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Please use this identifier to cite or link to this item: http://192.168.1.231:8080/dulieusoDIGITAL_123456789/5096
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dc.contributor.authorDoan Ha Phong-
dc.date.accessioned2020-06-25T05:43:49Z-
dc.date.available2020-06-25T05:43:49Z-
dc.date.issued2020-
dc.identifier.urihttp://192.168.1.231:8080/dulieusoDIGITAL_123456789/5096-
dc.description.abstractInformation on the area and spatial distribution of paddy rice fields is needed for food security, management of water resources, and estimation of Methan emission as well. MODIS remote sensing data including visible bands, near infrared band and short wave infrared band is foundation of calculating vegetation indices such as NDVI, EVI and LSWI. These remote sensing indices are very sensitive and strongly correlative to physiological status of plant, they are useful means for detecting and mapping paddy rice. This paper focus on an algorithm that uses time series of these vegetation indices to identify paddy rice areas based on sensivity of LSWI to the increased surface moisture during the period of flooding and rice transplanting.en_US
dc.publisherĐại học Quốc gia Hà Nộien_US
dc.titleUsing temporal MODIS data to detect paddy rice in Red River Deltaen_US
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