How valuable is remotely sensed information? The case of tropical deforestation modelling

An economic approach to remote-sensing applications needs to be developed to demonstrate the cost–advantage ratio of Earth observation for decision makers. This article aims to conduct such an analysis of the information derived by remote sensing for a specific operational project, following some general chemical consideration about the economic value the economic value of information highlight that: of information. In our study of tropical deforestation modelling the main advantages of the remote-sensing-based information system came from: (i) an improvement of decision making as decisions could be made with a higher degree of confidence, leading to a shorter and less expensive decision cycle, and to earlier implementation of decisions; and (ii) avoidance of bad decisions, as the rate of project failure, and the associated resource wastes, was expected to decrease as a result of the availability of more accurate information. The costs of the model development and calibration and model implementation are also discussed. The economic approach is then generalised to three generic categories of remote-sensing projects (private, public with short-term implications and public with long-term implications).     

Filtering of discontinuous processes arising in marine integratednavigation systems

A refined stochastic model for the errors of the Loran-C radio navigation aid is described, and it is shown how this model can be used to improve the performance of integrated navigation systems. In addition to the usual propagation errors, Loran-C time of arrival measurements are occasionally plagued with sudden intermittent errors of a particular magnitude and caused by receiver cycle selection errors. These result in sudden large jumps in the calculated position solution. The Loran-C error has been modeled as the sum of a diffusion process, representing the normal propagating errors, and a pure jump process of Poisson type, representing the cycle selection errors. A simple integrated navigation system is then described, based on the Loran-C model and the standard dead reckoning (heading and speed) system model. Assuming that the observed process is governed by a linear stochastic difference equation, a recursive linear unbiased minimum variance filter is developed, from which the Loran-C and dead reckoning errors, and hence position and velocity, can be estimated     

Fuel Savings in the WHECON Attitude Control System Using an Asymmetric Controller

This paper investigates the possibility of generating an on-off limit cycle mode in the WHECON attitude control system. lt is shown that, by eliminating the off set angle ? in the roll-actuated control torquer, the WHECON system can be reduced to the structure considered earlier by Mendel and, therefore, an on-off limit cycle can be generated simply by introducing an appropriate amount of asymmetry into the deadzone characteristic of the WHECON controller. Because with this mode of on-off limit cycle the thruster jets will fire only once in each cycle of the oscillation, it is claimed that a considerable amount of fuel can be saved by the proposed modifications to the original WHECON design. Dynamic simulation study was conducted with the actual nonlinear model of the WHECON system considered and the results indicate that, for both zero and nonzero values of the off set angle ?, substantial fuel savings can be achieved by using the asymmetric controller.     

Instantaneous Frequency Estimation Using Adaptive Linear Predictor Weights

A computationally efficient scheme for estimating the digital instantaneous frequencies of narrowband inputs is introduced. The frequency estimates are obtained by searching for minima of the inverse input power spectrum. This spectrum is estimated at each input sample from the weights of an adaptive linear predictor which uses the LMS (least mean square) algorithm to update its weights. The related minima are sought via an iterative search algorithm, referred to as the iterative frequency estimator. This algorithm is computationally more efficient than available methods, and also provides a higher resolution. Simulation results are included; these include tracking of random message sequences in FM signals, and the formant frequency estimation of speech.     

Parametric models for helicopter identification using ANN

An artificial neural network (ANN) based helicopter identification system is proposed. The feature vectors are based on both the tonal and the broadband spectrum of the helicopter signal, ANN pattern classifiers are trained using various parametric spectral representation techniques. Specifically, linear prediction, reflection coefficients, cepstrum, and line spectral frequencies (LSF) are compared in terms of recognition accuracy and robustness against additive noise. Finally, an 8-helicopter ANN classifier is evaluated. It is also shown that the classifier performance is dramatically improved if it is trained using both clean data and data corrupted with additive noise.     

Spatial heterogeneity in the radiogenic activity of the lunar interior: Inferences from CHACE and LLRI on Chandrayaan-1

In the past, clues on the potential radiogenic activity of the lunar interior have been obtained from the isotopic composition of noble gases like Argon. Excess Argon (40) relative to Argon (36), as compared to the solar wind composition, is generally ascribed to the radiogenic activity of the lunar interior. Almost all the previous estimates were based on, ‘on-the-spot’ measurements from the landing sites. Relative concentration of the isotopes of ⁴⁰Ar and ³⁶Ar along a meridian by the Chandra’s Altitudinal Composition Explorer (CHACE) experiment, on the Moon Impact Probe (MIP) of India’s first mission to Moon, has independently yielded clues on the possible spatial heterogeneity in the radiogenic activity of the lunar interior in addition to providing indicative ‘antiquity’ of the lunar surface along the ground track over the near side of the moon. These results are shown to broadly corroborate the independent topography measurements by the Lunar Laser Ranging Instrument (LLRI) in the main orbiter Chandrayaan-1. The unique combination of these experiments provided high spatial resolution data while indicating the possible close linkages between the lunar interior and the lunar ambience.     

Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.     

Optimal Precession Control of Randomly Perturbed Spin-Stabilized Satellite

Dynamics of the satellite angular momenta is modeled by ordinary differential equations with additive white noise. A feedback controller er is desired to maintain tolerable satellite momenta and to economize ze the fuel consumption. The stochastic optimal control problem is transformed into an equivalent deterministic optimization problem involving a parabolic partial differential equation. Necessary optimality y conditions are used to develop a computation algorithm. Results regarding optimal controls, expected costs, and confinement probabilities in different noisy environments are presented.