Mapping paddy rice agriculture in southern China using multi-temporal MODIS images Xiangming Xiao a, T , Stephen Boles a , Jiyuan Liu b , Dafang Zhuang b , Steve Frolking a , Changsheng Li a , William Salas c , Berrien Moore III a a Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, NH 03824, USA b Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing 100001, China c Applied Geosolutions, LLC., Durham, NH 03824, USA Received 8 September 2004; received in revised form 21 December 2004; accepted 24 December 2004 Abstract Information on the area and spatial distribution of paddy rice fields is needed for trace gas emission estimates, management of water resources, and food security. Paddy rice fields are characterized by an initial period of flooding and transplanting, during which period open canopy (a mixture of surface water and rice crops) exists. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Terra satellite has visible, near infrared and shortwave infrared bands; and therefore, a number of vegetation indices can be calculated, including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) that is sensitive to leaf water and soil moisture. In this study, we developed a paddy rice mapping algorithm that uses time series of three vegetation indices (LSWI, EVI, and NDVI) derived from MODIS images to identify that initial period of flooding and transplanting in paddy rice fields, based on the sensitivity of LSWI to the increased surface moisture during the period of flooding and rice transplanting. We ran the algorithm to map paddy rice fields in 13 provinces of southern China, using the 8-day composite MODIS Surface Reflectance products (500-m spatial resolution) in 2002. The resultant MODIS-derived paddy rice map was evaluated, using the National Land Cover Dataset (1:100,000 scale) derived from analysis of Landsat ETM+ images in 1999/2000. There were reasonable agreements in area estimates of paddy rice fields between the MODIS-derived map and the Landsat-based dataset at the provincial and county levels. The results of this study indicated that the MODIS-based paddy rice mapping algorithm could potentially be applied at large spatial scales to monitor paddy rice agriculture on a timely and frequent basis. D 2005 Elsevier Inc. All rights reserved. Keywords: Paddy rice fields; MODIS images; Land surface water index; Enhanced vegetation index 1. Introduction Rice is one of the world’s major staple foods and paddy rice fields account for approximately 15% of the world’s arable land (IRRI, 1993). A unique physical feature of paddy fields is that the rice is grown on flooded soils. This feature is significant in terms of both trace gas emissions and water resources management. Seasonally flooded rice paddies are a significant source of methane emissions (Denier Van Der Gon, 2000; Li et al., 2002; Neue & Boonjawat, 1998), contributing over 10% of the total methane flux to the atmosphere (Prather & Ehhalt, 2001), which may have substantial impacts on atmospheric chemistry and climate. Agricultural water use (in the form of irrigation withdrawals) accounted for ~70% of global fresh water withdrawals (Samad et al., 1992), and the majority of Asian rice agriculture is irrigated (Huke, 1982; Huke & Huke, 1997). Intensification in rice farming practices in the near future could have significant impacts on the emissions of various greenhouse gases and 0034-4257/$ - see front matter D 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2004.12.009 T Corresponding author. E-mail address: xiangming.xiao@unh.edu (X. Xiao). Remote Sensing of Environment 95 (2005) 480 – 492 www.elsevier.com/locate/rse