From pollen percentage to vegetation cover: evaluation of the Landscape Reconstruction Algorithm in western Norway   总被引：1，自引：0，他引：1       下载免费PDF全文

KARI LOE HJELLE  INGVILD KRISTINE MEHL  SHINYA SUGITA  GIDSKE LEKNÆS ANDERSEN 《第四纪科学杂志》2015,30(4):312-324

The Landscape Reconstruction Algorithm (LRA) with the two models REVEALS and LOVE is developed to transform pollen percentage data to vegetation cover. This paper presents the first study to evaluate LRA in a region with large topographic variations within a short distances. The REVEALS model estimates regional vegetation abundance based on pollen assemblages from large lakes (100–500 ha). Pollen surface samples from one large and 28 small lakes are used together with a combination of regionally derived pollen productivity estimates and available estimates from other regions of Europe. The results show a good relationship between REVEALS‐estimated forest cover and vegetation abundance based on the CORINE land‐cover data. The REVEALS results using various sets of pollen assemblages from small lakes were comparable to those using one large lake. Local vegetation abundance using the LOVE model was estimated around 26 lakes. For common taxa, such as Pinus and Poaceae, the LOVE‐based estimates of plant abundance match well with the distance‐weighted plant abundances based on vegetation maps. Our results indicate that the LRA approach is effective for reconstruction of long‐term vegetation changes in western Norway and other regions with high topographic relief when no major gradients exist in the pollen data.  相似文献   

基于遗传算法-支持向量机模型在热带气旋强度预报中的应用   总被引：1，自引：0，他引：1  

顾锦荣  刘华强  刘向陪  吕庆平 《海洋预报》2011,28(3)

利用遗传算法对支持向量机(SVM)模型参数进行寻优,找到最优参数组合后代入SVM模型中,得到基于遗传算法的支持向量机模型(GA-SVM),利用此模型对热带气旋强度进行预报实验。该模型对热带气旋强度12 h、24 h和48 h的预报平均绝对误差分别为3.01 m/s、4.46 m/s和6.57 m/s;比最小二乘回归法的预报精度分别提高了12%、11%、14%。  相似文献   

Time-frequency decomposition of seismic signals via quantum swarm evolutionary matching pursuit     

Amir Semnani  Liang Wang  Mehdi Ostadhassan  Majid Nabi-Bidhendi  Babak Nadjar Araabi 《Geophysical Prospecting》2019,67(7):1701-1719

Matching pursuit belongs to the category of spectral decomposition approaches that use a pre-defined discrete wavelet dictionary in order to decompose a signal adaptively. Although disengaged from windowing issues, matching point demands high computational costs as extraction of all local structure of signal requires a large size dictionary. Thus in order to find the best match wavelet, it is required to search the whole space. To reduce the computational cost of greedy matching pursuit, two artificial intelligence methods, (1) quantum inspired evolutionary algorithm and (2) particle swarm optimization, are introduced for two successive steps: (a) initial estimation and (b) optimization of wavelet parameters. We call this algorithm quantum swarm evolutionary matching pursuit. Quantum swarm evolutionary matching pursuit starts with a small colony of population at which each individual, is potentially a transformed form of a time-frequency atom. To attain maximum pursuit of the potential candidate wavelets with the residual, the colony members are adjusted in an evolutionary way. In addition, the quantum computing concepts such as quantum bit, quantum gate, and superposition of states are introduced into the method. The algorithm parameters such as social and cognitive learning factors, population size and global migration period are optimized using seismic signals. In applying matching pursuit to geophysical data, typically complex trace attributes are used for initial estimation of wavelet parameters, however, in this study it was shown that using complex trace attributes are sensitive to noisy data and would have lower rate of convergence. The algorithm performance over noisy signals, using non-orthogonal dictionaries are investigated and compared with other methods such as orthogonal matching pursuit. The results illustrate that quantum swarm evolutionary matching pursuit has the least sensitivity to noise and higher rate of convergence. Finally, the algorithm is applied to both modelled seismograms and real data for detection of low frequency anomalies to validate the findings.  相似文献   

Regional evapotranspiration rate of oasis and surrounding desert     

Jihong Jia  Wenzhi Zhao  Shoubo Li 《水文研究》2013,27(24):3409-3414

The surface energy balance algorithm for land method was used in this study to calculate the evapotranspiration (ET) rate for the middle reaches of the Heihe River Basin, Gansu Province, China, to analyse ET distribution within the oasis and the surrounding desert and, especially, on the edge zone of the oasis. Five profile graphs were created vertical to the river. Because of the inverse humidity phenomenon, the least amount of evapotranspiration occurred on the desert close to the oasis. The average evapotranspiration rate was roughly proportioned from the edge of the oasis to inside and outside its boundary. Two meteorological ground stations located close to the oasis edge showed a notable difference in net radiation flux that led to the difference found in ET. The primary reason for the significant differences observed in net radiation may be largely the result of differences in flux reflectivity and surface temperature. Meteorological data show that water supply also played an important role. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

