Improved digital processing method used for image motion measurement based on hybrid opto-digital joint transform correlator

Hybrid opto-digital joint transform correlator (HODJTC) is effective for image motion measurement, but it is different from the traditional joint transform correlator because it only has one optical transform and the joint power spectrum is directly input into a digital processing unit to compute the image shift. The local cross-correlation image can be directly obtained by adopting a local Fourier transform operator. After the pixel-level location of cross-correlation peak is initially obtained, the up-sampling technique is introduced to relocate the peak in even higher accuracy. With signal-to-noise ratio >= 20 dB, up-sampling factor k >= 10 and the maximum image shift <= 60 pixels, the root-mean-square error of motion measurement accuracy can be controlled below 0.05 pixels.

重离子加速器注入器电源控制器的设计；Design of digital power control system applied in sector focusing cyclotron

设计了一种应用于兰州重离子加速器注入器的电源控制器,该控制器基于微处理器AT-mega128,结合MAX7000系列的复杂可编程器件和RTL8019AS网关芯片来实现对电源系统的控制,并通过RS-232总线实现与上位机的串口通信。应用结果表明,该控制器具有良好的通用性、灵活性、可远程控制及性能稳定等特点,实现了注入器磁铁电源10-4量级的幅度稳定性,使注入器引出的束流强度、束流品质、束流稳定性和供束效率等得到很大的提高。

基于CPLD和ATMEGAL128的数字电源系统的设计；Design of Digital Power Control System Based on CPLD and ATMEGAL128

介绍了一种基于CPLD设计的电源控制模块,并且利用Atmegal128单片机和RTL8019S实现逻辑功能和远程控制功能。该电源系统主要用于重离子加速器注入器(SFC)中,具有很好的灵活性、可远程控制、性能稳定等特点。

Digital regionalization of geomorphology in Xinjiang

National Natural Science Foundation of China [40871177]; Project of State Key Lab of Resources and Environmental Information System [088RA304SA]; CAS Knowledge Innovation Project

Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

Digital simulation in a thin layer spectroelectrochemical cell with minigrid platinum electrode by microregion approximation explicit finite difference method

The microregion approximation explicit finite difference method is used to simulate cyclic voltammetry of an electrochemical reversible system in a three-dimensional thin layer cell with minigrid platinum electrode. The simulated CV curve and potential scan-absorbance curve were in very good accordance with the experimental results, which differed from those at a plate electrode. The influences of sweep rate, thickness of the thin layer, and mesh size on the peak current and peak separation were also studied by numerical analysis, which give some instruction for choosing experimental conditions or designing a thin layer cell. The critical ratio (1.33) of the diffusion path inside the mesh hole and across the thin layer was also obtained. If the ratio is greater than 1.33 by means of reducing the thickness of a thin layer, the electrochemical property will be far away from the thin layer property.

Application of digital image analysis to the study of banded spherulite during growing and melting process

A digital image analysis(DIA) technique can be applied directly to the image obtained by polarizing microscope. The time-resolved DIA apparatus including image collecting, showing and data analysis has been home-made. As an example, it has been used to study the banded spherulite in the blends of poly(epsilon-caprolactone) (PCL) and poly(styrene-ran-acrylonitrile) (SAN).

Speed ambiguity in hurricane wind retrieval from SAR imagery

Under strong ocean surface wind conditions, the normalized radar cross section of synthetic aperture radar (SAR) is dampened at certain incident angles, compared with the signals under moderate winds. This causes a wind speed ambiguity problem in wind speed retrievals from SAR, because two solutions may exist for each backscattered signal. This study shows that the problem is ubiquitous in the images acquired by operational space-borne SAR sensors. Moreover, the problem is more severe for the near range and range travelling winds. To remove this ambiguity, a method was developed based on characteristics of the hurricane wind structure. A SAR image of Hurricane Rita (2005) was analysed to demonstrate the wind speed ambiguity problem and the method to improve the wind speed retrievals. Our conclusions suggest that a speed ambiguity removal algorithm must be used for wind retrievals from SAR in intense storms and hurricanes.

