Processing of multitemporal Landsat TM imagery to optimizeextraction of forest cover change features

Digital procedures to optimize the information content of multitemporal Landsat TM data sets for forest cover change detection are described. Imagery from three different years (1984, 1986, and 1990) were calibrated to exoatmospheric reflectance to minimize sensor calibration offsets and standardize data acquisition aspects. Geometric rectification was followed by atmospheric normalization and correction routines. The normalization consisted of a statistical regression over time based on spatially well-defined and spectrally stable landscape features spanning the entire reflectance range. Linear correlation coefficients for all bitemporal band pairs ranged from 0.9884 to 0.9998. The correction mechanism used a dark object subtraction technique incorporating published values of water reflectance. The association between digital data and forest cover was maximized and interpretability enhanced by converting band-specific reflectance values into vegetation indexes. Bitemporal vegetation index pairs for each time interval (two, four, and six years) were subjected to two change detection algorithms, standardized differencing and selective principal component analysis. Optimal feature selection was based on statistical divergence measures. Although limited to spectrally-radiometrically defined change classes, results show that the relationship between reflective TM data and forest canopy change is explicit enough to be of operational use in a forest cover change stratification phase prior to a more detailed assessment     

Contextual clustering for image labeling: an application to degraded forest assessment in Landsat TM images of the Brazilian Amazon

The modified adaptive pappas clustering (MPAC) algorithm, previously published in the image processing literature, is proposed as a valuable tool in the analysis of remotely sensed images where texture information is negligible. Owing to its contextual, adaptive, and multiresolutional labeling approach, MPAC preserves genuine but small regions, is easy to use (i.e., it requires minor user interaction to run), and is robust to changes in input parameters. As an application example, an MPAC-based three-stage classifier is applied to degraded forest detection in Landsat Thematic Mapper (TM) scenes of the Brazilian Amazon, where intermediate states of forest alterations caused by anthropogenic activities can be characterized by image structures 1-3 pixels wide. In three TM images of the Para test site, where classification results are validated by means of qualitative and quantitative comparisons with aerial photos, degraded forest areas cover 13% to 45% of the image ground coverage. In the Mato Grosso test site, the degraded forest class overlaps with 1) 10% of the closed-canopy forest detected by the deforestation mapping program of the Food and Agriculture Organization (FAO, 1992), and 2) 19% of the closed-canopy forest detected by the Tropical Rain Forest Information Center (TRFIC, 1996). These figures are in line with the conclusions of a study where present estimates of annual deforestation for the Brazilian Amazon are speculated to capture less than half of the forest area that is actually impoverished each year.     

A sampling scheme for estimating the reliability of a series system

The reliability estimation of a series system in which the component reliabilities are unknown is considered. The optimal sampling scheme depends on parameters that are typically unknown. A sequential sampling scheme is introduced and compared with both balanced allocation and optimal allocation. Numerical comparisons for a two-component series system are given. The results indicate that the proposed sequential sampling scheme is much better than balanced allocation and is nearly optimal     

Comparson of Landsat MSS and TM Data for Urban Land-Use Classification

A supervised classification of digital Landsat Multispectral Scanner (MSS) data for the Raleigh, North Carolina, metropolitan area was conducted in 1982. These data were categorized into 10 land-use/land-cover types representative of the area. Digital Landsat Thematic Mapper (TM) data, for the Raleigh metropolitan area, were obtained in 1985 and analyzed for comparison to the MSS data. A stratified classification based upon principal components analysis was applied to the TM data, classifying the data into the 10 land-use/land-cover categories used in the analysis of the MSS data. Comparison of photo-interpreted land-use types and Landsat derived land-use types indicates that TM data provides significantly higher classification accuracies than can be obtained from MSS data. However, an increase in confusion between urban cover types was observed for the classified TM data over the MSS data. It is felt that the stratified classification approach was instrumental in reducing classification errors between general land-use/land-cover types such as urban areas, coniferous forests, and deciduous forests. It is not clear that the information extracted from the TM data regarding the urban environment will be of much more use to city planners than that obtained from MSS data.     

