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植被分类的英文

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"植被分类"怎么读用"植被分类"造句

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  • vegetative breakdown

例句与用法

  • The classification of vegetation seems an eternal problem .
    植被分类好象一个永无答案、争论不休的问题。
  • This paper summarized the current status of vegetation classification based on rs technology at home and abroad , and pointed out the developing trend as follows : ( 1 ) from single - phase , single - source classification to fusion of multitemporal , multi - source data ; ( 2 ) from single classifier to hybird classifiers ; ( 3 ) from hard classification to soft classification ; ( 4 ) from pixel - based classification to pixel unmixing and object - oriented classification ; ( 5 ) from traditional classification to intelligent classification
    摘要综述了国内外基于遥感技术进行植被分类的研究现状,并提出植被分类的发展趋势: ( 1 )从单时相、单源遥感分类向多时相、多源信息融合发展; ( 2 )从单一分类方法向复合分类方法发展; ( 3 )从“硬”分类向“软”分类方向发展; ( 4 )从基于像元分类向混合像元分解分类和面向对象分类方向发展; ( 5 )从传统分类向智能分类方向发展。
  • This article mainly deals with the investigation of the pangquan gully , a ecotourism place , by ways of quantitative analysis and qualitative analysis in the ordination and classification evaluation of resources , planning and management perspectives , natural conservation region , with all kinds of configure of earth surface , lots of living resources , and obvious vertical changes of climate , vegetation and soil
    该保护区气候怡人,景色秀丽,是黄土高原上不可多得的“绿色明珠” ,也是一处旅游胜地。本文主要从旅游区植被分类、排序,旅游资源评价,旅游规划与管理这几个方面,对庞泉沟生态旅游进行研究。利用twinspan分类方法和dca排序方法,对庞泉沟主要旅游资源? ?植被群落进行数量研究。
  • And understanding and studying the spectral features and variation rules of geo - targets in the experimental area , raising that it is the basis of geo - targets information collection with imaging spectrometer data to understand spectral features and variation rules of geo - targets , realizing that in a great extent spectral - integrated - form - based classification method can remove the phenomenon of " different spectrum with same objects " resulted from reflection ratio curve translation because of the angle change among sensor , targets and observation direction , and the average and variance images can be introduced to solve the problem of two kinds of geo - target with similar spectral forms and much different values of whole reflection ratio . it is suggested that " red edge " range bands of vegetation , which has close relationship with vegetation cover and biomass , is the main characteristic bands and important basis for careful vegetation classification and quantitative retrieval , and pixel - based derivative spectral analysis is very useful for removing the effects of soil background values and quantitatively retrieving vegetation biomass and cover . the remote sense quantitative retrieval model is developed for main appraisable factors of desertification monitoring assessment with imaging spectrometer data and then the applicability of model is analyzed
    研究结果如下:首先针对荒漠化地区的地物特征,对高光谱数据不同波段的数据质量、波段组合进行了评价,提出了适用于荒漠化监测的基本波段选择集;初步了解和掌握了研究地区的地物光谱特性及变异规律,进一步明确了掌握地物光谱特征和变异规律是用成像光谱仪数据提取地物信息的基础;发现了基于光谱整体形状的分类方法在很大程度上能够消除由于传感器、地物目标观测方向之间的角度变化引起的反射率曲线整体平移的“同物异谱”现象,对于谱形相似而整体反射率的值相差较大的两类地物,通过引入均值和方差图像参与分类得到解决;研究还表明在植被“红边”范围内的波段是进行荒漠化监测的主要特征波段,这些波段与植被生物量和盖度都有密切的关系,是开展精细植被分类研究和植被定量反演的重要基础;像元的导数光谱分析可以消除土壤背景的影响,是进行植被生物量和盖度定量反演的有力工具;建立了荒漠化监测主要评价因子的定量反演模型,并分析了模型的适用性。
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