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At least 505 records · Page 28

The least-squares mixing models to generate fraction images derived from remote sensing multispectral data

Constrained-least-squares and weighted-least-squares mixing models for generating fraction images derived from remote sensing multispectral data are presented. An experiment considering three components within the pixels-eucalyptus, soil (understory), and shade-was performed. The generated fraction images for shade (shade image) derived from these two methods were compared by considering the performance and computer time. The derived shade images are related to the observed variation in forest structure, i.e., the fraction of inferred shade in the pixel is related to different eucalyptus ages.

Shimabukuro, Yosio Edemir↗

Multispectral image fusion using neural networks

A prototype system is being developed to demonstrate the use of neural network hardware to fuse multispectral imagery. This system consists of a neural network IC on a motherboard, a circuit card assembly, and a set of software routines hosted by a PC-class computer. Research in support of this consists of neural network simulations fusing 4 to 7 bands of Landsat imagery and fusing (separately) multiple bands of synthetic imagery. The simulations, results, and a description of the prototype system are presented.

Kagel, J. H.↗

The measurement of mangrove characteristics in southwest Florida using SPOT multispectral data

An intensive in situ sampling program near Marco Island, Florida during 19-23 October 1988 collected information on mangrove type, maximum canopy height, and percent canopy closure. These data were correlated with selected vegetation index information derived from analysis of SPOT multispectral (XS) data obtained on 21 October 1988. The Normalized Difference (ND) vegetation index information was the most highly correlated index with percent canopy closure (r = 0.91). Percent canopy closure information can be used as a surrogate for mangrove density which is of great value when predicting which parts of the mangrove ecosystem are at greatest risk after an oil spill occurs. Such information is very valuable when constructing oil spill Environmental Sensitivity Index (ESI) Maps for tropical regions of the world.

Jensen, John R.↗

Synergistic use of multispectral satellite data for monitoring land surface change

Observations by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites were used to compute visible and near infrared reflectances and surface temperature, while passive microwave observations at 37 GHz frequency by the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) on board, respectively, the Nimbus-7 and DMSP-F8 satellites were used to compute polarization difference. These observations were analyzed along transects from rainforest to desert over northern Africa for the period 1979-1987, which included an unprecedented drought during 1984 over the Sahel zone. Model simulations were made to understand the interrelationship among multispectral data.

Choudhury, Bhaskar J.↗

Multispectral Image Processing for Plants

The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

Miles, Gaines E.↗

Sea surface velocities from visible and infrared multispectral atmospheric mapping sensor imagery

High resolution (100 m), sequential Multispectral Atmospheric Mapping Sensor (MAMS) images were used in a study to calculate advective surface velocities using the Maximum Cross Correlation (MCC) technique. Radiance and brightness temperature gradient magnitude images were formed from visible (0.48 microns) and infrared (11.12 microns) image pairs, respectively, of Chandeleur Sound, which is a shallow body of water northeast of the Mississippi delta, at 145546 GMT and 170701 GMT on 30 Mar. 1989. The gradient magnitude images enhanced the surface water feature boundaries, and a lower cutoff on the gradient magnitudes calculated allowed the undesirable sunglare and backscatter gradients in the visible images, and the water vapor absorption gradients in the infrared images, to be reduced in strength. Requiring high (greater than 0.4) maximum cross correlation coefficients and spatial coherence of the vector field aided in the selection of an optimal template size of 10 x 10 pixels (first image) and search limit of 20 pixels (second image) to use in the MCC technique. Use of these optimum input parameters to the MCC algorithm, and high correlation and spatial coherence filtering of the resulting velocity field from the MCC calculation yielded a clustered velocity distribution over the visible and infrared gradient images. The velocity field calculated from the visible gradient image pair agreed well with a subjective analysis of the motion, but the velocity field from the infrared gradient image pair did not. This was attributed to the changing shapes of the gradient features, their nonuniqueness, and large displacements relative to the mean distance between them. These problems implied a lower repeat time for the imagery was needed in order to improve the velocity field derived from gradient imagery. Suggestions are given for optimizing the repeat time of sequential imagery when using the MCC method for motion studies. Applying the MCC method to the infrared brightness temperature imagery yielded a velocity field which did agree with the subjective analysis of the motion and that derived from the visible gradient imagery. Differences between the visible and infrared derived velocities were 14.9 cm/s in speed and 56.7 degrees in direction. Both of these velocity fields also agreed well with the motion expected from considerations of the ocean bottom topography and wind and tidal forcing in the study area during the 2.175 hour time interval.

