REMOTE SENSING RESEARCH IN GEOGRAPHY AT MOSCOW UNIVERSITY

A paper describing activities of the Laboratory of Remote Sensing Methods at Moscow University presents a chronology of the Laboratory's efforts to improve sensor capabilities for acquiring remote sensing data and to develop more effective image processing techniques. Among the accomplishments cited are early advances in sensor system design and photochemical processing in conjunction with “Salyut” orbital station activities, multispectral imaging experiments in conjunction with high-resolution space photography from the Soyuz-12 (1973) and Soyuz-22 (1976) missions, testing of the first high-resolution Soviet (“Fragment”) scanner imagery (1984), and ongoing work in digital and applied image processing. Translated from: Vestnik Moskovsskogo Universiteta, geografiya, 1987, No. 2, pp. 27-31.     

NEW IDEAS IN A QUANTITATIVE APPROACH TO IMAGE PROCESSING

The authors present a statistical approach for multi-band image processing based on “synthesizing” processing methods, i.e., methods which transform N original band-specific images into a smaller number of (synthetic) image products. Such techniques are increasingly replacing “one-dimensional” methods (one-to-one correspondence between number of original and processed images) because of the normally greater informational content and enhanced feature discrimination capability afforded by composite image products. The ultimate objective is development of a complex of image processing strategies balancing user demands for information quantity, image diversity, and efficient use of computer time. Translated from: Metody kompleksnykh aerokosmicheskikh issledovaniy Sibiri, L. K. Zyat'kova, ed. Novosibirsk: Nauka, 1985, pp. 84-87.     

SELECTION OF AN OPTIMAL ALGORITHM FOR RECOGNITION OF NATURAL FEATURES

Two widely used Soviet algorithms for the classification of hydromete-orological features are compared for the purposes of mapping water temperature, electrical conductivity, pH, transparency/turbidity, dissolved surface concentration of chemical elements, depth, etc. The KLASS algorithm, using a solution to the “traveling salesman” problem for classifying objects in feature space, produced higher intra-class proximity and greater inter-class “distances” than the KSS algorithm, based on optimizing “shortest-path” criteria. This was determined through the use of five similar measures of recognition quality. Translated from: Vestnik Leningrad-skogo Universiteta, 1985, No. 14, pp. 95-100.     

AN INSTRUMENT-AIDED METHOD OF INTERPRETING SCANNER IMAGERY OF THE EARTH'S CLOUD COVER

The author, noting the high cost and complexity of automated methods of processing imagery of the earth's cloud cover, presents a less sophisticated, instrument-aided method yielding similar results. A procedure for analyzing cloud cover patterns based on color synthesis of two-band scanner imagery from Soviet “Meteor” and American NOAA-series weather satellites using a synthesizing projector is outlined. This method adds the interpretation key of color to those of cloud structure and form in the analysis of cloud patterns, enhances cloud-underlying surface contrasts, and compares favorably with more highly automated methods in image preparation and interpretation time. Translated by Jay Mitchell; PlanEcon, Inc.; Washington, DC 20005 from: Izvestiya vysshykh uchebnykh zavedeniy, Geodeziya i aerofotos'yemka, 1987, No. 5, pp. 95-98.     

AN EXPERIMENT IN AUTOMATED INTERPRETATION OF REMOTE SENSING IMAGERY

Algorithms, designed for digital image processing in standard mainframe computers and representing sequential stages in a land-use classification procedure, are used to produce maps of agricultural crop types from multispectral satellite imagery. Pixel reflectance values are first grouped according to an unsupervised “rapid classification algorithm,” or data compression procedure. Mean reflectance values of the resulting classes then go into a supervised “sequential clustering algorithm” where classes are refined according to training value and other parameter inputs. The objective is to increase the accessibility of automated image interpretation while balancing classification accuracy and processing time. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1984, No. 4, pp. 63-69.     

IMAGE INTERPRETATION AS A SYSTEM OF SCIENTIFIC RESEARCH

The article provides insights derived from conceptualization of the totality of elements (subsystems) of image interpretation as part of a larger system of scientific research. Among the elements discussed in some detail in terms of their impacts on the appearance of features interpreted on remote sensing imagery include solar radiation, the atmosphere, distinctive characteristics of the surface of the area being imaged, the remote sensors employed for image recording, processing techniques, the image medium, and the “human” element (interpreter). It then describes an evolutionary process in image interpretation by which knowledge gained in early stages represents an input leading to refinement of approaches employed in later stages. A final section describes factors contributing to dynamics (“scintillation” or “flickering”) of features on imagery of the same area but recorded at different times or under different imaging conditions. Translated by Edward Torrey, Alexandria, VA 22308 from: Izvestiya Akademii Nauk, seriya geograficheskaya, 1993, No. 3, pp. 102-109.     

