MODIS遥感监测滇池蓝藻水华分布

以中分辨率的MODIS数据作为遥感影像源,运用蓝藻水华在蓝波段、红波段和近红外波段的光谱特征,使用假彩色合成法（RGB：6-2-1）和归一化植被指数法对滇池的蓝藻水华进行遥感监测。通过星地同步试验,证明了该两种方法的正确性。其中假彩色合成法通过色彩差异表现蓝藻水华,具有视觉效果较好的优点,归一化植被指数法则以数值大小的方式区别水华浓度,该方法建立反演模型后可用于定量研究。     

两种反映东亚夏季风异常的指数的比较研究

本文利用文献^ [4]提出的一种新的反映东亚夏季风异常的海陆温差指数分析了夏季风异常时我国气温、降水异常以及东亚环流状况，通过分析指出，东亚夏季风偏强，则中国东部夏季气温偏高，江淮干旱，华北多雨；夏季风偏弱则夏季气温偏低，江淮多雨，易涝，华北少雨。通过两种夏季风指数的对比，海陆温差指数能更好地反映东亚夏季环流及天气气候异常。文中还指出，海陆温差指数能更好的反映夏季风异常的原因是它的定义方法更科学，更全面的反映东亚海陆热力差异，既包含了东亚纬向海陆热力差异的影响，又考虑了东亚经向海陆热力差异的因素，并用地表气温和海表温度差来表示海陆热力差，好于以往用海平面气压差来反映海陆热力差。     

干旱监测预警指数研究

提出以降水的应时性、有效性、土层水的后效作用,以及大气温湿状况为依据,建立干旱指标的问题,给出了评价短期气候干旱状况的干旱实时监测和预警指数。同时对如何科学地度量干旱灾害程度也进行探讨。     

版本差量式时空数据模型研究

时空数据模型是时态地理信息系统的关键和核心。本文在分析国内外已有研究成果的基础上,结合国家基础测绘项目,提出了“版本-差量”式时空数据模型,采用“版本管理-动态关联”以及“动态分级索引”技术实现时态地理数据的存储管理和查询检索。该模型能有效降低数据冗余,提高数据访问效率。     

基于NDVI时间序列数据的江西省水稻种植制度变化研究

利用Savitzky-Golay滤波对覆盖江西省范围的SPOT VGT NDVI时间序列数据进行平滑处理的基础上,结合坡度数据,通过非监督分类的方法提取了江西省2000、2005和2010年水稻种植范围,并根据NDVI的年内动态变化,从水稻种植范围、水稻生长季起始时间、水稻复种指数和NDVI最大振幅等分析了江西省水稻种植和生长情况,探讨2000~2010年江西省水稻生产的变化。     

The MV Rena shipwreck: time-critical scientific response and environmental legacies

ABSTRACT

The sinking of the MV Rena on Astrolabe Reef (Otaiti) in the Bay of Plenty, New Zealand, resulted in the release of oil and ship debris, including dangerous goods carried as cargo. Two key questions of concern to the public and environmental managers were posed immediately: what was the impact of the Rena oil spill and how long would it take for the marine environment to recover? The research that began immediately after the ship grounded provided answers, as documented in this special issue.     

Missing the boat: Critical threats to coral reefs are neglected at global scale

Coral reefs have experienced a global decline due to overfishing, pollution, and warming oceans that are becoming increasingly acidic. To help halt and reverse this decline, interventions should be aimed at those threats reef experts and managers identify as most severe. The survey included responses from 170 managers, representing organizations from 50 countries and territories, and found that respondents generally agreed on the two major threats: overfishing and coastal development. However, resource allocation did not match this consensus on major threats. In particular, while overfishing receives much attention, coastal development and its attendant pollution are largely neglected and underfunded. These results call for a re-examination of how resources are allocated in coral reef conservation, with more attention given to aligning how money is spent with what are perceived to be the primary threats.     

中国人口城镇化质量评价及省际差异分析

新型城镇化是中国的重要国策,对人的城镇(市)化的科学评价是正确认识城镇化和制定相关政策的重要基础.目前城--乡二元分析框架下的以城镇化率和城镇(或区域)城镇化质量为主的评价方法,难以反映城镇化过程中社会结构的变化,同时乡村人口的城镇化发展也被忽略.本文提出人口城镇化质量的概念,建立了衡量人口城镇化质量的指标体系.对1995,2000,2005,2010和2012年全国及各省市的城镇人口,乡村人口及总人口的城镇化质量进行了分析.研究发现:① 尽管城镇人口的城镇化速度显著快于乡村人口,但城镇化并非城镇人口独有的社会过程.② 城乡两类人口的城镇化质量在省域尺度上正逐步形成差异明显的空间格局.③ 北京,上海,浙江等少数省市乡村人口的城镇化质量已经超越部分内地省市城镇人口的城镇化质量.建议更新对城镇化的认识和评价标准,探索在城镇化发达的地区调整城--乡二元体制的新途径,促进中国城镇化的健康发展.     

Aspects of reproduction of the brown mussel Perna perna at the Iture rocky beach near Cape Coast,Ghana

Aspects of the reproductive biology of the brown mussel Perna perna at the Iture rocky beach near Cape Coast, Ghana, were studied from September 2014 to August 2015. The current study was aimed at providing information useful for managing the mussel fishery in this locality and also that would form the basis for designing appropriate culture methods for the species. Microscopic examination of fresh smears of gonadal material, as well as histological preparations of the gonad, were used to study the sexuality and breeding pattern of the species. Monthly gonadal and condition indices were also determined. Perna perna exhibited gonochoristic sexuality with a sex ratio of approximately 1:1 throughout the study period. Sexes were identifiable at shell lengths of 15.0–19.9 mm. Five stages of gonadal development were identified in both sexes. Gametogenic activity was continuous throughout the year, with two major spawning activities, from April to June and from August to December. These periods coincided with the major and minor rainy seasons, respectively, as well as the major upwelling period in August. Condition indices suggest that the mussels were in better condition for harvesting in March and August prior to the major spawning events.     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.