Snow depth estimation over north‐western Indian Himalaya using AMSR‐E

This paper presents the estimation of snow depth over north‐western Indian Himalaya using the 18.7H and 36.5H GHz channels of Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E). The Microwave Emission Model of Layered Snowpacks (MEMLS) was used along with AMSR‐E to understand the difference in the snow pack emitted and sensor received signals due to the prevailing topography. The study shows that the brightness temperature of AMSR‐E and MEMLS are comparable at 18.7 GHz with some differences in their values at 36.5 GHz showing the sensitivity of this channel to the prevailing topography.

Three years of AMSR‐E data were used to modify the 1.59 algorithm to suit the terrain and snow conditions of the north‐western Indian Himalayas. The retrieved snow depth is then compared with ground observations. Data from December to February 2003–2006 were used for the study of snow depths less than 1 m. The modified algorithm estimates the snow depth better than the old algorithm over the mountainous terrains of the north‐western Himalayas.     

Comparison of AMSR‐E and TMI sea surface temperature with Argo near‐surface temperature over the Indian Ocean

Sea surface temperature (SST) measurements from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared with near‐surface temperature (foundation SST) in situ measurements obtained from Argo floats over the Indian Ocean. Spatial variation was compared for 2002–2006 and 11 floats were used for temporal variation collocated observations. The results show that TMI and AMSR‐E SST measurements are slightly overestimated during the pre‐ and post‐monsoon seasons and underestimated during the monsoon season. Statistical analysis shows that the SST from the AMSR‐E is better correlated with the Argo foundation SST compared to the TMI. The standard deviation (SD) and root mean square error (RMSE) for AMSR‐E SST are 0.58°C and 0.35°C, respectively, over the Equatorial Indian Ocean (EIO). The corresponding values for the TMI are 0.66°C and 0.47°C. Over the Arabian Sea the SD values are slightly higher compared to the EIO values, whereas RMSE values are less for both TMI and AMSR‐E SST. These retrieval accuracies are above the expected retrieval accuracy. The seasonal average spatial distribution of AMSR‐E SST shows a better match with the Argo foundation SST compared to TMI SST distributions. The robustness of the good spatial match during the monsoon season may be attributed to strong winds.     

Extreme‐learning‐machine‐based land cover classification

The extreme learning machine (ELM), a single hidden layer neural network based supervised classifier is used for remote sensing classifications. In comparison to the backpropagation neural network, which requires the setting of several user‐defined parameters and may produce local minima, the ELM requires setting of one parameter, and produces a unique solution for a set of randomly assigned weights. Two datasets, one multispectral and another hyperspectral, were used for classification. Accuracies of 89.0% and 91.1% are achieved with this classifier using multispectral and hyperspectral data, respectively. Results suggest that the ELM provides a classification accuracy comparable to a backpropagation neural network with both datasets. The computational cost using the ELM classifier (1.25 s with Enhanced Thematic Mapper (ETM+) and 0.675 s with Digital Airborne Imaging Spectrometer (DAIS) data) is very small in comparison to the backpropagation neural network.     

A WWW‐assisted fax system for Internet fax‐to‐fax communication

This paper describes a WWWassisted fax system (WAX) that is developed to provide reliable and enhanced Internet faxtofax communication. It integrates the easytouse WWW interface with conventional faxing procedures, resulting in an Internet fax system which not only circumvents the cost of long distance fax charges but also adds enhanced functionality not otherwise possible. The WAX system comprises two gateways, namely, the FaxIn and the FaxOut Gateways. The FaxIn Gateway accepts fax messages over Public Switched Telephone Network (PSTN) and stores them in a transit database. The system interfaces with the user over the WWW to provide access to his stored faxes, with the basic ability to send them out over the Internet to recipients. The FaxOut Gateway receives fax files from the FaxIn Gateway through the Internet and transmits them out to the intended recipients via the local PSTN. WAX users do not require any additional hardware except for a fax machine and a personal computer with Internet connectivity to gain access to WAX via any WWW browser. In addition, WAX provides a host of other enhanced features such as the ability to construct minifaxes from a single incoming fax as well as dynamically attach cover notes to outgoing faxes.     

