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The high temperature damage index series of 25 stations were calculated from 1960 to 2007, and these series were consisted of a matrix. After doing EOF to the matrix, two meaningful eigenvector fields were got, and therefore two main patterns about the spatial distribution of the high temperature damage to Rice in Jiangsu were found: the whole distribution pattern and the south-north distribution...
The paper discussed the change process of cultivated land and spatial difference in Qingdao city nearly 60 years according to the statistical data. By means of the social economic statistical software - SPSS18.0, the paper studied the driving forces on the cultivated land changes of Qingdao using Principal Component Analysis (PCA). The results indicated that the change of cultivated land was influenced...
It was very difficult to acquire satisfy classification result only using spectral information and textual information on the broad land of China. This paper divided the land cover regions based on multivariate data to improve classification accuracy which were Pa, BT, DEM, AVHRR NDVI time-series data and IM. Through principal components analysis, the information percent of first three principal components...
Focus on major eco-environment problems in Dongjiangyuan area, the paper selected twelve evaluation indexes (including terrain, climate, soil, vegetation index, land use type, socio-economic data) were set up based on RS and GIS technology. Using 100 m×100 m real area as basic unit, the spatial principal components analysis method is apply to calculate the eco-environment synthesis exponent according...
In order that researches the influence of driver factors on driving reliability under raining environment, this paper utilizes method of Principal Component Analysis to obtain representative indexes in five main driver parameters of sight, perception reaction capacity, perceptive capacity of environment, concentrating degree of attention and impatient emotion, therefore illuminates important influence...
Based on the analysis of driving forces of urban land expansion by Principal component analysis (PCA), this paper established a predicting model of urban built-up area for future by using socio-economical data. Being good at the performance of nonlinear approximation, artificial neural network (ANN), especially the back propagation algorithm (BP), is applied in the prediction of bulit-up land and...
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