写真測量とリモートセンシング
Online ISSN : 1883-9061
Print ISSN : 0285-5844
ISSN-L : 0285-5844
植物フェノロジー観測における時系列NDVIデータの雑音除去手法
大吉 慶竹内 渉安岡 善文
著者情報
ジャーナル フリー

2008 年 47 巻 1 号 p. 4-16

詳細
抄録

Vegetation phenology is closely related to seasonal dynamics of the lower atmosphere, and important elements in global models and vegetation monitoring. Time-series NDVI data based on imagery from AVHRR or MODIS are suitable for phenological monitoring, because these sensors provide data with a high temporal frequency. In order to reduce noises caused by cloud contamination or atmospheric variability, Maximum Value Composite (MVC) is applied to the data. However, composite data have undesirable noises due to remained cloud contamination and inequality of observation intervals. Though MVC technique is applied, these noises disturb phenological monitoring. This paper proposed new noise reduction algorithm which integrates Best Index Slope Extraction (BISE) and Maximum Value Interpolated (MVI) algorithms. Integrated algorithm was applied to timeseries NDVI data consists of NOAA AVHRR composite images. This algorithm worked well in areas dominated by vegetation such as cropland including double cropping area, deciduous broadleaf forest and evergreen needleleaf forest. We confirmed that the algorithm reduced effects of cloud contamination, and equalized each observation interval. Therefore, applying developed algorithm to time-series NDVI data allows us to phenological monitoring more precisely.

著者関連情報
© 社団法人 日本写真測量学会
前の記事 次の記事
feedback
Top