Design‐code traceability for object‐oriented systems

Traceability is a key issue to ensure consistency among software artifacts of subsequent phases of the development cycle. However, few works have so far addressed the theme of tracing object oriented (OO) design into its implementation and evolving it. This paper presents an approach to checking the compliance of OO design with respect to source code and support its evolution. The process works on design artifacts expressed in the OMT (Object Modeling Technique) notation and accepts C++ source code. It recovers an “as is” design from the code, compares the recovered design with the actual design and helps the user to deal with inconsistencies. The recovery process exploits the edit distance computation and the maximum match algorithm to determine traceability links between design and code. The output is a similarity measure associated to design‐code class pairs, which can be classified as matched and unmatched by means of a maximum likelihood threshold. A graphic display of the design with different green levels associated to different levels of match and red for the unmatched classes is provided as a support to update the design and improve its traceability to the code.     

Issues in modified problem‐based learning: A self‐study in pre‐service science‐teacher education

Abstract:

In this self‐study, the author gained in‐depth understanding of how to plan and implement problem‐based learning (PBL), a student‐centred approach to teaching and learning that is driven by messy, open‐ended problems. This paper focuses primarily on the issues and concerns that arose as she developed and implemented a modified form of traditional PBL (Barrows, 1996) in large, pre‐service science‐teacher education classes. To view the research from many perspectives, a variety of data collection methods and sources were used, including field notes, semi‐structured interviews, student‐generated documents, and student journals. The outcomes of this study describe challenges (problem development, facilitation of groups, and assessment) encountered by the author as she planned for and implemented PBL. Furthermore, changes in the author's classroom practice, the connection between these changes and constructivist learning principles, and implications for science‐teacher education are addressed.     

Cross‐calibration of MSG1‐SEVIRI infrared channels with Terra‐MODIS channels

This paper addresses the cross‐calibration of the infrared channels 4 (3.9 µm), 9 (10.8 µm) and 10 (12.0 µm) of the Spinning Enhanced Visible and Infra‐Red Imager (SEVIRI) onboard the Meteosat Second Generation 1 (MSG1) satellite with the channels of the MODerate resolution Imaging Spectroradiometer (MODIS) onboard Terra. The cross‐calibrations, including the Ray‐Matching (RM) method and the Radiative Transfer Modelling (RTM) method, were developed and implemented over a tropical area using SEVIRI and MODIS measurements of July 2005 and July 2006 with absolute view zenith angle differences (|ΔVZA|)<0.5°, absolute view azimuth angle differences (|ΔVAA|)<0.5° and absolute time differences (|ΔTime|)<10 min. The results obtained by the RM and RTM methods revealed calibration discrepancies between the two sensors. The results obtained by the RM method were consistent with previously published results. The results obtained by the RTM method were consistent with the results obtained by the RM method if the temperature differences caused by the spectral differences between the two sensors were taken into account. From the cross‐calibration results obtained by the two methods, the use of the results obtained by the RTM method to recalibrate the SEVIRI data is recommended. The recalibrations remove the overestimation of the Land Surface Temperature (LST) retrieved from the SEVIRI data by a split‐window method.     

Analysis of co‐occurrence and discrete wavelet transform textures for differentiation of forest and non‐forest vegetation in very‐high‐resolution optical‐sensor imagery

The extraction of texture features from high‐resolution remote sensing imagery provides a complementary source of data for those applications in which the spectral information is not sufficient for identification or classification of spectrally similar landscape features. This study presents the results of grey‐level co‐occurrence matrix (GLCM) and wavelet transform (WT) texture analysis for forest and non‐forest vegetation types differentiation in QuickBird imagery. Using semivariogram fitting, the optimal GLCM windows for the land cover classes within the scene were determined. These optimal window sizes were then applied to eight GLCM texture measures (mean, variance, homogeneity, dissimilarity, contrast, entropy, angular second moment, and correlation) for the scene classification. Using wavelet transformation, up to five levels of macro‐texture were computed and tested in the classification process. Comparing the classification results, (1) the spectral‐only bands classification gave an overall accuracy of 58.69%; (2) the statistically derived 21×21 optimal mean texture combined with spectral information gave the best results among the GLCM optimal windows with an accuracy of 73.70%; and (3) the combined optimal WT‐texture levels 4 and 5 gave an accuracy of 63.56%. The combined classification of these three optimal results gave an overall accuracy of 77.93%. The results indicate that even though vegetation texture was generally measured better by the GLCM‐mean texture (micro‐textures) than by WT‐derived texture (macro‐textures), the results show that the micro–macro texture combination would improve the differentiation and classification of the overall vegetation types. Overall, the results suggests that computer‐assisted classification of high‐spatial‐resolution remotely sensed imagery has a good potential to augment the present ground‐based forest inventory methods.     

