期刊
REMOTE SENSING
卷 3, 期 8, 页码 1644-1662出版社
MDPI
DOI: 10.3390/rs3081644
关键词
spectral index; MODIS; Phenological Eyes Network; cloud noise; NDVI; EVI; EVI2; NDWI; NDII
类别
资金
- Japan Society for the Promotion of Science [08J1376]
- Ministry of Education, Culture, Sports, Science and Technology in Japan [19088012]
- JSPS-KOSEF-NSFC A3 Foresight Program
- Global Change Observation Mission (GCOM) of the Japan Aerospace Exploration Agency (JAXA) [102]
Cloud contamination is one of the severest problems for the time-series analysis of optical remote sensing data such as vegetation phenology detection. Sub-pixel clouds are especially difficult to identify and remove. It is important for accuracy improvement in various terrestrial remote sensing applications to clarify the influence of these residual clouds on spectral vegetation indices. This study investigated the noises caused by residual sub-pixel clouds on several frequently-used spectral indices (NDVI, EVI, EVI2, NDWI, and NDII) by using in situ spectral data and sky photographs at the satellite overpass time. We conducted in situ continuous observation at a Japanese deciduous forest for over a year and compared the MODIS spectral indices with the cloud-free in situ spectral indices. Our results revealed that residual sub-pixel clouds potentially contaminated about 40% of the MODIS data after cloud screening by the state flag of MOD09 product. These residual clouds significantly decreased NDVI values during the leaf growing season. However, such noises did not appear in the other indices. This result was thought to be caused by the different combination of wavelengths among spectral indices. Our results suggested that the noises by residual sub-pixel clouds can be reduced by using EVI, NDWI, or NDII in place of NDVI.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据