INTERPRETATION OF REMOTE SENSING DATA: THE FOREIGN EXPERIENCE

A report by Soviet delegates to the 15th Congress of the International Society for Photogrammetry and Remote Sensing provides a forum for a Soviet assessment of foreign achievements in the practical application of remote sensing in various fields of economic activity, particularly oil and gas exploration, prospecting for metallic minerals, forestry, and oceanography. Special emphasis is given to digital image processing for land-use classification, a field in which Soviet researchers are becoming increasingly involved. The Congress is described as contributing greatly to the development of common data processing methodologies and the exchange of information and opinions on common problems. Translated from: Geodeziya i kartografiya, 1985, No. 4, pp. 53-58.     

THE METEOR AND METEOR-PRIRODA EARTH OBSERVATION SATELLITES

This first installment in a series of papers extracted from a Soviet “manual” of remote sensing describes the design, operation, and payloads of the “Meteor” and “Meteor-Priroda” earth observation satellites-the latter as name given to “Meteor” satellites used for economic land-use studies, instead of their original meteorological applications. Issues such as orbit parameters, spatial resolution, scan width, and telemetry are also addressed. Translated from: Priroda Zemli iz kosmosa, A.P. Tishchenko and S.V. Viktorov, eds. Leningrad: Gidrometeoizdat, 1984, pp. 16-24.     

PHOTOGRAMMETRIC PRINCIPLES FOR THE COMBINATION OF REMOTE SENSING AND THREE-DIMENSIONAL MAPPING

A review of Soviet research describes methods of combining remote sensing and geodetic data in cartometric data bases—for the purposes of compiling more detailed and accurate “three-dimensional” terrain maps. The major objective is to provide, by means of photogrammetric techniques employing stereopairs or series of overlapping images, elevational data on selective key geomorphological points (along structure lines, summits of ridges, valley bottoms, etc.) which can be used to supplement (or replace) data obtained for the control points of a rectangular grid. Creation of digital models from these “geomorphological” points provides more accurate three-dimensional terrain maps. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1986, No. 6, pp. 56-64.     

DEVELOPMENT OF QUANTITATIVE METHODS OF STUDYING THE EARTH FROM SPACE

The paper surveys the development of “space geography”–a field of knowledge applying the methods of remote sensing, the physical sciences, and mathematics in the solution of geographic problems. Early advances featured methodological improvements (use of quantitative methods in image processing), whereas future research must focus upon perfecting our knowledge of: (a) relationships underlying the use of these methods, i.e., between environmental parameters and reflectance values, (b) methods of effectively combining different types of imagery, and image products and field work, in research, and (c) appropriate quantitative indices for feature recognition. Examples of the operationalization of such concerns are demonstrated for land-use and soil mapping projects. Translated from: Izvestiya, AN SSSR, seriya geograficheskaya, 1985, No. 5, pp. 110–116.     

RADIO-TELEVISION COMPLEXES OF THE METEOR-PRIRODA SATELLITES

A second installment in a series of papers describing the technical basis for Soviet remote sensing from space focuses on the multispectral scanners of the “Meteor-Priroda” series of earth observation satellites. Designs of the various models are provided, as well as explanations of how such tasks as band separation, signal formation, and telemetry are performed. Translated from: Priroda Zemli iz kosmosa, A. P. Tishchenko and S. V. Viktorov, eds. Leningrad: Gidrometeoizdat, 1984, pp. 25-25-34.     

A CENTER FOR IMAGE PROCESSING IN SIBERIAN RESOURCE DEVELOPMENT

The authors describe the structure and operations of a special Center for Geographic Information [digital image] Processing, now being established in support of the “Sibir” “program—a comprehensive research project on applications of remote sensing in Siberian resource development undertaken by the Siberian section of the USSR Academy of Sciences. Translations of related papers on technical aspects of image processing, also products of the program's research, will appear in subsequent installments of Mapping Sciences and Remote Sensing. Translated from: Metody kompleksnykh aerokosmicheskikh issledovaniy Sibiri, edited by L. K. Zyat'kova. Novosibirsk: Nauka, 1985, pp. 57-60.     

