Monitoring agricultural cropping patterns across the Laurentian Great Lakes Basin using MODIS-NDVI data

The Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composite data product (MOD12Q) was used to develop annual cropland and crop-specific map products (corn, soybeans, and wheat) for the Laurentian Great Lakes Basin (GLB). The crop area distributions and changes in crop rotations were characterized by comparing annual crop map products for 2005, 2006, and 2007. The total acreages for corn and soybeans were relatively balanced for calendar years 2005 (31,462 km² and 31,283 km², respectively) and 2006 (30,766 km² and 30,972 km², respectively). Conversely, corn acreage increased approximately 21% from 2006 to 2007, while soybean and wheat acreage decreased approximately 9% and 21%, respectively. Two-year crop rotational change analyses were conducted for the 2005–2006 and 2006–2007 time periods. The large increase in corn acreages for 2007 introduced crop rotation changes across the GLB. Compared to 2005–2006, crop rotation patterns for 2006–2007 resulted in increased corn–corn, soybean–corn, and wheat–corn rotations. The increased corn acreages could have potential negative impacts on nutrient loadings, pesticide exposures, and sediment-mediated habitat degradation. Increased in US corn acreages in 2007 were related to new biofuel mandates, while Canadian increases were attributed to higher world-wide corn prices. Additional study is needed to determine the potential impacts of increases in corn-based ethanol agricultural production on watershed ecosystems and receiving waters.     

On a PUB methodology from Chinese lessons

Abstract

Based on a Chinese saying: “Even a clever housewife cannot cook a meal without rice”, a simple categorization of the methods for Predictions in Ungauged Basins (PUB) is proposed, including: Borrowing, obtaining hydrological information by transplanting measurements from a similar basin, or extrapolating/interpolating the data from neighbouring catchments; Substituting, finding substitutes either from the ungauged basin or from donating area(s); and Generating, obtaining data via field or laboratory observations. The Substituting category is classified further into: S1, substitution only from within the ungauged basin using fully process-based models without calibration; S2-1, from similar gauged basins using established index/distribution; S2-2, from various gauged basins using regression and/or process-based relationships between the climate/catchment features and hydrological signatures (CCH), and S3, from the information beyond the CCH relationship. Based on a review, the Darwinian S2-2 and Newtonian S1 were found to be the two most popular methods, both for China and worldwide PUB.

Editor Z.W. Kundzewicz     

一种形式概念分析的陆地水系语义分类

地理信息分类体系划分是否合理直接影响地理信息交互与共享。以国家基础地理信息陆地水系（GB/T 13923-2006）分类标准为例,借助地理要素的元概念特性抽取要素描述语义,利用形式化分析方法获取形式概念表及概念格Hasse图,通过格-树转化的方法,得到具有直接包含关系的陆地水系层次分类。该方法消除了原有分类系统当中存在的概念重叠与语义交叉,是对现有分类方法的一种有益补充。     

利用主题模型的遥感图像场景分类

提出了一种基于主题模型与特征组合相结合的遥感图像分类方法。该方法首先对图像进行尺度不变特征变换(SIFT)、几何模糊特征(GB)和颜色直方图特征(CH)提取,接着利用潜在概率语义分析(pLSA)模型分别对所得到的图像特征进行潜在主题的挖掘,然后对所得到的主题概率特征进行组合,最后利用支持向量机(SVM)分类器进行场景分类。实验表明,与传统分类方法相比,主题模型更具优势;与使用单特征相比,特征组合具有更高的分类准确率。     

后缀树聚类在专用搜索引擎中的应用研究与改进

为了提高专用搜索引擎的分类精确度和可控度,提出了一种新算法。根据现有的后缀树文本聚类,通过建立基本分类表,并结合专用搜索引擎的特点进行改进,将文本分类和文本聚类有机地结合起来,使改进后的算法能够通过人工的干预,不断修正自己的分类结果。实验表明,相比传统的文本分类算法,这种算法能通过自我修正能力不断提高分类准确度,并且计算开销和传统文本分类算法相当。因此,该算法通过结合文本分类和文本聚类算法,在专用搜索引擎结果处理上提出了新的思路。     

SVM在文本自动分类中的应用

支持向量机(S、M)是基于统计学习理论的一种新的模式识别技术。介绍了文本自动分类技术的主要研究概况，并进一步从支持向量机的原理及其在文本分类中的优点等方面阐述了支持向量机在文本分类中的应用。     

Vulnerability Studies: A Bibliometric Review

This article presents a bibliometric analysis of the vulnerability research field. We analyze 200 articles on vulnerability published between 1973 and 2012, in the context of the United States. The intent of this article is to compare the levels of activity of several academic disciplines and bodies of work in vulnerability scholarship and to examine which topics are most studied in them. Topic code use was assessed using the qualitative research data analysis tool Atlas.ti, which permits users to locate, code, and annotate article text fragments. Article categorization was measured both by coding first author organizational affiliation and using the ISI Web of Knowledge journal citation reports categorization scheme that assigns journals to a discipline; each article was coded by its journal category.     

后缀树聚类在专用搜索引擎中的应用研究与改进

为了提高专用搜索引擎的分类精确度和可控度,提出了一种新算法。根据现有的后缀树文本聚类,通过建立基本分类表,并结合专用搜索引擎的特点进行改进,将文本分类和文本聚类有机地结合起来,使改进后的算法能够通过人工的干预,不断修正自己的分类结果。实验表明,相比传统的文本分类算法,这种算法能通过自我修正能力不断提高分类准确度,并且计算开销和传统文本分类算法相当。因此,该算法通过结合文本分类和文本聚类算法,在专用搜索引擎结果处理上提出了新的思路。     

新词“X门”的认知新解

＂X门＂在当代汉语中已经高度泛化,从认知的角度来说,从＂X＂到＂X门＂,再到＂-门＂,形成了一个认知上的连续统,也反映了语法结构跟人的经验结构之间有一种自然的联系,这为我们的新词语研究开辟了一条新路。     

一种基于Co-Training的海洋文献分类方法

使用有监督机器学习方法进行海洋文献的分类往往存在人工标注量太大的缺点,针对这个问题,提出利用半监督机器学习中的协同训练(Co-training)方法来实现减小人工标注量的目标。该方法从2个View分别训练不同的分类器,在此基础上,根据少量有标注文档从大量无标注文档中获取有用信息,通过协同训练来提升2个分类器的性能,并训练出最终分类模型。实验结果表明,在人工标注仅2篇文献的条件下,该方法最终的分类性能十分接近需人工标注1 500多篇文献的有监督分类器。这说明将Co-training方法应用于海洋文献分类可以大大减小人工标注量,并有着较为良好的分类性能。