Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.

Adaptive Keeper Design for Dynamic Logic Circuits Using Rate Sensing Technique

The increasing variability in device leakage has made the design of keepers for wide OR structures a challenging task. The conventional feedback keepers (CONV) can no longer improve the performance of wide dynamic gates for the future technologies. In this paper, we propose an adaptive keeper technique called rate sensing keeper (RSK) that enables faster switching and tracks the variation across different process corners. It can switch upto 1.9x faster (for 20 legs) than CONV and can scale upto 32 legs as against 20 legs for CONV in a 130-nm 1.2-V process. The delay tracking is within 8% across the different process corners. We demonstrate the circuit operation of RSK using a 32 x 8 register file implemented in an industrial 130-nm 1.2-V CMOS process. The performance of individual dynamic logic gates are also evaluated on chip for various keeper techniques. We show that the RSK technique gives superior performance compared to the other alternatives such as Conditional Keeper (CKP) and current mirror-based keeper (LCR).

V-CE Sensing for IGBT Protection in NPC Three Level Converters-Causes For Spurious Trippings and Their Elimination

Neutral point clamped (NPC), three level converters with insulated gate bipolar transistor devices are very popular in medium voltage, high power applications. DC bus short circuit protection is usually done, using the sensed voltage across collector and emitter (i.e., V-CE sensing), of all the devices in a leg. This feature is accommodated with the conventional gate drive circuits used in the two level converters. The similar gate drive circuit, when adopted for NPC three level converter protection, leads to false V-CE fault signals for inner devices of the leg. The paper explains the detailed circuit behavior and reasons, which result in the occurrence of such false V-CE fault signals. This paper also illustrates that such a phenomenon shows dependence on the power factor of the supplied three-phase load. Finally, experimental results are presented to support the analysis. It is shown that the problem can be avoided by blocking out the V-CE sense fault signals of the inner devices of the leg.

High sensitive Static fiber Bragg grating strain sensing using lasers locked to relative frequency reference

A novel high sensitive fiber Bragg grating (FBG) strain sensing technique using lasers locked to relative frequency reference is proposed and analyzed theoretically. Static strain on FBG independent of temperature can be measured by locking frequency of diode laser to the mid reflection frequency of matched reference FBG, which responds to temperature similar to that of the sensor FBG, but is immune to strain applied to the same. Difference between light intensities reflected from the sensor and reference FBGs (proportional to the difference between respective pass band gains at the diode laser frequency) is not only proportional to the relative strain between the sensor and reference FBGs but also independent of servo residual frequency errors. Usage of relative frequency reference avoids all complexities involved in the usage of absolute frequency reference, hence, making the system simple and economical. Theoretical limit for dynamic and static strain sensitivities considering all major noise contributions are of the order of 25 (p epsilon) / root Hz and 1.2 n epsilon / root Hz respectively.

Understanding changes in the Himalayan cryosphere using remote sensing techniques

In the Himalayas, a large area is covered by glaciers and seasonal snow and changes in its extent can influence availability of water in the Himalayan Rivers. In this paper, changes in glacial extent, glacial mass balance and seasonal snow cover are discussed. Glacial retreat was estimated for 1868 glaciers in 11 basins distributed in the Indian Himalaya since 1962. The investigation has shown an overall reduction in glacier area from 6332 to 5329km2 from 1962 to 2001/2 - an overall deglaciation of 16%. Snow line at the end of ablation season on the Chhota Shigri glacier observed using field and satellite methods suggests a change in altitude from 4900 to 5200m from the late 1970s to present. Seasonal snow cover was monitored in the 28 river sub-basins using normalized difference snow index (NDSI) technique in Central and Western Himalaya. The investigation has shown that in the early part of winter, i.e. from October to December, a large amount of snow retreat was observed. For many basins located in lower altitude and in the south of the Pir Panjal range, snow ablation was observed throughout the winter season. In addition, average stream runoff of the Baspa basin for the month of December increased by 75%. This combination of glacial retreat, negative mass balance, early melting of seasonal snow cover and winter-time increase in stream runoff might suggest an influence of global warming on the Himalayan cryosphere.

Self-assembly of neutral and cationic Pd-II organometallic molecular rectangles: synthesis, characterization and nitroaromatic sensing

Design and synthesis of three novel 2 + 2] self-assembled molecular rectangles 1-3 via coordination driven self-assembly of predesigned Pd(II) ligands is reported. 1,8-Diethynylanthracene was assembled with trans-Pd(PEt3)(2)Cl-2 in the presence of CuCl catalyst to yield a neutral rectangle 1 via Pd-C bond formation. Complex 1 represents the first example of a neutral molecular rectangle obtained via C-Pd coordination driven self-assembly. A new Pd-2(II) organometallic building block with 180 degrees bite-angle 1,4-bistrans-(ethynyl)Pd(PEt3)(2)(NO3)] benzene (M-2) containing ethynyl functionality was synthesized in reasonable yield by employing Sonagashira coupling reaction. Self-assembly of M-2 with two organic clip-type donors (L-2-L-3) afforded 2 + 2] self-assembled molecular rectangles 2 and 3, respectively L-2 = 1,8-bis(4-pyridylethynyl) anthracene; L-3 = 1,3-bis(3-pyridyl) isophthalamide]. The macrocycles 1-3 were fully characterized by multinuclear NMR and ESI-MS spectroscopic techniques, and in case of 1 the structure was unambiguously determined by single crystal X-ray diffraction analysis. Incorporation of Pd-ethynyl bonds helped to make the assemblies p-electron rich and fluorescent in nature. Complexes 1-2 showed quenching of fluorescence intensity in solution in presence of nitroaromatics, which are the chemical signatures of many commercially available explosives.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

Bayesian Decentralized Spectrum Sensing in Cognitive Radio Networks

This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.

