再论青藏高原范围   总被引：5，自引：0，他引：5  

张镱锂  李炳元  刘林山  郑度 《地理研究》2021,40(6):1543-1553

伴随青藏高原研究的深入,高原内外多学科研究程度和认识的提高,及地理大数据、地球观测科学和技术的进步,对青藏高原范围提出了新的要求。本研究系统论述了确定青藏高原范围的原则、依据和方法,分析探讨了高原地貌宏观结构（高原面、高原内低盆地与高原边缘河谷低地等）和周围边界各自然地段构成的基本特征。采用ArcMap软件,通过遥感影像和DEM数据及新资料对高原地貌比较研究,实现了1：100万比例尺地图精度的青藏高原范围的界定。研究表明,青藏高原北起西昆仑山-祁连山山脉北麓,南抵喜马拉雅山等山脉南麓,南北最宽达1560 km;西自兴都库什山脉和帕米尔高原西缘,东抵横断山等山脉东缘,东西最长约3360 km;范围为25°59′30″N~40°1′0″N、67°40′37″E~104°40′57″E,总面积为308.34万km²,平均海拔约4320 m。在行政区域上,青藏高原分布于中国、印度、巴基斯坦、塔吉克斯坦、阿富汗、尼泊尔、不丹、缅甸、吉尔吉斯斯坦等9个国家。其中中国境内的青藏高原面积约258.09万km²（占高原总面积的83.7%）,平均海拔约4400 m,分布在西藏、青海、甘肃、四川、云南和新疆等6省区,西藏和青海两省区主体分布在高原范围内（约占高原总面积的60.6%）。  相似文献   

Spatial Differentiation Characteristics and Driving Forces of Forest Transition: A Case Study of Zunyi City,Guizhou     

DONG Shunzhou  ZHAO Yuluan  LI Xiubin 《资源与生态学报(英文版)》2018,9(4):341-351

Spatial differentiation in forest transition was measured in terms of space transition and function transition using the exploratory spatial data analysis method (ESDA) and data from 2004—2014 for Zunyi city, Guizhou province, China. The validity of factors affecting forest transition was analyzed by constructing radial basis function neural networks (RBFNN) based on the data processing system (DPS). Our results will provide references for scientific understanding of the potential mechanism underlying forest transition in mountainous areas. We found that Global Moran’s I of space transition and function transition of forest land was 0.0336 and 0.2323, respectively. This suggests a significant positive correlation in spatial distribution of space transition and function transition of forest land, and significant spatial aggregation. The Global Moran’s I of function transition was higher than that of space transition, and the spatial aggregation characteristics of function transition were more significant than for space transition. The Global Moran’s I at each time period tended to increase, and the spatial aggregation degree of the function transition and space transition was further enhanced. Hot and cold spots of space transition of forest land stably evolved, suggesting a minor spatial difference in forest land among different administrative units at the county level. The number of hot spots at the county level in function transition increased. Hot spots were intensively distributed at the western edge and continuously distributed in the northeast. The space transition and function transition of forest land were both greatly influenced by urbanization rate and second and third industries. The development of urbanization and industrialization was the main factor driving forest transition, suggesting a positive role of economic growth on forest transition in mountainous areas. The development of urbanization and industrialization is an effective approach to forest transition in mountainous areas.  相似文献   

A pan-sharpening method based on NSCT and formulated as compressive sensing problem     

Sarah Mazari  Miloud Chikr El Mezouar  Kamel Belloulata 《国际地球制图》2016,31(10):1142-1157

In this paper, a pan-sharpening method, using non-subsampled contourlet transform (NSCT) and the theory of compressive sensing (CS), is proposed. The NSCT is used for sparse image representation to perform a multiscale and directional decomposition of source images in order to express their detail and express the sparsity of their high frequency. The CS is used to merge the multispectral (MS) and panchromatic (pan) images from partial random measurements. Two different fusion rules are then applied. The final pan-sharpened image is obtained by inverse NSCT. Experimental results show the efficiency of the proposed method, compared with pan sharpening based on standard NSCT, in terms of visual quality and objective assessment. Moreover, the proposed technique is very effective when the storage and transmission bandwidth are limited.  相似文献   

基于神经网络模型的中国表层土壤有机质空间分布模拟方法   总被引：4，自引：0，他引：4  

李启权  王昌全  岳天祥  张文江  余勇 《地球科学进展》2012,27(2):175-184

基于全国第二次土壤普查得到的6 241个典型土壤剖面数据,采用主成分分析方法和径向基函数神经网络模型建立不同植被类型—土纲单元内土壤有机质与气候、地形和植被等环境因子间的非线性关系,模拟全国表层土壤有机质的空间分析格局。结果表明,该模型具有较准确的预测能力,性能指数达到1.94。与普通克里格法、反比距离法和多元回归模型相比,神经网络模型对621个验证点模拟结果与实测值的相关系数为0.799,分别提高了0.265、0.181和0.120,平均绝对误差分别降低了4.25、4.43和2.34 g/kg,平均相对误差分别降低了30.16%、32.66%和5.93%,均方根误差则分别降低了8.61、8.24和6.24 g/kg;从模拟结果图来看,神经网络模型能够提供更多的细节信息。该方法为大尺度土壤性质空间分布模拟提供了有益的参考。  相似文献   

