Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data

Combined optical and laser altimeter data offer the potential to map and monitor plant communities based on their spectral and structural characteristics. A problem unresolved is, however, that narrowly defined plant communities, i.e. plant communities at a low hierarchical level of classification in the Braun-Blanquet system, often cannot be linked directly to remote sensing data for vegetation mapping. We studied whether and how a floristic dataset can be aggregated into a few major discrete, mappable classes without substantial loss of ecological meaning. Multi-source airborne data (CASI and LiDAR) and floristic field data were collected for a floodplain along the river Waal in the Netherlands. Mapping results based on floristic similarity alone did not achieve highest levels of accuracy. Ordination of floristic data showed that terrain elevation and soil moisture were the main underlying environmental drivers shaping the floodplain vegetation, but grouping of plant communities based on their position in the ordination space is not always obvious. Combined ordination-based grouping with floristic similarity clustering led to syntaxonomically relevant aggregated plant assemblages and yielded highest mapping accuracies.     

Exploring uncertainty in remotely sensed data with parallel coordinate plots

The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and fuzzy membership vector of each pixel. Based on these vectors, the Shannon's entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty. Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest. This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels.     

The design and the development of a hyperspectral and multispectral airborne mapping system

Flexible and cost-effective tools for rapid image acquisition and natural resource mapping are needed by land managers. This paper describes the hardware and software architecture of a low-cost system that can be deployed on a light aircraft for rapid data acquisition. The Hyperspectral and Multispectral Cameras for Airborne Mapping (HAMCAM) was designed and developed in the Geospatial Laboratory for Environmental Dynamics at the University of Idaho as a student-learning tool, and to enhance the existing curriculum currently offered. The system integrates a hyperspectral sensor with four multispectral cameras, an Inertial Navigation System (INS), a Wide Area Augmentation System (WAAS)-capable Global Positioning System (GPS), a data acquisition computer, and custom software for running the sensors in a variety of different modes. The outputs include very high resolution imagery obtained in four adjustable visible and near-infrared bands from the multispectral imager. The hyperspectral sensor acquires 240 spectral bands along 2.7 nm intervals within the 445–900 nm range. The INS provides aircraft pitch, roll and yaw information for rapid geo-registration of the imagery. This paper will discuss the challenges associated with the development of the system and the integration of components and software for implementation of this system for natural resource management applications. In addition, sample imagery acquired by the sensor will be presented.     

Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard

In this work we have developed a theoretical model that helps the interpretation of the remotely sensed thermal infrared measurements carried out over citrus orchards. A detailed analysis of the different factors which take part in the definition of the effective emissivity and temperature (observation height, viewing angle, type of soil, dimensions and separation between orange trees) is made. The model was validated under vertical observation in a citrus orchard during seven nights. In this situation we have determined that the model performs to an accuracy of about 1%.     

Land damage assessment - a case study

The paper discusses the land damage assessment and change detection analysis with reference to a mineral bearing zone in Manjhi, Manuni and Churan valleys. The area is located in environmentally sensitive and fragile region of Himalaya and constitutes of nearly 400 small-scale mines of slate, which were operative since last one hundred years and are stopped by court of law since 1995 on account of environment deterioration. The status of land degradation has been studied using IRS-1B satellite data of 1988,1992 and 1995. The geo-coded data on 1:50,000 scale has been interpreted and an increase in land degradation status was noticed. Finally, the management strategy for arresting the further land damage in a broader perspective is suggested.     

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.     

TEXTURE OF FOREST COMMUNITIES ON AERIAL PHOTOGRAPHS

The authors discuss a method by which the image characteristics of forest vegetation can be used to determine various valuational characteristics of forest stands through the combination of air photo interpretation and ground surveys at selected training sites. Construction of curves showing changes in image texture and tone occurring at different stages in the growth cycle of a pine forest community are used to estimate the age of a forest stand, and through known relationships between age and other stand characteristics incorporated into yield tables, to approximate such valuational characteristics as mean diameter, mean height, and stand volume. Translated from: Distantsionnyye issledovaniya rel'yefa Sibiri, A. L. Yanshin and V. N. Sharanov, eds. Novosibirsk, Nauka, 1985, pp. 73-78.     

A METHOD OF AUTOMATING THE PRESENTATION OF INFORMATION DURING COMPLEX AIR PHOTO INTERPRETATION

A method of complex image processing, i.e., the simultaneous use of various kinds of remote sensing imagery in the mapping and study of geographic features, is outlined. It features the use of computerized techniques (a) to identify shots or frames of auxiliary types of imagery containing the same specific geographic features identified on the principal type of imagery [this through the scanning of code lines containing information about the coordinates of imaging, flight direction and altitude of the plane or sensing platform, etc.], and (b) to precisely locate the features of interest within these shots or frames. Translated from: Izvestiya vysshykh uchebnykh zavededeniy, Geodeziya i aerofotos'yemka, 1986, No. 1, pp. 86–91.     

A REMOTE SENSING METHOD FOR DETERMINING HEAT FLUX AT THE OCEAN-ATMOSPHERE BOUNDARY LAYER

Results of experiments in the measurement of heat flux at the ocean-atmosphere boundary layer are described. More specifically, an algorithm is presented for the calculation of the different components of total heat flux (from the ocean into the atmosphere) based on estimates of water temperature, wind velocity, and cloud cover obtained from remote sensing imagery. Use of the algorithm yields values for total heat flux which, when averaged over a ten-day period, are only 10% less accurate than those obtained according to traditional methods (research vessels, buoys, offshore platforms). Translated from: Izvestiya vysshykh uchebnykh zavedeniy, Geodezlya i aerofotos”yemka, 1986, No. 5, pp. 117-120.     

SEASONAL CHANGES IN THE SPECTRAL REFLECTANCE OF PASTURE GRASSES IN THE IDENTIFICATION OF AREAS OF VARIABLE DRAINAGE EFFICIENCY

Spectral reflectances of artificial pastures are examined at various wavelengths and stages in the grazing/field work cycle to identify inadequately drained, marginally productive sites. Mesophytic pasture grasses and crops on well-drained sites are replaced by more hygrophytic species on poorly drained sites (each group with distinctive brightness values). This relationship, plus less significant spectral differences reflecting grazing intensity and soil moisture content at particular points in time, provided a methodological basis for the study. Poorly drained pastures are most reliably identified in the infrared and visible green portions of the spectrum during the middle of the grazing season. Translated from: Geografiya I prirodnyye resursy, 1988, No. 1, pp. 134-139.