Development and testing of a statistical texture model for land cover classification of the Black Sea region with MODIS imagery

A statistical model is proposed for analysis of the texture of land cover types for global and regional land cover classification by using texture features extracted by multiresolution image analysis techniques. It consists of four novel indices representing second-order texture, which are calculated after wavelet decomposition of an image and after texture extraction by a new approach that makes use of a four-pixel texture unit. The model was applied to four satellite images of the Black Sea region, obtained by Terra/MODIS and Aqua/MODIS at different spatial resolution. In single texture classification experiments, we used 15 subimages (50 × 50 pixels) of the selected classes of land covers that are present in the satellite images studied. These subimages were subjected to one-level and two-level decompositions by using orthonormal spline and Gabor-like spline wavelets. The texture indices were calculated and used as feature vectors in the supervised classification system with neural networks. The testing of the model was based on the use of two kinds of widely accepted statistical texture quantities: five texture features determined by the co-occurrence matrix (angular second moment, contrast, correlation, inverse difference moment, entropy), and four statistical texture features determined after the wavelet transformation (mean, standard deviation, energy, entropy). The supervised neural network classification was performed and the discrimination ability of the proposed texture indices was found comparable with that for the sets of five GLCM texture features and four wavelet-based texture features. The results obtained from the neural network classifier showed that the proposed texture model yielded an accuracy of 92.86% on average after orthonormal wavelet decomposition and 100% after Gabor-like wavelet decomposition for texture classification of the examined land cover types on satellite images.     

复合材料易碎盖薄弱区结构设计分析

 针对复合材料易碎盖关键部位薄弱区结构进行设计,并采用数值模拟方法对其力学性能进行了研究。首先对易碎盖整体进行数值模拟,为薄弱区结构局部模型分析提供了边界条件与载荷。其次通过局部数值模拟结果结合相应的强度准则,预测了相应的易碎盖冲破压力,并通过对易碎盖实验件进行冲破实验验证了设计方案与理论方法的准确性。最后讨论了薄弱区参数对易碎盖冲破压力的影响。     

基于密度聚类与匹配算法的异常飞行行为挖掘

在空中交通愈加拥挤的背景下,航空器的异常飞行行为的有效挖掘可以辅助管制员进行调配决策。现有方法只能辨识飞机空间位置特征异常,存在水平可扩展性的局限。本文考虑位置、速度、高度和航向4个异常特征,采用高度层划分策略、局部异常因子和快速覆盖树对基于密度的有噪声应用中的空间聚类（Density-based spatial clustering of applications with noise, DBSCAN）方法进行改进,提出局部异常因子改进的考虑速度、方向及高度的基于密度聚类方法（Density-based spatial clustering considering speed, direction and high level improved by local outlier factor,LOFDBSC-SDH）密度聚类算法对正常航迹模式进行快速准确提取。然后,基于正常航迹模式设计考虑过点时间和上述异常特征的航迹匹配算法,挖掘异常飞行行为。最后,通过实验仿真验证了本文方法的有效性和应用价值。     

小尺寸高温透波盖板双温区边界隔热性能试验研究

针对小尺寸高温透波盖板迎风面和上表面需同时满足不同热环境的要求,研究使用一组红外辐射加热试验设备,同时进行双温区边界条件下的非线性气动加热环境等效模拟试验。在辐射换热条件下,考虑试件结构导热及周围介质换热影响,采用数值模拟方法对试验方案进行可行性分析。参照计算结果,使用石英灯高温辐射加热设备,对试件进行隔热性能考核试验,完成了双温区边界条件下的热环境加载试验。试验数据与数值模拟结果吻合度较好,验证了数值模拟方法的可信性和有效性。     

