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Quantitative Assessment of Remotely Sensed Global Surface Models Using Various Land Classes Produced from Landsat Data in Istanbul

机译:利用伊斯坦布尔山顶数据生产的各种陆地课程的远程感测全球表面模型的定量评估

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摘要

Digital elevation model(DEM) is the most popular product for three-dimensional(3D) digital representation of bare Earth surface and can be produced by many techniques with different characteristics and ground sampling distances(GSD). Space-borne optical and synthetic aperture radar(SAR) imaging are two of the most preferred and modern techniques for DEM generation. Using them, global DEMs that cover almost entire Earth are produced with low cost and time saving processing. In this study, we aimed to assess the Satellite pour l'observation de la Terre-5(SPOT-5), High Resolution Stereoscopic(HRS), the Advanced Space-borne Thermal Emission and Reflection Radiometer(ASTER), and the Shuttle Radar Topography Mission(SRTM) C-band global DEMs, produced with space-borne optical and SAR imaging. For the assessment, a reference DEM derived from 1∶1000 scaled digital photogrammetric maps was used. The study is performed in 100 km2 study area in Istanbul including various land classes such as open land, forest, built-up land, scrub and rough terrain obtained from Landsat data. The analyses were realized considering three vertical accuracy types as fundamental, supplemental, and consolidated, defined by national digital elevation program(NDEP) of USA. The results showed that, vertical accuracy of SRTM C-band DEM is better than optical models in all three accuracy types despite having the largest grid spacing. The result of SPOT-5 HRS DEM is very close by SRTM and superior in comparison with ASTER models.

著录项

  • 来源
    《中国地理科学(英文版)》 |2014年第3期|307-316|共10页
  • 作者单位

    Department of Geomatics Engineering Davutpasa Campus Yildiz Technical University Istanbul 34210 Turkey;

    Department of Geomatics Engineering Bulent Ecevit University Zonguldak 67100 Turkey;

    Mescioglu Engineering Ankara 06810 Turkey;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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