细粒氯化钠对光卤石分解结晶过程的影响研究

以细粒高钠光卤石为原料,研究光卤石中的细粒氯化钠对氯化钾品位的影响,并探讨其原因。实验结果表明光卤石中含有的细粒 NaCl会严重降低 KCl品位,细粒 NaCl浮选夹带不是导致 KCl品位降低的主要原因。溶解速率实验结果表明,光卤石中的细粒 NaCl溶解速度较快,溶液中 NaCl浓度很快达到较高值,随溶液 MgCl2浓度不断升高,新生 NaCl晶体析出量增加, NaCl和 KCl之间的共生晶体数量增加,新生 KCl和 NaCl晶体之间的共生现象是导致 KCl品位降低的主要因素。     

高光谱遥感土地质量指标信息提取研究进展

高光谱遥感技术已成为提取土地质量指标的前沿技术之一。该文回顾了国内外高光谱遥感技术在土地质量指标提取中的研究进展,总结归纳了作为土地生态系统载体的土壤属性质量指标和反映生态系统结构功能的质量指标中的土壤有机质、全氮、土壤水分、铁氧化物、土壤重金属、土壤质地、土壤盐分、植被覆盖度、生物量、指示种10个指标的提取、敏感波段选择与反演方法,指出研究中存在的问题,最后展望了高光谱遥感技术在土地质量指标提取研究中的应用前景。     

2004年苏门答腊地震前后海面高趋势的变化

利用苏门答腊附近海域T/P、Jason-1测高卫星近20年的海面高连续观测资料,分别计算了该区域(80°E~105°E,5°S~20°N)在2004年苏门答腊大地震前后的海面高变化趋势,并与该区域对应时间段GRACE重力卫星反演的地表质量迁移结果进行比较。研究结果表明,由卫星测高观测资料估算的震区地震前后海平面趋势的变化与卫星重力反演结果基本一致。由于卫星测高沿轨观测具有高精度、高时空分辨率的特性,卫星测高资料估算的海平面趋势变化可以更为准确地反映震区海平面变化的局部特征。还对该区域震后形变特征进行了初步分析。     

淤泥质潮滩沉积物含水量遥感反演模型研究

潮滩沉积物含水量是表征潮滩地物信息的一个重要特征量,它影响着遥感提取潮滩地物信息的准确性。利用含水量-反射率指数衰减模式建立单波段模型,同时参考4种植被指数的形式构建含水量指数,建立适用于潮滩环境的含水量反演波段组合模型,实现了沉积物含水量的遥感反演。研究结果显示:对反射率数据利用干土反射率进行归一化处理后构建的NEWCI(Normalized Enhanced Water Content Index)归一化增强型含水量指数模型的含水量反演效果最佳。在含水量结果中,除了砂类别反演的确定性系数R2为0.675以外,粉砂、砂质粉砂、粉砂质砂、粘土质粉砂等4种沉积物类型反演的确定性系数均在0.83以上;当不考虑沉积物类型时,NEWCI指数模型的反演精度也达到0.8,RMSE为0.059,表明NEWCI指数模型对沉积物类型不敏感,且能够保持较高的含水量模拟精度,因而适合潮滩沉积物含水量的大范围预测。其反演结果可在潮滩地物信息遥感反演时有效削弱水分的影响,进而提高地物信息提取的效率。     

山石成精·山岭之巅风光无限——广西浦北五皇山国家地质公园

山不在高,有仙则名。 听闻广西浦北五皇山山顶风光无限,怪石成精。还传闻五皇山的树,会＂抓＂石,还会＂咬＂人。于是我们慕名前来,观赏广西浦北五皇山国家地质公园。对于这些传闻的真假,只有到实地察看才见分晓。     

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation （NPP） to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model （CanESM2） of the Canadian Centre for Climate Modelling and Analysis （CCCma）, which are part of the phase 5 of the Coupled Model Intercomparison Project （CMIP5）. The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m^-2 yr^-1 and-0.14 gC m^- 2 yr^-2, respec- tively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at -1.79 gC m^-2 yr^-2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m^-2 yr^-1 and 0.84 gC m^-2 yr^-2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m^2 yr^-1 and 0.83 gC m^2 yr^-2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of-0.39 kg m^-2 yr^-1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration （experiment M2）, and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-     