探讨利用SCIAMACHY数据反演温室气体二氧化碳   总被引：1，自引：0，他引：1  

廖秀英  孙九林  吕宁  王卷乐  程辉 《地球物理学进展》2012,27(3):837-845

自工业革命以来CO2已经成为引起全球气候变暖的一种最主要的人为温室气体,由此引起的全球气候变化是当今社会经济可持续发展面临的最严峻挑战之一.为了更好的研究二氧化碳在时间与空间尺度上的格局及变化,综合分析CO2与太阳辐射、地面反照率、气溶胶等要素之间的关系,本文回顾了以往利用新型卫星传感器获取多源遥感数据的特点,分析了多种反演计算方法的优缺点,并结合地面实测数据进行对比分析的方法与理论,全面阐述国际上有关CO2柱浓度反演的思想.作者认为目前在地面观测站较少的情况下,针对先进的SCIAMACHY传感器数据利用DOAS相关算法及BESD算法进行CO2柱体浓度反演的数据连续,技术成熟,并由此提出了下一步工作中应解决的3个问题.  相似文献   

无控制DEM表面差异探测研究   总被引：1，自引：1，他引：0  

张同刚  岑敏仪  吴兴华 《测绘科学》2006,31(3):36-38

本文提出了一个新的无控制DEM差异探测算法。它可以将不同时期获取的DEM纳入到统一坐标系中,这样就可以根据匹配后的DEM来定量探测地表变化情况。该方法通过差分模型考虑了观测量的数值及其相互关系。与目前差异探测能力最强的LMS-LZD方法相比,新方法具有更好的差异能力和更高的匹配精度。普歪沟泥石流沟多时相DEM差异探测实例验证了新方法的优越性。  相似文献   

基于模糊神经网络(FNN)的赤潮预警预测研究   总被引：1，自引：0，他引：1  

张容  阎红  杜丽萍 《海洋通报(英文版)》2006,8(1):83-91

为研究各种理化因子与赤潮藻类浓度间的非线性对应规律和有效预测赤潮藻类浓度,构建了基于BP 算法的一个四层模糊神经网络模型。将模糊神经网络(FNN)技术引入赤潮预测研究,并与普通 BP 网络、RBF 网络的结果作比较,结果表明,该模型能够较好地反演出各种理化因子与夜光藻密度的非线性对应变化规律,有更好的预测功能。  相似文献   

气溶胶光学厚度的时空变化   总被引：2，自引：0，他引：2  

高飞  李铜基 《海洋技术学报》2003,22(3):15-19

在大气中气溶胶微粒是一种重要的大气微量成分。气溶胶光学厚度也是大气校正所需的重要大气参数，同时也是海洋水色卫星主要的数据产品。由于气溶胶光学厚度的时空变化较大，所以如何准确获取大气校正和卫星数据产品真实性检验所需的气溶胶光学厚度则是至关重要的。在简述气溶胶光学性质的基础上，并结合2002年6月HY—1南海实验数据来阐述现场气溶胶光学厚度的准确获取。  相似文献   

Reconstruction of sea surface dimethylsulfide in the North Pacific during 1970s to 2000s     

Y.W. Watanabe  H. Yoshinari  A. Sakamoto  Y. Nakano  N. Kasamatsu  T. Midorikawa  T. Ono 《Marine Chemistry》2007,103(3-4):347-358

We proposed an empirical equation of sea surface dimethylsulfide (DMS, nM) using sea surface temperature (SST, K), sea surface nitrate (SSN, μM) and latitude (L, °N) to reconstruct the sea surface flux of DMS over the North Pacific between 25°N and 55°N: ln DMS = 0.06346 · SST − 0.1210 · SSN − 14.11 · cos(L) − 6.278 (R² = 0.63, p < 0.0001). Applying our algorithm to climatological hydrographic data in the North Pacific, we reconstructed the climatological distributions of DMS and its flux between 25 °N and 55 °N. DMS generally increased eastward and northward, and DMS in the northeastern region became to 2–5 times as large as that in the southwestern region. DMS in the later half of the year was 2–4 times as large as that in the first half of the year. Moreover, applying our algorithm to hydrographic time series datasets in the western North Pacific from 1971 to 2000, we found that DMS in the last three decades has shown linear increasing trends of 0.03 ± 0.01 nM year^− 1 in the subpolar region, and 0.01 ± 0.001 nM year^− 1 in the subtropical region, indicating that the annual flux of DMS from sea to air has increased by 1.9–4.8 μmol m^− 2 year^− 1. The linear increase was consistent with the annual rate of increase of 1% of the climatological averaged flux in the western North Pacific in the last three decades.  相似文献   

Geoacoustic Inversion via Genetic Algorithm and Its Application to Manganese Sediment Identification     

Woojae Seong  Cheolsoo Park 《Marine Georesources & Geotechnology》2001,19(1):37-50

An acoustic inversion method using a wide-band signal and two near field receivers is proposed and applied to multiple layered seabed models including a manganese sediment. The inversion problem can be formulated into a probabilistic model comprised of signals, a forward model, and additive noise. The forward model simulates wide-band signals, such as chirp signals, and is chosen to be the source-waveletconvolution plane wave modeling method. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the possible numerical ranges for a priori uniform distribution is based. The genetic algorithm is applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L 2 norm of the difference between measured and modeled signals. Not only the marginal pdf but also its statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm.  相似文献