Analysis of estimated satellite clock biases and their effects on precise point positioning

This study provides a systemic analysis to identify the biases in estimated satellite clocks and illustrates their effects in precise point positioning (PPP). First, the precise satellite clock estimation method considering pseudorange and carrier phase hardware delays is derived. Two methods for satellite clock estimation are compared, and their equivalency is discussed. The results show that apart from the well-known constant code hardware biases, the time-variant phase hardware biases are also absorbed by the estimated clocks. Also, the satellite clocks contain biases caused by modeling errors. To analyze the effects of these biases, they are grouped into initial clock biases (ICBs) and time-dependent biases (TDBs). Then, a detailed analysis of the impact of the biases on PPP-based troposphere and coordinate estimates is conducted. The experimental analysis demonstrates that TDBs affect positioning and tropospheric estimates, and their impacts are more significant in the static mode. The ICBs affect coordinate accuracy, zenith total delay mean bias, and its standard deviations only at the millimeter level for kinematic and static PPP, which is negligible. However, the ICBs affect the convergence period for both static and real kinematic PPP, and the magnitude of their impact largely depends on data quality. Note that satellites clocks are generally estimated with the P1/P2 and L1/L2 ionospheric-free combinations, and that hardware-specific parts of ICBs and TDBs cancel if users employ the same type of observables as the clock providers. Otherwise, the effects of biases cannot be ignored, especially for triple-frequency applications. Also, modeling-specific parts of ICBs and TDBs are significant in real-time clocks, which also affect user applications. Our conclusion is applicable for understanding the effects of these biases.     

Object- and pixel-based classifications of macroalgae farming area with high spatial resolution imagery

Macroalgae plays an important role in coastal ecosystems. The accurate delineation of macroalgae areas is important for environmental management. This study compared the pixel- and object-based methods using Gaofen satellite no. 2 image to explore an efficient classification approach. Expert system rules and nearest neighbour classifier were adopted for object-based classification, whereas maximum likelihood classifier was implemented in the pixel-based approach. Normalized difference vegetation index, normalized difference water index, mean value of the blue band and geometric characteristics were selected as features to distinguish macroalgae farms by considering the spectral and spatial characteristics. Results show that the object-based method achieved a higher overall accuracy and kappa coefficient than the pixel-based method. Moreover, the object-based approach displayed superiority in identifying Porphyra class. These findings suggest that the object-based method can delineate macroalgae farming areas efficiently and be applied in the future to monitor the macroalgae farms with high spatial resolution imagery.     

Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

The accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.     

小冰期时中国南方地区降水模式的差异研究

小冰期是过去一千年中全球气候变化的重要事件之一。关于小冰期时中国季风区和西风影响区气候变化的对比研究众多,但是缺乏中国南方地区降水模式时空差异的研究,难以了解中国南方地区降水变化规律。为了系统地了解小冰期时中国南方地区降水的复杂性,本文将中国南方地区划分为东南—华南沿海地区、中部地区以及西南地区三个区域,总共选取了19条高分辨率的古气候记录进行对比研究,主要有以下几点认识:(1)相对于中世纪暖期而言,小冰期期间中国南方东南—华南沿海地区的气候偏湿,这可能与雨带在中国南方的滞留时间延长和沿海地区受台风的影响增强有关。(2)中国中部地区秦岭南麓和神农架高山林区在小冰期时期主要呈"冷湿"的模式,差异在于秦岭南麓区域主要在小冰期中后期偏湿,这与中部其他区域偏"冷干"的模式不同。这种区域差异可能是由于地形地势和大气环流的复杂性导致。(3)中国西南地区受印度夏季风和东亚夏季风的共同影响,且该区域地形复杂,其气候变化在小冰期时期存在更加明显的空间差异,没有呈现出比较一致的降水模式。与小冰期期间的降水变化不同的是,近30年东南—华南沿海地区除了台湾和雷州半岛,其他区域降水明显减少,可能受气温和人类活动等因素的影响。通过结合高分辨率的古气候记录,我们系统分析了中国南方小冰期的干湿模式在时空上的差异及其可能的影响因子,这对于认识小冰期时中国南方不同区域降水的复杂性及未来旱涝灾害的防控具有一定意义。     

玄武岩柱状节理六边形结构形成机制探讨

玄武岩柱状节理往往呈现完美的六边形石柱,这种现象引起了人们的广泛关注和好奇,但是对于其形成机理尚无合理的解释。本文通过对冷却过程中的玄武岩进行受力分析,提出当岩石（浆）冷凝收缩的凝聚力达到其抗张强度时,岩石（浆）内部发生潜在破裂和微形变;当潜在破裂面形成后,因岩石的泊松效应,微小潜在破裂面处的应力状态发生重整,形成新的潜在破裂面;当新的潜在破裂面处的剪应力等于岩石抗张强度时,岩石（浆）发生剪切破裂,形成如今所见的柱状节理。根据前人相关岩石实验数据,推算得到玄武岩相应温度下的内摩擦角、黏聚力、抗张强度和泊松比,采用应力莫尔圆方法进行数值计算,获得玄武岩在冷却到800 ℃左右时发生破裂,六棱柱形柱状节理开始形成,内角约119.1°。进一步分析认为,岩石的黏聚力、石英含量等因素可能控制着柱状节理的发育和形状。     

