位置:成果数据库 > 期刊 > 期刊详情页
基于NDVI密度分割的冬小麦种植面积提取
  • ISSN号:1009-1041
  • 期刊名称:麦类作物学报
  • 时间:2014.7.15
  • 页码:997-1002
  • 分类:P[天文地球]
  • 作者机构:[1]Chuzhou Meteorological Bureau, Chuzhou 239000, China, [2]Institute of Agricultural Economy and Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China, [3]School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044,China
  • 相关基金:Supported by National Natural Science Foundation of China(41171336).
  • 相关项目:遥感信息与生长模型协同的小麦估产方法研究
中文摘要:

MODTRAN model was used for the atmospheric correction of one HJ-1B/CCD2 image, and the effect of atmospheric correction was evaluated from the changes of spectral characteristics of typical ground objects,the comparison with the MODIS surface refluctance product,and the effect on normalized differential vegetation index ( NDVI). The results show that atmospheric correction eliminated the increase effect in visible bands and the absorption in near-infrared band. Atmospheric correction results and the MODIS surface reflectance product with high accuracy were highly consistent in the reflectance of vegetation, water and residents, and the average error of vegetation was 12.8%.According to the comparison of changing characteristics of NDVI before and after atmospheric correction, it could be found that atmospheric correction had corrected NDVI of mixed pixels and made it more reasonable. NDVI of each kind of ground objects improved, among which NDVI of vegetation increased most greatly,which can help differentiate vegetation from other ground objects. In a word, MODTRAN model has a good effect on atmospheric correction of HJ/CCD images.

同期刊论文项目
同项目期刊论文
期刊信息
  • 《麦类作物学报》
  • 北大核心期刊(2011版)
  • 主管单位:中华人民共和国教育部
  • 主办单位:西北农林科技大学 中国作物学会 国家小麦工程技术研究中心
  • 主编:孙其信
  • 地址:陕西省杨凌邰城路3号《麦类作物学报》编辑部
  • 邮编:712100
  • 邮箱:mlzwxb@163.com
  • 电话:029-87082032
  • 国际标准刊号:ISSN:1009-1041
  • 国内统一刊号:ISSN:61-1359/S
  • 邮发代号:52-66
  • 获奖情况:
  • 从2003年起被收录为国家科技部“中国科技核心期刊”,2002年获第三届全国优秀农业期刊一等奖,1999年获陕西省科技期刊一等奖,1995年获陕西省优秀期刊二等奖
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,美国化学文摘(网络版),英国农业与生物科学研究中心文摘,波兰哥白尼索引,美国剑桥科学文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版)
  • 被引量:13981