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Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

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Title Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data
 
Creator Zhang, Geli
 
Contributor Xiao, Xiangming
Dong, Jinwei
Kou, Weili
Jin, Cui
Qin, Yuanwei
Zhou, Yuting
Wang, Jie
Menarguez, Michael Angelo
Biradar, Chandrashekhar
 
Subject paddy rice fields
modis images
land surface water index (lswi)
enhanced vegetation index (evi)
land surface temperature (lst)
northeastern china
 
Description management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture
has expanded rapidly in northeastern China in the last decade, but there are no updated maps of
paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the
unique physical features of paddy rice during the flooding and transplanting phases and use vegetation
indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding
phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature
(LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine
the temporal window of flooding and rice transplantation over a year to improve the existing
phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies,
and sparse vegetation) with potential influences on paddy rice identification were removed (masked out)
due to their different temporal profiles. The accuracy assessment using high-resolution images showed
that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer
and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable
accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area
and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and
optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice
fields in temperate and cold temperate zones, the northern frontier of rice planting.
2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier
 
Date 2015-08-31
2016-05-12T07:58:33Z
2016-05-12T07:58:33Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/dspace/limited
http://www.sciencedirect.com/science/article/pii/S0924271615001483
Geli Zhang, Xiangming Xiao, Jinwei Dong, Weili Kou, Cui Jin, Yuanwei Qin, Yuting Zhou, Jie Wang, Michael Angelo Menarguez, Chandrashekhar Biradar. (31/8/2015). Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data. ISPRS Journal of Photogrammetry and Remote Sensing, 106, pp. 157-171.
https://hdl.handle.net/20.500.11766/4775
Limited access
 
Language en
 
Format PDF
 
Publisher Elsevier
 
Source ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING;106,(2015) Pagination 157-171