论中国国家公园地质考察与评价——以浙江丽水百山祖国家公园为例

鉴于保护地调查评价历史与目标,国家公园地质考察评价基准是地质学关于地球的“时间、空间、演化”知识的发现路径,既识别国家公园候选地的国家符合性地质事件,又识别国家公园自然性、独特性、优美性、多样性、整体性的地质机制,提供国家公园最重要的自然生态系统与自然景观保育管理的地质学支撑。浙江丽水百山祖国家公园符合性的地质事件是公园发现的4.0~4.2 Ga冥古宙陆核物质的锆石晶体、中生代岛弧陆盆火山酸性火山岩系列和从流纹岩山岭到花岗岩—变质岩谷底的“峰—岭—丘—谷（盆）”的亚热带滨海山地地貌结构,地貌结构发育演化是百山祖公园最重要的自然生态系统、区域性流域水源地、独特山水景观的形成基础。保护百祖山公园地貌结构和过程的完整性与真实性是确保其重要自然生态系统自然演化和生态服务产品持续供给的基础。     

磁法三维建模在龙王沟磁铁矿勘探中的应用

以龙王沟磁铁矿高精度磁测数据为基础,采用小波多尺度分解方法,对化极后的磁法数据进行多尺度分解,通过功率谱法计算小波多尺度分解后的各阶细节异常的场源深度。结合地形、地质及钻孔资料,采用2.5D人机交互反演对磁测剖面上的磁铁矿体进行拟合,利用Golden Software公司开发的Voxler软件,在虚拟三维环境下实现二维小波多尺度分解数据的可视化,建立三维地质体模型,直观的预测磁铁矿体的空间范围和分布形态,实现地质、物探和地上、地下信息一体化集成展示,进行专业分析评价和辅助决策,可以有效的提高地质找矿效果。     

基于ASTER与Sentinel-2A融合数据的云南普朗铜矿化蚀变信息提取

云南普朗铜矿区是我国提高战略性金属矿产铜矿资源的主要潜力地段,该矿区位于多云多雨山地高原区,采用传统地面调查方法开展找矿勘查工作受限较大,而遥感技术可在其中发挥重要作用。鉴于此,本研究选取ASTER和Sentinel-2A多光谱遥感数据,在光谱协同统一两种数据源的地表反射率基础上,采用高通滤波(High-Pass Filtering,HPF)的融合方法兼顾两种数据在短波红外波段和可见光近红外波段的优势,获取了具有高空间分辨率和高光谱保真度的ASTER-Sentinel-2A融合数据集;进而利用"比值+主成分分析法"与"主成分分析+能谱-面积法",开展了普朗铜矿区矿化遥感蚀变信息识别,并通过深入分析及野外验证,提出了对普朗铜矿蚀变信息分布特征及找矿潜力地带的新认识:(1)在原蚀变填图工作中判定为青磐岩化带的东部区域,重新进行了蚀变带的划分;(2)东部区域中新划分的钾化硅化带和绢英岩化带,具有较大找矿潜力。本研究可为普朗铜矿找矿勘查提供参考。     

滇西盈江地区新泡山离子吸附型稀土矿床成矿条件及找矿前景

滇西盈江地区是近年来离子吸附型稀土矿床找矿突破较大的地区,典型代表为腾冲岩浆弧内新发现的新泡山稀土矿床,为一中型离子吸附型稀土矿床,是滇西高海拔地区新发现的典型矿床。新泡山稀土矿床的发现对今后高海拔地区的找矿工作具有重要的示范意义。通过对新泡山稀土矿床的地质特征、风化壳结构特征、矿体垂向变化特征进行研究,认为新泡山稀土矿床类型为富钕轻稀土离子吸附型稀土矿床,并伴生有重稀土钇。滇西盈江地区与花岗岩有关的离子吸附型稀土矿主要受控于母岩稀土元素丰度、气候以及地形地貌。"沟-谷-盆"地貌两侧及周缘低缓山丘和平缓山坡、山脊是有利的成矿部位。结合区域找矿成果,认为研究区稀土矿找矿潜力较大,可达超大型远景规模,在后续的找矿工作中应加强对重稀土元素钇的评价。     

Dynamic Response and Mechanical Behaviours of Geogrid for High Earth-rockfill Dams

Geotechnical and Geological Engineering - Due to the complexity of the interaction between the geogrid and the soil interface in high earth-rock dams, the method of replacing the grid with steel...