Genetic parameter estimation for juvenile growth and upper thermal tolerance in turbot (Scophthalmus maximus Linnaeus)

Twenty-six half-sib groups(53 full-sib families) of turbot, Scophthalmus maximus Linnaeus, were obtained by artificial insemination. We measured growth in the offspring(40–50 individuals/family) and subjected them to a thermal tolerance challenge over a period of 34 d. There was no significant difference in daily mortality(range: 0.580%–1.391%) between Days 1–13 during the thermal tolerance challenge. However, daily cumulative mortality increased rapidly between Days 14 and 29, especially on Days 15 and 16(20.232% and 34.377%, respectively). Mortality was highest on Day 16(14.145%). We estimated the genetic parameters using the average information restricted maximum likelihood method. We used a likelihood ratio test to evaluate the significance of effects in models with and without identity as an effect, and compared the final log-likelihoods(maximum log L). Lastly, we estimated phenotypic and genetic correlation between the upper thermal tolerance limit(UTT) and body weight(BW). In this study, the positive phenotypic correlation was low between UTT and BW(0.093±0.029). The genetic correlation between UTT and BW was negative(-0.044±0.239). The heritability for upper thermal tolerance was low(0.087±0.032), which is of approximately moderate heritability. The heritability for body weight was high(0.303±0.074). Our results suggest there is significant potential for improvement in the culture of turbot by selective breeding.     

高光谱大气红外探测仪(AIRS)反演大气不稳定度指数在强对流天气个例中的应用试验

使用探空、NCEP-FNL,数据和高光谱分辨率大气垂直探测仪(AIRS)标准反演数据计算大气不稳定度指数,对2011年6月23日北京强对流天气发生前的本地及上游大气中不稳定能量进行分析研究。分析发现:利用08、14和20时探空数据计算的北京站不稳定度指数显示了在"6·23暴雨"过程发生前后北京上空不稳定能量变化,上游关键区无探空数据;利用NCEP和AIRS数据计算的不稳定度指数显示,强对流天气发生前,在北京的上游关键区大气处于极端不稳定状态(K指数大于40,SI指数小于一5),有利于强对流天气发生。文章的研究结果表明,探空数据时空分辨率较低,不利于监测强对流天气的发生;质量控制后AIRS数据计算的不稳定度指数可以监测对流天气的发生;空间分辨率较低的NCEP数据监测小范围大气不稳定层结能力较低。综上所述,AIRS反演产品具有弥补探空资料时空分辨率不足的优势,利用AIRS L2反演产品计算晴空大气不稳定度指数产品可以监测到"6·23暴雨"天气发生前上游关键区大气层结稳定度状态,为预报员决策提供有效的辅助信息。     

天宫一号高光谱数据辐射校正的CUDA并行优化

高光谱图像经过辐射校正后,消除了探测元的响应差异,能更好地满足专题信息提取的数据要求.利用探测元的列均值、列标准差等统计信息对天宫一号高光谱短波红外数据进行辐射校正检验,并基于GPU CUDA计算模型对均值归一化、矩匹配、相邻列均衡等3种相对辐射校正算法进行了并行计算优化.通过辐射校正计算流程拆分,CPU控制流程逻辑,GPU执行数据级并行计算,并建立CUDA的计算单元与数据单元的映射关系,获得5—7倍的计算加速比,这些辐射校正算法依据图像自身统计信息,且易于进行并行计算优化,满足实时校正的处理时效要求,为未来高光谱数据在轨实时辐射校正提供了新思路.     

面向对象规则和支持向量机的天宫一号高光谱影像分类

传统的高光谱分类方法通常基于单一像元的光谱或纹理特征,很少考虑地物空间结构信息与空间相关特征.本文将面向对象规则与基于像元的分类进行融合,利用对象的空间结构特征和光谱特征进行混合分类,旨在克服像元层次分类的不足.本文尝试性的提出了两种混合分类方法:(1)基于分形网络演化的多尺度分割支持向量机分类(2)基于多层分水岭分割的SVM分类,并将这两种方法应用到天宫一号高光谱数据上.结果表明:基于面向对象规则的混合分类方法有效地提高了分类精度,不仅能够改善同谱异物现象,而且解决分类结果中地物破碎的问题.