古生物学数据库现状与数据驱动下的科学研究     

邓怡颖  樊隽轩  王玥  史宇坤  杨娇  鲁铮博 《高校地质学报》2020,26(4):361-383

化石数据是了解地球历史以及深时生命演化的重要信息来源。通过数百年的积累，古生物学家已经发表了海量的古生物学数据。过去三、四十年里，随着计算机、数据库和互联网技术的快速发展，国内外涌现出大量的古生物学数据库，彼此间的目标、体系架构、数据组织方式和服务对象通常存在显著差异，呈现百花齐放的特点。文章系统介绍了古生物学领域主要数据库的发展历史、数据表结构、数据特征和数据量等建设情况，对比分析了其数据整理方式、核心在线功能、数据共享特点和数据质量控制措施。同时，结合近年来数据驱动下的古生物学领域的科学研究实例，提出一站式全生态链数据平台的建设设想，为深时数字地球（DDE）建设多学科融合、数据开放与共享的大数据平台提供参考。  相似文献   

基于混合聚类的岩体结构面优势分组方法     

许扬  张文  符锐  聂振邦  兰志广  陈怀玉  单博 《世界地质》2020,39(1):113-120

提出一种基于凝聚层次法和模糊C均值法的混合聚类法,用于对岩体结构面的优势组划分。该方法将结构面投放到在单位球面上,并使用欧式距离作为极点的相似性度量准则。先剔除结构面数据中的孤值产状,然后用凝聚层次法得到初步聚类结果,并将其作为FCM法的初始聚类中心,最后用FCM法划分优势组。通对人工生成产状样本的分组,验证了该法的正确性。将该方法应用于大藤峡坝址区实测的结构面数据的划分。在实测数据中寻找到两个孤值产状,成功将大藤峡D1y^1-3地层岩体结构面划分为两组,得到了符合实际的分组结果。  相似文献   

深时全球海平面变化重建方法的回顾与展望     

许艺炜  胡修棉 《高校地质学报》2020,26(4):395-410

全球海平面变化对古地理、古生物、古气候演化以及能源矿产分布具有重要的控制作用。然而，目前学界对深时海平面变化的驱动机制尚不清楚，部分归因于缺乏高精度全球海平面变化的恢复。文章回顾了全球海平面变化研究的起始与发展过程，归纳出五种类型的深时海平面变化重建方法和技术，即地层学、沉积学、洋盆动力学、同位素地球化学方法和大数据技术。并总结了上述研究方法的原理、优势和不足，并以白垩纪全球海平面重建为实例，讨论了当前深时全球海平面重建的难点和争议点，并对未来深时全球海平面变化重建进行了展望。  相似文献   

An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest     

《Chinese Astronomy and Astrophysics》2020,44(1):41-60

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   

基于超像元词包特征和主动学习的高分遥感影像变化检测     

杨进一  徐伟铭  王成军  翁谦 《地球信息科学学报》2019,21(10):1594-1607

为解决高分辨率遥感影像变化检测中存在底层特征缺乏语义信息、像元级的检测结果存在“椒盐”现象以及监督分类中样本标注自动化程度较低,本文提出一种基于超像元词包特征和主动学习的变化检测方法。首先采用熵率分割算法获取叠加影像的超像元对象;其次提取两期影像像元点对间的邻近相关影像特征（相关度、斜率和截距）和顾及邻域的纹理变化强度特征（均值、方差、同质性和相异性）,经线性组合作为像元点对的底层特征;然后基于像元点对底层特征利用BOW模型构建超像元词包特征,并采用一种改进标注策略的主动学习方法从无标记样本池中优选信息量较大的样本,且自动标注样本类别;最后训练分类器模型完成变化检测。通过选用2组不同地区的GF-2影像和Worldview-Ⅱ影像作为数据源进行实验,实验结果中2组数据集的F1分数分别为0.8714、0.8554,正确率分别为0.9148、0.9022,漏检率分别为0.1681、0.1868,误检率分别为0.0852、0.0978。结果表明,该法能有效识别变化区域、提高变化检测精度。此外,传统主动学习方法与改进标注策略的主动学习方法的学习曲线对比显示,改进的标注策略可在较低精度损失下,有效提高样本标注自动化程度。  相似文献   

The Basic Shape Classification of Space Debris with Light Curves     

LU Yao  ZHAO Chang-yin 《Chinese Astronomy and Astrophysics》2021,45(2):190-208

We study the machine learning method for classifying the basic shape of space debris in both simulated and observed data experiments, where light curves are used as the input features. In the dataset for training and testing, simulated light curves are derived from four types of debris within different shapes and materials. Observed light curves are extracted from Mini-Mega TORTORA (MMT) database which is a publicly accessible source of space object photometric records. The experiments employ the deep convolutional neural network, make comparisons with other machine learning algorithms, and the results show CNN (Convolutional Neural Network) is better. In simulational experiments, both types of cylinder can be distinguished perfectly, and two other types of satellite have around 90% probability to be classified. Rockets and defunct satellites can achieve 99% success rate in binary classification, but in further sub-classes classifications, the rate becomes relatively lower.  相似文献   

