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.     

INTERPRETATION OF THE AGRICULTURAL LANDSCAPE WITH SPACE IMAGERY

Heterochronous multispectral imagery from the “Fragment” scanner is used to identify and map a series of “natural-agricultural complexes,” or agricultural landscapes, of southern European Russia. Interpretation is based on imagery in the green, orange, red, and near-infrared zones of the spectrum (0.5-1.1 μm). Interpretation keys and other information designed to facilitate feature discrimination (optimal wavelengths, best seasons for imagining) are provided in many instances. Natural landscape and soil erosion maps are also compiled from the imagery, which supply information (an optimal crop rotation scheme and needed reclamation measures) used on the agricultural landscape map. Translated from: Vestnik Moskovs-kogo Unlversiteta, geografiya, 1985, No. 2, pp. 34-41.     

Forest cover trends from time series Landsat data for the Australian continent

In perennial and natural vegetation systems, monitoring changes in vegetation over time is of fundamental interest for identifying and quantifying impacts of management and natural processes. Subtle changes in vegetation cover can be identified by calculating the trends of a vegetation density index over time. In this paper, we apply such an index-trends approach, which has been developed and applied to time series Landsat imagery in rangeland and woodland environments, to continental-scale monitoring of disturbances within forested regions of Australia. This paper describes the operational methods used for the generation of National Forest Trend (NFT) information, which is a time-series summary providing visual indication of within-forest vegetation changes (disturbance and recovery) over time at 25 m resolution. This result is based on a national archive of calibrated Landsat TM/ETM+ data from 1989 to 2006 produced for Australia's National Carbon Accounting System (NCAS). The NCAS was designed in 1999 initially to provide consistent fine-scale classifications for monitoring forest cover extent and changes (i.e. land use change) over the Australian continent using time series Landsat imagery. NFT information identifies more subtle changes within forested areas and provides a capacity to identify processes affecting forests which are of primary interest to ecologists and land managers. The NFT product relies on the identification of an appropriate Landsat-based vegetation cover index (defined as a linear combination of spectral image bands) that is sensitive to changes in forest density. The time series of index values at a location, derived from calibrated imagery, represents a consistent surrogate to track density changes. To produce the trends summary information, statistical summaries of the index response over time (such as slope and quadratic curvature) are calculated. These calculated index responses of woody vegetation cover are then displayed as maps where the different colours indicate the approximate timing, direction (decline or increase), magnitude and spatial extent of the changes in vegetation cover. These trend images provide a self-contained and easily interpretable summary of vegetation change at scales that are relevant for natural resource management (NRM) and environmental reporting.     

THE STUDY OF SOIL-VEGETATION DYNAMICS THROUGH REMOTE SENSING

Remote sensing imagery at widely varying scales is used in the analysis of the soil-vegetation cover of the west-central Siberia. Space imagery and smaller-scale air photographs initially are used to divide a study area into basic soil-vegetation complexes based on the criterion of figure outline. The internal structure of the complexes are then analyzed in greater detail, using larger-scale air photographs and a standard interpretation key based on selected field observations. Tonal-textural variations establish the ecological affiliations of separate elements within each complex and their dynamic states at a particular point in time. Translated from: Geografiya i prirodnyye resursy, 1985, No. 2, pp. 112-119.     

A comparison of three image-object methods for the multiscale analysis of landscape structure

Within the conceptual framework of Complex Systems, we discuss the importance and challenges in extracting and linking multiscale objects from high-resolution remote sensing imagery to improve the monitoring, modeling and management of complex landscapes. In particular, we emphasize that remote sensing data are a particular case of the modifiable areal unit problem (MAUP) and describe how image-objects provide a way to reduce this problem. We then hypothesize that multiscale analysis should be guided by the intrinsic scale of the dominant landscape objects composing a scene and describe three different multiscale image-processing techniques with the potential to achieve this. Each of these techniques, i.e., Fractal Net Evolution Approach (FNEA), Linear Scale-Space and Blob-Feature Detection (SS), and Multiscale Object-Specific Analysis (MOSA), facilitates the multiscale pattern analysis, exploration and hierarchical linking of image-objects based on methods that derive spatially explicit multiscale contextual information from a single resolution of remote sensing imagery. We then outline the weaknesses and strengths of each technique and provide strategies for their improvement.     

