in detail was increased from the original 8. Detailed ground and aerial studies were carried out of two outbreak cases of considerable importance. It was demonstrated that multiple regression was able to predict the tornadic potential of a given thunderstorm cell by its cirrus anvil plume characteristics. It was also shown that the plume outflow intensity and the deviation of the plume alignment from storm relative winds at anvil altitude could account for the variance in tornadic potential for a given cell ranging from 0.37 to 0.82 for linear to values near 0.9 for quadratic regression. Several predictors were used in various discriminant analysis models and in censored regression models to obtain forecasts of whether a cell is tornadic and how strong tornadic it could be potentially. The experiments were performed with the synoptic scale vertical shear in the horizontal wind and with synoptic scale surface vorticity in the proximity of the cell.
Anderson, Charles E.↗
A comparison of sea ice parameters computed from Advanced Very High Resolution Radiometer and Landsat satellite imagery and from airborne passive microwave radiometry
AVHRR-derived sea ice parameters from the Bering Sea are compared with those computed from nearly coincident (within 6 hr) Landsat MSS imagery and from the Aircraft Multichannel Microwave Radiometer (AMMR) flown on the NASA DC-8 in order to evaluate the accuracy and reliability of AVHRR-mapped sea-ice concentration and ice edge. Mean ice-concentration differences between AVHRR near-infrared (channel 2) and Landsat MSS data ranged from -0.8 to 1.8 percent with a mean value of 0.5 percent; rms differences ranged from 6.8 to 17.7 percent. Mean differences were larger for AVHRR thermal infrared (channel 4) ice concentrations ranging from -2.2 to 8.4 percent with rms differences from 8.6 to 26.8 percent. Mean differences between AVHRR channel 2 concentrations and the AMMR data ranged from -19.7 to 18.9 percent, while rms values went from 17.0 to 44.8 percent.
Emery, W. J.↗
Automated extraction of metadata from remotely sensed satellite imagery
The paper discusses research in the Intelligent Data Management project at the NASA/Goddard Space Flight Center, with emphasis on recent improvements in low-level feature detection algorithms for performing real-time characterization of images. Images, including MSS and TM data, are characterized using neural networks and the interpretation of the neural network output by an expert system for subsequent archiving in an object-oriented data base. The data show the applicability of this approach to different arrangements of low-level remote sensing channels. The technique works well when the neural network is trained on data similar to the data used for testing.
Cromp, Robert F.↗
Retrieval of aerosol optical properties from multi-angle satellite imagery
Simulation multiangle imagery have been used to investigate the capabilities of a novel method for retrieval of atmospheric aerosol optical properties over land; this method employs spatial contrasts within the imagery and compares the spatial Fourier transforms of the multiangle images at zero and nonzero spatial frequencies. While requiring the definition of a relationship between the angular variation of the Fourier transform of the intrinsic surface angular reflectance at the zero and nonzero frequencies, the method assumes no a priori knowledge about aerosols or surface characteristics. Sensitivities to various aerosol properties are assessed.
Martonchik, John V.↗
Surface velocity fields of Ice Streams D and E derived from repeat satellite imagery
Sequential Landsat TM images were used to map in detail the surface velocity of Ice Streams D and E by tracking small ice features in coregistered images. The majority of both ice streams have now been mapped for velocity, and in most areas, approximate strain-rates are also determined. Tracking was accomplished semiautomatically using an image-to-image cross-correlation technique. Measurement density is roughly four per sq km in regions with distinct surface features (crevasses, snow dunes, etc.), and with cloud-free image coverage.
Scambos, Ted A.↗
Effect of Amazon smoke on cloud microphysics and albedo - Analysis from satellite imagery
The effect of smoke aerosol particles on the properties of low cumulus and stratocumulus clouds is studied on the basis of NOAA AVHRR images taken over the Brazilian Amazon Basin during the biomass burning season of 1987. The reflectance at a wavelength of 0.64 micron and the drop size, derived from the cloud reflectance at 3.75 microns, is studied for tens of thousands of clouds. It is shown that the presence of dense smoke can reduce the remotely sensed drop size of continental cloud drops from 15 to 9 microns. Due to both the high initial reflectance of clouds in the visible part of the spectrum and the presence of graphitic carbon, the average cloud reflectance at 0.6 micron is reduced from 0.71 to 0.68 for an increase in smoke optical thickness from 0.1 to 2.0. High concentration of aerosol particles is shown to cause a decrease in the cloud-drop size, and smoke is found to darken the bright Amazonian clouds.
