Engineering topics

Chen, D. W.

Publications and source records attributed to Chen, D. W..

5 records

NASA NTRS1990

Cumulus cloud field morphology and spatial patterns derived from high spatial resolution Landsat imagery

Using high-spatial-resolution Landsat MSS imagery, the cumulus cloud morphology, cloud nearest-neighbor distributions, and cloud clumping scales were investigated. It is shown that the cloud-size distribution can be represented by a mixture of two power laws; clouds of diameters less than 1 km have power-law slope range of 1.4-2.3, while larger clouds have slopes from 2.1 to 4.75. The break in power-law slope occurs at the cloud size that makes the largest contribution to cloud cover. Results suggest that larger clouds grow at the expense of smaller clouds. It was also found that the cloud inhomogeneities have significant impact on radiative fluxes.

Sengupta, S. K.↗

NASA NTRS1990

Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

Welch, R. M.↗

NASA NTRS1989

Cloud field classification based upon high spatial resolution textural features. II - Simplified vector approaches

This paper compares the results of cloud-field classification derived from two simplified vector approaches, the Sum and Difference Histogram (SADH) and the Gray Level Difference Vector (GLDV), with the results produced by the Gray Level Cooccurrence Matrix (GLCM) approach described by Welch et al. (1988). It is shown that the SADH method produces accuracies equivalent to those obtained using the GLCM method, while the GLDV method fails to resolve error clusters. Compared to the GLCM method, the SADH method leads to a 31 percent saving in run time and a 50 percent saving in storage requirements, while the GLVD approach leads to a 40 percent saving in run time and an 87 percent saving in storage requirements.

Chen, D. W.↗

NASA NTRS1988

Cloud field classification based upon high spatial resolution textural features. I - Gray level co-occurrence matrix approach

Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.

Welch, R. M.↗

NASA NTRS1987

Classification of cloud fields based on textural characteristics

The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.

Welch, R. M.↗