Spatial Reasoning in Remotely Sensed Data

Photointerpreters employ a variety of implicit spatial models to provide interpretations from remotely sensed aerial or satellite imagery. The process of making the implicit models explicit and the subsequent use of the explicit models in computer processing is difficult. In this paper one application is illustrated: how ridges and valleys can be automatically interpreted from LANDSAT imagery of a mountainous area and how a relative elevation terrain model can be constructed from this interpretation. It is shown how an illumination model is being used to explain many of the features of a LANDSAT image. Finally, it is shown how to examine valleys for the possible presence of streams or rivers and it is shown how a spatial relational model can be set up to make a final interpretation of the river drainage network.     

Development of Agrometeorological Crop Model Inputs from Remotely Sensed Information

The goal of developing agrometeorological crop model inputs from remotely sensed information (AgRISTARS Early Warning/Crop Condition Assessment Project Subtask 5 within the U. S. Department of Agriculture (USDA)) provided a focus and a mission for crop spectral investigations that would have been lacking otherwise. Because the task had never been attempted before, much effort has gone into developing measurement and interpretation skill, convincing the Scientific community of the validity and information content of the spectral measurements, and providing new understanding of the crop scenes viewed as affected by bidirectional, atmospheric, and soil background variations. Nonetheless, experiments conducted demonstrate that spectral vegetation indices (VI) a) are an excellent measure of the amount of green photosynthetically active tissue present in plant stands at any time during the season, and b) can reliably estimate leaf area index (LAI) and intercepted photosynthetically active radiation (IPAR)-two of the inputs needed in agrometeorological models. Progress was also made on using VI to quantify the effects of yield-detracting stresses on crop canopy development. In a historical perspective, these are significant accomplishments in a short time span. Spectral observations of fields from aircraft and satellite make direct checks on LAI and IPAR predicted by the agrometeorological models feasible and help extend the models to large areas. However, newness of the spectral interpretations, plus continual revisions in agrometeorological models and lack of feedback capability in them, have prevented the benefits of spectral inputs to agrometeorological models from being fully realized.     

A Simulation Study of Some Contextual Classification Methods For Remotely Sensed Data

Various methods for contextual classification of multispectral scanner data have been developed during the last 15 years, aiming at increased accuracy in classified images. The methods have for a large part been of four main types: 1) neighborhood-based classification based on stochastic models for the classes over the scene and for the vectors given the classes; 2) simultaneous classification of all pixels, using, e.g., Markov random-field models; 3) relaxation methods that iteratively modify posterior probabilities using information from an increasing neighborhood; and 4) methods using ordinary noncontextual rules based on transformed data. In the present paper a selection of these methods is presented and compared using computer-gented data on different scenes. Spatial autocorrelation is present in the data. Error rates are compared, and an attempt is made to characterize what kind of errors each particular method makes.     

Use of Remotely Sensed Data for Assessing Forest Stand Conditions in the Eastern United States

The results of three interrelated research activities conducted by Goddard scientists in support of the AgRISTARS Renewable Resources Inventory (RRI) project are summarized. The central theme of the research conducted at Goddard was the development of techniques for the detection, classification, and measurement of forest disturbances using digital, remotely sensed data. Three study areas located in Pennsylvania, North Carolina, and Maine were investigated with respect to: a) the delineation and assessment of forest damage associated with two different forest insect defoliators, and b) an assessment of the improved capabilities to be expected from Landsat Thematic Mapper (TM) data relative to Multispectral Scanner (MSS) data for delineating forest stand characteristics. Key results include the development of a statewide MSS digital data base and associated image processing techniques for accurately delineating (approximately 90 precent correct classification accuracy) insect damaged and healthy forest. Comparison of analyses using MSS and TM Simulator (TMS) data indicated that for broad land cover classes which are spectrally homogeneous, the accuracy of the classification results are similar. However, TMS data provided superior results (20 percent overall accuracy increase relative to MSS results) when detailed (Level III) forest classes were mapped. These studies also illustrated the utility of having at least one band in the visible, near infrared, and middle infrared portion of the electromagnetic spectrum for assessing specific (Level III) forest cover types.     

信息系统数据集成技术浅析

根据目前信息化的发展现状和趋势,对信息系统中数据集成技术进行了综合分析.重点阐述了ETL(数据抽取、转换和装载)和数据清洗的工作过程,并对目前流行的几种主要商业ETL工具进行了评估和比较.这种评估比较能进一步指导信息系统的使用,同时也为信息系统的演化提供了理论支持.     

大数据助推人工智能在公安指挥调度上的应用

大数据为人工智能在公安指挥调度上的应用提供了海量的数据基础,高度还原现场场景,智能推送态势信息,并围绕某一案事件的全景信息,为决策者快速提供辅助参考信息,节约决策成本、提高警情处置效率,高效化处置流程、便捷化人民群众.     

