In the present paper, making use of the invariant embedding, an initial-value solution of the transfer equation in air-water system with allowance for the interaction of radiation at the system interface is provided. The Cauchy system of the scattering function under consideration requires much computational works. In order to make tractable the inverse solution, we introduce the effective water surface albedo into the Cauchy system of the scattering function for the specular reflection problem, allowing for the multiple scattering effect of radiation in the water. Then, the least squares estimation of the effective water surface albedo from the noisy measurements of the total spectral radiance of water from space is made via the quasilinearization. The numerical experiments showed rapid convergence of the desired results. Based on these data, aqueous optical properties such as chlorophyll concentration and turbidity will be discussed in our subsequent papers.

High resolution photographs were used to prepare a vegetation map of all pure plant communities and dense Melaleuca stands in a 14km2 study site. Landsat data was manipulated with the Image 100 until the spectral limits of dense Melaleuca stands, Flatwoods, Cypress, Swale, Sand and Water produced a coverage map that agreed with the ground truth map. Using the entire Landsat scene, each spectral band of all pixels identified as being one of the pure community forms was averaged to produce six sets of four point spectra (library spectra).

Pixel data from the study site was hand entered on an Apple II computer where a Pascal program determined what proportions of the six library spectra provided the best least squares fit of the unknown pixel's spectrum. Since some spectra could yield several different solutions, the program forced a number of solutions, each accompanied by three measurements of the solution's error. The program evaluated the error terms of all solutions, printing that solution with the least error; if all solutions exceeded acceptable limits, the pixel was labeled unsolvable.

Comparison of the computer's assessment of sixty pixels with that observed in aerial photos of an equivalent area was encouraging. Melaleuca was found to have an average coverage of 54.7% with the Apple as opposed to 55.6% as estimated from aerial photos. In addition, communities which were minor components of many pixels were fairly accurately measured (Sand, 13.2% by Apple vs. 14.9% by photo; Flatwood, 11.4% vs 16.8%; Swale, 7.1% vs 5.7%; Water, 4.4% vs. 3.2%; and Cypress, 1.6% vs 4.2%). Three of sixty pixels were unsolvable.

With this system aerial surveys, mainly for Pollution studies, are carried out.

The purpose of this paper is to comment about a Remote Sensing Data Acquisition System and its digital processing features.

This structuration, according to the HBDS model, seems interesting to take into account many qualitative or/and quantitative data and to manage their relations. This application to drilling data deals with scientific and technical purposes, in coal mine.

In this study, a man-machine interactive processing system performed the analysis of LANDSAT digital data. Specifically, multispectral agricultural crop identification and spatial area determination, within the study areas, were carried out.

A temporal coordination between the multispectral LANDSAT satellite and the ground truth of the same area was attained, from which two test fields digitally classified, in accordance with crop species, crop varieties and soil types of the same place were chosen.

The results illustrate the importance of interactive processing for analyzing LANDSAT data. It must be pointed out that they do not represent the full potential of temporal information since they are preliminary results.

Since the Bhaskara TV data is having a low resolution and as the data was acquired in only one band, namely, 0.54-0. 66 µm, the utility of the data from the point of view of information extraction on earth resources is limited. Moreover, because of its orbital characteristics the data is acquired at different times of the day and thus under various illumination conditions.

This note discusses an approach that is designed to increase the scope of utilisation of this data. This approach is developed using both digital and photographic techniques with a view to arrive at a standard set of keys for analysing and interpreting the TV data. The basis of the digital technique is the frequency distribution of gray tones (reflectance values) for identifying major cover types, classifying them and generation of three new data sets by assigning pseudo grey codes to the classified data. The pseudo gray coded data is then used to generate photographically colour codes for each of the cover type. Each pseudo data set is turned into a photographic film transparency and is assigned the colours red, green and blue respectively. The colour composite made using these transparencies is the new colour coded thematic ground cover picture from Bhaskara.