E人E本

EAE本通过坚持不懈在手写原笔迹输入方面与其他安卓平板做差异化竞争,到目前为止可谓是获得了成功。就市场现状来看,Surface、iPad以及各类Android平板让人目不暇接,尽管定位并不相同,但竞争依然存在,E．X．E本将如何继续保持竞争力,其后的产品将有哪些改进？我们为此特别邀请了该公司的高层领导进行了访谈,这些领导包括     

E来E往

盼啊,盼啊,终于真正地盼到了奥运,不知道你是怎样的状态？是和小编们一样还在工作岗位上浴血奋战,还是为了奥运请假在家好好感受这百年盛事呢？不管你现在身处何方,做着何事,又是怎样的心情,我相信只要是继承了炎黄血脉的人,在这一时刻都必定心系北京,心系奥运。让我们一起手拉手,心连心,为奥运加油,为北京欢呼!     

E来E往

“清明时节雨纷纷”，没想到北京的天气也这么多情，也时常地下起淅沥沥的小雨来。在家时，非常不喜欢四月，因为南方的这个时候刚刚踏进梅雨季节，每天阴雨绵绵，让漂亮的女孩儿没办法炫耀自己的春装。不过，北方的雨水就显得格外可爱，它正好滋润了周围的万物，甚至让女孩儿干燥的皮肤也焕发水嫩了。所以，不得不承认，我喜欢北方的这种多愁善感!     

E时代 E打印

曾经有人把喷墨打印机的打印速度和打印质量认定是“鱼和熊掌”的关系，是一对永远无法调和的矛盾体，但是，科技的发展步伐总是让人屡屡“大跌眼镜”，日前，佳能公司发布的５６００喷墨打印机以无与伦比的打印速度和打印质量展示了“二者可以得兼”的实力。它是专门针对商业用户设计的提供高品质网页打印效果的打印机。不信的话，请随我到产品实验室，听我一一道来。 ８６００外观继承了佳能公司的一贯风格，通体乳白色，流线型机身圆润光滑，大方典雅，有大家闺秀的风范，不仅如此，它多才多艺，颇具内涵。     

E开发E应用

全球著名的电子商务基础架构供应商Ｓｙｂａｓｅ公司８月２日在京宣布,历时４个月的“Ｓｙｂａｓｅ ｅ－—开发者应用技巧大赛”圆满结束,并由此拉开了“ｅ──开发者暨ＰＢ８．０新产品开发会”在北京、上海及广州巡展的序幕。 会上,Ｓｙｂａｓｅ推出最新版本的广用开发工具──ＰＢ８．０。ＰＢ８．０通过诸多创新特性以及与应用服务器的无缝集成,提供了基于客户机／服务器、Ｗｅｂ及多层结构的快速开发环境。同时,卓越的应用开发效率及强大的ＷｅＢ功能为新版本增色不少。ＰＢ８．０的发布正值ＰｏｗｅｒＢｕｉｌｄｅｒ产品推向全球…     

Phase‐correlation‐based hyperspectral image classification using multiple class representatives obtained with k‐means clustering

In this letter, a modification to a phase–correlation‐(PC‐)based supervised classification method for hyperspectral data is proposed. An adaptive approach using different numbers of multiple class representatives (CRs) extracted using PC‐based k‐means clustering for each class is compared with the use of selecting a small, pre‐determined number of dissimilar CRs. PC is used as a distance measure in k‐means clustering to determine the spectral similarity between each pixel and cluster centre. The number of representatives for each class is chosen adaptively, depending on the number of training samples in each class. Classification is performed for each pixel according to the maximum value of PCs obtained between test samples and the CRs. Experimental results show that the adaptive method gave the highest classification accuracy (CA). Experiments on the effect of reducing the size of the feature vectors found that CA increased as the feature vector decreased.     

