DocumentCode :
2227595
Title :
Using MODIS imagery to estimate the damage of rainfed rice in northeastern Thailand
Author :
Liou, Yuei-An ; Sha, Hsueh-chun
Author_Institution :
Center for Space & Remote Sensing Res., Nat. Central Univ., Jhongli, Taiwan
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6601
Lastpage :
6604
Abstract :
Northeastern Thailand is one of the representative rainfed lowland rice agriculture areas in Asia, where rice yield is limited due to unstable rainfall and poor soil. The area of rainfed lowland rice in northeast Thailand is approximately 5.27 million hectares, representing 57% of rice-growing area of the country. Heavy monsoon rainfall over central and northern Thailand began in July 2011 and lasted until October, causing a great impact on national agriculture. Huge tracts of farmland are submerged, threatening the annual rice crop. The objective of this paper is to assess the damage of regional rainfed rice after severe floods by using MODIS Surface Reflectance 8-Day L3 Global 250 m (MOD09Q1) and 500 m (MOD09A1). During the rice flooding period, Land Surface Water Index (LSWI) values are increased and even become higher than vegetation indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)). For this reason, the rice flooding period is a crucial indicator to identify the rice. The algorithm for mapping rice paddy uses time-series MODIS retrievals to identify the rice paddy in northeastern Thailand. The result indicates that the MODIS-derived rice evaluations are useful for obtaining spatial distribution maps of rice on a large-scale region.
Keywords :
agriculture; crops; floods; rain; time series; vegetation mapping; AD 2011 07 to 10; EVI; LSWI; MOD09A1; MOD09Q1; MODIS imagery; MODIS surface reflectance; NDVI; damage estimation; enhanced vegetation index; land surface water index; monsoon rainfall; normalized difference vegetation index; northeastern Thailand; rainfed lowland rice agriculture area; regional rainfed rice; rice paddy uses time series MODIS retrievals; rice yield; severe floods; Agriculture; Distribution functions; Floods; Graphical models; Indexes; MODIS; Remote sensing; MODIS images; Rainfed rice; Thailand; agriculture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352086
Filename :
6352086
Link To Document :
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