REMOTE SENSING APPLICATIONS IN AGRICULTURE AND SOIL SCIENCE PART II: REMOTE SOIL MONITORING: ORGANIZATION OF SOIL MONITORING BASED ON REMOTE SENSING IMAGERY

A paper addressing general issues of concern in organizing a system of soil monitoring based on remote sensing imagery covers such topics as general principles which must be observed, the selection of indices optimizing the acquisition of useful information, and the adoption of suitable methodologies. A subsequent section of the paper focuses on the types of information to be derived from soil monitoring in arid regions and areas susceptible to heightened soil erosion. 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. 154–161.     

AN OVERVIEW OF GEOLOGICAL EXPERIMENTS CARRIED OUT ON BOARD MANNED SPACECRAFT AND SPACE STATIONS

An introductory paper to a series of articles on geological applications of remote sensing imagery produced from manned space flights chronicles a progression in research from the simple identification of geomorphological complexes during space flight to specific programs of observation and hand-held photography on board orbiting space stations. The coverage is primarily devoted to Soviet achievements over the period 1961–1982, especially to work conducted on board the space stations Salyut-5 through Salyut-7. Translated by Jay K. Mitchell, PlanEcon, Inc., Washington, DC 20005 from: B. M. Zubarev, V. V. Kozlov, and V. V. Lebedev, Kosmonavty issleduyut Zemlyu [Cosmonauts Study the Earth]. Moscow: Nauka, 1991, pp. 37–41.     

Employing spatial information technologies to monitor biological control of saltcedar in West Texas

The saltcedar leaf beetle (Diorhadha spp.) has shown promise as a biocontrol agent for saltcedar (Tamarix spp.) invasions in the USA. In Texas, natural resource managers need assistance in monitoring biological control of invasive saltcedars. This study describes application of a medium-format, digital camera acquiring natural colour imagery and global positioning system (GPS) and geographic information system (GIS) technologies to check biological control of saltcedar in west Texas. On 8 July and 8 September 2011, natural colour airborne digital imagery was collected along a 155.8?km transect covering portions of Presidio and Brewster counties of Texas. The camera was tethered to a GPS receiver that geotagged each image and saved the coordinates to a key-hole marked up language file that was viewable on Google Earth. Saltcedar trees exhibiting severe feeding damage and those that were totally defoliated were easily identified in the imagery. The former appeared in orange to brown colour tones; the latter exhibited grey colour tones. Point distribution maps showing locations of saltcedar trees exhibiting feeding damage were developed from GPS information in the GIS. Coordinate points on the map were linked to the corresponding image, permitting the user to have quick access to view imagery. The results of this study show a practical method for monitoring biological control of saltcedar.     

Use of Kendall's coefficient of concordance to assess agreement among observers of very high resolution imagery

Ground-based vegetation monitoring methods are expensive, time-consuming and limited in sample size. Aerial imagery is appealing to managers because of the reduced time and expense and the increase in sample size. One challenge of aerial imagery is detecting differences among observers of the same imagery. Six observers analysed a set of 1-mm ground sample distance aerial imagery for graminoid species composition and important ground-cover characteristics. Kendall's coefficient of concordance (W) was used to measure agreement among observers. The group of six observers was concordant when assessed as a group. When each of the observers was assessed independently against the other five, lack of agreement was found for those graminoid species that were difficult to identify in the aerial images.     

MONITORING ENVIRONMENTAL IMPACTS OF LENINGRAD ON THE SURROUNDING AREA

The author, a remote sensing specialist in Leningrad University's Department of Atmospheric Physics, describes the use of space imagery in a program for monitoring the city's impacts on the surrounding environment. The paper examines applications of LANDSAT and “Meteor” satellite imagery and “Soyuz-22” space photography in the study of industrial smoke plumes, jet contrails, atmospheric haze, albedo, the urban heat island, urban sprawl (including nighttime imagery), fallout of suspended particulates, and wastewater discharges into the Gulf of Finland. Translated from: Grigor'yev, A. A. Antropogennyye vozdeystviya na prirodnuyu sredy po nablyudeniyam iz kosmosa [Human Impacts on the Environment From Observations From Space]. Leningrad: Nauka, 1985, pp. 129-141 [Chapter 7].     

Generic rule-sets for automated detection of urban tree species from very high-resolution satellite data

The sustainable management and monitoring of urban forests is an important activity in the urbanized world, and operational approaches require information about the status of urban trees to determine the best strategy. One limitation in urban forest studies is the detection and discrimination of tree species using limited training data. Thus, this study focuses on developing generic rule sets from high-resolution WorldView-2 imagery in conjunction with spectral, spatial, colour and textural information for automated urban tree species detection. The object-based image analysis and its combination with statistical analysis of object features is utilized for this purpose. Results of attribute selection indicated that from 55 attributes, only 26 were useful to discriminate urban tree species, namely Messua ferrea L., Samanea saman and Casuarina sumatrana. Finally, the high overall accuracy, approximately 86.87% with kappa of 0.75 confirmed the transferability of the generic model.     