滑坡泥石流信息遥感获取与空间预测

On the issue of geological hazard evaluation（GHE）, taking remote sensing and GIS systems as experimental environment, assisting with some programming development, this thesis combines multi-knowledges of geo-hazard mechanism, statistic learning, remote sensing (RS), high-spectral recognition, spatial analysis, digital photogrammetry as well as mineralogy, and selects geo-hazard samples from Hong Kong and Three Parallel River region as experimental data, to study two kinds of core questions of GHE, geo-hazard information acquiring and evaluation model. In the aspect of landslide information acquiring by RS, three detailed topics are presented, image enhance for visual interpretation, automatic recognition of landslide as well as quantitative mineral mapping. As to the evaluation model, the latest and powerful data mining method, support vector machine (SVM), is introduced to GHE field, and a serious of comparing experiments are carried out to verify its feasibility and efficiency. Furthermore, this paper proposes a method to forecast the distribution of landslides if rainfall in future is known baseing on historical rainfall and corresponding landslide susceptibility map. The details are as following: (a) Remote sensing image enhancing methods for geo-hazard visual interpretation. The effect of visual interpretation is determined by RS data and image enhancing method, for which the most effective and regular technique is image merge between high-spatial image and multi-spectral image, but there are few researches concerning the merging methods of geo-hazard recognition. By the comparing experimental of six mainstream merging methods and combination of different remote sensing data source, this thesis presents merits of each method ,and qualitatively analyzes the effect of spatial resolution, spectral resolution and time phase on merging image. (b) Automatic recognition of shallow landslide by RS image. The inventory of landslide is the base of landslide forecast and landslide study. If persistent collecting of landslide events, updating the geo-hazard inventory in time, and promoting prediction model incessantly, the accuracy of forecast would be boosted step by step. RS technique is a feasible method to obtain landslide information, which is determined by the feature of geo-hazard distribution. An automatic hierarchical approach is proposed to identify shallow landslides in vegetable region by the combination of multi-spectral RS imagery and DEM derivatives, and the experiment is also drilled to inspect its efficiency. (c) Hazard-causing factors obtaining. Accurate environmental factors are the key to analyze and predict the risk of regional geological hazard. As to predict huge debris flow, the main challenge is still to determine the startup material and its volume in debris flow source region. Exerting the merits of various RS technique, this thesis presents the methods to obtain two important hazard-causing factors, DEM and alteration mineral, and through spatial analysis, finds the relationship between hydrothermal clay alteration minerals and geo-hazards in the arid-hot valleys of Three Parallel Rivers region. (d) Applying support vector machine (SVM) to landslide susceptibility mapping. Introduce the latest and powerful statistical learning theory, SVM, to RGHE. SVM that proved an efficient statistic learning method can deal with two-class and one-class samples, with feature avoiding produce ‘pseudo’ samples. 55 years historical samples in a natural terrain of Hong Kong are used to assess this method, whose susceptibility maps obtained by one-class SVM and two-class SVM are compared to that obtained by logistic regression method. It can conclude that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping. (e) Predicting the distribution of rainfall-induced landslides by time-series analysis. Rainfall is the most dominating factor to bring in landslides. More than 90% losing and casualty by landslides is introduced by rainfall, so predicting landslide sites under certain rainfall is an important geological evaluating issue. With full considering the contribution of stable factors (landslide susceptibility map) and dynamic factors (rainfall), the time-series linear regression analysis between rainfall and landslide risk mapis presented, and experiments based on true samples prove that this method is perfect in natural region of Hong Kong. The following 4 practicable or original findings are obtained: 1) The RS ways to enhance geo-hazards image, automatic recognize shallow landslides, obtain DEM and mineral are studied, and the detailed operating steps are given through examples. The conclusion is practical strongly. 2) The explorative researching about relationship between geo-hazards and alteration mineral in arid-hot valley of Jinshajiang river is presented. Based on standard USGS mineral spectrum, the distribution of hydrothermal alteration mineral is mapped by SAM method. Through statistic analysis between debris flows and hazard-causing factors, the strong correlation between debris flows and clay minerals is found and validated. 3) Applying SVM theory (especially one-class SVM theory) to the landslide susceptibility mapping and system evaluation for its performance is also carried out, which proves that advantages of SVM in this field. 4) Establishing time-serial prediction method for rainfall induced landslide distribution. In a natural study area, the distribution of landslides induced by a storm is predicted successfully under a real maximum 24h rainfall based on the regression between 4 historical storms and corresponding landslides.