留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data

YANG Fei Zhu Yunqiang Zhang Jiahua YAO Zuofang

YANG Fei Zhu Yunqiang Zhang Jiahua YAO Zuofang. Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. 中国地理科学, 2012, 22(1): 63-74.
引用本文: YANG Fei Zhu Yunqiang Zhang Jiahua YAO Zuofang. Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. 中国地理科学, 2012, 22(1): 63-74.
Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. Chinese Geographical Science, 2012, 22(1): 63-74.
Citation: Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. Chinese Geographical Science, 2012, 22(1): 63-74.

Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data

基金项目: 国家自然科学基金;中国博士后基金;全球变化国家重大研究计划

Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data

Funds: ;China Postdoctoral Science Foundation;Global Change Research National Key Research Project
计量
  • 文章访问数:  1258
  • HTML全文浏览量:  71
  • PDF下载量:  1170
  • 被引次数: 0
出版历程
  • 收稿日期:  2011-02-18
  • 修回日期:  2011-04-06
  • 刊出日期:  2012-01-03

Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data

    基金项目:  国家自然科学基金;中国博士后基金;全球变化国家重大研究计划

摘要: The fraction of photosynthetically active radiation (FPAR) is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and FPAR data over Northeast China, the correlations between corn-canopy FPAR and hyperspectral reflectance were analyzed, and the FPAR estimation performances using vegetation index (VI) and neural network (NN) methods with different two-band-combination hyperspectral reflectance were investigated. The results indicated that the corn-canopy FPAR retained almost a constant value in an entire day. The negative correlations between FPAR and visible and shortwave infrared reflectance (SWIR) bands are stronger than the positive correlations between FPAR and near-infrared band re-flectance (NIR). For the six VIs, the normalized difference vegetation index (NDVI) and simple ratio (SR) performed best for estimating corn FPAR (the maximum R2 of 0.8849 and 0.8852, respectively). However, the NN method esti-mated results (the maximum R2 is 0.9417) were obviously better than all of the VIs. For NN method, the two-band combinations showing the best corn FPAR estimation performances were from the NIR and visible bands; for VIs, however, they were from the SWIR and NIR bands. As for both the methods, the SWIR band performed exceptionally well for corn FPAR estimation. This may be attributable to the fact that the reflectance of the SWIR band were strongly controlled by leaf water content, which is a key component of corn photosynthesis and greatly affects the absorption of photosynthetically active radiation (APAR), and makes further impact on corn-canopy FPAR.

English Abstract

YANG Fei Zhu Yunqiang Zhang Jiahua YAO Zuofang. Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. 中国地理科学, 2012, 22(1): 63-74.
引用本文: YANG Fei Zhu Yunqiang Zhang Jiahua YAO Zuofang. Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. 中国地理科学, 2012, 22(1): 63-74.
Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. Chinese Geographical Science, 2012, 22(1): 63-74.
Citation: Estimating Fraction of Photosynthetically Active Radiation of Corn with Vegetation Indices and Neural Network from Hyperspectral Data[J]. Chinese Geographical Science, 2012, 22(1): 63-74.

目录

    /

    返回文章
    返回