NATURAL ENVIRONMENT AND RESOURCES OF THE WORLD—A NEW SOVIET ATLAS

The authors employ remote sensing imagery and existing landscape maps to gain greater insight into how pre-glacial tectonic activity contributes to landscape development in old glaciated regions by affecting the form and movements of lobes of past continental ice sheets. Using the Belorussian SSR as a study area, the authors identify several features of current landscape structure which can serve as indicators of past tectonic activity, the most reliable being various characteristics of the landscape family—defined as a combination of natural territorial complexes of similar origin and age. Translated from: Izvestiya Vsesoyuznogo Geograficheskogo Obshchestva, 1990, No. 6, pp. 560–565.     

Description of a New Method for Retrieving the Aerosol Optical Thickness from Satellite Remotely Sensed Imagery Using the Maximum Contrast Value and Darkest Pixel Approach

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative remotely sensed imagery and quantitative data, such as aerosol optical depth which is the basic unknown parameter for any atmospheric correction method in the pre‐processing of satellite imagery. This article presents a new method for retrieving aerosol optical thickness directly from satellite remotely sensed imagery for short wavelength bands in which atmospheric scattering is the dominant contribution to the at‐satellite recorded signal. The method is based on the determination of the aerosol optical thickness through the application of the contrast tool (maximum contrast value), the radiative transfer calculations and the ‘tracking’ of the suitable darkest pixel in the scene. The proposed method that needs no a‐priori information has been applied to LANDSAT‐5 TM, LANDSAT‐7 ETM+, SPOT‐5 and IKONOS data of two different geographical areas: West London and Cyprus. The retrieved aerosol optical thickness values show high correlations with in‐situ visibility data acquired during the satellite overpass. Indeed, for the West London area a logarithmic regression was fitted for relating the determined aerosol optical thickness with the in‐situ visibility values. A high correlation coefficient (r²= 0.82; p= 0.2) was found. Plots obtained from Tanre et al. (1979, 1990) and Forster (1984 ) were reproduced and estimates for these areas were generated with the proposed method so as to compare the results. The author's results show good agreement with Forster's aerosol optical thickness vs. visibility results and a small deviation from Tanre's model estimates.     

THE ECOLOGY OF URBAN GEOSYSTEMS FROM SPACE IMAGERY

This study uses space imagery, particularly false-color composites, to identify and map major natural complexes of the Yerevan basin and the changes they are undergoing as a result of a variety of in situ and “imported” pollution impacts. Interpretation aides in the identification of areas affected by different types of pollution in the basin are identified. Translated by Edward Torrey, Alexandria, VA 22308 from: Izvestiya [Rossiyskoy] Akademii Nauk, seriya geograficheskaya, 1992, No. 1, pp. 112–121.     

Mapping trees in high resolution imagery across large areas using locally variable thresholds guided by medium resolution tree maps

Large area tree maps, important for environmental monitoring and natural resource management, are often based on medium resolution satellite imagery. These data have difficulty in detecting trees in fragmented woodlands, and have significant omission errors in modified agricultural areas. High resolution imagery can better detect these trees, however, as most high resolution imagery is not normalised it is difficult to automate a tree classification method over large areas. The method developed here used an existing medium resolution map derived from either Landsat or SPOT5 satellite imagery to guide the classification of the high resolution imagery. It selected a spatially-variable threshold on the green band, calculated based on the spatially-variable percentage of trees in the existing map of tree cover. The green band proved more consistent at classifying trees across different images than several common band combinations. The method was tested on 0.5 m resolution imagery from airborne digital sensor (ADS) imagery across New South Wales (NSW), Australia using both Landsat and SPOT5 derived tree maps to guide the threshold selection. Accuracy was assessed across 6 large image mosaics revealing a more accurate result when the more accurate tree map from SPOT5 imagery was used. The resulting maps achieved an overall accuracy with 95% confidence intervals of 93% (90–95%), while the overall accuracy of the previous SPOT5 tree map was 87% (86–89%). The method reduced omission errors by mapping more scattered trees, although it did increase commission errors caused by dark pixels from water, building shadows, topographic shadows, and some soils and crops. The method allows trees to be automatically mapped at 5 m resolution from high resolution imagery, provided a medium resolution tree map already exists.     

