Beijing 2008
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
981
jpping index
P
0.100
0.000
0.000
0.123
0.990
0.061
0.000
0.002
0.912
0.002
0.104
0.146
0.977
0.000
0.000
0.001
0.000
ice cropping
ing
5.95
8 10 12
e trends
I VCI> 2
change trend
5. CONCLUSION
Based on the understanding and definition of cropping index by
remote sensing data, this study developed a method for
extracting cropping index based on NDVI time-series. This
method could correct cloud and other contaminations
effectively. The most important part of this new method is
circular correcting of curve based on the definition of “one-
cropping”. By applying this new method to GIMMS NDVI data,
the cropping index of 17 provinces of northern China from
1982 to 2003 was extracted, and then the Cropping Index
Variation of every arable land pixel during these 22 years was
calculated by the Least Absolute Deviation linear regression
method. The high accordance between remotely sensed
cropping index data and statistical data suggests that this
method could provide an effective way to extract spatial
information of cropping index.
Northern China experienced a cropping index increase from
1982 to 2003, and VCI varies among different regions, with
Huang-Huai-Hai drainage area experiencing a clear cropping
index increase and other regions relatively less cropping index
change. These results imply that it is possible to improve the
food production of limited arable land by enhancing the
cropping index. This is of value for regions and countries where
food production suffers from arable land decrease along with
economic growth.
ACKNOWLEDGEMENTS
This work was supported by the Hi-tech Research and
Development Program of China (863 program) under Grant
2006AA12Z103.
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