SAR image despeckling with a multilayer perceptron neural network

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.     

Recent insights into physiological responses to nutrients by the cylindrospermopsin producing cyanobacterium,Cylindrospermopsis raciborskii

The harmful cyanobacterium Cylindrospermopsis raciborskii is a widespread species increasingly being recorded in freshwater systems around the world. Studies have demonstrated some key attributes of this species which may explain its global dominance. It has a high level of flexibility with respect to light and nutrients, being capable of growth under low and variable light conditions. However, it is the strategy with respect to nutrient utilization that has received more attention. Unlike many bloom forming species, the dominance of this species is not simply linked to higher nutrient loads. In fact it appears that it is more competitive when phosphorus and nitrogen availability is low and/or variable. An important component of this flexibility appears to be the result of within-population strain variability in responses to nutrients, as well as key physiological adaptations. Strain variability also appears to have an effect on the population-level cell quota of toxins, specifically cylindrospermopsins(CYNs). Field studies in Australia showed that populations had the highest proportion of toxic strains when dissolved inorganic phosphorus was added, resulting in stoichiometrically balanced nitrogen and phosphorus within the cells. These strategies are part of an arsenal of responses to environmental conditions, making it a challenging species to manage. However, our ability to improve bloom prediction will rely on a more detailed understanding of the complex physiology and ecology of this species.     

等效沙厚度研究进展

风、沉积物和地表覆盖是控制沙丘地貌的三大要素.沉积物尤其是沙源供应对沙丘地貌的影响仍有待深入研究.沙丘体积的研究促使了等效沙厚度(equivalent sand thickness,EST)概念的提出.EST研究经历了多个沙丘和亚沙丘尺度2个研究阶段.多个沙丘EST研究发现,EST与沙丘高度之间具有较好的一致性,其与方...     

全国重要矿产总量预测方法

全国重要矿产资源评价涉及25种重要矿产的近百种矿床类型,需要在1∶20万尺度水平圈定成矿预测远景区,并科学估算各远景区资源量,为国家矿产资源战略勘查和战略部署提供技术支撑。为了保证预测成果在同一层面上进行全国汇总,制定了全国一致的、标准的技术要求和方法。通过对中国以往一轮、二轮区划预测方法、全国矿产资源总量预测方法及国外最新预测方法的分析和总结,结合近年来预测理论的新发展,确定了全国重要矿产总量预测的理论基础是成矿系列理论、现代成矿动力学理论和综合信息矿产预测理论,采用的预测思路是矿床模型综合地质信息预测方法。文章陈述了总量预测的方法流程和预测技术要求,有关方法思路可供资源评价人员参考。     

深圳西涌滨海旅游区海滩裂流风险评估及特征分析

基于海滩地形动力学、遥感影像的风险预识别以及现场排查等方法,对西涌滨海旅游区海滩裂流风险进行了初步评估.评估结果表明:地形动力分析结果显示,西涌滨海旅游区泳场逐月平均沙滩类型大部分是沿岸沙坝和裂流沟槽交替的沙坝型(B),风险等级高;影像特征判断该沙滩属于沿岸沙坝和裂流沟槽交替的沙坝型(B)或者低潮位附近伴有冲流沙坝及裂...     

基于R语言的NetCDF文件分析和可视化应用

气象领域目前有多种广泛应用的气象数据分析和可视化工具集,包括GrADS、NCL、CDO和IDL等。R语言是一种由统计学家开发的统计计算和绘图的语言和环境,具有大数据处理的能力。R语言数量众多的扩展包为R语言用于海量气象数据分析和可视化提供了强有力的支持。基于R语言对NCEP发布的数据集进行了统计分析和可视化,展示了R语言在气象数据处理和可视化方面的应用。结合R语言提供的贝叶斯统计扩展包和高性能并行计算扩展包探讨了R语言在气象数据处理和可视化应用方面的广泛前景。     

华南锋面与暖区暴雨个例对比分析

分析了1961～1999年亚洲热带近海海温与云南降水的关系.通过研究云南夏季降水对近海海温异常的响应,发现云南初夏的降水与亚洲热带近海海温有明显的负相关关系,这种降水减少海温正距平的情况在北印度洋西部和阿拉伯海表现比孟加拉湾和南海更显著,但是在盛夏相关关系不显著.同时发现云南西南部的夏季降水与前期盂加拉湾海温有显著的正相关,而与其它海域的海温相关不显著.滇东南的夏季降水只与前期南海的海温有显著的正相关.     

CA FCM方案与其它几种人工增雨评估方案的比较

对河南省12次飞机增雨作业,分别采用作业区域趋势对比双比分析评估方案、区域趋势相关回归分析方案、区域趋势协变量多元回归分析方案、浮动对比区历史回归分析方案（FCM）、以降水量为协变量的CAFCM（ClusterAnalysis〖CD*2〗based Floating Control historical regression Method）方案和以降水量和整层大气可降水量为协变量的CAFCM方案进行效果评估,均得到大于15％的相对增雨量。对结果比较分析表明：协变量由降水量和整层大气降水量两个组成的C     

如何正确理解海洋倾废的定义

我国的海洋倾废管理制度和体系日臻完善,既制定了《海洋环境保护法》等国内海洋法律、法规,又相继批准了《联合国海洋法公约》和加入了《1972伦敦公约》,在原则上与国际公约保持一致。但随着海洋经济的蓬勃发展,海洋倾废活动日益频繁,不断出现新的处置方式,从而导致对海洋倾废的定义有不同的理解,并因此引发了一些争议。文章从法律的角度,结合倾废管理实践,对海洋倾废的定义进行了深入研究。     

海岸带石油污染物自然衰减研究综述

石油在海岸带泄漏后会形成长期危害生态环境的污染源区。在水动力、微生物和地球化学等的作用下,石油污染物的质量、浓度、体积、毒性和流动性降低的过程称为自然衰减。本文系统综述了海岸带石油污染物的自然衰减特征及其研究手段,阐明了石油性质、沉积物类型、水动力因素、光氧化反应和微生物等因素对海岸带石油污染源区自然衰减的影响,归纳总结了表征石油污染源区自然衰减过程的地球化学、地球生物和地球物理指标。同时,通过总结自然衰减过程的预测方法,指出了研究方向多学科交叉、多数据驱动的重点及难点,最后对海岸带石油污染源区自然衰减研究提出了展望。