Publications

Zhao, JL; Xu, C; Huang, LS; Zhang, DY; Liang, D (2016). Characterisation of spatial patterns of regional paddy rice with time series remotely sensed data. PADDY AND WATER ENVIRONMENT, 14(4), 439-449.

Abstract
Remote sensing has facilitated the identification of acreage and spatial distribution of field crops with obvious seasonal dynamics. The primary objective of this study is to identify the spatial patterns of double-season early rice, single-season middle rice and double-season late rice of Hunan Province and Yuanjiang City, China, in 2010, using two kinds of time series remotely sensed imagery: 8-day composite MODIS surface reflectance product data (MOD09A1) and HJ-1A/B satellite images with a 4-day revisit period. The available MODIS and HJ-1 CCD images of transplanting and heading stages were first assured in accordance with the schedules of local traditional paddy fields tillage. Based on the MOD09A1 data product, time series normalised difference vegetation index (NDVI) images were calculated and smoothed to remove the noise and the atmospheric effects. Second, the spatial distribution and planting acreage of three types of rice of Hunan Province were derived from combining the enhanced vegetation index and land surface water index according to the water background and variation characteristics of NDVI values at transplanting and heading stages. Conversely, a two-test procedure was used to finish the identification of paddy rice in Yuanjiang City using time series HJ-CCD imagery. The first test was to derive the potential rice pixels using the NDVI image (a dagger NDVI) between heading and transplanting stages, and the second test was to remove the non-rice pixels using maximum likelihood supervised classification. The experimental results showed that three types of rice were mainly distributed along the Dongting Lake Basin in Hunan Province and the relative errors were -10.99, 1.46 and -5.87 %, respectively, while they were primarily planted in the northern plains of Dongting Lake in Yuanjiang City, where the relative errors were 12.1, 16.7 and 0.8 %, respectively. We conclude that transplanting and heading stages are the best phenological combinations for identifying paddy rice through remote sensing time series analysis, and this study can provide a basis for evaluating paddy rice yield on a large scale .

DOI:
10.1007/s10333-015-0513-z

ISSN:
1611-2490