USE OF SPACE IMAGERY IN THE STUDY OF MASS EXCHANGE IN GLACIER SYSTEMS

The author surveys the use of remote sensing imagery in the study of mass exchange in glaciers, i.e., glacier dynamics resulting from phase changes in the water which they contain. A program of research now underway at the Institute of Geography (USSR Academy of Sciences) in conjunction with the “Priroda” Remote Sensing Center (Moscow) focuses on improving methods of data collection and mapping of glacier dynamics from space imagery, and particularly on identifying natural glacioclimatic zones believed to represent specific mass exchange conditions or regimes. The boundary of glacier nourishment separating areas of accumulation and ablation represents a key glacioclimatic indicator of mass exchange on satellite imagery and aerial photography. Translated from: Geodeziya i kartografiya, 1986, No. 5, pp. 26–31.     

MAPPING THE DYNAMICS OF COMPLEX ECOSYSTEMS BASED ON SEQUENTIAL REMOTE SENSING IMAGERY

A quantitative method for mapping the contemporary dynamics of ecosystems is described. Particular reference is to the mapping of the desertification of complex ecosystems of the lower reaches of the Amudar'ya using a time series of four surveys. The types of ecological transitions identified from remote sensing imagery and their frequencies are described. Translated by Edward Torrey, Alexandria, VA 22308 from: Izvestiya Akademii Nauk, seriya geograficheskaya, 1994, No. 5, pp. 112-122.     

USE OF SPACE IMAGERY IN THE FOREST ECONOMY

This paper provides a broad overview of current Soviet applications of remote sensing in the performance of forest inventories and related valuational studies, and in the production of derivative thematic maps—in particular, the photostatistical method of forest inventory based on interactive computer-assisted interpretation of satellite imagery and large-scale air photos. The ultimate future objective is the formation of a unified remote sensing-geographic information system for forest management and inventory purposes that will encompass the entire forested area of the country. Advances in the use of satellite imagery in the monitoring of forest fires, insect infestations, and rangeland deterioration have also been made since the late 1970s. Translated from: Geodeziya i kartografiya, 1986, No. 4, pp. 30–36.     

REMOTE SENSING IN THE STUDY OF DEEP GEOLOGIC STRUCTURE IN OIL AND GAS FIELDS

The paper presents a series of guidelines, developed by the “Aerogeologiya” prospecting trust, for the use of remote sensing imagery in the study of oil-gas potential in remote areas of the USSR. These guidelines take into consideration both conventional oil-gas exploration strategies and the sequence typical of remote sensing research [from small-scale, general analysis, to large-scale detailed studies]. At present predominantly small-scale imagery is used for general reconnaissance, although instances where larger-scale images provide the basis for more specific investigations are also mentioned. A diagram demonstrates how remote sensing might be incorporated into the traditional framework of oil-gas exploration. Translated from: Kompleksnyye aerokosmicheskiye issledovaniya Sibiri, A. L. Yanshin and L. K. Zyat'kova, eds. Novosibirsk: Nauka, 1984, pp. 33-40.     

FIRST-ORDER TRAVERSES IN CEYLON

Abstract

In the last three years about 250 miles of “precise” traverse have been surveyed in this country to provide control for detail surveys. A brief account of the results may be of general interest. The traverses are situated where trig. points are far apart, and the cost of subsidiary triangulation would have been excessive on account of the flat nature of the country.     

REMOTE SENSING METHODS IN THE STUDY OF SOILS IN BELARUS'

Applications of remote sensing in the study of soils of Belarus' are investigated. The focus is upon ascertaining relationships between phototone of cultivated soils and various soil characteristics (humus content, texture, etc.); upon ensuring the best times for imaging; on the revision of existing soil maps from remote sensing imagery; and on determinations of humus content from spectral reflectance values. Translated by Edward Torrey, Alexandria, VA 22308 from: G. V. Dobrovol'skiy and V. L. Andronikov, eds., Aerokosmicheskiye metody v pochvovedenii i ikh ispol'zovaniye v sel'skom khozyaystve: sbornik nauchnykh trudov [Remote Sensing Methods in Soil Science and Their Utilization in Agriculture: A Collection of Scientific Works]. Moscow: Nauka, 1990, pp. 109–116.     

REMOTE SENSING IN PROFESSIONAL TRAINING OF CARTOGRAPHER-GEOGRAPHERS

The author reviews the contributions of the “aerospace” disciplines (remote sensing, photogrammetry, photometry) in the training of cartographers at Moscow University. Changes in the present curriculum are advocated, leading to the emergence of a unified educational discipline referred to alternately as “remote mapping methods,” or “remote sensing and mapping.” Training in this discipline is designed to enhance the interpretation and map compilation skills of cartographers working with space imagery. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1984, No. 5, pp. 40-43.     