MOSAICS: Multiplexed Optimal Signal Acquisition Involving Compressed Sensing

It is possible to sample signals at sub-Nyquist rate and still be able to reconstruct them with reasonable accuracy provided they exhibit local Fourier sparsity. Underdetermined systems of equations, which arise out of undersampling, have been solved to yield sparse solutions using compressed sensing algorithms. In this paper, we propose a framework for real time sampling of multiple analog channels with a single A/D converter achieving higher effective sampling rate. Signal reconstruction from noisy measurements on two different synthetic signals has been presented. A scheme of implementing the algorithm in hardware has also been suggested.

Self-assembled molecular squares containing metal-based donor: synthesis and application in the sensing of nitro-aromatics

Self-assemblies between a linear Pt-based donor and ferrocene- chelated metallic acceptors produced novel heterometallic squares 4 and 5, which show fluorescence quenching upon the addition of nitro-aromatics.

Spectral Sensing of Adaptive Frequency Hopping Signal for Cognitive Radio

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Sensing of delaminations in composite laminates using embedded magnetostrictive particle layers

This is an exploratory study to illustrate the feasibility of detecting delamination type of damage in polymeric laminates with one layer of magnetostrictive particles. One such beam encircled with excitation and sensing coils is used for this study. The change in stress gradient of the magnetostrictive layer in the vicinity of delamination shows up as a change in induced voltage in the sensing coil, and therefore provides a means to sense the presence of delamination. Recognizing the constitutive behavior of the Terfenol-D material is highly nonlinear, analytical expressions for the constitutive relations are developed by using curve fitting techniques to the experimental data. Analytical expressions that relate the applied excitation field with the stress and magnetic flux densities induced in the magnetostrictive layer are developed. Numerical methods are used to find the relative change in the induced voltage in the sensing coil due to the presence of delamination. A typical example of unidirectional laminate, with embedded delaminations, is used for the simulation purposes. This exploratory study illustrates that the open-circuit voltage induced in the sensing coil changes significantly (as large of 68 millivolts) with the occurrence of delamination. This feature can be exploited for device off-line inspection techniques and/or linking monitoring procedures for practical applications.

Fluorescence and visual sensing of nitroaromatic explosives using electron rich discrete fluorophores

Several pi-electron rich fluorescent aromatic compounds containing trimethylsilylethynyl functionality have been synthesized by employing Sonogashira coupling reaction and they were characterized fully by NMR (H-1, C-13)/IR spectroscopy. Incorporation of bulky trimethylsilylethynyl groups on the peripheral of the fluorophores prevents self-quenching of the initial intensity through pi-pi interaction and thereby maintains the spectroscopic stability in solution. These compounds showed fluorescence behavior in chloroform solution and were used as selective fluorescence sensors for the detection of electron deficient nitroaromatics. All these fluorophores showed the largest quenching response with high selectivity for nitroaromatics among the various electron deficient aromatic compounds tested. Quantitative analysis of the fluorescence titration profile of 9,10-bis(trimethylsilylethynyl) anthracene with picric acid provided evidence that this particular fluorophore detects picric acid even at ppb level. A sharp visual detection of 2,4,6-trinitrotoluene was observed upon subjecting 1,3,6,8-tetrakis (trimethylsilylethynyl) pyrene fluorophore to increasing quantities of 2,4,6-trinitrotoluene in chloroform. Furthermore, thin film of the fluorophores was made by spin coating of a solution of 1.0 x 10(-3) M in chloroform or dichloromethane on a quartz plate and was used for the detection of vapors of nitroaromatics at room temperature. The vapor-phase sensing experiments suggested that the sensing process is reproducible and quite selective for nitroaromatic compounds. Selective fluorescence quenching response including a sharp visual color change for nitroaromatics makes these fluorophores as promising fluorescence sensory materials for nitroaromatic compounds (NAC) with a detection limit of even ppb level as judged with picric acid.

Cyclic Prefix Based Cooperative Sequential Spectrum Sensing Algorithms for OFDM

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user is using Orthogonal Frequency Division Multiplexing (OFDM). For this we develop cooperative sequential detection algorithms that use the autocorrelation property of cyclic prefix (CP) used in OFDM systems. We study the effect of timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. We also modify the detector to mitigate the effects of these impairments. The performance of the proposed algorithms is studied via simulations. We show that sequential detection can significantly improve the performance over a fixed sample size detector.