基于SMAP卫星雷达资料的海冰密集度反演技术研究   总被引：1，自引：0，他引：1  

闻斌  周旋  种劲松  石立坚  叶小敏 《海洋学报》2018,40(6):29-39

SMAP是美国于2015年初发射的一颗卫星，搭载了L波段的雷达。它采用圆锥扫描方式，具有固定的入射角、较大的幅宽和千米级的分辨率，在海冰监测方面具有独特的优势。本文利用SMAP卫星雷达资料分别与德国Bremen大学海冰密集度产品和美国国家冰雪数据中心（NSIDC）海冰密集度产品建立3.125 km和25 km匹配数据集，分析了L波段雷达后向散射系数、极化比和归一化极化差与海冰密集度之间相关性，建立基于人工神经网络的海冰密集度反演算法。为了验证SMAP卫星雷达资料反演海冰密集度的精度，本文选择德国Bremen大学和美国冰雪数据中心发布的海冰密集度产品分别与SMAP海冰密集度产品进行对比分析，SMAP海冰密集度与Bremen海冰密集度的偏差为0.07、均方根误差为0.14；与NSIDC海冰密集度的偏差为0.04、均方根误差为0.18，这表明SMAP海冰密集度产品与现有业务化海冰密集度产品具有很好的一致性。  相似文献   

Estimation and prediction of plastic waste annual input into the sea from China   总被引：5，自引：0，他引：5  

BAI Mengyu  ZHU Lixin  AN Lihui  PENG Guyu  LI Daoji 《海洋学报(英文版)》2018,37(11):26-39

Marine plastic debris has been a pervasive issue since the last century, and research on its sources and fates plays a vital role in the establishment of mitigation measures. However, data on the quantity of plastic waste that enters the sea on a certain timescale remain largely unavailable in China. Here, we established a model using material flow analysis method based on life cycle assessment to follow plastic product from primary plastic to plastic waste with statistical data and monitoring data from accurate sources. This model can be used to estimate and forecast the annual input of plastic waste into the sea from China until 2020. In 2011, 0.547 3–0.751 5 million tons of plastic waste entered the seas in China, with a growth rate of 4.55% per year until 2017. And the amount will decrease to0.257 1 to 0.353 1 million tons in 2020 under the influence of governmental management. The amount of plastic waste discharged from coastal areas calculated in this study was much larger than that from river, thus it is suggested to strengthen the governance and control of plastic waste in coastal fishery activities in China in order to reduce the amount of marine plastic waste input.  相似文献   

灰色稳健总体最小二乘估计及高铁路基变形预测     

陈洋  文鸿雁  覃辉  王清涛  周吕 《大地测量与地球动力学》2018,38(2):140-146

最小二乘估计和部分变量误差模型的总体最小二乘估计不具备抵御粗差的能力。鉴于粗差可能同时出现在灰色白化微分方程的观测值和系数矩阵中，本文提出基于IGGⅢ抗差方案的部分变量总体最小二乘稳健估计。结合仿真数据和高铁路基观测数据，系统地比较稳健最小二乘、部分变量总体最小二乘、本文算法参数估计结果和算法稳定性。结果表明，本文算法预测精度高，可以应用到高铁路基沉降预测中。  相似文献   

近30 a甘肃省河东地区极端气温指数时空变化特征及趋势预测          下载免费PDF全文

黄浩  张勃  黄涛  王怀军  马尚谦  马彬  王晓丹  崔艳强 《干旱区地理》2020,43(2):319-328

基于甘肃省河东地区61个气象站点1988—2017年逐日气温数据，利用Mann-Kendall检验，Sen’s斜率估计方法分析甘肃省河东地区极端气温指数的时空变化趋势，并探讨极端气温指数与其影响因素之间的关系，最后利用NAR神经网络结合Hurst指数对甘肃省河东地区极端气温指数变化进行预测分析。结果表明：(1)从时间上看，冷极值相对指数呈下降趋势，冷极值绝对指数、暖极值以及气温日较差、作物生长期呈上升趋势。(2)从空间上看，对冷极值变化反应最为敏感的是高寒湿润区，对暖极值变化反应最为敏感的是温带半湿润区和北亚热带湿润区，除北亚热带湿润区外各区域作物生长期的变化都达到了显著水平，而气温日较差仅在温带半湿润区达到了显著水平。(3)多数极端气温指数与经纬度、海拔之间有显著相关性，但受区域自然特点影响，经度与海拔对其影响实为一类。(4)亚洲区极涡强度、北半球极涡强度以及青藏高原指数B与极端气温指数变化有密切关系，而太阳黑子等只与个别指数之间存在显著的相关性。(5)预测出的极端气温指数冷极值相对指数仍呈现下降趋势，冷极值的绝对指数、暖极值以及气温日较差、作物生长期仍然呈现增加趋势，但大多数指数与1988—2017年相比变化幅度有所降低。（6）与其他区域相比甘肃省河东地区大多数气温指数变化幅度处于中间水平，表现出其为多种不同气候区、自然区交界地带的特色。  相似文献   

A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes     

Yibin Ren  Huanfa Chen  Tao Cheng  Yang Zhang  Ge Chen 《International journal of geographical information science》2020,34(4):802-823

