植被类型图

  • 网络vegetation type map
植被类型图植被类型图
  1. 运用3S技术和野外数据作出了植被类型图,并对该流域植被进行了分类,该流域共有7个植被型,14个植被亚型,31个群系,植被类型多样性丰富。

    There are 7 vegetation types , 14 vegetation subtypes , 31 formations . The diversity of vegetation is relatively rich .

  2. 收集和整理河北省鸡形目鸟类的分布资料,借助GIS的绘图功能,把解译的遥感影像数据数字化为植被类型图和地貌图;

    The geographical distribution of Galliformes in Hebei Province was analyzed by use of the correlative references of the distribution . The RS image was digitized to the vegetation map and the geomorphologic map utilizing the drawing function of GIS techniques .

  3. 最小值出现在11月,只占3-11月平均NPP值的2.58%。(4)通过三峡库区的植被类型图,得到不同植被类型对应的NPP值。

    The minimum NPP value for month appeared in November , shared 2.58 % of the average NPP from March to November . ( 4 ) Got the NPP that respectively corresponding to the different types of vegetation by mask processing the mean NPP .

  4. 草场植被类型图测制方法的实践

    Practice on the surveying and mapping method for the type of vegetation map of grass land

  5. 最后对图像进行成图编辑,得到了盐渍化区域盐生植被类型的分布图。

    Finally , the distribution map of regional salinity vegetation types is achieved after category image is edited .

  6. 本文在利用MSS卫片影像编制贵州植被类型和乌江流域植被类型图的基础上,就贵州岩溶植被类型的卫片影像特征、解译方法及分布作一些初步探讨。

    The paper discusses preliminarily the features and interpretation method of satellite photographic image and distribution of karst vegetation in Guizhou , based on the maps of vegetation types of Guizhou and Wujiang river valley , compiled from satellite MSS image .

  7. 本文采用辅以纹理特征的神经网络分类法提高了盐生植被的分类精度,提取的盐渍化区域植被类型分布图能够为当地合理开发利用盐渍土资源提供科学依据。

    The distribution map of regional salinity vegetation types which is obtained based on BP neural network with texture feature extraction provides the scientific basis for reasonable development and utilization of local saline soil resources .