ArticleInternational journal of applied earth observation and geoinformation : ITC journal2016
Mapping paddy rice planting area in rice-wetland coexistent areas through analysis of Landsat 8 OLI and MODIS images.
Article in International journal of applied earth observation and geoinformation : ITC journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 141 citations in OpenAlex.
- Estimating Rice Cropping Area and Analyzing Land Use and Land Cover Changes in Jiangsu Province Using Multispectral Satellite Imagery.Plants (Basel, Switzerland) · 2026Article
- Research on the application of remote sensing image super-resolution reconstruction techniques in crop phenology extraction.Frontiers in plant science · 2025Article
- Building social resilience in North Korea can mitigate the impacts of climate change on food security.Nature food · 2022Article
- Environmental Controls on Multi-Scale Dynamics of Net Carbon Dioxide Exchange From an Alpine Peatland on the Eastern Qinghai-Tibet Plateau.Frontiers in plant science · 2021Article
- Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms.Sensors (Basel, Switzerland) · 2018Article
- A Review of Wetland Remote Sensing.Sensors (Basel, Switzerland) · 2017Review
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Authors and funding
9 authors at 3 institutions in 2 countries.
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Abstract
Accurate and up-to-date information on the spatial distribution of paddy rice fields is necessary for the studies of trace gas emissions, water source management, and food security. The phenology-based paddy rice mapping algorithm, which identifies the unique flooding stage of paddy rice, has been widely used. However, identification and mapping of paddy rice in rice-wetland coexistent areas is still a challenging task. In this study, we found that the flooding/transplanting periods of paddy rice and natural wetlands were different. The natural wetlands flood earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. We used this asynchronous flooding stage to extract the paddy rice planting area from the rice-wetland coexistent area. MODIS Land Surface Temperature (LST) data was used to derive the temperature-defined plant growing season. Landsat 8 OLI imagery was used to detect the flooding signal and then paddy rice was extracted using the difference in flooding stages between paddy rice and natural wetlands. The resultant paddy rice map was evaluated with in-situ ground-truth data and Google Earth images. The estimated overall accuracy and Kappa coefficient were 95% and 0.90, respectively. The spatial pattern of OLI-derived paddy rice map agrees well with the paddy rice layer from the National Land Cover Dataset from 2010 (NLCD-2010). The differences between Rice
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