军民测绘标准融合方法研究

为了统筹军地资源,加强国防建设和经济建设,国家对军民融合的发展战略进行了统一部署。军民测绘标准融合是推动军民测绘事业发展的一项重要内容。通过梳理和对比分析现有军民测绘标准体系及其标准之间的相互关系,提出军民测绘标准融合的工作建议,从而为军民测绘标准融合工作的开展与实施提供参考。     

Earth Observation Scientific Workflows in a Distributed Computing Environment

Geospatially Enabled Scientific Workflows offer a promising toolset to help researchers in the earth observation domain with many aspects of the scientific process. One such aspect is that of access to distributed earth observation data and computing resources. Earth observation research often utilizes large datasets requiring extensive CPU and memory resources in their processing. These resource intensive processes can be chained; the sequence of processes (and their provenance) makes up a scientific workflow. Despite the exponential growth in capacity of desktop computers, their resources are often insufficient for the scientific workflow processing tasks at hand. By integrating distributed computing capabilities into a geospatially enabled scientific workflow environment, it is possible to provide researchers with a mechanism to overcome the limitations of the desktop computer. Most of the effort on extending scientific workflows with distributed computing capabilities has focused on the web services approach, as exemplified by the OGC's Web Processing Service and by GRID computing. The approach to leveraging distributed computing resources described in this article uses instead remote objects via RPyC and the dynamic properties of the Python programming language. The Vistrails environment has been extended to allow for geospatial processing through the EO4Vistrails package ( http://code.google.com/p/eo4vistrails/ ). In order to allow these geospatial processes to be seamlessly executed on distributed resources such as cloud computing nodes, the Vistrails environment has been extended with both multi‐tasking capabilities and distributed processing capabilities. The multi‐tasking capabilities are required in order to allow Vistrails to run side‐by‐side processes, a capability it does not currently have. The distributed processing capabilities are achieved through the use of remote objects and mobile code through RPyC.     

DMSP-OLS与NPP-VIIRS夜间灯光遥感影像数据整合

DMSP-OLS夜间灯光遥感数据截至2013年,现已被NPP-VIIRS夜间灯光数据取代。因此,要获得长时间序列且稳定的夜间灯光数据集,需要整合两类夜间灯光数据。基于此,本文提出了基于重采样的两类数据整合方法,对2013—2020年NPP-VIIRS数据进行模拟,最终建立了1992—2020年长时间序列校正—模拟DMSP-OLS夜光遥感数据集。结果表明,基于重采样的整合方法效果良好(城市区域Pearson相关系数ρ=0.9852,RMSE=3.4607),整合数据集与相关社会经济参考量高度契合(影像DN值总和与GDP的相关系数ρ=0.946,与人口的相关系数ρ=0.971,二次多项式模型拟合R²≈0.98,RMSE<5.55),优于已有研究。因此,利用该方法整合后的数据集能更好地支撑基于夜间灯光影像的长时间序列研究。     

The next layer: Towards open pedagogy in geospatial education

Open-source software and open data are becoming increasingly popular in the teaching and learning of geographic information science. The cost savings that are derived from using free software over proprietary software are one driving factor, yet the move from “closed” to “open” represents much more than financial austerity—it signifies a broader shift in educational philosophy. This article documents the gradual transition of an introductory undergraduate course in geographic information systems from an entirely closed course to one that has become increasingly open. Having completely adopted the first three layers of open—software, data, and educational resources—the course is now turning toward the next layer: embracing the philosophy of open pedagogy.     

A Composite Semisupervised SVM for Classification of Hyperspectral Images

This letter presents a novel composite semisupervised support vector machine (SVM) for the spectral-spatial classification of hyperspectral images. In particular, the proposed technique exploits the following: 1) unlabeled data for increasing the reliability of the training phase when few training samples are available and 2) composite kernel functions for simultaneously taking into account spectral and spatial information included in the considered image. Experiments carried out on a hyperspectral image pointed out the effectiveness of the presented technique, which resulted in a significant increase of the classification accuracy with respect to both supervised SVMs and progressive semisupervised SVMs with single kernels, as well as supervised SVMs with composite kernels.     

顾及多个因素的城市建成区用地规模预测研究——以郑州市为例

目前,城市建成区用地规模受社会、经济、城市环境和政策等多因素影响,传统统计方法已经难以准确预测城市用地规模,从多因素的角度研究城市用地是合理的。BP神经网络法和多元回归分析法都是顾及多个因素的统计方法。以郑州市1984—2005年相关统计数据为样本数据,用BP神经网络法、多元回归分析法、灰色系统GM(1,1)法和Logistic法建立预测模型,对2006年和2007年建成区规模进行模拟预测。预测结果表明,顾及多个因素的预测方法预测精度较高,其中BP神经网络法优于多元回归分析法。     

几种模型在格网坐标转换应用中的比较与分析

2000国家大地坐标系(CGCS 2000)在我国的启用,使得许多测绘成果面临坐标转换问题.在进行我国天文大地网向高精度地心坐标系坐标转换时,如果仅使用Bursa模型,转换完成后仍剩余较大的残差,分别采用基于最小曲率、协方差推估、多元同归、加权平均、多面甬数五种模型的格网坐标转换方法进行坐标转换,并通过试验比较,结果表明,这几种方法都具有较高的转换精度,而基于多而函数模型和多元回归模型的格网坐标转换推估精度更高一些.从实用性方面考虑,多面函数模型和多元回归模型应该作为格网坐标转换中优先选择的数学模型.     

Using spectral information from the NIR water absorption features for the retrieval of canopy water content

Canopy water content (CWC) is important for mapping and monitoring the condition of the terrestrial ecosystem. Spectral information related to the water absorption features at 970 nm and 1200 nm offers possibilities for deriving information on CWC. In this study, we compare the use of derivative spectra, spectral indices and continuum removal techniques for these regions. Hyperspectral reflectance data representing a range of canopies were simulated using the combined PROSPECT + SAILH model. Best results in estimating CWC were obtained by using spectral derivatives at the slopes of the 970 nm and 1200 nm water absorption features. Real data from two different test sites were analysed. Spectral information at both test sites was obtained with an ASD FieldSpec spectrometer, whereas at the second site HyMap airborne imaging spectrometer data were also acquired. Best results were obtained for the derivative spectra. In order to avoid the potential influence of atmospheric water vapour absorption bands the derivative of the reflectance on the right slope of the canopy water absorption feature at 970 nm can best be used for estimating CWC.     

An image engineering system for the inspection of transparent construction materials

This article presents a modular photogrammetric recording and image analysis system for inspecting the material characteristics of transparent foils, in particular Ethylen–TetraFluorEthylen-Copolymer (ETFE) foils. The foils are put under increasing air pressure and are observed by a stereo camera system. Determining the time-variable 3D shape of transparent material imposes a number of challenges: especially the automatic point transfer between stereo images and, in temporal domain, from one image pair to the next. We developed an automatic approach that accommodates for these particular circumstances and allows reconstruction of the 3D shape for each epoch as well as determining 3D translation vectors between epochs by feature tracking. Examples including numerical results and accuracy measures prove the applicability of the system.