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Sensors 2017, 17(1), 10; doi:10.3390/s17010010

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

1
University of Chinese Academy of Sciences, Beijing 100049, China
2
Division of Digital Agriculture, Institute of Remote Sensing and Digital Earth, Olympic Village Science Park, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Academic Editors: Huajun Tang, Wenbin Wu and Yun Shi
Received: 27 October 2016 / Revised: 13 December 2016 / Accepted: 19 December 2016 / Published: 22 December 2016
(This article belongs to the Special Issue Sensors and Smart Sensing of Agricultural Land Systems)
View Full-Text   |   Download PDF [12877 KB, uploaded 22 December 2016]   |  

Abstract

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. View Full-Text
Keywords: paddy rice mapping; object-based; fusion; classification, HJ-1A/B; temporal features; Assam paddy rice mapping; object-based; fusion; classification, HJ-1A/B; temporal features; Assam
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Singha, M.; Wu, B.; Zhang, M. Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data. Sensors 2017, 17, 10.

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