ART neural networks for remote sensing: vegetation classificationfrom Landsat TM and terrain data

A new methodology for automatic mapping from Landsat thematic mapper (TM) and terrain data, based on the fuzzy ARTMAP neural network, is developed. System capabilities are tested on a challenging remote sensing classification problem, using spectral and terrain features for vegetation classification in the Cleveland National Forest. After training at the pixel level, system performance is tested at the stand level, using sites not seen during training. Results are compared to those of maximum likelihood classifiers, as well as back propagation neural networks and K nearest neighbor algorithms. ARTMAP dynamics are fast, stable, and scalable, overcoming common limitations of back propagation. Best results are obtained using a hybrid system based on a convex combination of fuzzy ARTMAP and maximum likelihood predictions. A prototype remote sensing example introduces each aspect of data processing and fuzzy ARTMAP classification. The example shows how the network automatically constructs a minimal number of recognition categories to meet accuracy criteria. A voting strategy improves prediction and assigns confidence estimates by training the system several times on different orderings of an input set     

Evaluation of SPOT and TM data for forest stratification: a casestudy for small-size poplar stands

The value of SPOT and TM data for stratification of poplar stands prior to volume inventory is assessed. The stratification is based upon the poplar development stage, which is determined by canopy closure and tree height. The effect of development stage and type of understorey vegetation on the spectral radiance of poplar stands is analyzed throughout the vegetation period. The optimal acquisition date(s) and spectral range(s) and the most suited classification approach for discrimination of poplar development stages are determined. Satellite images recorded during the full growing season are preferred for poplar stand stratification according to development stage. In this period the interfering effect of the understory vegetation is minimal in proportion to the effect of the poplar stand development stage. Young poplar stands can accurately be classified as long as the appropriate spectral range of an image registered during the full growing period is selected. The discrimination between young and other popular development stages is accurate enough for use in a stratification prior to volume inventory     

A hierarchical model for estimating the early reliability of complex systems

We describe a hierarchical Bayesian model for assessing the early reliability of complex systems, for which sparse or no system level failure data are available, except that which exists for comparable systems developed by different categories of manufacturers. Novel features of the model are the inclusion of a "quality" index to allow separate treatment for systems produced by "experienced" & "inexperienced" manufacturers. We show how this index can be employed to distinguish the behavior of systems produced by each category of manufacturer for the first few applications, with later pooling of outcomes from both categories of manufacturers after the first few uses (i.e., after inexperienced manufacturers gain experience). We demonstrate how this model, together with suitable informative priors, can reproduce the reliability growth in the modeled systems. Estimation of failure probabilities (and associated uncertainties) for early launches of new space vehicles is used to illustrate the methodology. Disclaimer-This paper is provided solely to illustrate how hierarchical Bayesian methods can be applied to estimate systems reliability (including uncertainties) for newly introduced complex systems with sparse or nonexistent system level test data. The example problem considered (i.e. estimating failure probabilities of new launch vehicles) is employed solely for illustrative purposes. The authors have made numerous assumptions & approximations throughout the document in order to demonstrate the central techniques. The specific methodologies, results, and conclusions presented in this paper are neither approved nor endorsed by the United States Air Force or the Federal Aviation Administration.     

On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance

The 16-day revisit cycle of Landsat has long limited its use for studying global biophysical processes, which evolve rapidly during the growing season. In cloudy areas of the Earth, the problem is compounded, and researchers are fortunate to get two to three clear images per year. At the same time, the coarse resolution of sensors such as the Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer (MODIS) limits the sensors' ability to quantify biophysical processes in heterogeneous landscapes. In this paper, the authors present a new spatial and temporal adaptive reflectance fusion model (STARFM) algorithm to blend Landsat and MODIS surface reflectance. Using this approach, high-frequency temporal information from MODIS and high-resolution spatial information from Landsat can be blended for applications that require high resolution in both time and space. The MODIS daily 500-m surface reflectance and the 16-day repeat cycle Landsat Enhanced Thematic Mapper Plus (ETM+) 30-m surface reflectance are used to produce a synthetic "daily" surface reflectance product at ETM+ spatial resolution. The authors present results both with simulated (model) data and actual Landsat/MODIS acquisitions. In general, the STARFM accurately predicts surface reflectance at an effective resolution close to that of the ETM+. However, the performance depends on the characteristic patch size of the landscape and degrades somewhat when used on extremely heterogeneous fine-grained landscapes.     

Use of concomitant variables for reliability exploration of microcomputer systems

The Weibull proportional hazards model is utilized for reliability exploration of microcomputer systems. The influence of two concomitant variables (temperature and mean daily user's exploitation time of the system) on system reliability is examined. The usefulness of the model for reliability exploration of microcomputer systems is shown.     

New techniques for efficiently assessing reliability of SOCs

In this paper we propose an approach to speed-up Fault Injection campaigns for the evaluation of dependability properties of complex digital systems. The approach exploits FPGA devices for system emulation, and new techniques are described, allowing emulating the effects of faults and to observe faulty behavior. Thanks to its flexibility and efficiency, the approach is suitable to be applied to SOC devices. The paper points out the flexibility of the approach, able to inject different faults of different types in custom logic, memory blocks, and processor cores. The proposed approach combines the speed of hardware-based techniques, and the flexibility of simulation-based techniques. Experimental results are provided showing that speed-up figures of up to 3 orders of magnitude with respect to state-of-the-art simulation-based techniques can be achieved.     