Corn‐yield estimation through assimilation of remotely sensed data into the CSM‐CERES‐Maize model

One of the applications of crop simulation models is to estimate crop yield during the current growing season. Several studies have tried to integrate crop simulation models with remotely sensed data through data‐assimilation methods. This approach has the advantage of allowing reinitialization of model parameters with remotely sensed observations to improve model performance. In this study, the Cropping System Model‐CERES‐Maize was integrated with the Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) products for estimating corn yield in the state of Indiana, USA. This procedure, inversion of crop simulation model, facilitates several different user input modes and outputs a series of agronomic and biophysical parameters, including crop yield. The estimated corn yield in 2000 compared reasonably well with the US Department of Agriculture National Agricultural Statistics Service statistics for most counties. Using the seasonal LAI in the optimization procedure produced the best results compared with only the green‐up LAIs or the highest LAI values. Planting, emergence and maturation dates, and N fertilizer application rates were also estimated at a regional level. Further studies will include investigating model uncertainties and using other MODIS products, such as the enhanced vegetation index.     

RVM‐based multi‐class classification of remotely sensed data

The relevance vector machine (RVM), a Bayesian extension of the support vector machine (SVM), has considerable potential for the analysis of remotely sensed data. Here, the RVM is introduced and used to derive a multi‐class classification of land cover with an accuracy of 91.25%, a level comparable to that achieved by a suite of popular image classifiers including the SVM. Critically, however, the output of the RVM includes an estimate of the posterior probability of class membership. This output may be used to illustrate the uncertainty of the class allocations on a per‐case basis and help to identify possible routes to further enhance classification accuracy.     

Artificial immune‐based supervised classifier for land‐cover classification

This paper explores the potential of an artificial immune‐based supervised classification algorithm for land‐cover classification. This classifier is inspired by the human immune system and possesses properties similar to nonlinear classification, self/non‐self identification, and negative selection. Landsat ETM+ data of an area lying in Eastern England near the town of Littleport are used to study the performance of the artificial immune‐based classifier. A univariate decision tree and maximum likelihood classifier were used to compare its performance in terms of classification accuracy and computational cost. Results suggest that the artificial immune‐based classifier works well in comparison with the maximum likelihood and the decision‐tree classifiers in terms of classification accuracy. The computational cost using artificial immune based classifier is more than the decision tree but less than the maximum likelihood classifier. Another data set from an area in Spain is also used to compare the performance of immune based supervised classifier with maximum likelihood and decision‐tree classification algorithms. Results suggest an improved performance with the immune‐based classifier in terms of classification accuracy with this data set, too. The design of an artificial immune‐based supervised classifier requires several user‐defined parameters to be set, so this work is extended to study the effect of varying the values of six parameters on classification accuracy. Finally, a comparison with a backpropagation neural network suggests that the neural network classifier provides higher classification accuracies with both data sets, but the results are not statistically significant.     

E时代＆E书店

在一个叫做“E时代”的名词还没到来之前，大概每个人都有过这样的经历——     

Phase correlation pixel‐to‐pixel image co‐registration based on optical flow and median shift propagation

With singular value decomposition (SVD) and robust 2‐dimensional fitting phase correlation algorithms, it is possible to achieve pixel‐to‐pixel image co‐registration at sub‐pixel accuracy via local feature matching. However, the method often fails in featureless and low correlation areas making it not robust for co‐registration of images with considerable spectral differences and large featureless ground objects. A median shift propagation (MSP) technique is proposed to eliminate the problem, in a phase correlation and Normalized Cross‐Correlation (NCC) combined approach. The experiment results using images from different sensor platforms and spectral bands indicate that the new method is very robust to featureless and low correlation areas and can achieve very accurate pixel‐to‐pixel image co‐registration with good tolerance of spectral and spatial differences between images. The method will significantly improve change detection in various remote sensing applications.     

E时代VS E书店

在一个叫做“E时代”的名词还没到来之前,大概每个人都有过这样的经历——逛书店时,遇到一本喜欢的好书,可是囊中羞涩,于是,站在书架前,拼命地翻,想在最短的时间把它看完。今天看不完,明天再来;明天看不完,后天再来。努力和售货员阿姨叔叔陪笑脸,希望他们不要赶走我们。就这样,把一本书看完。等到哪天口袋里终于有钱了,直奔书店,想把那本书买回来。去往书店的路上,心里拼命祈祷,千万不要卖完啊。E时代终于来到,网上书店开张了!我们不但能享用互联网免费下载书籍的午餐,还能以最快捷的方式、最经济的价钱,买下自己喜欢的书籍。将网络和书店…