Massive sedimentation of fine sediment with organic matter and enhanced benthic-pelagic coupling by an artificial dyke in semi-enclosed Chonsu Bay, Korea

To assess the impact of an artificial dyke in Chonsu Bay (CBD) on the organic carbon (C(org)) cycle, we measured excess (210)Pb activities, C(org) and nitrogen content in sediment cores. The C(org) oxidation rates (C(ox)) on the surface sediment and benthic nutrient fluxes were also quantified with an in situ benthic chamber. The higher excess (210)Pb inventory, C(org) and nitrogen in cores near the CBD indicated lateral transport and local, massive deposition of particulate matter due to tidal circulation altered by artificial dyke construction. The C(ox) in sediment near the CBD was about twice as high as that out of the bay, suggesting the importance of benthic remineralization of organic matter. The benthic fluxes of dissolved inorganic nitrogen and phosphate were four to six times higher than those outside the bay, corresponding to 141% and 131% respectively, of the requirements for primary production.     

工业测量系统在多波束天线安装检测中的应用

根据多波束天线测量和检测的实际情况 ,主要介绍了多波束天线的数学模型、解算方法、测量方案的设计以及调整量的计算等问题。最后对实测结果进行了分析。     

星载微波SSM/Ⅰ遥感在中国东北华北农田的辐射特征分析

本文研究了星载微波ＳＳＭ／Ⅰ１９９６年在中国东北华北平原农田上７个通道辐射亮度温度（ＴＢ）的遥感数据,提出用几个通道ＴＢ组合的散射指数和极化指数来分析中国平原地区农田的微波辐射特征,及其随生长季节的时间性变化。星载ＳＳＭ／Ⅰ数据可以监视农作物的生长和平原地区地面湿度的变化。本文还给出了大气和农作物地表矢量辐射传输的数值模拟结果。     

星载微波SSM/Ⅰ遥感在中国东北华北农田的辐射特征分析

国家遥感应用工程技术研究中心ＮａｔｉｏｎａｌＥｎｇｉｎｅｅｒｉｎｇＲｅｓｅａｒｃｈＣｅｎｔｅｒｆｏｒＧｅｏｍａｔｉｃｓ（ＮＣＧ）国家遥感应用工程技术研究中心于１９９６年１２月２５日由国家科委正式批准组建（国科发计字［１９９６］６０３号文件）。中国科学...     

地球参考框架的建立和维持

详细总结了ITRF等参考框架的原理,分析了其优缺点和特性并分析了不同地球参考框架的区别。本文在协议研究的基础上,结合我国实际,提出了建立我国新一代地球参考系统的若干建议。     

利用数值投影变换构建全球六边形离散格网

本文针对全球离散格网构建过程中从平面格网到球面格网的关键步骤进行讨论,提出了一种新型的评价球面离散格网几何属性最优化的目标函数,使用遗传算法优化,得到了球面上有限层次内最优化条件下的直接剖分格网。利用有限层次内最优化格网提供的控制点数据,结合数值投影变换理论,成功地构建了几何属性更加均匀的全球六边形离散格网系统。实验表明,相对于现有Snyder等积投影建立的全球格网,在格网单元的均匀度上更优;在运算效率方面,速度大约是Snyder投影的2.5-3倍。     

全球六边形离散格网数据的三维可视化方法

针对全球六边形离散格网的三维显示化方法开展研究,设计了一种六边形格网的空间层次结构(hexagonalquaternary balanced structure,HQBS),采用四位码元对格网单元进行编码,定义并实现了格网向量的基本运算,利用这些运算可以方便地实现格网单元的空间索引。在此基础上还研究了全球离散格网的动态生成与显示算法、可视化区域裁剪等相关内容。试验表明:全球格网动态生成的效率110～370单元/ms之间,加载空间数据后,格网数据和空间数据逐层加载的时间在300 ms左右,能够保证加载空间数据后的显示刷新率在20帧/s左右。     

The challenges of integrating explainable artificial intelligence into GeoAI

Although explainable artificial intelligence (XAI) promises considerable progress in glassboxing deep learning models, there are challenges in applying XAI to geospatial artificial intelligence (GeoAI), specifically geospatial deep neural networks (DNNs). We summarize these as three major challenges, related generally to XAI computation, to GeoAI and geographic data handling, and to geosocial issues. XAI computation includes the difficulty of selecting reference data/models and the shortcomings of attributing explanatory power to gradients, as well as the difficulty in accommodating geographic scale, geovisualization, and underlying geographic data structures. Geosocial challenges encompass the limitations of knowledge scope—semantics and ontologies—in the explanation of GeoAI as well as the lack of integrating non-technical aspects in XAI, including processes that are not amenable to XAI. We illustrate these issues with a land use classification case study.