不动产大数据在城市更新潜力空间评估中的应用     

汪洋  唐华  潘进  李洋  褚峤  刘雨晴 《测绘通报》2020,(12):71

我国在发展新常态与城市精细化治理背景下，对城市更新精准施策与量化评估提出了更高的要求。城市更新过程与人、地、房的相互作用紧密相关。不动产登记数据包含丰富的人、地、房空间属性信息，能够在城市的建成环境评估过程中发挥重要作用，现有城市更新评估模型几乎均未使用这一数据支持。本文从大数据量化评估视角出发，在文献研究的基础上，利用不动产登记大数据构建城市更新潜力评估体系，建立评估方法，并以南京市为应用案例，在街道（乡、镇）尺度上，对评估对象区域进行城市更新潜力的量化评估，实现精细化尺度的空间分析，辅助城市更新方向与选址，引导精准施策。  相似文献   

Groundwater contaminant source identification based on iterative local update ensemble smoother          下载免费PDF全文

YANG Ai-lin  JIANG Si-min  LIU Jin-bing  JIANG Qian-yun  ZHOU Ting  ZHANG Wen 《地下水科学与工程》2020,8(1):1-9

Identification of the location and intensity of groundwater pollution source contributes to the effect of pollution remediation, and is called groundwater contaminant source identifcation. This is a kind of typical groundwater inverse problem, and the solution is usually ill-posed. Especially considering the spatial variability of hydraulic conductivity field, the identification process is more challenging. In this paper, the solution framework of groundwater contaminant source identification is composed with groundwater pollutant transport model (MT3DMS) and a data assimilation method (Iterative local update ensemble smoother, ILUES). In addition, Karhunen-Loève expansion technique is adopted as a PCA method to realize dimension reduction. In practical problems, the geostatistical method is usually used to characterize the hydraulic conductivity feld, and only the contaminant source information is inversely calculated in the identifcation process. In this study, the identification of contaminant source information under Kriging K-field is compared with simultaneous identification of source information and K-field. The results indicate that it is necessary to carry out simultaneous identification under heterogeneous site, and ILUES has good performance in solving high-dimensional parameter inversion problems.  相似文献   

Swelter in the city: Urban greenery and its effects on temperature in Guwahati,India     

Monjit Borthakur  Anup Saikia  Kiran Sharma 《Singapore journal of tropical geography》2020,41(3):341-366

Changing urban landscape with multistoried high rises, roads and pavements is continuously reducing urban green space. These structures result in high surface temperature variation within cities. To explore the relationship between surface temperature and normalized difference vegetation index (NDVI), this study estimates two models—geographically weighted regression (GWR) and a fixed effect panel data model in relation to the Guwahati Metropolitan Area (GMA), a secondary city in north east India. The results indicate the superiority of GWR regression in presence of spatial dependence. Panel data analysis shows that the densely populated urban areas in the GMA with less than 10 per cent greenery are 1°C warmer than the sub-urban areas with 50 per cent greenery.  相似文献   

不同结构深度神经网络的时间域航空电磁数据成像性能分析     

李金峰  刘云鹤 《世界地质》2020,39(1):159-166

时间域航空电磁系统采样密集,数据量大,所以在该领域较为实用的数据处理方法主要为一维反演和电阻率成像法。笔者从成像问题出发,建立了庞大的数据模型训练集,研究并分析了不同结构的神经网络的成像精度。通过对比分析测试结果,获得了在一定条件下适用于航空电磁成像的最优网络模型结构,包含其神经元个数和层数等信息。本文采用早停法训练神经网络,压制数据中噪声对成像结果的影响。  相似文献   

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   

重庆地震应急资料产出系统研发与应用     

龚丽文  陈石  郭卫英  黄世源  李翠平  高见 《地震地磁观测与研究》2020,41(5):192-199

地震应急资料具有较强的时效性、专业性和多学科融合的特点。中强地震发生后启动应急响应，工作人员需在短时间内产出多学科、跨领域、多手段的专业地震会商资料。以地震会商系统为平台，利用其灵活开发、自动计算和智能分析的优势，建立地震应急资料产出系统（包括会商资料处理模块、应急图件产出模块和震情报告生成模块），通过地震触发，根据预设流程和报告模板，自动产出专业报告，为震情形势研判和震后应急救援提供专业可靠的应急资料，最大限度地发挥应急救援和灾损评估的效能。  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   

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