Phasing of segmented mirrors: a new algorithm for piston detection

The point spread function of a segmented-mirror telescope is severely affected by segment misalignment, which can nullify the performance of adaptive optics systems. The piston and tilt of each segment must be precisely adjusted in relation to the other segments. Furthermore, the direct detection of the alignment error with natural stars would be desirable in order to monitor the errors during astronomical observation.
We have studied the lost information of the piston error caused by the presence of atmospheric turbulence in the measurements of curvature, and present a new algorithm for obtaining the local piston using the curvature sensor. A phase-wrapping effect is shown as responsible for the loss of curvature information and so the piston errors can no longer adequately be mapped; this happens not only in the presence of atmospheric turbulence, but also in its absence.
Good results are obtained using a new iterative method for obtaining the local piston error map. In the presence of atmospheric perturbation, the turbulent phase information obtained from a Shack–Hartmann sensor is introduced in our new iterative method. We propose a hybrid sensor composed of a curvature sensor and a Shack–Hartmann sensor, in order to complete all the information for the phasing. This design takes a short computation time and could be used in real time inside an adaptive optics system, where tilt and piston errors must be corrected.     

Optimal Compensation and Implementation for Adaptive Optics Systems

This paper develops a compensation algorithm based on Linear–Quadratic–Gaussian (LQG) control system design whose parameters are determined (in part) by a model of the atmosphere. The model for the atmosphere is based on the open-loop statistics of the atmosphere as observed by the wavefront sensor, and is identified from these using an auto-regressive, moving average (ARMA) model. The (LQG) control design is compared with an existing compensation algorithm for a simulation developed at ESO that represents the operation of MACAO adaptive optics system on the 8.2 m telescopes at Paranal, Chile. This revised version was published online in July 2006 with corrections to the Cover Date.     

利用高光谱数据进行植被生化成分反演方法研究

高光谱数据包含着丰富光谱信息,能够定量地分析物质成分^[1]。由高光谱数据,可以运用多元逐步线性回归方法反演植被生化组分含量,从而达到监测植被生长状况的目的^[2]。本文具体介绍了多元逐步线性回归方法,及其在氮、木质素和纤维素含量估算中的应用。     

REVIEWS OF GEOGRAPHIC SOFTWARE

Reviews of geographic software in this article: DEMO-GRAPHICS: WORLD POPULATIONS AND PROJECTIONS. ESP GAUSS. CEMODEL S. Damus LIMDEP. William H. Greene MICROSTAT 4.1 OTIS PCIPS. (Personal Computer Image Processing System) . H.J. Meyers and R. Bernstein. REGRESSION ANALYSIS OF TIME SERIES (RATS) SPSS/PC+ URBAN DATA MANAGEMENT SOFTWARE (UDMS)     

Distribution and fluxes of metals in the St. Lawrence River from the outflow of Lake Ontario to Québec City

Six anchor stations in the St. Lawrence River from the outflow of Lake Ontario to Quebec City, were occupied for ca. 24 hours in June 1987 during low flow conditions. Samples of water and suspended particulate matter were separated by continuous-flow centrifugation, and were collected every two hours.During this sampling period, fluxes of dissolved forms of zinc, copper and nickel increased in Lac St. François and downstream relative to the sum of the fluxes for the two upstream stations at the outflow of Lake Ontario. Increases in the flux of dissolved zinc and copper were pronounced below Montreal and above Lac St. Pierre. For particulate forms of metals, all five metals show that there are significant inputs in the section of the St. Lawrence River between Lac St. François and the station just above the entrance to Lac St. Pierre.The average concentrations of dissolved cadmium, lead, zinc, copper and nickel ranged from 7–23 ng/l; 9–35 ng/l; 0.434–0.939 g/l; 0.15–0.89 g/l and 0.58–1.12 g/l respectively.Regression analysis of the dissolved and particulate metal concentrations suggests that the concentration of dissolved cadmium, lead, zinc and nickel can be predicted from the regression equation and the determination of particulate metal concentration. This prediction appears to be independent of the suspended particulate matter concentration which varies from ca. 1 to 10 mg/l from the outflow of Lake Ontario to Québec City.     

Soil contamination from urban and industrial activity: example of the mining district of Linares (southern Spain)

The Linares region (southern Spain) has been subjected to two important sources of pollution: the intensive mining works and the urban-industrial activity. To obtain a geochemical characterisation of the soil, 31 trace elements were analysed and 669 soil samples were collected. By means of clustering analysis, we identified groups of elements and grid squares in which relations could be established concerning soil lithology, urban and industrial activities and the degree of pollution impact; in addition, we were able to characterise the geochemical background of the study area. The multivariate study led us to identify four factors. Particularly important was factor 2, which represented the elements associated with mineral paragenesis (Cu, Pb, As, Co, Mn, Zn, Sn, Ba). This factor also contains elements related with an urban-industrial activity, such as Pb, Cu, Zn, As and Ba. Furthermore, we identified factor 4, associating Ni, V and Cr, and which is related to the use of fuels.     

Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain)

In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline probability map. The primary variable in the doline development in this area is geomorphology, represented by the location of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient.     

An operational multiscale system for hazards prediction, mapping, and response

By definition, a crisis is a situation that requires assistance to be managed. Hence, response to a crisis involves the merging of local and non-local emergency response personnel. In this situation, it is critical that each participant: (1) know the roles and responsibilities of each of the other participants; (2) know the capabilities of each of the participants; and (3) have a common basis for action. For many types of natural disasters, this entails having a common operational picture of the unfolding events, including detailed information on the weather, both current and forecasted, that may impact on either the emergency itself or on response activities. The Consequences Assessment Tool Set (CATS) is a comprehensive package of hazard prediction models and casualty and damage assessment tools that provides a linkage between a modeled or observed effect and the attendant consequences for populations, infrastructure, and resources, and, hence, provides the common operational picture for emergency response. The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is an atmospheric simulation system that links the latest methods in computational fluid dynamics and high-resolution gridding technologies with numerical weather prediction to provide specific weather analysis and forecast capability that can be merged into the geographic information system framework of CATS. This paper documents the problem of emergency response as an end-to-end system and presents the integrated CATS–OMEGA system as a prototype of such a system that has been used successfully in a number of different situations.     

Rain-induced debris and mudflow triggering factors assessment in the Santiago cordilleran foothills,Central Chile

Debris and mudflows are some of the main geological hazards in the mountain foothills of the Chilean capital city of Santiago. There, the risk of flows triggered in the basins of ravines that drain the range into the city increases with time due to the city growth. A multivariate statistical study based on the logistic regression method is presented. The model provides equations that allow the computation of combined meteorological triggering factors associated with a probability of rain-induced flow occurrence. Daily rainfall, accumulated rainfall and the snowfall level, traditionally considered as the relevant factors, are analysed for a 25-year period. The results show a strong relevance of the rainfall on the day of the flow event over the other factors. However, the relatively low probabilities returned for some real flow events suggest that the model does not capture all the significant variables and the problem is more complex than as it has been traditionally assumed, and further investigations are needed to develop predictive models of flow triggering.