Kaufman, Yoram J.↗
Age discrimination among eruptives of Menengai Caldera, Kenya, using vegetation parameters from satellite imagery
Results are presented of an investigation to determine the degree to which digitally processed Landsat TM imagery can be used to discriminate among vegetated lava flows of different ages in the Menengai Caldera, Kenya. A selective series of five images, consisting of a color-coded Landsat 5 classification and four color composites, are compared with geologic maps. The most recent of more than 70 postcaldera flows within the caldera are trachytes, which are variably covered by shrubs and subsidiary grasses. Soil development evolves as a function of time, and as such supports a changing plant community. Progressively older flows exhibit the increasing dominance of grasses over bushes. The Landsat images correlated well with geologic maps, but the two mapped age classes could be further subdivided on the basis of different vegetation communities. It is concluded that field maps can be modified, and in some cases corrected by use of such imagery, and that digitally enhanced Landsat imagery can be a useful aid to field mapping in similar terrains.
Blodget, Herbert W.↗
A technique for determining cloud free versus cloud contaminated pixels in satellite imagery
Weather forecasting has been called the second oldest profession. To do so accurately and with some consistency requires an ability to understand the processes which create the clouds, drive the winds, and produce the ever changing atmospheric conditions. Measurement of basic parameters such as temperature, water vapor content, pressure, windspeed and wind direction throughout the three dimensional atmosphere form the foundation upon which a modern forecast is created. Doppler radar, and space borne remote sensing have provided forecasters the new tools with which to ply their trade.
Wohlman, Richard A.↗
Automatic registration of satellite imagery
Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. The objective of this paper is to present an automatic registration algorithm which uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The registration algorithm is very simple and easy to apply because it needs basically one parameter. We have obtained very encouraging results on test data sets from the TM and SPOT sensor images of forest, urban and agricultural areas.
Fonseca, Leila M. G.↗
A scale space feature based registration technique for fusion of satellite imagery
Feature based registration is one of the most reliable methods to register multi-sensor images (both active and passive imagery) since features are often more reliable than intensity or radiometric values. The only situation where a feature based approach will fail is when the scene is completely homogenous or densely textural in which case a combination of feature and intensity based methods may yield better results. In this paper, we present some preliminary results of testing our scale space feature based registration technique, a modified version of feature based method developed earlier for classification of multi-sensor imagery. The proposed approach removes the sensitivity in parameter selection experienced in the earlier version as explained later.
Raghavan, Srini↗
Iterative edge- and wavelet-based image registration of AVHRR and GOES satellite imagery
Most automatic registration methods are either correlation-based, feature-based, or a combination of both. Examples of features which can be utilized for automatic image registration are edges, regions, corners, or wavelet-extracted features. In this paper, we describe two proposed approaches, based on edge or edge-like features, which are very appropriate to highlight regions of interest such as coastlines. The two iterative methods utilize the Normalized Cross-Correlation of edge and wavelet features and are applied to such problems as image-to-map registration, landmarking, and channel-to-channel co-registration, utilizing test data, AVHRR data, as well as GOES image data.
LeMoigne, Jacqueline↗
Landscape characterization of peridomestic risk for Lyme disease using satellite imagery
Remotely sensed characterizations of landscape composition were evaluated for Lyme disease exposure risk on 337 residential properties in two communities of suburban Westchester County, New York. Properties were categorized as no, low, or high risk based on seasonally adjusted densities of Ixodes scapularis nymphs, determined by drag sampling during June and July 1990. Spectral indices based on Landsat Thematic Mapper data provided relative measures of vegetation structure and moisture (wetness), as well as vegetation abundance (greenness). A geographic information system (GIS) was used to spatially quantify and relate the remotely sensed landscape variables to risk category. A comparison of the two communities showed that Chappaqua, which had more high-risk properties (P < 0.001), was significantly greener and wetter than Armonk (P < 0.001). Furthermore, within Chappaqua, high-risk properties were significantly greener and wetter than lower-risk properties in this community (P < 0.01). The high-risk properties appeared to contain a greater proportion of broadleaf trees, while lower-risk properties were interpreted as having a greater proportion of nonvegetative cover and/or open lawn. The ability to distinguish these fine scale differences among communities and individual properties illustrates the efficiency of a remote sensing/GIS-based approach for identifying peridomestic risk of Lyme disease over large geographic areas.
Topography, Medical↗
Imageodesy: A Tool for Mapping Subpixel Terrain Displacements in Satellite Imagery
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Mapping↗
High Accuracy 3D Processing of Satellite Imagery
Automatic DSM/DTM generation reproduces not only general features, but also detailed features of the terrain relief. Height accuracy of around 1 pixel in cooperative terrain. RMSE values of 1.3-1.5 m (1.0-2.0 pixels) for IKONOS and RMSE values of 2.9-4.6 m (0.5-1.0 pixels) for SPOT5 HRS. For 3D city modeling, the manual and semi-automatic feature extraction capability of SAT-PP provides a good basis. The tools of SAT-PP allowed the stereo-measurements of points on the roofs in order to generate a 3D city model with CCM The results show that building models with main roof structures can be successfully extracted by HRSI. As expected, with Quickbird more details are visible.
Gruen, A.↗