Detection of Tamarisk Defoliation by the Northern Tamarisk Beetle Based on Multitemporal Landsat 5 Thematic Mapper Imagery

The spread of tamarisk (Tamarix spp., also known as saltcedar) is a significant ecological disturbance in western North America and has long been targeted for control, leading to the importation of the northern tamarisk beetle (Diorhabda carinulata) as a biological control agent. Following its initial release along the Colorado River near Moab, Utah in 2004, the beetle has successfully established and defoliated tamarisk across much of the upper Colorado River Basin. However, the spatial distribution and seasonal timing of defoliation are complex and difficult to quantify over large areas. To address this challenge, we tested and compared two remote sensing approaches to mapping tamarisk defoliation: Disturbance Index (DI) and a decision tree method called Random Forest (RF). Based on multitemporal Landsat 5 TM imagery for 2006-2010, changes in DI and defoliation probability from RF were calculated to detect tamarisk defoliation along the banks of Green, Colorado, Dolores and San Juan rivers within the Colorado Plateau area. Defoliation mapping accuracy was assessed based on field surveys partitioned into 10 km sections of river and on regions of interest created for continuous riparian vegetation. The DI method detected 3711 ha of defoliated area in 2007, 7350 ha in 2008, 10,457 ha in 2009 and 5898 ha in 2010. The RF method detected much smaller areas of defoliation but proved to have higher accuracy, as demonstrated by accuracy assessment and sensitivity analysis, with 784 ha in 2007, 960 ha in 2008, 934 ha in 2009, and 1008 ha in 2010. Results indicate that remote sensing approaches are likely to be useful for studying spatiotemporal patterns of tamarisk defoliation as the tamarisk leaf beetle spreads throughout the western United States.     

BASE MEASUREMENT IN THE ANGLO-EGYPTIAN SUDAN

Abstract

Since 1899 cadastral mapping in the Sudan has been concentrated along the banks of the Nile from the Egyptian frontier to latitude 13°N., in the towns, and in the area of the Gezira, south of Khartoum, where cotton has been developed. These surveys were controlled by theodolite and steel tape either in the form of traverses or rectangulation. The early triangulation was used mainly to control topographical surveys, for it was essential to cover the whole country as rapidly as possible with a series of maps on scale 1: 250,000. As a consequence much of this early triangulation is of a relatively low order of accuracy, indifferently marked on the ground, and unfit for inclusion in a framework for medium and large scale mapping.     

Tracking desertification on the Mongolian steppe through NDVI and field-survey data

Abstract

Changing environmental and socio-economic conditions make land degradation, a major concern in Central and East Asia. Globally satellite imagery, particularly Normalized Difference Vegetation Index (NDVI) data, has proved an effective tool for monitoring land cover change. This study examines 33 grassland water points using vegetation field studies and remote sensing techniques to track desertification on the Mongolian plateau. Findings established a significant correlation between same-year field observation (line transects) and NDVI data, enabling an historical land cover perspective to be developed from 1998 to 2006. Results show variable land cover patterns in Mongolia with a 16% decrease in plant density over the time period. Decline in cover identified by NDVI suggests degradation; however, continued annual fluctuation indicates desertification – irreversible land cover change – has not occurred. Further, in situ data documenting greater cover near water points implies livestock overgrazing is not causing degradation at water sources. In combination of the two research methods – remote sensing and field surveys – strengthen findings and provide an effective way to track desertification in dryland regions.     

GEODETIC LEVELLING IN KENYA

Abstract

Kenya-Topography. Kenya lies astride the Equator between latitudes 4°N and 4°S and extends from Lake Victoria to the Indian Ocean (34°E to 42°E). Between long. 36° and 36½°E it is traversed from north to south by the great Rift Valley, the surface of which is generally 2000-3000ft. lower than the level of the plateau on each side. The plateau culminates in the Aberdare Range (13,000 ft.) east of the Rift, and the Mau Forest (10,000 ft.) and Cherangani Hills (11,000ft.) west of the Rift. Together with the isolated mountain masses of Elgon (14,000 ft.), Kenya (17,000ft.) and Kilimanjaro (19,500ft.), this topography may be expected to cause considerable local distortion in the shape of the geoid. Gravity surveys in 1933-4 indicated a negative anomaly below the floor of the Rift Valley, suggesting that it had been forced down by over-riding pressure from both sides.     

