Mapping rice planting areas in southern China using the China Environment Satellite data

The objective of this research is to investigate the potential of application of China Environment Satellite HJ-1A/B in monitoring rice cultivation areas in Guangdong province in southern China. Information on the rice cultivation areas is of global economic and environmental significance. A CCD camera sensor with 30 m spatial resolution onboard China Environment Satellite HJ-1A and B has visible and near infrared bands and a revisit period of four days; the temporal Normalized Difference Vegetation Index (NDVI) can therefore be obtained from HJ-1A and B data. The characteristics of the temporal NDVI derived from HJ-1A and B images of rice fields and other crops at rice growth stages in the western part of Guangdong province of China with an area of about 67000 km^2 were first analyzed in this research and an algorithm for mapping paddy rice fields was developed based on the temporal changes of NDVI of rice fields from January to July, 2009. The mapping result was evaluated by field survey and the data from China Ministry of Agriculture and the promising accuracy was found with a Kappa factor of 0.71. The result of this study suggests that the China Environment Satellite HJ-1A/B has great potential in the development of an operational system for monitoring rice crop growth in southern China.

[1]  Hongling Fang,et al.  Rice crop area estimation of an administrative division in China using remote sensing data , 1998 .

[2]  Changsheng Li,et al.  Mapping paddy rice agriculture in southern China using multi-temporal MODIS images , 2005 .

[3]  R. Myneni,et al.  The interpretation of spectral vegetation indexes , 1995 .

[4]  Hui Lin,et al.  Application of ENVISAT ASAR Data in Mapping Rice Crop Growth in Southern China , 2007, IEEE Geoscience and Remote Sensing Letters.

[5]  V. Wuwongse,et al.  Discrimination of irrigated and rainfed rice in a tropical agricultural system using SPOT VEGETATION NDVI and rainfall data , 2005 .

[6]  Dominique Bachelet,et al.  Rice paddy inventory in a few provinces of China using AVHRR data , 1995 .

[7]  J. C. Price,et al.  Visible near-infrared radiation parameters for sugar-beets , 1996 .

[8]  Mutlu Ozdogan,et al.  A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental US , 2008 .

[9]  C. Woodcock,et al.  The status of agricultural lands in Egypt: The use of multitemporal NDVI features derived from landsat TM☆ , 1996 .

[10]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[11]  Hugo A. C. Denier van der Gon,et al.  Changes in CH4 emission from rice fields from 1960 to 1990s: 1. Impacts of modern rice technology , 2000 .

[12]  V. Murty,et al.  Estimation of cropped area and grain yield of rice using remote sensing data , 1992 .

[13]  K. Okamoto Estimation of rice-planted area in the tropical zone using a combination of optical and microwave satellite sensor data , 1999 .

[14]  Xiangming Xiao,et al.  Landscape-scale characterization of cropland in China using Vegetation and Landsat TM images , 2002 .

[15]  Paul J. Crutzen,et al.  Global distribution of natural freshwater wetlands and rice paddies, their net primary productivity, seasonality and possible methane emissions , 1989 .

[16]  Changsheng Li,et al.  Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data , 2002 .

[17]  S. Liang,et al.  Calculating environmental moisture for per-field discrimination of rice crops , 2003 .

[18]  M. Tamura,et al.  Estimation of leaf water status to monitor the risk of forest fires by using remotely sensed data , 2004 .

[19]  W. Dulaney,et al.  Normalized difference vegetation index measurements from the Advanced Very High Resolution Radiometer , 1991 .