FY-3卫星积雪监测产品概述及在遥感服务中的应用

介绍了风云三号(FY-3)气象卫星主要成像传感器及其积雪监测产品情况,FY-3卫星利用其1级数据能反演积雪覆盖、积雪深度、雪水当量等多种积雪监测参数和产品。卫星可见光-近红外传感器提供积雪覆盖监测信息,微波成像传感器提供积雪深度、雪水当量监测信息。针对防灾减灾以及应对气候变化分别给出积雪监测产品的遥感服务应用。结合国内外积雪遥感监测技术的发展趋势,提出利用FY-3卫星进行积雪监测的未来前景。FY-3卫星积雪监测产品在防灾减灾和应对气候变化方面能为遥感部门提供客观、可靠、全面、及时的参考信息。     

YVF315～630系列高压变频调速三相异步电动机

设计开发了新一代YVF315~630系列高压变频调速三相异步电动机,产品具有系统节能、低振动、低噪声、外形小、重量轻、型谱广、功率密度高、节能环保等特点。特别对变频调速系统节能、基本数据、高效设计、绝缘结构设计、强迫通风内外风路设计、绝缘端盖设计做了重点介绍。最后通过产品试验数据与目标数据对比,分析得出了该系列产品开发设计达到了预期目标。     

Land use/land cover classification using time series Landsat 8 images in a heavily urbanized area

It is of great significance to timely, accurately, and effectively monitor land use/cover in city regions for the reasonable development and utilization of urban land resources. The remotely sensed dynamic monitoring of Land use/land cover (LULC) in rapidly developing city regions has increasingly depended on remote-sensing data at high temporal and spatial resolutions. However, due to the influence of revisiting periods and weather, it is difficult to acquire enough time-series images with high quality at both high temporal and spatial resolution from the same sensor. In this paper we used the temporal-spatial fusion model ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) to blend Landsat8 and MODIS data and obtain time-series Landsat8 images. Then, land cover information is extracted using an object-based classification method. In this study, the proposed method is validated by a case study of the Changsha City. The results show that the overall accuracy and Kappa coefficient were 94.38% and 0.88, respectively, and the user/producer accuracies of vegetation types were all over 85%. Our approach provides an accurate and efficient technical method for the effective extraction of land use/cover information in the highly heterogeneous regions.     

风雪运动数值模拟中自保持平衡边界条件研究

在目前风场自保持性研究的基础上,结合等效物理粗糙高度,给出一类近似满足自保持性的用于风雪运动数值模拟的边界条件.首先结合低温风洞实验室的风雪实验数据,把文献的方法应用于风雪运动数值模拟中.经对比验算发现,文献的方法应用于风雪数值模拟中不能很好满足自保持性.为了进一步满足自保持性要求,引入等效物理粗糙高度,建立起雪跃移高度与等效物理粗糙高度的关系.结果表明:通过引入等效物理粗糙高度,边界条件的自保持特性得到了进一步的提高.最后对该方法的应用进行了推广验证.     

某改型温度测量探针结构气动特性试验与数值分析

针对某型温度测量探针在使用过程中的测量误差,对探针滞止罩进行了结构改型设计。为清晰认识改型滞止罩结构气动特性和后续改进方案效果,分别对面积比为2、4和8的改型滞止罩进行了稳态数值仿真,并从静温恢复系数、速度分布以及气流流场分布情况对其气动特性进行了分析。结果表明:改进型滞止罩结构在较大面积比下可以满足最初设计要求,且面积比为8.1的结构气动特性较好。     

Fractal signatures for multiscale processing of hyperspectral image data

A multiscale approach to hyperspectral image data analysis using fractal signatures was proposed and implemented in the Interactive Data Language (IDL). For 2-D hyperspectral curves, fractal signature measures the changes in curve length with changing scale. Using NASA’s Earth Observing-1 (EO-1) Hyperion image from a study area near Denton, Texas, USA, the capabilities of fractal signatures in discriminating different land cover types were presented in three different ways: (1) fractal signature curves, (2) distances between fractal signatures, and (3) fractal signature images. The asymmetry in length measurement was found to be effective in handling hyperspectral curves obtained from Hyperion radiance data. The contribution of fractal signature images was shown through comparison of image classification results. The results from the Hyperion radiance data suggest that fractal signatures at certain scales can reveal important differences in land cover types.