利用高光谱数据进行植被生化成分反演方法研究

高光谱数据包含着丰富光谱信息,能够定量地分析物质成分^[1]。由高光谱数据,可以运用多元逐步线性回归方法反演植被生化组分含量,从而达到监测植被生长状况的目的^[2]。本文具体介绍了多元逐步线性回归方法,及其在氮、木质素和纤维素含量估算中的应用。     

REVIEWS OF GEOGRAPHIC SOFTWARE

Reviews of geographic software in this article: DEMO-GRAPHICS: WORLD POPULATIONS AND PROJECTIONS. ESP GAUSS. CEMODEL S. Damus LIMDEP. William H. Greene MICROSTAT 4.1 OTIS PCIPS. (Personal Computer Image Processing System) . H.J. Meyers and R. Bernstein. REGRESSION ANALYSIS OF TIME SERIES (RATS) SPSS/PC+ URBAN DATA MANAGEMENT SOFTWARE (UDMS)     

Distribution and fluxes of metals in the St. Lawrence River from the outflow of Lake Ontario to Québec City

Six anchor stations in the St. Lawrence River from the outflow of Lake Ontario to Quebec City, were occupied for ca. 24 hours in June 1987 during low flow conditions. Samples of water and suspended particulate matter were separated by continuous-flow centrifugation, and were collected every two hours.During this sampling period, fluxes of dissolved forms of zinc, copper and nickel increased in Lac St. François and downstream relative to the sum of the fluxes for the two upstream stations at the outflow of Lake Ontario. Increases in the flux of dissolved zinc and copper were pronounced below Montreal and above Lac St. Pierre. For particulate forms of metals, all five metals show that there are significant inputs in the section of the St. Lawrence River between Lac St. François and the station just above the entrance to Lac St. Pierre.The average concentrations of dissolved cadmium, lead, zinc, copper and nickel ranged from 7–23 ng/l; 9–35 ng/l; 0.434–0.939 g/l; 0.15–0.89 g/l and 0.58–1.12 g/l respectively.Regression analysis of the dissolved and particulate metal concentrations suggests that the concentration of dissolved cadmium, lead, zinc and nickel can be predicted from the regression equation and the determination of particulate metal concentration. This prediction appears to be independent of the suspended particulate matter concentration which varies from ca. 1 to 10 mg/l from the outflow of Lake Ontario to Québec City.     

Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain)

In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline probability map. The primary variable in the doline development in this area is geomorphology, represented by the location of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient.     

Rain-induced debris and mudflow triggering factors assessment in the Santiago cordilleran foothills,Central Chile

Debris and mudflows are some of the main geological hazards in the mountain foothills of the Chilean capital city of Santiago. There, the risk of flows triggered in the basins of ravines that drain the range into the city increases with time due to the city growth. A multivariate statistical study based on the logistic regression method is presented. The model provides equations that allow the computation of combined meteorological triggering factors associated with a probability of rain-induced flow occurrence. Daily rainfall, accumulated rainfall and the snowfall level, traditionally considered as the relevant factors, are analysed for a 25-year period. The results show a strong relevance of the rainfall on the day of the flow event over the other factors. However, the relatively low probabilities returned for some real flow events suggest that the model does not capture all the significant variables and the problem is more complex than as it has been traditionally assumed, and further investigations are needed to develop predictive models of flow triggering.     

Defect properties of albite

Knowledge of the defect properties of Lunar and Mercurian minerals has recently become important, with the advent of models which attempt to explain the formation of the thin exosphere of these celestial bodies. Here, we have calculated the formation energies of sodium and oxygen vacancies in the mineral albite (NaAlSi₃O₈), as well as the Schottky defect energy for the removal of a Na₂O unit. We have employed both the supercell and Mott–Littleton approaches, using Kohn–Sham density functional theory and classical interatomic potential methods. As well as reporting the defect energies and structures, we comment upon the relative merits of the methods used.     

Prediction of local scour around circular piles under waves using a novel artificial intelligence approach

Abstract

The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.     

青岛港风暴潮经验统计预报

本文利用青岛港多年实测资料,分析了该港风暴潮概况。而后通过多元回归技术,求取了该港极值增减水的预报公式。经非独立和独立检验,结果令人满意。     

Practical implementation of Hilbert-Huang Transform algorithm

Hilbert-Huang Transform (HHT) is a newly developed powerful method for nonlinear and non-stationary time series analysis. The empirical mode decomposition is the key part of HHT, while its algorithm was protected by NASA as a US patent, which limits the wide application among the scientific community. Two approaches, mirror periodic and extrema extending methods, have been developed for handling the end effects of empirical mode decomposition. The implementation of the HHT is realized in detail to widen the application. The detailed comparison of the results from two methods with that from Huang et al. (1998, 1999), and the comparison between two methods are presented. Generally, both methods reproduce faithful results as those of Huang et al. For mirror periodic method (MPM), the data are extended once forever. Ideally, it is a way for handling the end effects of the HHT, especially for the signal that has symmetric waveform. The extrema extending method (EEM) behaves as good as MPM, and it is better t