Yoshifumi Yasuoka

High-speed spectroradiometer for remote sensing

A high-speed spectroradiometer designed for spectral reflectance measurement in remote sensing is described. This instrument uses a monochromatic grating and a photomultiplier system for light detection and sweeps over the 400-850-nm wavelength spectral range with the spectral resolution of 2 nm within 1 s. The instrument has the inherent advantage of portability and speed of operation which make it particularly suitable for field work in the area of fast moving surfaces, e.g., water with wave motion. Some applications of its use in laboratory and field experiments also have been presented. The instrument would seem to be an appropriate instrument for ground data collection in remote sensing.

Utilization of a best linear discriminant function for designing the binary decision tree

This paper describes an accurate and efficient method for supervised classification of multispectral images. First, a simple derivation of a best linear discriminant function (BLD) is presented through geometrical consideration on ellipses with equi-Mahalanosis distance. It is shown that the function satisfies the Minimax criterion, which implies the robutness with regard to prior probabilities. Then, the binary decision tree (BDT) is introduced in order to make the method efficient, where the BLD is utilized as a decision rule. Care is taken to prevent a decline in the classification accuracy during the process of constructing the BDT

Advanced visible near-infrared radiometer (AVNIR)

AVNIR is a high spatial resolution imager on ADEOS with four multispectral bands and one panchromatic band covering the visible and the near-infrared range. AVNIR also has multi- view angle observation (pointing) function with the range of plus or minus 40 degrees from nadir. These two characteristics of AVNIR, high spatial resolution observation and stereoscopic observation, enable it to produce high quality land cover/use maps and digital elevation models (DEM). Besides these two practical products AVNIR is expected to observe scientific parameters including space reflectance and surface reflectance which would play an important role in assessing the radiation budget at the earth surface. Also AVNIR is expected to produce several science data sets for monitoring coastal environment, volcanic activities as well as terrestrial ecosystems.

Evaluation Of Atmospheric Effect On Remotely Sensed Data Based On Measurement Of Spectral Radiance

Atmospheric parameters were evaluated from the measurement of the upward surface radiance and the downward solar radiance above the surface in water area. The atmospheric transmittance and the path radiance were estimated by regression analysis between a set of radiance data which are the radiance detected by a remote sensor and the upward radiance simultaneously measured at the surface. Also the transmittance was estimated from the direct solar beam radiance measured at the surface by asuming the extraterrestrial solar radiance.

Pattern Model for Prediction of Regional Distribution

Abstract An attempt is made of devising a pattern model to represent area-wide distribution of pollution. In deriving the model, a kind of mathematical filter is first applied to environmental data monitored at several points to provide areal patterns. The feature extracted from the patterns are then correlated with various environmental factors by mean of the cluster analysis. Thus derived relationship is practically applicable to predicting future environmental pollution. Besides this, the presented procedure can be of great use in environmental data management and some other purpouses. No other works similar to the present one have ever appeared.

Region Extraction and Classification of Multi-Spectral Images by Entropy Index

Abstract A practical method is proposed for extracting and classifying regions in remotely sensed multi-spectral images. First, an entropy index based on the gray level histogram of local sub-area is shown to be effective for extracting regions which have homogeneous gray levels in the image. It is demonstrated in the next step that the maximum likelihood method using spectral characteristics of the extracted regions is capable of classifying regions in the image. This multi-stage unsupervised method is applied to the actual environmental land use classification.