人工智能技术在信息检索中的应用

因特网固有的特点使传统信息检索暴露出许多问题。如信息过载、信息模糊、信息可靠性差等,这给用户利用信息带来了障碍。人工智能在网络信息检索中的应用给信息用户带来了希望。这里着重论述了人工智能在网络信息检索中的三个应用:语义网的建设,信息过滤与多媒体检索。     

人工智能:信息技术的制高点——献给《中兴通讯技术》创刊20周年

人工智能一直处于技术创新的前沿,成为信息技术的制高点。在本刊创办20周年之际,编辑部特邀本刊编委会主任、人工智能著名专家、北京邮电大学钟义信教授就人工智能技术的定位及发展发表高见。钟教授认为,发展和应用人工智能技术是实现科技创新和应对复杂挑战的有效途径,需要中兴通讯这样的创新型企业大力研究人工智能技术,积极推动人工智能技术的快速发展和广泛应用。     

A Review of Three Discrete Multivariate Analysis Techniques Used in Assessing the Accuracy of Remotely Sensed Data from Error Matrices

Three discrete multivariate analysis techniques were used to assess the accuracy of land use/land cover classifications generated from remotely sensed data. Error matrices or contingency tables were analyzed using these techniques and the results reported. The first technique is a normalization procedure using an "iterative proportional fitting" algorithm that allows for direct comparison of Corresponding cell values in different matrices irregardless of sample size. The second technique provides a method of testing for significant differences between error matrices that vary by only a single variable or factor. The third technique allows for multivariable comparisons to be made between matrices. Each technique is implemented through the use of a computer program.     

A Wavelet-Based Method for the Determination of the Relative Resolution Between Remotely Sensed Images

Spatial resolution is a key parameter of all remote sensing satellites and platforms. The nominal spatial resolution of satellites is a well-known characteristic because it is directly related to the area in ground that represents a pixel in the detector. Nevertheless, in practice, the actual resolution of a specific image obtained from a satellite is difficult to know precisely because it depends on many other factors such as atmospheric conditions. However, if one has two or more images of the same region, it is possible to compare their relative resolutions. In this paper, a wavelet-decomposition-based method for the determination of the relative resolution between two remotely sensed images of the same area is proposed. The method can be applied to panchromatic, multispectral, and mixed (one panchromatic and one multispectral) images. As an example, the method was applied to compute the relative resolution between SPOT-3, Landsat-5, and Landsat-7 panchromatic and multispectral images taken under similar as well as under very different conditions. On the other hand, if the true absolute resolution of one of the images of the pair is known, the resolution of the other can be computed. Thus, in the last part of this paper, a spatial calibrator that is designed and constructed to help compute the absolute resolution of a single remotely sensed image is described, and an example of its use is presented.     

人工智能若干前沿技术及其在信息对抗中的应用展望

讨论了机器学习、数据挖掘、统计学习理论与支持向量机的研究现状,简要介绍了近年来涌现的一些比较前沿的新方法,如概率图模型、马尔可夫逻辑网络等。在此基础上,结合信息对抗的需求和特点,初步探讨了这些AI技术和方法在信息对抗中的可能应用。     

Big Data in Intelligent Information Systems

Mobile Networks and Applications -     

大数据+AI:构筑数字化转型的未来

数字化转型是信息社会发展的必然要求。在数字化转型的浪潮中,大数据、人工智能(AI)及区块链技术相互协作、融合,将数字化转型的未来推向更高的层次。以数字化转型为出发点,充分认识了大数据的升维价值、发展方向及关键驱动因素,揭示了数字化转型过程中大数据作为核心要素驱动的信息基础设施的转变方向,阐释了数字化转型时代下大数据与人工智能、区块链技术协同发展的关系,及共同推动全面数字化转型的作用。     

视音频智能切换开关

针对我台需对多路视音频信号进行检测、倒换的要求,介绍了对一种四选一信号手动切换器进行改进,使其具有视频信号检测功能和自动切换功能。     

大数据和人工智能技术在智慧地铁上的应用分析

现行地铁系统的分支系统较为分散,信息共享效果差.运行过程的智能化程度低、安全性差以及效率低下是目前地体系统存在的主要问题.而大数据和人工智能技术在地铁系统上的应用可以解决这些问题.对此,阐述智慧地铁的含义,详细分析大数据和人工智能技术在智慧地铁的技术层面和运维方面的应用,旨在推动地铁系统的效率和安全性.     

信息化系统在跨行业/领域信息整合中的应用

本文介绍了信息化系统在跨行业/领域信息整合中的应用.     

人工智能的原理及应用

介绍了人工智能的发展，并对改进的神经网络专家系统的优越性做了介绍，指出了神经网络专家系统广阔的应用前景及实现。     

数据广播中的信息业务整合

针对目前终端资源"瓶颈"与数据广播业务拓展之间的矛盾,提出一种全新的数据广播信息业务实现方式--"信息业务整合".     

Antecedents and Consequences of Information Systems Planning Integration

Successful utilization of the firm's information technology (IT) investments continues to be a difficult but important task for senior business and information systems managers. This paper focuses on one potentially important determinant of IT investment outcomes-integration of business and IT planning. Integration is examined using three kinds of participation: business managers' participation in IT planning, IT managers' participation in business planning, and top managers' participation in IT resource allocation. Based on considerations of knowledge sharing and commitment, a theoretical model linking these three aspects to three potential consequences-quality of IT plans, IT project problems, and IT-based organization performance-and two antecedents-top managers' perception of IT importance and environmental heterogeneity-is developed. The model is tested using data collected through a survey of 274 chief information officer (CIO) respondents. Results of structural equation modeling analysis support 12 of the 15 hypotheses. Surprisingly, top managers' participation in resource allocation had a stronger association with IT-based organizational performance than either quality of IT plans or the absence of IT project problems. This implies that the role of IT planning and alignment might be weakened when investments reflect top managements' selection. Implications of the study for practice and future research are examined.