On the exponential formula for reliability

It is usually assumed that the exponential formula commonly used in reliability & survival analysis holds for the case of conditioning on "smooth" external covariates, and is not valid for the case of internal covariates. Using an example of external shocks affecting an item, it is shown that, though formally the influence is not smooth in this case, the corresponding exponential formula still holds. On the other hand, internal covariates do not necessarily lead to the not-absolutely-continuous conditional Cdf. If the internal covariate process specifies the full information on the item's failure process, then the corresponding conditional Cdf is not absolutely continuous. If the observed internal covariate does not provide complete information on the item's state, then the corresponding conditional Cdf can be still absolutely continuous, and the exponential formula holds.     

A reliability analysis technique for object-oriented model using a reliability petri net

We propose a reliability analysis technique for the design specifications which are made by CRC methodology. We use a reliability Petri net as an analysis technique for CRC specification. The procedure of analyzing the system reliability is as follows: first, the collaboration graphs and message flow diagrams of CRC specification are transformed into an equivalent reliability Petri net which consists of places, transitions, input functions, output functions, failure rate of the input and output functions, and tokens. Secondly, we construct a reachability tree from a reliability Petri net, and establish the paths of all transitions for the reachability tree. These paths can be test cases. Finally, we calculate the values of reliability effect for all transitions in a reliability Petri net, select the transitions that have most effect on the system reliability, and search the messages and classes that are places of input and output fucntion in these transitions. Therefore, we can design these messages and classes very well for increasing the system reliability.     

Short pulse techniques for estimating the temperature and impurity concentration of the active layer of a Gunn diode

A coaxial mount has been designed to allow the short pulse current-voltage characteristics of a Gunn diodes to be measured at various ambient temperatures. The results can be used, in conjunction with c.w. measurements, to estimate the temperature of the active layer and provide a simple means of comparing the thermal properties of both different forms of diode construction and heat sinking. The mount can also be used in an experiment to estimate the impurity concentration of the diode.     

On the design of a reliability circuit simulator

This paper describes the outcome of a study into the feasibility of a reliability circuit simulator for ICs in general and the critical parameters involved in particular. The necessary conditions are formulated that have to be fulfilled before any construction of the reliability simulator is meaningful or can be done at all. It has been found that failure mechanisms in the wear-out regime meet these conditions. Next, a general approach is given to make a simulator. This approach is actually derived from circuit simulator activities on hot carrier degradation and electromigration, respectively. Finally, the different groups of parameters are defined.     

On estimating the stability of linear parametric circuits during frequency symbol analysis

In the article the possibility of estimating asymptotic stability of linear parametric circuits during frequency symbolic analysis and approximation of the circuit’s transfer function by truncated Fourier series is considered. Estimate of asymptotic stability is conducted on the basis of normal, not the bi-frequency, transfer function as in the usual case. An example of estimating asymptotic stability of a single-contour parametric amplifier is provided.     

On the accuracy of estimating the parameters of a regularstationary process

Any regular stationary random processes can be represented as the sum of a purely indeterministic process and a deterministic one. This paper considers the achievable accuracy in the joint estimation of the parameters of these two components, from a single observed realization of the process. An exact form of the Cramer-Rao bound (CRB) is derived, as well as a conditional CRB. The relationships between these bounds, and their relations to the previously derived asymptotic bound, are explored by analysis and numerical examples     

RELVEC — a tool for control system reliability analysis

This article will present a computerized reliability analysis tool for large control systems. It will also show a new dynamic representation of system structure. It enables us to model the physical system only once for any number of control tasks. The algorithm for computing minimal cut sets for the control tasks has been developed and automated. The result is RELVEC, an interactive computer program that performs reliability/availability calculation, sensitivity analysis and critical component identification. It can handle two repair policies and common mode failures. Reconfiquring of the physical system or the control tasks is simple. RELVEC is becoming an everyday tool in control system reliability analysis at VTT.     

On the reliability of links in a ring network

This paper analyzes the reliability of links in a computer network which is configured in a ring topology. It will be shown that the expression for reliability of elements connected in series is not adequate for computing the reliability of links in a ring network. Consequently, new expressions for computing such reliability for rings with and without back-up links are proposed. Furthermore, an optimal back-up links assignment which guarantees optimal links reliability is formulated.