A Rice Mapping Method Based on Time-Series Landsat Data for the Extraction of Growth Period Characteristics

Jing Liao, Yueming Hu, Hongliang Zhang, Luo Liu, Zhenhua Liu, Zhengxi Tan and Guangxing Wang
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Jing Liao: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Yueming Hu: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Hongliang Zhang: Guizhou Academy of Sciences, Guiyang 550001, China
Luo Liu: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Zhenhua Liu: College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Zhengxi Tan: ASRC Federal, U.S. Geological Survey Earth Resources Observation and Science (EROS), Sioux Falls, SD 57198, USA
Guangxing Wang: Department of Geography and Environmental Resources, College of Liberal Arts, Southern Illinois University Carbondale (SIUC), Carbondale, IL 62901, USA

Sustainability, 2018, vol. 10, issue 7, 1-19

Abstract: The rapid and accurate acquisition of rice cultivation information is very important for the management and assessment of rice agriculture and for research on food security, the use of agricultural water resources, and greenhouse gas emissions. Rice mapping methods based on phenology have been widely used but further studies are needed to clearly quantify the rice characteristics during the growth cycle. This paper selected the area where rice agriculture has undergone tremendous changes as the observation object. The rice areas were mapped in three time periods during the period from 1993 to 2016 by combining the characteristics of the harvested areas, flooded areas, and the time interval when harvesting and flooding occurred. An error matrix was used to determine the mapping accuracy. After exclusion of clouds and cloud shadows, the overall accuracy of the paddy fields was higher than 90% (90.5% and 93.5% in period 1 and period 3, respectively). Mixed pixels, image quality, and image acquisition time are important factors affecting the accuracy of rice mapping. The rapid economic development led to an adjustment of people’s diets and presumably this is the main reason why rice cultivation is no longer the main agricultural production activity in the study area.

Keywords: rice mapping method; time-series Landsat data; combined classifier; characteristics of growth period; rice agriculture assessment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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