Separation of global time-variable gravity signals into maximally independent components

The Gravity Recovery and Climate Experiment (GRACE) products provide valuable information about total water storage variations over the whole globe. Since GRACE detects mass variations integrated over vertical columns, it is desirable to separate its total water storage anomalies into their original sources. Among the statistical approaches, the principal component analysis (PCA) method and its extensions have been frequently proposed to decompose the GRACE products into space and time components. However, these methods only search for decorrelated components that on the one hand are not always interpretable and on the other hand often contain a superposition of independent source signals. In contrast, independent component analysis (ICA) represents a technique that separates components based on assumed statistical independence using higher-order statistical information. If one assumes that independent physical processes generate statistically independent signal components added up in the GRACE observations, separating them by ICA is a reliable strategy to identify these processes. In this paper, the performance of the conventional PCA, its rotated extension and ICA are investigated when applied to the GRACE-derived total water storage variations. These analyses have been tested on both a synthetic example and on the real GRACE level-2 monthly solutions derived from GeoForschungsZentrum Potsdam (GFZ RL04) and Bonn University (ITG2010). Within the synthetic example, we can show how imposing statistical independence in the framework of ICA improves the extraction of the ‘original’ signals from a GRACE-type super-position. We are therefore confident that also for the real case the ICA algorithm, without making prior assumptions about the long-term behaviour or on the frequencies contained in the signal, improves over the performance of PCA and its rotated extension in the separation of periodical and long-term components.     

Evaluating the impact of data quantity, distribution and algorithm selection on the accuracy of 3D subsurface models using synthetic grid models of varying complexity

Testing the accuracy of 3D modelling algorithms used for geological applications is extremely difficult as model results cannot be easily validated. This paper presents a new approach to evaluate the effectiveness of common interpolation algorithms used in 3D subsurface modelling, utilizing four synthetic grids to represent subsurface environments of varying geological complexity. The four grids are modelled with Inverse Distance Weighting and Ordinary Kriging, using data extracted from the synthetic grids in different spatial distribution patterns (regular, random, clustered and sparse), and with different numbers of data points (100, 256, 676 and 1,600). Utilizing synthetic grids for this evaluation allows quantitative statistical assessment of the accuracy of both interpolation algorithms in a variety of sampling conditions. Data distribution proved to be an important factor; as in many geological situations, relatively small numbers of randomly distributed data points can generate more accurate 3D models than larger amounts of clustered data. This study provides insight for optimizing the quantity and distribution of data required to accurately and cost-effectively interpolate subsurface units of varying complexity.     

Using spectral information from the NIR water absorption features for the retrieval of canopy water content

Canopy water content (CWC) is important for mapping and monitoring the condition of the terrestrial ecosystem. Spectral information related to the water absorption features at 970 nm and 1200 nm offers possibilities for deriving information on CWC. In this study, we compare the use of derivative spectra, spectral indices and continuum removal techniques for these regions. Hyperspectral reflectance data representing a range of canopies were simulated using the combined PROSPECT + SAILH model. Best results in estimating CWC were obtained by using spectral derivatives at the slopes of the 970 nm and 1200 nm water absorption features. Real data from two different test sites were analysed. Spectral information at both test sites was obtained with an ASD FieldSpec spectrometer, whereas at the second site HyMap airborne imaging spectrometer data were also acquired. Best results were obtained for the derivative spectra. In order to avoid the potential influence of atmospheric water vapour absorption bands the derivative of the reflectance on the right slope of the canopy water absorption feature at 970 nm can best be used for estimating CWC.     

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.     

Consideration of time-correlated errors in a Kalman filter applicable to GNSS

An algorithm for considering time-correlated errors in a Kalman filter is presented. The algorithm differs from previous implementations in that it does not suffer from numerical problems; does not contain inherent time latency or require reinterpretation of Kalman filter parameters, and gives full consideration to additive white noise that is often still present but ignored in previous implementations. Simulation results indicate that the application of the new algorithm yields more realistic and therefore useful state and covariance information than the standard implementation. Results from a field test of the algorithm applied to the problem of kinematic differential GPS demonstrate that the algorithm provides slightly pessimistic covariance estimates whereas the standard Kalman filter provides optimistic covariance estimates.     

Conjoint modeling of residential group preferences: A comparison of the internal validity of hierarchical information integration approaches

 In this paper, two approaches for measuring residential group preferences, based on the method of Hierarchical Information Integration (HII), are compared. In particular, the hypothesis that group-based preference models estimated from integrated HII experiments better predict group preferences than part individual-based group models estimated from classical HII experiments is tested. To that effect, the models' ability to predict group preferences for new residential alternatives is compared in a study of residential preferences of co-ops. Results indicate that integrated HII group experiments indeed result in better predictions of residential preferences.     

The effects of frequency-dependent quasar variability on the celestial reference frame

We examine the relationship between source position stability and astrophysical properties of radio-loud quasars making up the International Celestial Reference Frame (ICRF2). Understanding this relationship is important for improving quasar selection and analysis strategies, and therefore reference frame stability. We construct flux density time series, known as light curves, for 95 of the most frequently observed ICRF2 quasars at both the 2.3 and 8.4 GHz geodetic very long baseline interferometry (VLBI) observing bands. Because the appearance of new quasar components corresponds to an increase in quasar flux density, these light curves alert us about potential changes in source structure before they appear in VLBI images. We test how source position stability depends on three astrophysical parameters: (1) flux density variability at X band; (2) time lag between flares in S and X bands; (3) spectral index root-mean-square (rms), defined as the variability in the ratio between S and X band flux densities. We find that the time lag between S and X band light curves provides a good indicator of position stability: sources with time lags $<$ 0.06 years are significantly more stable ( $>$ 20 % improvement in weighted rms) than sources with larger time lags. A similar improvement is obtained by observing sources with low $(<$ 0.12) spectral index variability. On the other hand, there is no strong dependence of source position stability on flux density variability in a single frequency band. These findings can be understood by interpreting the time lag between S and X band light curves as a measure of the size of the source structure. Monitoring of source flux density at multiple frequencies therefore appears to provide a useful probe of quasar structure on scales important to geodesy. The observed astrometric position of the brightest quasar component (the core) is known to depend on observing frequency. We show how multi-frequency flux density monitoring may allow the dependence on frequency of the relative core positions along the jet to be elucidated. Knowledge of the position–frequency relation has important implications for current and future geodetic VLBI programs, as well as the alignment between the radio and optical celestial reference frames.     

Satellite remote sensing of forest type and landcover in the subalpine forest region,Kananaskis Valley,Alberta

Landsat Thematic Mapper (TM) imagery and a digital elevation model (DEM) of the Kananaskis Valley in southwestern Alberta have been used to separate three forest types and eight landcover classes with mapping accuracies up to 76% overall. Image transformations based on a principal components analysis (PCA) were used to distinguish vegetation type and separate surface features in visual interpretations, and to reduce the 10 channel data set (TM 1–7, elevation, slope and incidence) to a more manageable 7 channel data set (PCA 1–4, elevation, slope and incidence). The DEM was shown to be critical in providing explanation of surface cover variability even though the original model was produced from medium scale aerial photography on a relatively coarse 100 metre grid. Discrimination increased up to 50% for pure stands of Lodgepole Pine (Pinus contorta Dougl.) and Englemann Spruce (Picea englemanii Parry) based on analysis of 100 pixels in test areas. Overall increases in map accuracy were between 2 and 11%. Success at this level of classification is required prior to detailed ecological study and modelling of mountain vegetation productivity at the community level using current satellite and aerial remote sensing technology.     

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.