Regionalization for large area crop estimates by remote sensing

The crop estimates by remote sensing, developing quickly in recent decades, is a up-to-date technique. Regionalization for large area crop estimates by remote sensing, a special applied regionalization, is the foundation of crop estimates in a large area by remote sensing. According to the actual demands of wheat yield estimation by remote sensing and wheat agroclimatic demarcation of China, this paper first puts forward some principles upheld in this regionalization and analyses its main bases. Secondly, it works out the classificatory schemes about the optimum temporal for estimating wheat yield by remote sensing, information sources of space remote sensing and landuse structure in China. Finally, According to the regionalization indices, this study divides the wheat plantable region of China into 14 regions of crop yield estimates and 31 subregions of crop yield estimates.     

Geostatistical regionalization of glacial aquitard thickness in northwestern Germany, based on fuzzy kriging

In many instances hydrogeological parameters obtained by conventional methods for selected localities within an aquifer or an aquitard are not sufficient for adequate regionalization at the scale of the entire layer. Here, we demonstrate an application of the fuzzy kriging method in regionalization of hydrogeological data, in which the set of conventional, crisp values is supplemented by imprecise information subjectively estimated by an expert. It is believed that such an approach eventually may reflect the real-world conditions more closely than a traditional crisp-value approach, because the former does not impose exactness artificially on phenomena which are diffuse by their nature. Spatial interpolation was done for the thickness of one of the major aquitards (till and glaciolacustrine clay) in northwestern Germany. The dataset consists of 329 crisp values from boreholes supplemented by 172 imprecise values defined as fuzzy numbers. It is demonstrated that the reliability of regionalization was higher, compared to regionalization performed with the crisp dataset only. Fuzzy kriging was performed with FUZZEKS (Fuzzy Evaluation and Kriging System) developed at the Ecosystem Research Center at the University of Kiel.     

中国综合气候变化风险区划

气候变化作用于自然环境与社会经济系统,产生一系列影响。随着未来社会经济发展,气候变化危险性与自然环境和社会经济承险体耦合形成有规律的风险时空格局。将此时空格局系统化表达即是综合气候变化风险区划,是适应气候变化的科学基础之一。本文基于RCP 8.5下的近中期（2021-2050年）气候情景,分析了中国未来气温和降水变化趋势与速率,评价了干旱、高温热浪以及洪涝等极端事件危险性,选取人口、经济、粮食生产和生态系统等承险体风险作为综合风险定量评估的指标。在系统性、主导因素以及空间连续性原则的指导下,提出中国综合气候变化风险区划三级区域系统方案,划分出8个气候变化敏感区、19个极端事件危险区和46个承险体综合风险区。结果发现：2021-2050年RCP 8.5情景下中国的气候变化高风险区主要包括：华北弱暖增雨敏感区,华北平原热浪危险区,人口经济粮食高风险区;华南—西南弱暖增雨敏感区,黔滇山地热浪危险区,生态经济粮食人口高风险区;华南沿海涝热危险区,生态粮食经济人口高风险区。中国综合气候变化风险区划涵盖了气候变化情景、极端事件发生、社会经济与生态系统的可能损失信息,可以为国家或地方应对气候变化及气候变化风险管理提供科技支撑。     

于桥水库流域农业非点源磷污染控制区划研究

以于桥水库流域28个次级小流域作为区划对象,以影响该区域农业非点源磷污染的6个主要因子,包括降雨侵蚀力因子(R),土壤可蚀性因子(K),地形因子(LS),植被覆盖因子(C)以及土壤有效磷含量(SAP)和化肥磷施用量(FP),作为区划因子,采用系统聚类法进行区划,将于桥水库流域分为4类磷污染控制类型区,分析了各个类型区的生态环境特征、农业非点源磷污染特征和主要影响因子,提出相应的控制措施。为进一步进行更深入的研究提供科学依据。     

四川地质遗迹区划研究

《四川省地质遗迹景观调查评价》项目根据四川地质遗迹景观的空间分异和区域地质地貌特征,划分出四大地质遗迹区,再以其分布规律,景观形成时间、空间和成因的关联性划分出20个地质遗迹分区和28个地质遗迹小区,从而建立了四川地质遗迹景观区划系统。     