The analysis of the dual-polarized SAR imagery has shown that certain forest cover features are more easily identified in one polarization than the other, while some features look very similar in both polarizations. In general, the results for this data set have shown that the overall tonal contrast between features was greater on the HH image. Neither polarization was consistently better for identifying the various forest cover types examined. These results suggest the usefulness of a dual-polarized SAR system for mapping forest cover.

Although much previous work exists in this area, it is believed that some of the methods and findings are new. It is also hoped that the extensive testing results along with the constraints of a very high speed production environment will be of value to the remote sensing community.

Therefore, there seems no need to persist in Gaussian probability density function as the only representation of class histograms. In other words, if there are other functions which can approximate the original histograms more accurately than the Gaussian function can, we would better to adopt one of those functions as a representation of a pattern class histogram.

From this point of view, a probability density function was expanded by adding another parameter to the Gaussian function so that it can approximate histograms more flexibly and still can include the Gaussian function itself as a special case.

The expanded function used here is a non-symmetric Gaussian function which has two independent standard deviations for each Side of the mode so that it can approximate the anti-symmetricity of class histogram.

In this paper some characteristics of the non-symmetric Gaussian probability density function were studied. Then the fitness to the original histogram was examined by chi-square test and compared with that of the conventional symmetric Gaussian function. The comparison between symmetric and non-symmetric function was accomplished also on the results of a test run.

Traditionally, three data sources have been utilized in forest related information systems; imagery (aerial photographs), timber inventory and line maps as an output product combining the salient features of imagery and associated attributes. Of the three, only tabular data have been in a form compatible for computer processing, updating and retrieval.

Remote sensing, utilizing digital image processing technology, provides an opportunity, when combined with an interactive digital mapping system, to intergrate the three functional data bases; vis., imagery, maps and tabular inventory, into one geo-referenced information system. The resulting multistructural data base will be managed and organized through mini-host computer system. The St. Regis Forest Resource Information System (FRIS) represents such a scheme, applied in a cost effective operational environment.

This paper describes the applications of remote sensing and satellite image analysis techniques to monitor the forest and range resources Over 94.8 million hectares. The monitoring involves the acquisition and processing of conventional aerial photography, supplementary large scale 70 mm photography, LANDSAT imagery and airbourne multispectral scanner data. Prime interest is the forest land base, consisting of 52.1 million hectares, and the changes which occur in it continuously For example, the approximately' 200 000 hectares that are being harvested annually must be located by the end of each year, mapped and entered into the data base. This dynamic data base was developed during the past 10 years with remote sensing techniques and is now worth around $100 million. In 1978, the Branch acquired an Interactive Graphics Design System (I.G.D.S.) for computerized mapping. Currently, the 7000 forest cover maps are being digitized with the aid of I.G.D.S. and the corresponding inventory data attributes are set up on flexible data management systems.

Highlights of the paper and results of operational applications of remote sensing are illustrated at the conference through a slide presentation.

Generally, information requirements for renewable resource assessments include: (1) area, extent, geographic location, and structure of vegetation types; (2) ecological successional stages of the vegetation types keyed to potential natural vegetation; (3) kind of substrate of the vegetation types in relation to soils and topography to assist in evaluation of resource management options; (4) kinds, amounts, extent, and duration of water bodies, i.e. size of lakes, streams, rivers, and ponds; duration of flow including peak flows; and water quality for commercial, industrial, and recreational activities; and (5) faunal populations.

Information needs may be further categorized as to measured, observed, calculated, or assigned. Measurements include mapping and actual measurement of information items such as tree height, shrub cover, lake area, or vegetation type area. Observed items are the presence or absence of something such as structures or landslides. Both measured and observed items are amenable to remote sensing. Calculated items include such determinations as timber volume and grazing capacity toward which measurements contribute. Assigned information needs include such items as land ownership, political boundaries, management areas. Assigned information must be obtained from sources other than remote sensing.