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January 28, 2015Remote Sensing of Environment396 citationsOpen Access

Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms

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JDJinwei DongDalian Institute of Chemical PhysicsXXXiangming XiaoUnited NationsWKWeili KouSouthwest Forestry University

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Abstract

Agricultural land use change substantially affects climate, water, ecosystems, biodiversity, and human welfare. In recent decades, due to increasing population and food demand and the backdrop of global warming, croplands have been expanding into higher latitude regions. One such hotspot is paddy rice expansion in northeast China. However, there are no maps available for documenting the spatial and temporal patterns of continuous paddy rice expansion. In this study, we developed an automated, Landsat-based paddy rice mapping (Landsat-RICE) system that uses time series Landsat images and a phenology-based algorithm based on the unique spectral characteristics of paddy rice during the flooding/transplanting phase. As a pilot study, we analyzed all the available Landsat images from 1986 to 2010 (498 scenes) in one tile (path/row 113/27) of northeast China, which tracked paddy rice expansion in epochs with five-year increments (1986-1990, 1991-1995, 1996-2000, 2001-2005, and 2006-2010). Several maps of land cover types (barren land and built-up land; evergreen, deciduous and sparse vegetation types; and water-related land cover types such as permanent water body, mixed pixels of water and vegetation, spring flooded wetlands and summer flooded land) were generated as masks. Air temperature was used to define phenology timing and crop calendar, which were then used to select Landsat images in the phenology-based algorithms for paddy rice and masks. The resultant maps of paddy rice in the five epochs were evaluated using validation samples from multiple sources, and the overall accuracies and Kappa coefficients ranged from 84 to 95% and 0.6-0.9, respectively. The paddy rice area in the study area substantially increased from 1986 to 2010, particularly after the 1990s. This study demonstrates the potential of the Landsat-RICE system and time series Landsat images for tracking agricultural land use changes at 30-m resolution in the temperate zone with single crop cultivation. (C) 2015 Elsevier Inc. All rights reserved.

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Dong et al. (2015) studied this question.

synapsesocial.com/papers/6a011a13b124fe5819863855https://doi.org/10.1016/j.rse.2015.01.004
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