基于卫星遥感的太湖蓝藻水华时空分布规律认识

由于大尺度水文模型和无资料区水文研究是当前国际水文研究的重点和难点,通过参数区域化方法来估计大尺度区域和无资料区的模型参数值成为了研究的热点之一将HBV模型应用于东江流域及其子流域,采用代理流域法和全局乎均法来估计该区域内无资料流域的模型参数研究表明：HBV模型能较好得用于东江流域径流模拟;交叉检验中,较小的序和ME值对应的参数,其转移效果不一定比较大的R^2和ME值对应的参数转移效果差;全局平均法中,面积权重平均值和泰森多边形插值后平均并不能明显改进子流域算术平均值估计无资料流域的模型参数的模拟结果;两者都能有效用于东江流域无资料流域的参数估计,且效果相差不大。     

Voluntarism,defensive localism and spaces of resistance to health care restructuring

This paper examines the evolving role of volunteers and the voluntary sector in shaping community responses to structural change in health care systems. It contributes to the emerging understanding of the different forms voluntarism can take within and among places, including as a space of resistance to contemporary restructuring initiatives such as regionalization. Within the geographies of voluntarism literature, however, little attention has been directed towards interrogating the local dynamics of such voluntarism, especially as it is reflected in public discourse. We address this deficiency through a media-based case study of public reaction to the recent implementation of Ontario’s Local Health Integration Networks (a type of regional health authority). Specifically, we examine a decade of newspaper coverage in a mid-size Canadian city region to document and characterize how the activities of volunteers and voluntary sector organizations in the community are portrayed in light of the structural imperatives to integrate health care services and regionalize health care governance. The media findings reveal a suite of public concerns and related activities, with the voluntary sector called upon in various ways to defend the autonomy of the community against the perceived threats to local services, employment and vulnerable populations. We interpret the evident complexity of voluntary sector resistance as a form of ‘defensive localism’ and discuss implications for developing informed policy on health care restructuring and for advancing knowledge on the local geographies of voluntarism.     

Analyzing Population Density Disparity in China with GIS-automated Regionalization: The Hu Line Revisited

The famous ’Hu Line’, proposed by Hu Huanyong in 1935, divided China into two regions(southeast and northwest) of comparable area size but drastically different in population. However, the classic Hu Line was derived manually in absence of reliable census data and computational technologies of modern days. It has been subject to criticism of lack of scientific rigor and accuracy. This research uses a GIS-automated regionalization method, termed REDCAP(Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning), to reconstruct the demarcation line based on the 2010 county-level census data in China. The results show that the logarithmic transformation of population density is a better measure of attributive homogeneity in derived regions than density itself, and produces two regions of nearly identical area size and greater contrast in population. Specifically, the revised Hu Line by Hu Huanyong in 1990 had the southeast region with 94.4% of total population and 42.9% of total land, and our delineation line yields a southeast region with 97.4% population and 50.8% land. Therefore, the population density ratio of the two regions is 27.1 by our line, much higher than the ratio of 22.4 by the Hu Line, and thus outperforms the Hu Line in deriving regions of maximum density contrast with comparable area size. Furthermore, more regions are delineated to further advance our understanding of population distribution disparity in China.     

长山群岛海洋农牧化海域环境分区研究

海洋农牧化就是要在海域中,对贝、藻、鱼、虾类生物资源进行人工养殖、增殖以提高资源量。从捕天然生物资源转变成为以捕增养殖资源为主的生产方式。通过对长山群岛海域发展海洋农牧化的海域环境以及海水的理化因子等进行评价,并对该海域海水增养殖的发展状况、养殖品种及构成变化特征进行了分析,最后,应用主成份-聚类分析方法,将长山群岛海域环境划分为三个海洋农牧化区域,为因海制宜、合理布局海水增养殖生产提供科学依据。     

Singularity and Nonnormality in the Classification of Compositional Data

Geologists may want to classify compositional data and express the classification as a map. Regionalized classification is a tool that can be used for this purpose, but it incorporates discriminant analysis, which requires the computation and inversion of a covariance matrix. Covariance matrices of compositional data always will be singular (noninvertible) because of the unit-sum constraint. Fortunately, discriminant analyses can be calculated using a pseudo-inverse of the singular covariance matrix; this is done automatically by some statistical packages such as SAS. Granulometric data from the Darss Sill region of the Baltic Sea is used to explore how the pseudo-inversion procedure influences discriminant analysis results, comparing the algorithm used by SAS to the more conventional Moore–Penrose algorithm. Logratio transforms have been recommended to overcome problems associated with analysis of compositional data, including singularity. A regionalized classification of the Darss Sill data after logratio transformation is different only slightly from one based on raw granulometric data, suggesting that closure problems do not influence severely regionalized classification of compositional data.