ABSTRACT

The spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns.  相似文献   

基于多变量LSTM神经网络的地下水水位预测     

闫佰忠  孙剑  王昕洲  韩娜  刘博 《吉林大学学报(地球科学版)》2020,50(1):208-216

为解决以往模型未考虑地下水位相关影响因素的问题，探讨长短期记忆（LSTM）神经网络在地下水位预测中的应用，利用长短期记忆神经网络，采用多变量输入的方式，构建了基于多变量LSTM神经网络的地下水水位预测模型。以泰安市岱岳区J1号监测井为例，采用2001-2014年地下水水位动态监测资料与相关影响因素数据，利用多变量LSTM神经网络对2015-2016年地下水位进行预测，并与单变量LSTM神经网络和反向传播（BP）神经网络进行对比。研究结果表明：以相关影响变量为输入的BP神经网络无法考虑时序变化规律，预测均方根误差最大，为2.399 3；以地下水位为变量输入的单变量LSTM神经网络仅能根据时序变化作出相应预测，无法考虑相关变量影响，预测均方根误差为2.102 2；基于多变量输入的LSTM神经网络的预测精度显著高于单变量LSTM神经网络和BP神经网络，预测均方根误差最小，仅为1.919 1。总体上，多变量LSTM神经网络地下水位预测模型仅在某些峰值处误差较大，但总体预测效果较为理想。  相似文献   

A location-aware GIServices quality prediction model via collaborative filtering     

Qingxi Peng  Na Dong 《International Journal of Digital Earth》2018,11(9):897-912

The quality of GIServices (QoGIS) is an important consideration for services sharing and interoperation. However, QoGIS is a complex concept and difficult to be evaluated reasonably. Most of the current studies have focused on static and non-scalable evaluation methods but have ignored location sensitivity subsequently resulting in the inaccurate QoGIS values. For intensive geodata and computation, GIServices are more sensitive to the location factor than general services. This paper proposes a location-aware GIServices quality prediction model via collaborative filtering (LAGCF). The model uses a mixed CF method based on time zone feature from the perspectives of both user and GIServices. Time zone is taken as the location factor and mapped into the prediction process. A time zone-adjusted Pearson correlation coefficient algorithm was designed to measure the similarity between the GIServices and the target, helping to identify highly similar GIServices. By adopting a coefficient of confidence in the final generation phase, the value of the QoGIS most similar to the target services will play a dominant role in the comprehensive result. Two series of experiments on large-scale QoGIS data were implemented to verify the effectivity of LAGCF. The results showed that LAGCF can improve the accuracy of QoGIS prediction significantly.  相似文献   

利用人工鱼群算法优化高斯过程模型及应用分析     

邱小梦  周世健  王奉伟  欧阳亮酉 《测绘通报》2018,(1):157-160,164

基于高斯过程利用传统共轭梯度法搜索超参数,存在对初始值依赖性强、获得局部最优解的不足。本文采用人工鱼群算法对超参数进行智能寻优,建立了基于人工鱼群算法的高斯过程模型对变形体形变进行预测分析。通过隧道和基坑两个工程实例计算比对分析,NN、SE和RQ 3种核函数中NN核函数的预测效果最好,平均相对误差分别为0.69%和1.06%。结果表明超参数优化模型的预测精度得到了较大的提高,改善了高斯过程算法本身存在的超参数求解方面的不足,效果明显。  相似文献   

Sub-seasonal Prediction of the South China Sea Summer Monsoon Onset in the NCEP Climate Forecast System Version 2     

Weiwei WANG  Song YANG  Tuantuan ZHANG  Qingquan LI  Wei WEI 《大气科学进展》2022,39(11):1969-1981

This study depicts the sub-seasonal prediction of the South China Sea summer monsoon onset (SCSSMO) and investigates the associated oceanic and atmospheric processes, utilizing the hindcasts of the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Typically, the SCSSMO is accompanied by an eastward retreat of the western North Pacific subtropical high (WNPSH), development of the cross-equatorial flow, and an increase in the east-west sea surface temperature (SST) gradient. These features are favorable for the onset of westerlies and strengthening of convection and precipitation over the South China Sea (SCS). A more vigorous SCSSMO process shows a higher predictability, and vice versa. The NCEP CFSv2 can successfully predict the onset date and evolution of the monsoon about 4 pentads (20 days) in advance (within 1–2 pentads) for more forceful (less vigorous) SCSSMO processes. On the other hand, the climatological SCSSMO that occurs around the 27th pentad can be accurately predicted in one pentad, and the predicted SCSSMO occurs 1–2 pentads earlier than the observed with a weaker intensity at longer leadtimes. Warm SST biases appear over the western equatorial Pacific preceding the SCSSMO. These biases induce a weaker-than-observed WNPSH as a Gill-type response, leading to weakened low-level easterlies over the SCS and hence an earlier and less vigorous SCSSMO. In addition, after the SCSSMO, remarkable warm biases over the eastern Indian Ocean and the SCS and cold biases over the WNP induce weaker-than-observed westerlies over the SCS, thus also contributing to the less vigorous SCSSMO.  相似文献   

Satellite estimates and subpixel variability of rainfall in a semi-arid grassland          下载免费PDF全文

Yong Chen  Jing Duan  Junling An  Huizhi Liu  Ulrich G?rsdorf  Franz H.Berger 《大气和海洋科学快报》2021,14(5):24-29

卫星估雨精度的不确定性受到当地降雨类型和像元内降雨非均匀性影响,而结合这两个关键因素开展半干旱草原卫星估雨的研究有限.2009年夏,我们在中国锡林郭勒半干旱草原用多部微雨雷达和雨量计构建了9 km卫星像元降雨观测网,观测了像元内降雨非均匀性(空间变异系数CV),并评估了卫星估雨精度.结果表明:(1)CV值受像元内平均降雨量,降雨类型,降雨云面积及移向等影响,如高Cv值的降雨过程大多为平均降雨量小,对流性降雨过程,降雨云边缘像元CV值较高;(2)TRMM 3B42V7卫星估雨产品适用性较好,CMORPH和PERSIANN次之,但TRMM 3B42V7易在半干旱草原湖泊处高估降雨.  相似文献