Pope, P. A.↗

Multispectral variable magnification glancing incidence x ray telescope

A multispectral, variable magnification, glancing incidence, x-ray telescope capable of broadband, high resolution imaging of solar and stellar x-ray and extreme ultraviolet radiation sources is discussed. The telescope includes a primary optical system which focuses the incoming radiation to a primary focus. Two or more rotatable mirror carriers, each providing a different magnification, are positioned behind the primary focus at an inclination to the optical axis. Each carrier has a series of ellipsoidal mirrors, and each mirror has a concave surface covered with a multilayer (layered synthetic microstructure) coating to reflect a different desired wavelength. The mirrors of both carriers are segments of ellipsoids having a common first focus coincident with the primary focus. A detector such as an x-ray sensitive photographic film is positioned at the second respective focus of each mirror so that each mirror may reflect the image at the first focus to the detector at the second focus. The carriers are selectively rotated to position a selected mirror for receiving radiation from the primary optical system, and at least the first carrier may be withdrawn from the path of the radiation to permit a selected mirror on the second carrier to receive the radiation.

Hoover, Richard B.↗

Commercial Applications Multispectral Sensor System

NASA's Office of Commercial Programs is funding a multispectral sensor system to be used in the development of remote sensing applications. The Airborne Terrestrial Applications Sensor (ATLAS) is designed to provide versatility in acquiring spectral and spatial information. The ATLAS system will be a test bed for the development of specifications for airborne and spaceborne remote sensing instrumentation for dedicated applications. This objective requires spectral coverage from the visible through thermal infrared wavelengths, variable spatial resolution from 2-25 meters; high geometric and geo-location accuracy; on-board radiometric calibration; digital recording; and optimized performance for minimized cost, size, and weight. ATLAS is scheduled to be available in 3rd quarter 1992 for acquisition of data for applications such as environmental monitoring, facilities management, geographic information systems data base development, and mineral exploration.

Birk, Ronald J.↗

Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

Steffen, Konrad↗

Spectral mixture analysis of multispectral thermal infrared images

Remote spectral measurements of light reflected or emitted from terrestrial scenes is commonly integrated over areas sufficiently large that the surface comprises more than one component. Techniques have been developed to analyze multispectral or imaging spectrometer data in terms of a wide range of mixtures of a limited number of components. Spectral mixture analysis has been used primarily for visible and near-infrared images, but it may also be applied to thermal infrared data. Two approaches are reviewed: binary mixing and a more general treatment for isothermal mixtures of a greater number of components.

Gillespie, Alan R.↗

Enhancement of multispectral thermal infrared images - Decorrelation contrast stretching

Decorrelation contrast stretching is an effective method for displaying information from multispectral thermal infrared (TIR) images. The technique involves transformation of the data to principle components ('decorrelation'), independent contrast 'stretching' of data from the new 'decorrelated' image bands, and retransformation of the stretched data back to the approximate original axes, based on the inverse of the principle component rotation. The enhancement is robust in that colors of the same scene components are similar in enhanced images of similar scenes, or the same scene imaged at different times. Decorrelation contrast stretching is reviewed in the context of other enhancements applied to TIR images.

