缺资料流域水文模型参数区域化研究进展

缺资料流域由于缺乏历史径流资料无法进行水文模型参数率定,因此模型参数识别具有很大的难度和不确定性。目前国内外学者对缺资料流域水文模型参数识别一般采用区域化方法,即通过某种途径,利用有资料流域的模型参数推求缺资料流域的模型参数,从而对缺资料流域进行预报。文章总结分析了缺资料流域水文模型参数区域化方法中的参数移植法和回归法的研究进展,对存在的方法选择问题、尺度问题等进行了讨论,并指出在参数不确定性、尺度转换以及多种信息源利用等方面还有待于进一步研究。     

河流功能区划方法及实例研究

河流功能区划是规范和引导各类河流功能开发利用行为的基础工作。按照中国河流功能属性特点并考虑流域管理的需求,分析了河流功能区划的理论依据和区划原则,构建了由属性层、区划层、指标层和管理层4个层面构成的河流功能区划体系,给出了河流功能区的区划方法和具体的操作步骤。以太浦河为例进行了河流功能区划实例研究,提出了太浦河河流功能区划成果及其管理目标与对策。结果表明,提出的河流功能区划的方法是合理、可行的,能够为河流管理提供一个新途径。     

贵州省自然区划与区域开发

贵州省位于中国西南合。以土地段为制图单元,根据初级地貌形态组合、土壤和植被的差别,可分出5种一级土地类型和78种二级土地类型。把土地类型结构相对一致的范围组合为自然小区,贵州省共有32个自然小区。参照“由上向下”的演绎,自然小区再“由下向上”地归纳为7个自然亚区和3个自然区,同时也明确地划定了界线。这样,全国自然区划方案在贵州省得以彻底贯彻,土地分类与自然区划也统一起来。然后以自然区划为框架,以自然资源结构为基础,论述了每个区划单元的区域开发战略。     

云南水土流失态势、分区与区域特征研究

水土流失分区是水土流失研究和水土保持管理的重要组成部分。笔者从云南省水土流失的基本情况分析入手,首先分析对比了1987年和1999年全省和六大流域水土流失的演变态势及其各侵蚀强度面积所占百分比,再以各区域不同的自然地理尤其是地貌、植被覆盖特点和陡坡耕地占耕地总面积的比例及所在区域农业人口密度,把全省分为7个水土流失自然区,并对每个自然区的水土流失现状、特点、趋势进行了分析。该研究对区域水土保持、生态环境建设和区域可持续发展有重要意义。     

地域主体功能区划理论与方法的初步研究

在对地域主体功能区划的理论依据与原则等进行深入分析的基础上,提出通过生态敏感性等级分区与经济社会发展综合潜力等级分区的空间叠置与地域聚类分析,进行地域主体功能区划的理论方法。并以江苏省新沂市为案例,进行地域主体功能区划实证研究,验证了所提出的地域主体功能区划理论方法的可行性。     

横断山区综合自然区划纲要

横断山区地域分异明显。各自然地理要素作地带性组合,自然地理环境呈水平分异,农业土地利用也大体呈纬向带状分布。根据温度和水分条件的地域组合及地势差异,将横断山区划分为5个自然地带、9个自然区,并与以往的方案进行了比较,阐述了自然地带界线的划分及各带特征。     

水稻生长期微波介电特性研究

利用植被介电常数的Debye-Cole双频色散模型，模拟计算了广东肇庆水稻试验区1996年晚稻和1997年早稻人插秧期、发蘖期、扬花期到成熟期各生长期的介电常数值，并根据计算结果，探讨了电磁波频率、水稻含水量、温度、含盐度及水稻冠层干体密度对介电常数的影响。其中，不同生长期水稻的介电常数各不相同，不同水稻类型（早稻和晚稻），介电常数的变化趋势不尽相同。电磁波频率、水稻含水量、温度和水稻冠层干体密度均对介电常数有不同程度的影响，而含盐度却对介电常数影响不大。     

Supervised Mineral Classification with Semiautomatic Training and Validation Set Generation in Scanning Electron Microscope Energy Dispersive Spectroscopy Images of Thin Sections

This paper addresses the problem of classifying minerals common in siliciclastic and carbonate rocks. Twelve chemical elements are mapped from thin sections by energy dispersive spectroscopy in a scanning electron microscope (SEM). Extensions to traditional multivariate statistical methods are applied to perform the classification. First, training and validation sets are grown from one or a few seed points by a method that ensures spatial and spectral closeness of observations. Spectral closeness is obtained by excluding observations that have high Mahalanobis distances to the training class mean. Spatial closeness is obtained by requesting connectivity. Second, class consistency is controlled by forcing each class into 5–10 subclasses and checking the separability of these subclasses by means of canonical discriminant analysis. Third, class separability is checked by means of the Jeffreys–Matusita distance and the posterior probability of a class mean being classified as another class. Fourth, the actual classification is carried out based on four supervised classifiers all assuming multinormal distributions: simple quadratic, a contextual quadratic, and two hierarchical quadratic classifiers. Overall weighted misclassification rates for all quadratic classifiers are very low for both the training (0.25–0.33%) and validation sets (0.65–1.13%). Finally, the number of rejected observations in routine runs is checked to control the performance of the SEM image acquisition and the classification. Although the contextual classifier performs marginally best on the validation set, the simple quadratic classifier is chosen in routine classifications because of the lower processing time required. The method is presently used as a routine petrographical analysis method at Norsk Hydro Research Centre. The data can be approximated by a Poisson distribution. Accordingly, the square root of the data has constant variance and a linear classifier can be used. Near orthogonal input data, enable the use of a minimum distance classifier. Results from both linear and quadratic minimum distance classifications are described briefly.     

Digital regionalization of geomorphology in Xinjiang

This paper presents a method of geomorphologic regionalization for Xinjiang, with the use of Srtm-DEM (resolution 90 m) and TM images for 1990 (resolution 30 m). After interpretation and classification of geomorphologic types, the present research focuses on the qualitative and quantitative distribution of different geomorphologic types based on geographical grid analysis. Then, by using system clustering analysis method, geomorphologic types are grouped into divisions. The resulting geomorphologic regionalization hierarchy of Xinjiang includes three levels, i.e., macro-landform divisions, medium-landform divisions, and micro-landform divisions, containing 6, 23 and 200 types, respectively. This method makes it possible to digitally delimit geomorphologic regions. Comparison and verification show that the spatial precision of the boundaries of geomorphologic subareas in Xinjiang is very high.     

地形图要素辅助下的影像面状地物提取

针对遥感影像与地形图变化检测中影像面状地物的提取问题,该文提出了一种地形图要素辅助下的影像面状地物提取方法。该方法首先利用配准后落在影像面状地物内的地形图面状要素中心进行区域生长,然后以人工选取的各类地物的初始样本和上述区域生长出影像上的各类地物作为训练样区进行监督分类,最终实现影像面状地物提取。实验结果表明,该方法能够有效地提取影像面状地物,并且自动化程度较高。