GEOLOGIC INTERPRETATION OF ANTARCTICA'S MOUNTAINOUS REGIONS WITH SPACE IMAGERY

This paper demonstrates how ice-surface relief identified on space imagery can be used in mapping selected elements of the geologic structure of the Antarctic Peninsula. The mapping procedure is based on the fact that all major subglacial relief forms appear, albeit in subdued form, on the surface of slow moving and relatively thin ice sheets. Since subglacial bedrock relief reflects geologic structure, particular surface configurations of ice identified on space imagery can be used as indicators of major structural elements. Examples of the procedure, including imagery of ice relief and corresponding cartographic representations of underlying structure are provided for faults and ring structures. Translated from: Antarktika, AN SSSR Mezhduvedomstvennaya komissiya po izucheniyu Antarktiki, Doklady komissii [USSR Academy of Sciences Joint Commission on Antarctic Research, Commission Report], No. 24. Moscow, 1985, pp. 50-55. An article demonstrating the application of these methods in the compilation of a geologic map for a part of the Antarctic Peninsula will appear in a later issue.     

MAPPING ANIMAL HABITATS

The authors propose a series of general methodological guidelines for animal habitat mapping. These include the use of “summary” indicators (of aggregate effects of environmental conditions on animal populations) as indices for mapping, the combination of laboratory and field work at all but the smallest scales of mapping, and explicit recognition (based on extensive studies of ecological characteristics and life cycles of species being mapped) that habitat boundaries in many cases vary dramatically from vegetation and landscape-geological boundaries. Habitat maps of two study areas are compared with vegetation and landscape maps at identical scales to demonstrate these differences. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1985, No. 3, pp. 95-101.     

EXPERIENCE IN COMPILING LARGE-SCALE MAPS OF EROSION-PRONE AREAS

Specific criteria used in the compilation of large-scale maps of erosion-prone areas are defined and evaluated for tracts of land representing a number of different agricultural cover types. Formulas are derived which facilitate the mapping of such areas based on such readily observable morphometric characteristics as slope length and steepness. Translated by Edward Torrey, Alexandria, VA 22308 from: Vestnik Moskovskogo Universiteta, geografiya, 1988, No. 5, pp. 25-31.     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.     

Remote classification of Cerrado (Savanna) and agricultural land covers in northeastern Brazil

Remote classification of land-use/land-cover (LULC) types in Brazil's Cerrado ecoregion is necessary because knowledge of Cerrado LULC is incomplete, sources of inaccuracy are unknown, and high-resolution data are required for the validation of moderate-resolution LULC maps. The aim of this research is to discriminate between Cerrado and agriculture using high-resolution Landsat 7 ETM⁺ imagery for the western region of Bahia state in northeastern Brazil. The Maximum Likelihood Classification (MLC) and Spectral Angle Mapper (SAM) algorithms were applied to a ～3000 km² subset, yielding comparable classification accuracies. The panchromatic band was reserved for validation. User's and producer's accuracies were highest for non-irrigated agriculture (～94%) but lower for Cerrado Lato Sensu (89%). Classification errors likely resulted from spatial and spectral characteristics of particular classes (e.g. riparian forest and burned) and overestimation of other classes (e.g. Eucalyptus and water). Manual misinterpretation of validation data may have also led to lower reported classification accuracies.     

A global inventory of coral reef stressors based on satellite observed nighttime lights

In this article, we present a satellite-based approach to gather information about the threat to coral reefs worldwide. Three chosen reef stressors – development, gas flaring and heavily lit fishing boat activity – are analysed using nighttime lights data derived from the Defense Meteorological Satellite Program (DMSP) produced at the National Oceanic & Atmospheric Administration, National Geophysical Data Center (NOAA/NGDC). Nighttime lights represent a direct threat to coral reef ecosystems and are an excellent proxy measure for associated human-caused stressors. A lights proximity index (LPI) is calculated, measuring the distance of coral reef sites to each of the stressors and incorporating the stressor's intensity. Colourized maps visualize the results on a global scale. Area rankings clarify the effects of artificial night lighting on coral reefs on a regional scale. The results should be very useful for reef managers and for state administrations to implement coral reef conservation projects and for the scientific world to conduct further research.     

Field Measurements of Plant Emissivity Spectra: An Experimental Study on Remote Sensing of Vegetation in the Thermal Infrared Region

Spectral features of plant species in the visible to SWIR (0.4–2.5 μm) region have been studied extensively, but scanty attention has been given to plant thermal infrared (TIR: 4–14 μm) properties. This paper presents preliminary results of a study that was conducted first time in India to measure radiance and emissivity properties of eight plant species in TIR spectral region in the field conditions using a FTIR (Fourier Transform Infrared) field spectroradiometer working in 4–14 μm at an agriculture experimental farm. Several spectral features in the emissivity spectra of plant species were observed that are probably related to the leaf chemical constituents, such as cellulose and xylan (hemicellulose) and structural aspects of leaf surface like abundance of trichomes and texture. Observations and results from the field measurements were supported by the laboratory measurements like biochemical analysis. These preliminary field emissivity measurements of leaves in TIR show that there is useful spectral information that may be detectable by field-based instrument. More detailed field and laboratory measurements are underway to explore this research theme.     

Multi‐sensor Image Maps from SPOT,ERS and JERS

Abstract

Image mapping using data from visible and infrared sensors has, as a major drawback, the frequent cloud cover experienced in many countries. This is one of the main reasons why topographic maps at 1:100,000 scale and larger are often outdated. The results of a study which investigated the possibilities of fusing up‐to‐date spaceborne microwave data with existing images from optical sensors for topographic map updating at a scale of 1:100, 000 are presented in this paper. A key issue researched was the influence of geometric distortions and corrections of remote sensing data on the results of pixel based digital image fusion. After having terrain‐geocoded and radiometrically enhanced imagery from the Landsat, SPOT, ERS‐1 and JERS‐1 satellites, the data were fused applying a variety of colour transformation techniques as well as statistical or arithmetic methods. Initially, the image fusion was implemented using images covering a test site in the north of The Netherlands in order to calibrate specified combinations and techniques in a rather flat area. With the experience gained, the remote sensing data acquired over the research site were processed. The research test site is located in a typical Developing Country in the humid Tropics, on the mountainous south‐west coast of Sumatra in Indonesia. The results of the various applied techniques and image combinations were evaluated with reference to their capability to overcome the cloud cover problem. New combinations of techniques and images were developed as result of an optimisation process. The research produced two prototypes of annotated 1:100,000 scale image maps containing fused, cloud‐free optical/microwave imagery.