A nonlinear data‐driven model for synthetic generation of annual streamflows     

K. P. Sudheer  K. Srinivasan  T. R. Neelakantan  V. V. Srinivas 《水文研究》2008,22(12):1831-1845

A hybrid model that blends two non‐linear data‐driven models, i.e. an artificial neural network (ANN) and a moving block bootstrap (MBB), is proposed for modelling annual streamflows of rivers that exhibit complex dependence. In the proposed model, the annual streamflows are modelled initially using a radial basis function ANN model. The residuals extracted from the neural network model are resampled using the non‐parametric resampling technique MBB to obtain innovations, which are then added back to the ANN‐modelled flows to generate synthetic replicates. The model has been applied to three annual streamflow records with variable record length, selected from different geographic regions, namely Africa, USA and former USSR. The performance of the proposed ANN‐based non‐linear hybrid model has been compared with that of the linear parametric hybrid model. The results from the case studies indicate that the proposed ANN‐based hybrid model (ANNHM) is able to reproduce the skewness present in the streamflows better compared to the linear parametric‐based hybrid model (LPHM), owing to the effective capturing of the non‐linearities. Moreover, the ANNHM, being a completely data‐driven model, reproduces the features of the marginal distribution more closely than the LPHM, but offers less smoothing and no extrapolation value. It is observed that even though the preservation of the linear dependence structure by the ANNHM is inferior to the LPHM, the effective blending of the two non‐linear models helps the ANNHM to predict the drought and the storage characteristics efficiently. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

顾及稳定性检验的测量机器人变形监测系统开发     

毕增辉  匡翠林  戴吾蛟  吴学群 《测绘与空间地理信息》2021,44(4):208-211,214

随着近年来自动化变形监测的发展,测量机器人变形监测的优势越发凸显,但其数据处理目前多数采用极坐标法或交会法直接计算,而没有进行严密平差改正和已知点稳定性检验,其结果的可靠性有时难以得到保证。针对此问题,本文采用VC++.net语言开发了一个顾及基准点与工作基点稳定性检验的可靠、精确的自动化变形监测系统,并通过实验验证了该系统在应用中的优越性。  相似文献   

Rainfall‐runoff modelling using artificial neural networks: comparison of network types     

A. R. Senthil Kumar  K. P. Sudheer  S. K. Jain  P. K. Agarwal 《水文研究》2005,19(6):1277-1291

Growing interest in the use of artificial neural networks (ANNs) in rainfall‐runoff modelling has suggested certain issues that are still not addressed properly. One such concern is the use of network type, as theoretical studies on a multi‐layer perceptron (MLP) with a sigmoid transfer function enlightens certain limitations for its use. Alternatively, there is a strong belief in the general ANN user community that a radial basis function (RBF) network performs better than an MLP, as the former bases its nonlinearities on the training data set. This argument is not yet substantiated by applications in hydrology. This paper presents a comprehensive evaluation of the performance of MLP‐ and RBF‐type neural network models developed for rainfall‐runoff modelling of two Indian river basins. The performance of both the MLP and RBF network models were comprehensively evaluated in terms of their generalization properties, predicted hydrograph characteristics, and predictive uncertainty. The results of the study indicate that the choice of the network type certainly has an impact on the model prediction accuracy. The study suggests that both the networks have merits and limitations. For instance, the MLP requires a long trial‐and‐error procedure to fix the optimal number of hidden nodes, whereas for an RBF the structure of the network can be fixed using an appropriate training algorithm. However, a judgment on which is superior is not clearly possible from this study. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

An RBF‐based model with an information processor for forecasting hourly reservoir inflow during typhoons     

Gwo‐Fong Lin  Ming‐Chang Wu  Guo‐Rong Chen  Fei‐Yu Tsai 《水文研究》2009,23(25):3598-3609

Inflow forecasting is essential for decision making on reservoir operation during typhoons. In this paper, a radial basis function (RBF)‐based model with an information processor is proposed for more accurate forecasts of hourly reservoir inflow. Firstly, based on the multilayer perceptron neural (MLP) network, an information processor is developed to pre‐process the typhoon information (namely, typhoon characteristics and rainfall) and to produce forecasts of rainfall. The forecasted rainfall and the observed inflow are then used as input to the RBF‐based model, which is a nonlinear function approximator, to produce forecasts of hourly inflow. For parameter estimation of the RBF‐based model, the fully‐supervised learning algorithm is used. Actual applications of the proposed model are performed to yield 1‐ to 6‐h ahead forecasts of inflow. To assess the improvement due to the use of the typhoon information processor, models without the typhoon information processor are constructed and compared with the proposed model. The results show that the proposed model performs the best and is capable of providing improved forecasts of hourly inflow, especially for long lead‐time. In conclusion, the proposed model with a typhoon information processor can extract useful information from typhoon characteristics and rainfall, and consequently improve the forecasting performance. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

ON THE VERTICAL DISCRETIZATION OF ATMOSPHERIC MODELS—PART I:EXISTING PROBLEMS,DATA PROCESSING AND CHOICE OF VERTICAL COORDINATE AND BASIS FUNCTIONS          下载免费PDF全文

廖洞贤  朱艳秋 《Acta Meteorologica Sinica》1997,(2)

Discussions are carried out on the vertical discretization of current atmospheric models.It ispointed out that there exist problems in the integration of the hydrostatic equation and thecomputation of vertical advection,vertical diffusion and so on.Then some possible ways forsolving or alleviating them are suggested.Finally,the choice of vertical coordinate and basisfunctions is discussed.  相似文献   

基于径向基函数神经网络的混合像元分解   总被引：10，自引：1，他引：10  

张彦  邵美珍 《遥感学报》2002,6(4):285-288

遥感图像中普通存在着混合像元。对这部分像元进行分类（即混合像元分解）是遥感图像处理中的难点。基于主分量分析的混合像元分解 法是一种较为成熟的算法，但它存在着计算量大，适应性差等缺点。在深入研究混合像元分解原理的基础上，提出了用径向基函数神经网络拟合分解结果超平面，以实现混合像元分解的算法，实验结果证明：该算法的结果与基于主分量分析的混合像元分解算法结果相近（相关系数达到0．00），而计算量大大减少，具有较强的适应性。  相似文献