目视解译

  • 网络Visual interpretation
目视解译目视解译
  1. 通过对民勤盆地1959年航片,1973年MSS影像,1987、1994、1998和2001年TM影像的人机交互目视解译结合自动分类,制作了6个典型年代的绿洲分布图。

    The oasis distribution maps of six typical years were made using aerial photo in 1959 , MSS image in 1973 and TM images in 1987 , 1994 , 1998 , 2001 by combining visual interpretation and automatic classification method .

  2. 遥感图像目视解译值得注意的几个问题

    Several notable issues on visual interpretation of remote sensing image

  3. 为提高高分辨率遥感影像的分类精度,本文提出了一种GIS、RS与目视解译集成的分类技术。

    In order to improve the classifying precision of high-resolution image , this paper presented a specific kind of GIS & RS integration technology .

  4. 在对重庆市忠县区域TM遥感数据进行波谱信息特征实验分析的基础上,建立了土地覆被信息提取的渡段组合方案;通过人机交互目视解译和野外数据检验工作。

    Based on spectrum information analysis of TM images of Zhongxian County of Chongqing City , a band combined program about the extraction of land cover information was developed in this paper .

  5. 以TM影象为信息源,建立目视解译标志,对内蒙古东北部24旗(市)1986~1996年间土地资源开发利用变更进行了调查。

    By using TM satellite image , the changes on the exploration and utilization of the land resources in the 24 banners ( cities ) northeast Inner Mongolia during the last ten years ( 1986 ~ 1996 ) .

  6. 以2000年和2005年TM影像为信息源,在建立目视解译标志的基础上,利用GIS的图像、数据处理功能,对科尔沁沙地近5年来土地沙漠化动态变化进行监测。

    Visual interpretation remarks were established by taking TM images in 2000 and 2005 as information source . Then desertification dynamic in Horqin Sandy Land in recent five years is monitored with the help of images and data processing function of GIS .

  7. 通过对图像几何和投影系统转换,图像标准假彩色合成,影像空间增强处理,并结合划分的土地利用/覆被类型,建立TM影像目视解译标志,进行荒漠化信息的提取。

    Through geometrical and projection system transform , standard false color composite , spatial enhance to image , link with land use / cover type , establish interpret symbol of TM image , and to extract information of desertification .

  8. 利用NDVI计算机分类与目视解译结果相结合对影像进行分类处理后,提取了各年植被景观基础数据,通过计算获取各年份的景观格局指数,进行分析。

    Used computer classification based on the NDVI and visual interpretion results of image classification combined , after extraction of vegetation data . Calculate the landscape pattern index for each year , which is analyzed .

  9. 通过对福州市TM图像资料进行几何校正和不同的增强处理,以监督分类和非监督分类两种方法提取人工建筑物信息,并与目视解译相比较。

    The TM image material of Fuzhou city were emendated geometrically and enhanced differently , and the artificial building information was derived by supervised classification and unsupervised classification , at the same time , those information were compared with the result of translated by eyes .

  10. 对于IKONOS高分辨率融合影像,人机交互目视解译是一个最佳方法,森林四级类型的目视解译面积精度可达97.60%。

    As to the IKONOS image , the human-computer interaction interpretation is most effective , the area relative precision of which can be up to97.60 % .

  11. 取1990年、1995年、2000年和2005年4个时相覆盖广州市的TM遥感影像为数据源,经非监督分类及人工目视解译,获得研究区各时相土地覆被类型图。

    Four TM remote sensing images of Guangzhou in 1990 , 1995 , 2000 and 2005 were taken as data for the present study . The images fully covered the area of Guangzhou . The data sources of land-cover landscape were translated under manual and un-supervised interpretations with GIS software .

  12. 对不同分区进行非监督分类研究,根据地面状况确定非监督分类初次分类数、参考2004年目视解译结果确定自动分类重编码(Recode)方式,分类精度达到60~70%;

    · Unsupervised classification was explored in each subarea , and the feasible number of the first classification and the appropriate way of recoding were fixed while the precision can reach 60-70 % .

  13. 遥感图像目视解译土地信息之管见

    Express My Opinions on Land Information by Visual Image Interpretation

  14. 其中,传统的沙化信息提取技术包括监督与非监督分类法及目视解译法;

    The former incorporate supervision and non-supervision classification methods and visual interpretation methods ;

  15. 这种方法相对于传统的目视解译来说,其精度较高。

    Comparing with traditional visual interpretation , the precision of this method is higher .

  16. 卫星影象目视解译方法在湖区植被制图中的应用&以湖南洞庭湖区水域、洲滩植被图为例

    A method of satellite image visual interpretation used in vegetation mapping for lake regions

  17. 参照密度值进行目视解译估测一个县的森林分布及蓄积量方法的研究

    A research on estimating the area and stock of forests in a county with density value

  18. 根据实践经验指出了线性影像目视解译原则和线性影像统计方法;

    Visual interpretation criteria and statistic methods of the linear images are suggested according to practical experience .

  19. 四川盆西平原黄壤性水稻土卫片目视解译研究

    Visual interpretation of satellite image about paddy soil of yellow earth in West Plain of Sichuan Basin

  20. 实验结果证实融合图像的目标特征突出,易于目视解译。

    The experimental results show the fused image is of obvious feature , visibility and image interpretation .

  21. 借助地学知识,运用目视解译方法,对滩涂围垦区内的土地利用景观进行分类。

    Land use landscape within tideland reclamation area is classified by means of geographical knowledge and visual interpretation .

  22. 黄泛平原低产土壤卫星像片目视解译制图的试验研究

    An experimental study on low-yielding soil mapping in the Yellow River flood plain through visual interpretation of Landsat images

  23. 对监督分类结果进行人机交互目视解译纠正,得到精度较高的崇明岛东部海岸带的景观图,并可此基础上进一步进行各种景观特征的定量分析和景观变化研究。

    On this basis , the quantitative analysis of landscape features and research on landscape change could be done .

  24. 本文介绍用光学处理的ERTS&相片,目视解译地下水赋存的各种条件。

    This paper introduces the ERTS-photograph treated with optical process , interpreting the varied conditions for storing subterranean water .

  25. 由于早期的目视解译法在高分辨率遥感影像信息提取中应用虽广但费时费力,因而如何利用计算机技术快速、精确的提取泥石流具有实际应用价值。

    Since the early visual interpretation in the high-resolution remote sensing image information extraction is widely used but time-consuming .

  26. 能够用于系统的产状量测工作,为图像的目视解译提供了更多的信息。

    It can be used in systematic surveying attitudes so as to provide much information for naked interpretation of images .

  27. 一种辅助草原遥感影像目视解译方法的探讨&影像与基础图件半透明叠加法

    Discuss A Method of Assistant Remotely Sensed Imagery Visual Interpretation on Grassland & Remotely Sensed Image and Thematic Map Semitransparent Overlap

  28. 决策树分类方法的结果可比性强,但精度明显低于人机交互目视解译。

    The result of decision tree is high in comparability , but the precision is obviously lower than that of interactive interpretation .

  29. 因此,传统的基于空间形态的目视解译方法无法实现对这类目标的探测识别。

    Therefore , the traditional manual visual interpretation methods based on spatial form cannot achieve the detection of this kind of targets .

  30. 利用微机多因子自动分类和目视解译对比分析,定性分类精度达94%;

    In the comparison analysis between the multi-factor auto-classification on microcomputer and visual interpretation , both qualitative accuracy can reach to 94 percent .