In this study, the temperature vegetation dryness index (TVDI) which derived from NOAA/AVHRR data was
applied to monitor the severe drought in Sichuan Basin in the summer of 2006. The result using TVDI shown : the
drought developed rapidly in the last ten days of July, and became most severe at the end of August, then alleviated in
the first ten days of September. The change trends of TVDI with low rainfall and high air temperature were basically
consistent. The sensitivity of TVDI to air temperature and principle was also analyzed. TVDI had positive correlation
with temperature, negative correlation with precipitation. TVDI is an effective method for the monitoring of the regional
Information of crop phenological stages is essential for evaluating crop productivity and crop management. We used
MODIS EVI time-series to monitoring winter-wheat phenology in North China. The phenological estimations from
MODIS EVI measurements were compared with situ data. Results indicate that winter-wheat phenological stages
derived from MODIS EVI time series data is feasible. The spatial pattern of winter-wheat shows obvious latitudinal
trends in this region. Green up, tassel, and maturity onset dates in more southern zone begin earlier progressively than
the northern zone.
In the present study, a detailed analysis of AVHRR-based Vegetation Health Indices and meteorological data of
Huanghuai region has been carried out for the years 1981-2008. Detailed analyses of spatial and temporal drought
dynamics have been carried out. The results revealed that the low-grade of droughts are common phenomena in north
China's main agricultural area. Moreover, the area coverage of droughts in different seasons and different regions
displayed different trends. There is a decrease tendency for soil moisture in recent years.
In this paper, 30 years conventional data of China are processed, the anomaly of precipitation, land
surface temperature and air temperature are calculated and their relations are analyzed by using
regressive statistics analysis and Singular Value Decomposition (SVD). The result shows that
precipitation anomaly has a good negative correlation to both surface temperature anomaly and air
temperature anomaly. Moreover, 20 years satellite brightness temperature anomaly and the same period
precipitation anomaly are also calculated and analyzed; the similar result is obtained. It indicates that
brightness temperature anomaly is an important factor for drought monitoring by using remote sensing
data. Moreover, compared with historic data, the change of Normalized Difference Vegetation Index (NDVI)
is another factor for drought monitoring. Drought index is formed by these two factors normalization and
mean in weight. This remote sensing method on drought was used to some experiments and the results
show that the drought distribution on space is very similar, compared with conventional drought index.
Now this method is being used in operational system on drought monitoring in National Satellite
Meteorological Center (NSMC), China meteorology administration (CMA).