Open AccessClimatological Averaging and Application of Optical Vegetation Index based on MODIS
Author(s) -
Jing Liang,
Hanyu Lu,
Song Wu,
Leiding Ding
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1288/1/012074
Subject(s) - normalized difference vegetation index , enhanced vegetation index , vegetation index , environmental science , vegetation (pathology) , remote sensing , pixel , snow , climatology , inversion (geology) , data set , physical geography , climate change , meteorology , geography , geology , mathematics , statistics , computer science , medicine , oceanography , pathology , paleontology , structural basin , computer vision
In view of the problem that the inversion of soil moisture is greatly affected by vegetation coverage, this paper uses MODIS vegetation products. By eliminating the data of cloud, rain, snow and other quality damage data, the global climate mean data set is compensated by the linear interpolation method after the data average processing. The results showed that NDVI vegetation index changed regularly with seasons, and the change rule was different in different regions. The single pixel interior can accurately reflect the variation trend of the vegetation index of different pixel NDVI in one year. It can describe the seasonal variation of vegetation in the global pixel, reflect the change of green degree, and meet the need to correct the accuracy of vegetation influence.