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


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


Object-Based Paddy Rice Mapping Using HJ-1A-B Data and Temporal Features Extracted from Time Series MODIS NDVI Data - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

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

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





Autor: Mrinal Singha 1,2, Bingfang Wu 2,* and Miao Zhang 2

Fuente: http://mdpi.com/



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