Gillespie, Alan R.↗

Biosphere/atmosphere CO2 exchange in tundra ecosystems - Community characteristics and relationships with multispectral surface reflectance

CO2 exchange rates were measured at selected tundra sites near Bethel, Alaska using portable, climate-controlled, instrumented enclosures. The empirically modeled exchange rate for a representative area of vegetated tundra was 1.2 +/- 1.2 g/sq m/d, compared to a tower-measured exchange over the same time period of 1.1 +.0- 1.2 g/sq m/d. Net exchange in response to varying light levels was compared to wet meadow and dry upland tundra, and to the net exchange measured by the micrometeoroidal tower technique. The multispectral reflectance properties of the sites were measured and related to exchange rates in order to provide a quantitative foundation for the use of satellite remote sensing to monitor biosphere/atmosphere CO2 exchange in the tundra biome.

Whiting, Gary J.↗

Calibration of EOS multispectral imaging sensors and solar irradiance variability

Earth Observation System (EOS) optical multispectral imaging sensors provide images of the earth at various spectral and spatial resolutions, in the visible (VIS) and infrared (IR) regions of the solar spectrum. Accurate knowledge of extraterrestrial solar spectral irradiance and its variations with time, are needed to trace sensor calibration in space, and for the development of terrestrial atmospheric models needed in data validation. A brief review of the extraterrestrial solar VIS/IR spectral irradiance available in the literature will be reviewed, and the need to develop an extraterrestrial solar spectral irradiance for the EOS studies will be pointed out. The solar calibration of the Earth Radiation Budget Experiments (ERBE), earth-viewing sensors will be discussed. Observed variations in the solar constant (solar irradiance, at the mean sun-earth distance of one astronomical unit, integrated over all wavelengths), and solar spectral irradiance with solar activity and its implications for EOS studies also will be discussed.

Mecherikunnel, Ann↗

Determination of water surface temperature based on the use of Thermal Infrared Multispectral Scanner data

A straightforward method for compensating Thermal Infrared Multispectral Scanner (TIMS) digital data for the influence of atmospheric path radiance and the attenuation of target energy by the atmosphere is presented. A band ratioing model useful for estimating water surface temperatures, which requires no ground truth measurements, is included. A study conducted to test the potential of the model and the magnitudes of the corrections for atmosphere encountered is presented. Results of the study, which was based on data collected during an engineering evaluation flight of TIMS, indicate errors in the estimate of the surface temperature of the water fall from +/- 1.0 C for uncorrected data to +/- 0.4 C when data have been corrected according to the model presented. This value approaches the noise-limited thermal resolution of the sensor at the time of the flight.

Anderson, James E.↗

An investigative study of multispectral lossy data compression using vector quantization

Spectral vector quantization is presently applied to multispectral imagery from airborne scanners; the vector is here defined as an array of pixels from the same location from each channel. Attention is given to the effect of varying the size of the vector codebook on the quality of the compression and on subsequent classification. The rate of compression is programmable, but higher degradation is associated with higher compression ratios.

Jaggi, S.↗

Commercial applications multispectral sensor system

NASA's Office of Commercial Programs is funding a multispectral sensor system to be used in the development of remote sensing applications. The Airborne Terrestrial Applications Sensor (ATLAS) is designed to provide versatility in acquiring spectral and spatial information and will be a test bed for the development of specifications for airborne and spaceborne remote sensing instrumentation for dedicated applications. This objective requires spectral coverage from the visible through thermal IR wavelengths, variable spatial resolution form 2-25 meters; high geometric and geolocation accuracy; on-board radiometric calibration; digital recording; and optimized performance for minimized cost, size, and weight.

Birk, Ronald J.↗

An algorithm for the estimation of water temperatures from thermal multispectral airborne remotely sensed data

A method for water temperature estimation on the basis of thermal data is presented and tested against NASA's Thermal IR Multispectral Scanner. Using realistic bounds on emissivities, temperature bounds are calculated and refined to estimate a tighter bound on the emissivity of the source. The method is useful only when a realistic set of bounds can be obtained for the emissivities of the data.

Jaggi, S.↗

A new clustering algorithm applicable to multispectral and polarimetric SAR images

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

Wong, Yiu-Fai↗