SPECTRAL BRIGHTNESS STUDIES OF AGRICULTURAL CROPS AND FORESTS

Spectrophotometric observations of agricultural crops and forest vegetation, taken for the purpose of establishing ground truth for remote sensing surveys, are analyzed. Special attention is given to variations in the spectral signatures of wheat, conifers, and deciduous trees occurring during the growing season. Variations of radiation absorption in the 550-730 nm band correspond closely with the physiological state and biological productivity of wheat during the growing season. Mean spectral brightness values of deciduous and coniferous forest stands during the growing season are sufficiently different to be diagnostic, especially during spring and autumn. Translated from: Kosmlcheskiye issledovaniya prirodnykh kompleksov Sibiri i Dal'nego Vostoka, Novosibirsk, 1983, pp. 126-132.     

PRINCIPLES OF MAPPING THE SOIL-VEGETATION STRUCTURE IN WEST SIBERIA BASED ON REMOTE SENSING IMAGERY

Procedures for mapping the soil-vegetation structure of West Siberia on the basis of remote sensing images are described. Four principal stages are involved: interpretation of individual structures on the images; determination of the functions of the interpreted structures; classification of soil-vegetation structures; and mapping of the territory by types of soil-vegetation structures (micro-, meso- and microstructures). Particular attention is given to detection of soil-vegetation hydromorphism using remote sensing imagry, important in the swampy Western Siberian environment, and the special problems related to image scale. Translated by Edward Torrey, Alexandria, VA 22308 from: Geografiya i prirodnyye resursy, 1990, No. 1, pp. 138–145.     

ERRORS IN THE INDICATION OF GEOSYSTEMS FROM REMOTE SENSING IMAGERY

After a general discussion of principles of remote sensing indication and image recognition theory, the particular errors in this process are analyzed individually: errors in data recording; errors in automated image analysis; errors in interpretation of the content of geosystems; errors in the selection of interpretation keys; and finally errors in generalization and the extrapolation of results. The total error in geosystem indication from remote sensing imagery can be determined by an analysis of these particular errors. Translated by Edward Torrey, Alexandria, VA 22308 from: Geografiya i prirodnyye resursy, 1988, No. 4, pp. 98-107.     

REMOTE SENSING IN THE STUDY OF LANDSCAPE STRUCTURE

Applications of remote sensing, in particular space imagery, in the study of the physical structure of landscapes are described. Special attention is paid to space imagery's capacity for instantaneous analysis of extensive areas, its potential for combined use with more traditional methods, and the multiscalar quality of the data obtained. Joint use of a variety of image products and imaging sequences provides diverse information which can be integrated for a more comprehensive understanding of landscape structure in a variety of physical environments. Translated from: Izvestiya Vsesoyuznogo geograficheskogo obshchestva, 1985, No. 3, pp. 266-270.     

Entropy-based fuzzy classification parameter optimization using uncertainty variation across spatial resolution

In the past researchers have suggested hard classification approaches for pure pixel remote sensing data and to handle mixed pixels soft classification approaches have been studied for land cover mapping. In this research work, while selecting fuzzy c-means (FCM) as a base soft classifier entropy parameter has been added. For this research work Resourcesat-1 (IRS-P6) datasets from AWIFS, LISSIII and LISS-IV sensors of same date have been used. AWIFS and LISS-III datasets have been used for classification and LISS-III and LISS-IV data were used for reference data generation, respectively. Soft classified outputs from entropy based FCM classifiers for AWIFS and LISS-III datasets have been evaluated using sub-pixel confusion uncertainty matrix (SCM). It has been observed that output from FCM classifier has higher classification accuracy with higher uncertainty but entropy-based classifier with optimum value of regularizing parameter generates classified output with minimum uncertainty.     

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.     

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.     

陆地总初级生产力遥感估算精度分析

准确估算陆地总初级生产力GPP(Gross Primary Productivity)数值对碳循环过程模拟有重要影响。本文介绍了多种基于植被指数以及基于光能利用率的遥感GPP算法,综述了不同算法在其研究区域的估算精度;并分析了MODIS/GPP以及BESS/GPP两种遥感GPP产品在不同植被类型的估算精度。通过对比全球碳通量站网络GPP数据表明,MODIS/GPP产品在全球估算结果具显著相关性(R2=0.59)及中等标准误差(RMSE=2.86 g C/m2/day),估算精度较高的植被类型有落叶阔叶林,草地等;估算精度较低类型包括常绿阔叶林,稀树草原等。本文对GPP产品中存在的不确定性进行分析,通过综述前人研究中发现的遥感估算GPP方法中存在的问题,指出可能的提高卫星遥感GPP产品估算精度的方法及发展趋势。