地理专家知识表示的框架网络模型研究

基于框架网络结构模型的专家知识表示方法 ,采用知识的框架网络结构描述地学环境的实体单元 ,将各级专家知识的表示以指针连接 ,形成了由知识到语义的专家知识表示的框架网络。以乌鲁木齐河流域土地合理利用规划决策专家系统的构建为例 ,阐述了该模型的构造方法和实现方案 ,并讨论了系统知识库的组织结构和推理规则的设计原理。     

Markov random field-based method for super-resolution mapping of forest encroachment from remotely sensed ASTER image

Forest encroachment (FE) is a problem in Andaman and Nicobar Islands (ANI) in India for environment and planning. Small gaps created in the forest slowly expand its periphery disturbing the biodiversity. Therefore, intrusion of poachers, slash and burn and other factors causing FE must be carefully detected and monitored. Remote sensing offers a great opportunity to accomplish this task because of its synoptic view. Conventional classification methods with remotely sensed images are problematic because of small size of FE and mixed landcover composition. This study presents an application of super-resolution mapping (SRM) based on Markov random field for detection of FE using ASTER (15 m) images. The SRM results were validated using multispectral IRS LISS-IV (5.8 m) image. Non-contiguous FE patches of various sizes and shapes are characterized using the spatial contextual information. The novelty of this approach lies in the identification and separability of small FE pockets which could not be achieved with pixel-based maximum likelihood classifier (MLC). The SRM parameters were optimized and found comparable to previous studies. Classification accuracy obtained with SRM at scale factor 3 is κ = 0.62 that is superior to accuracy of MLC (κ = 0.51). SRM is a promising tool for detection and monitoring of FE at Rutland Island in ANI, India.     

基于ERDAS的遥感影像分类方法研究

为了提高遥感影像分类精度,对传统的非监督分类、监督分类和专家分类进行机理分析,提出将影像中的纹理信息作为专家知识改进分类精度的技术方案。以胶州市QuickBird遥感影像作为试验数据,基于ERDAS IMAG-INE 8.6软件平台,对非监督分类、监督分类和专家分类进行实验数据比较分析,实验数据表明改进的专家分类方法分类精度最高,由于纹理信息参与专家分类,可较好地解决“同谱异物”和“同物异谱”对分类的干扰,优化分类后的影像,提高信息提取的准确度。     

根据岩石力学性质设计及合理使用金刚石钻头专家系统的研制

经过系统分析总结钻探专家们根据岩石力学性质设计及合理使用金刚石钻头方面的知识和经验，选择了合适的工具，编制成相应的专家系统，便于推广应用。     

利用地质图信息进行空间思维与数字思维的方法研究

本文通过对地质图信息的自动提取和处理，讨论了如何利用图形图像分析的方法以及专家系统的思想使地质图资料定量化，并利用非线性或非线性模型揭示各种地质特征间的空间关系及数字特征，从而达到定量分析图件资料的目的，文中以陕西勉略宁地区金及多金属的资源预测为实例，说明如何利用地质图信息进行了空间思维与数字思维，从而实现区域资源潜力的快速评价，最后给出该区域资源潜力的分布图。     

廊固凹陷大兴砾岩体隐蔽油气藏储层预测研究

廊固凹陷大兴断层下降盘沙三下砾岩体具有储层埋藏深、非均质性强的隐蔽性油气藏特征，近年来钻探成功率较低。针对该区地质条件，需充分借助综合地质专家系统，采取分级约束沆程开展砾岩体储层地震预测研究，可揭示砾岩体储层的空间展布和油气分布规律，明确大兴砾岩体下步滚动方向，并有效地降低了勘探风险。     

基坑工程支护选型多样性探讨

在建造深基坑工程支护选型专家系统ｔｙｐｅＥＳ过程中,通过对专家知识的分析后认为：支护选型要全面地考虑支护主类、复合型支护、支护亚类及地下水处理方案等才比较合理。最后举例用新的产生式规则形式表达出这些专家知识。     

Discrimination of agricultural crops in a tropical semi-arid region of Brazil based on L-band polarimetric airborne SAR data

Recent articles are indicating that polarimetric data provide significantly more information than conventional or multi-polarized images, particularly due to the additional phase information. The objective of this paper is to evaluate the multi-polarized and fully polarimetric L-band airborne SAR-R99B data, in terms of their capability to distinguish among different agricultural crops in the western part of Bahia State, Brazil. Emphasis was given to coffee, cotton and pasture crops which were at well developed growing stages. Discrimination among crops was carried out using graphical analysis of mean backscatter values. Crop classification was performed for single and multiple polarizations, and fully polarimetric images with a classifier that uses the contextual Iterated Conditional Modes–ICM algorithm. The investigation confirmed the potential of L-band multi-polarized and polarimetric airborne SAR-R99B data to distinguish and classify agricultural crops in the tropical condition of the test-site. In addition, it clearly indicated the gradual and considerable improvement that was achieved going from single to three polarizations and from multi-polarized to fully polarimetric images.     

Drivers of Change and Sustainability in Linked Social–Ecological Systems: An Analysis in the Volta River Basin of Ghana,West Africa

Understanding the nature and relative importance of various drivers of change is crucial for sustainable management of natural resources and in prioritizing management efforts, allocating limited resources, and understanding cumulative effects. For this article, we employed structured an expert judgments approach to identify, characterize, and assess the relative importance of the key biophysical and socioeconomic drivers of change within the Volta River Basin, West Africa. Precipitation variability, water availability, land use change, drought events, and population growth were perceived as most important, while biodiversity loss, social conflicts, pest and disease occurrence, urbanization, and pollution were viewed as less critical. A majority of these drivers were characterized as “slow” acting processes as compared to rapidly changing drivers. Intra- and interexpert groups agreement were found to be significant and convergent, indicating the reliability of the results. The implications of these results for sustainable water resources management and agricultural production are discussed.