Impact of flooded rice paddy on remotely sensed evapotranspiration in the Krishna River basin,India     

Pardhasaradhi Teluguntla  Dongryeol Ryu  Biju George  Jeffrey P. Walker 《水文研究》2020,34(10):2190-2199

Evapotranspiration (ET) is one of the major water exchange processes between the earth's surface and the atmosphere. ET is a combined process of evaporation from open water bodies, bare soil and plant surfaces, and transpiration from vegetation. Remote sensing-based ET models have been developed to estimate spatially distributed ET over large regions, however, many of them reportedly underestimate ET over semi-arid regions (Jamshidi et al., Journal of Hydrometeorology, 2019, 20, 947–964). In this work, we show that underestimation of ET can occur due to the open water evaporation from flooded rice paddies ignored in the existing ET models. To address the gap in ET estimation, we have developed a novel approach that accounts for the missing ET component over flooded rice paddies. Our method improved ET estimates by a modified Penman-Monteith algorithm that considered the fraction of open water evaporation from flooded rice paddies. Daily ET was calculated using ground based meteorological data and the MODIS satellite data over the Krishna River Basin. Seasonal and annual ET values over the Krishna Basin were compared with two different ET algorithms. ET estimates from these two models were also compared for different crop combinations. Results were validated with flux tower-based measurements from other studies. We have identified a 17 mm/year difference in average annual ET over the Krishna River Basin with this new ET algorithm. This is very critical in basin scale water balance analysis and water productivity studies.  相似文献   

数字正射影像结合LiDAR数据在山区测绘中的应用     

严慧敏 《测绘通报》2020,(1):115-119

随着信息化社会的到来，现代水利测绘已经由传统测绘向信息化测绘发展，无人机技术应用于测绘行业推进了信息化测绘进程。本文探讨了如何有效利用无人机技术解决测绘领域在山区遇到的问题。固定翼无人机能及时获取地面数字正射影像数据，捕获裸露地面的平面和高程，但是无法获取植被覆盖下的地表高程信息，因此，本文通过机载激光雷达获取植被覆盖下的LiDAR点云数据；将二者数据相结合，再通过EPS软件生成三维地表模型，可以快速获取任何测区地物和地形数据，不仅提高了工作效率，还降低了外业劳动强度。  相似文献   

Analysis and Comparison for Fusion Algorithms of Time Transfer     

WANG Wei-xiong  DONG Shao-wu  WU Wen-jun  GUO Dong  ZHANG Jian 《Chinese Astronomy and Astrophysics》2021,45(2):224-235

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Long-term hydrological,biogeochemical, and climatological data from Walker Branch Watershed,East Tennessee,USA     

Natalie A. Griffiths  Patrick J. Mulholland 《水文研究》2021,35(3):e14110

In 1967, the original Walker Branch Watershed (WBW) project was established to study elemental cycling and mass balances in a relatively unimpacted watershed. Over the next 50+ years, findings from additional experimental studies and long-term observations on WBW advanced understanding of catchment hydrology, biogeochemistry, and ecology and established WBW as a seminal site for catchment science. The 97.5-ha WBW is located in East Tennessee, USA, on the U.S. Department of Energy's Oak Ridge Reservation. Vegetation on the watershed is characteristic of an eastern deciduous, second-growth forest. The watershed is divided into two subcatchments: the West Fork (38.4 ha) and the East Fork (59.1 ha). Headwater streams draining these subcatchments are fed by multiple springs, and thus flow is perennial. Stream water is high in base cations due to weathering of dolomite bedrock and nutrient concentrations are low. Long-term observations of climate, hydrology, and biogeochemistry include daily (1969–2014) and 15-min (1994–2014) stream discharge and annual runoff (1969–2014); hourly, daily, and annual rainfall (1969–2012); daily climate and soil temperature (1993–2010); and weekly stream water chemistry (1989–2013). These long-term datasets are publicly available on the WBW website (https://walkerbranch.ornl.gov/long-term-data/ ). While collection of these data has ceased, related long-term measurements continue through the National Ecological Observatory Network (NEON), where WBW is the core terrestrial and aquatic site in the Appalachian and Cumberland Plateau region (NEON's Domain 7) of the United States. These long-term datasets have been and will continue to be important in evaluating the influence of climatic and environmental drivers on catchment processes.  相似文献