MAPPING THE DYNAMICS OF LANDSCAPES NEAR BELORUSSIAN RESERVOIRS FROM REMOTE SENSING IMAGERY

A program for monitoring changes in the shoreline zone caused by the creation of manmade reservoirs in the western USSR is described. More specifically, multilevel remote sensing imagery, ranging from 1:1,000,000-scale Landsat imagery to large-scale air photos, is employed in the study of shifts in shoreline positions, elevation of the water table, and changes in vegetation associations and soil types resulting from waterlogging produced by the filling of reservoirs. A map depicting changes in these characteristics both before and ten years after the filling of a reservoir is included. Translated from: Izvestiya Vsesoyuznogo Geograficheskogo Obshchestva, 1987, No. 4, pp. 351-356.     

THE CONCEPT OF AN INTEGRATED REPOSITORY OF SPACE IMAGERY AND NEW CRITERIA FOR ITS GEOGRAPHIC AND CARTOGRAPHIC ANALYSIS

This paper outlines some principles believed necessary for the establishment of integrated collections of remote sensing imagery, including, at the national level, a unified state image repository for the USSR. A multi-criterion classification of imagery is introduced, which provides a framework for structuring such a repository, and a number of measures for evaluating the utility of imagery within it are described. One of the latter is “geographic” resolution (levels of image detail), which provides a relatively straightforward indication of the type of geographic information embedded within particular types of remote sensing imagery. Translated by Jay K. Mitchell, PlanEcon, Inc., Washington, DC 20005 from: Vestnik Moskovskogo Universiteta, geografiya, 1988, No. 6, pp. 53-62.     

FORSAT: a 3D forest monitoring system for cover mapping and volumetric 3D change detection

ABSTRACT

A 3D forest monitoring system, called FORSAT (a satellite very high resolution image processing platform for forest assessment), was developed for the extraction of 3D geometric forest information from very high resolution (VHR) satellite imagery and the automatic 3D change detection. FORSAT is composed of two complementary tasks: (1) the geometric and radiometric processing of satellite optical imagery and digital surface model (DSM) reconstruction by using a precise and robust image matching approach specially designed for VHR satellite imagery, (2) 3D surface comparison for change detection. It allows the users to import DSMs, align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes (together with precision values) between epochs. FORSAT is a single source and flexible forest information solution, allowing expert and non-expert remote sensing users to monitor forests in three and four (time) dimensions. The geometric resolution and thematic content of VHR optical imagery are sufficient for many forest information needs such as deforestation, clear-cut and fire severity mapping. The capacity and benefits of FORSAT, as a forest information system contributing to the sustainable forest management, have been tested and validated in case studies located in Austria, Switzerland and Spain.     

SUB-SATELLITE COLLECTION OF SUPPLEMENTAL REMOTE SENSING INFORMATION

This paper, the third in a series on the design, payloads, and operation of Soviet earth resource observation satellites [see MSRS, 1984, No. 4 and 1985, No. 1], describes the collection of supplemental sub-satellite information. More specifically, it outlines how the Soviets use satellite-synchronized aerial, ground, and water-borne sensors to gather auxiliary information used in the improvement of space imagery (data verification and correction, instrument calibration, etc.). A later section demonstrates procedures for selection and preparation of field test sites (for ground truth), and design of sub-satellite information measurement complexes. Translated from: Priroda Zemli iz kosmosa, A. P. Tishchenko and S. V. Viktorov, eds. Leningrad: Gidrometeoizdat, 1984, pp. 35-38.     

An Automated System for Image-to-Vector Georeferencing

Although modern imagery usually has latitude and longitude or similar coordinates to provide true world location, much potentially useful imagery lacks this information. This includes historical imagery, as well as modern imagery that may have lost its locational information through inappropriate processing. Its provision through the process of georeferencing is still primarily a manual procedure. This paper proposes an efficient, fully- automated solution for massively asymmetric image-to-vector georeferencing whereby an image of a relatively small geographic area is automatically located relative to a substantially larger vector map base. For control points, road intersections are automatically extracted from high resolution aerial or satellite imagery using the new concepts of reference circles and central pixels. For automated control point pair identification between image and vector map, an invariant point pattern matching approach is proposed based on shape invariance for similarity transforms and invariant area ratios for affine transforms. The matching algorithm necessitates only a small subset of image points and requires no additional information beyond pixel and map coordinates. Further, it tolerates inaccurate, missing and spurious points, and provides high performance with linear scalability. A final step performs transformation verification, globalization and optimization based upon an Iterative Closest Point Greedy algorithm. Experimentation shows that images covering a few city blocks with as few as 6 to 17 extracted road intersection points can be efficiently and correctly located using the road network of Dallas County, Texas, with over 80,000 intersections.