Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM＋ Data

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution. Foundation item: Under the auspices of National Natural Science Foundation of China (No. 40701177)     

Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors ： an input vector and a class codebook vector. When a training sample is input into the model, Kohonen＇s competitive learning rule is applied to selecting the winning neuron from the Kohouen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training sam- ples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.     

文蛤Meretrix meretrix血细胞形态与分类

光镜观察湛江南三地区文蛤血细胞的形态与结构特征,并进行分类。按细胞大小、形态和结构特征可将文蛤血细胞分为4类:透明细胞、小颗粒细胞、大颗粒细胞和淋巴细胞。细胞直径有统计学上显著性差异(P<0.05),分别为10.11±0.44μm、10.99±0.32μm、9.63±0.41μm和9.22±0.25μm。透明细胞是血细胞中的主要成分,细胞质中无颗粒;小颗粒细胞的细胞质中存在大量细小颗粒;大颗粒细胞细胞质中的颗粒直径有1.0～2.5μm;淋巴细胞是血细胞中含量最少的,有很高的核质比,大约为0.5。     

使用支持向量机识别地震类型的影响因素分析

对山东地区2006~2017年3种地震事件--天然地震、爆破及塌陷的波形记录进行小波变换,对提取出的香农熵特征采用支持向量机LIBSVM方法进行分类识别,并设计一系列实验研究影响最终分类效果的因素。结果表明,5种影响因素--信号窗长度、小波分解方式、小波基类型、向量机算法类型、向量机核函数类型均对地震类型的分类识别结果产生一定的影响;识别率最高的3组处理方式均采用了2 000 s信号窗长度+db7小波基+υ-SVC算法的组合方式。所得的识别率较高的几种影响因素组合,在未来可应用于地震类型的实时识别,进一步提高地震类型的识别率和触发准确率。     

中国“数字黄土地貌”分类体系探讨

黄土地貌属中国典型地貌之一,其分类体系是制图的基础。过去各种黄土地貌分类研究方案由于标准不统一,在实际应用中没有形成公认的地貌分类系统。本文将形态和成因有机地结合在一起,采用分层分级方法,借助于地理信息系统技术,分析并提出适用于遥感影像数据(LandsatTM和ETM)的1:100万黄土地貌分类体系,拟定出相应的编码体系,建立了典型地貌的遥感图谱。该研究为利用中高分辨率卫星遥感数据编制中国1:100万黄土地貌类型图奠定了坚实的基础,该分类方案可充分反映黄土地貌的特征,也能与全国数字地貌分类方案保持一致,同时该分层分级分类方案可满足地貌类型的扩充性。     

利用FY-3C卫星GNSS掩星数据分析中国区域对流层顶参数变化

使用FY-3C气象卫星GNSS掩星数据反演得到2017-03-01～2018-02-28大气温度廓线,并估计对流层顶高度变化;然后利用探空气球数据和ERA5模型数据进行验证;最后以2°×2°的空间分辨率将中国区域划分为608个网格,针对每一个单元格,分别计算对流层顶参数,建立格网模型,分析中国区域对流层顶参数的时空分布...     

高精度直升机机载LiDAR在高速公路改扩建勘测中的应用可行性研究

机载LiDAR在公路勘测方面的用途日益广泛。该文对直升机机载LiDAR在高速公路改扩建中的应用技术路线可行性进行了研究论证,从地面控制测量、点云数据获取、点云数据处理、成果应用等多个方面进行了阐述,通过分析LiDAR点云数据在5种不同地面控制点布设方案校正下的点云数据精度,论证了利用地面控制点对直升机机载LiDAR点云数据进行平面和高程校正的可行性。     

误差椭圆在精密工程测量中的应用研究

进行精密工程测量时,要根据工程的要求和现场的具体条件,通过精度分析拟定切实可行的观测方案,采用合适的测量方法来获得最可靠的成果。据此探讨了误差椭圆在精密工程测量中的应用。     

三维激光扫描单点定位精度评定方法研究

三维激光扫描技术是当前的一种新技术,其仪器的精度评定方法还不完善,提出两种三维激光扫描单点定位精度评价方法,即外部符合精度评价方法和内部符合精度评价方法。介绍了两种方案的实施过程,并且通过实验进行了分析,得到了较好的评价结果。     

基于聚类分析的数据格式转换模型的改进

在深入细致分析各数据格式的相似性及差异性的基础上,针对传统数据格式转换模型一对一的转换方式,提出了分类通用数据格式转换模型——根据聚类分析对数据格式进行分类,归纳总结每类数据的通用数据格式,实现分类通用数据格式的相互转换,从而实现各数据格式的相互转换。