Using temporal MODIS data to detect paddy rice in Red River Delta
Information on the area and spatial distribution ofpaddy 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 calcul...
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oai:112.137.131.14:VNU_123-565732018-08-29T08:25:11Z Using temporal MODIS data to detect paddy rice in Red River Delta Doan, Ha Phong Remote Sensing Paddy rice NDVI LSWI Red River Delta Information on the area and spatial distribution ofpaddy 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 correlativeto 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. 2017-08-11T08:14:12Z 2017-08-11T08:14:12Z 2012 Article Doan, H. P. (2012). Using temporal MODIS data to detect paddy rice in Red River Delta. VNU Journal of Science, Earth Sciences 28 (2012) 100-105 0866-8612 http://repository.vnu.edu.vn/handle/VNU_123/56573 en VNU Journal of Science, Earth Sciences application/pdf ĐHQGHN |
| institution |
Vietnam National University, Hanoi |
| building |
VNU Library & Information Center |
| country |
Vietnam |
| collection |
VNU Digital Repository |
| language |
English |
| topic |
Remote Sensing Paddy rice NDVI LSWI Red River Delta |
| spellingShingle |
Remote Sensing Paddy rice NDVI LSWI Red River Delta Doan, Ha Phong Using temporal MODIS data to detect paddy rice in Red River Delta |
| description |
Information on the area and spatial distribution ofpaddy 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 correlativeto 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. |
| format |
Article |
| author |
Doan, Ha Phong |
| author_facet |
Doan, Ha Phong |
| author_sort |
Doan, Ha Phong |
| title |
Using temporal MODIS data to detect paddy rice in Red River Delta |
| title_short |
Using temporal MODIS data to detect paddy rice in Red River Delta |
| title_full |
Using temporal MODIS data to detect paddy rice in Red River Delta |
| title_fullStr |
Using temporal MODIS data to detect paddy rice in Red River Delta |
| title_full_unstemmed |
Using temporal MODIS data to detect paddy rice in Red River Delta |
| title_sort |
using temporal modis data to detect paddy rice in red river delta |
| publisher |
ĐHQGHN |
| publishDate |
2017 |
| url |
http://repository.vnu.edu.vn/handle/VNU_123/56573 |
| _version_ |
1680966099582058496 |