THE DEVELOPMENT AND INTRODUCTION OF AUTOMATION INTO CARTOGRAPHY

The author, in response to a critical review of his book on automation in cartography by K. A. Salishchev (see preceding article), defends his ideas on “raster digitizing” (proposed as only one of several approaches to cartographic automation) by documenting the need for a certain level of uniformity in the storage and presentation of information. In the process he continues a debate on the theoretical basis that should govern the development of automated cartography that occupied the entire “Cartography” section of the May 1986 issue of Geodeziya i kartografiya. In a preface to the section, the editorial board of the Soviet journal emphasized that there is no single, universally accepted position on standards for automating cartography or on the ultimate role automation should play in the discipline as a whole. Translated from: Geodeziya i kartografiya, 1986, No. 5, pp. 38–43.     

A GEOGRAPHIC INFORMATION SYSTEM FOR PHYSICAL-GEOGRAPHIC REGIONALIZATION

The design and functioning of a geographic information system established for the purpose of objectively delineating the boundaries of major physical geographic regions in the USSR is described. The basic components include an information input block for data collection and preliminary image processing; a recognition block for feature classification and analysis; a data base management system providing for repeated revision, addition, and use of spectral information; and a block for displaying results of processing in various forms. Applications of the system are demonstrated in the mapping of physical regions in a steppe and semi-desert area of the southern USSR. Translated from: Izvestiya Akademii Nauk SSSR, seriya geograficheskaya, 1988, No. 2, pp. 89-94.     

A STATISTICAL APPROACH TO FEATURE CLASSIFICATION ON REMOTE SENSING IMAGERY

The mathematical basis for a feature classification algorithm is described which combines elements of game theory with Bayesian and suboptimal [feature classification] decision rules. Comparison of reflectance values with training area parameters, according to a sequence of diminishing a priori probabilities that the values will be assigned to that particular class results in reductions in computer time during classification. Results of the procedure are demonstrated through a pair of “before” and “after” images. Translated from: Metody kompleksnykh aerokosmicheskikh issledovaniy Sibiri, L. K. Zyat'kova, ed. Novosibirsk: Nauka, 1985, pp. 75–79.     

THEMATIC MAPPING OF PLANETS: CURRENT SITUATION AND PROSPECTS

Principles and objectives governing Soviet thematic mapping of nearby planets are outlined, types of information sources for such mapping categorized, and the suitability of different types of information sources for thematic mapping are evaluated. This is followed by a classification of thematic planetary maps according to type. The need for a standardized, systems approach to the determination of map scales, compilation and generalization, symbolization, and map design is emphasized as an essential prerequisite for the development of complex atlases of individual planets, atlases of “comparative planetology,” and the establishment of “planetary information systems.” Translated by Jay Mitchell; PlanEcon, Inc.; Washington, DC 20005 from: Vestnik Moskovskogo Universiteta, geografiya, 1987, No. 6, pp. 60-67.     

AN EXPERIMENT IN THE COMPILATION AND USE OF A COMPLEX ENGINEERING-GLACIOLOGICAL MAP

A method for the compilation of 1:3,000,000-scale maps of natural nival-glacial phenomena is proposed for an area of the High Pamir Range in Soviet Central Asia. Such maps depict the distribution, frequency and intensity/magnitude, and potential impacts of such natural hazards as avalanches, mudslides, “dirty snow” avalanches (combined avalanches-mudslides in late spring), icings (naledy), and glacier pulsations, and are used in the planning of construction and the maintenance of roads and other transportation corridors during winter and spring. Hypothetical examples of the use of the maps are provided. Translated from: Materialy glyatsiologicheskikh issledovanly, USSR Geophysical Committee Publication No. 55. Moscow: Mezhduvedomstvenniy geofizicheskiy komitet, 1986, pp. 213–219.     

An automatic procedure for co-registration of terrestrial laser scanners and digital cameras

Driven by progress in sensor technology, algorithms and data processing capabilities, close range photogrammetry has found a wide range of new application fields over the past two decades. Particularly, the emergence of terrestrial laser scanner has contributed to the close range photogrammetry “popularization” through many promising new applications. Nevertheless, a central issue in many of these developments is the integration of sensor technology with reliable data processing schemes to generate highly automated photogrammetric measurements systems.This paper presents a flexible approach for the automatic co-registration of terrestrial laser scanners (TLS) and amateur digital cameras (DC) to be used effectively in practice. Particularly, the developed approach deals with two different images: a camera image acquired with a DC and a range image obtained with a TLS. To this end, an open-source tool “USAlign” has been developed for testing the different experiments.     

彩色影像的遗传自适应增强

提出了一种彩色色形像自适应增强的算法，此算法充分利用了彩色影像饱和度和亮度所包含的信息，并利用遗传算法自适应地调整增强系数。对于不同的影像，本文算法均能使其对比度，目标边缘以及纹理特征得到增强。