Author : Nguyen Thanh Son

Summary : Information on surface soil moisture is important for water management, while information on rice growing areas is vital for crop management and production prediction. This study aims to investigate surface soil moisture variability in relation to rice cropping systems in the Mekong Delta (MD), Vietnam using the Moderate Resolution Imaging Spectroradiometer (MODIS) data. The surface soil moisture using estimated from the MODIS data acquired during January to April from 2002 to 2007 using the Temparature Vegetation Dryness Index (TVDI) method. This index was empirically calculated by parameterizing the relationship between the MODIS Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI) data. From the results of soil moisture estimation, it was found that the low soil moisture occurred in 2006 and occupied the largest region of the study area compared to other years. Therefore, this extreme year 2006 and a normal year, in this case 2002, were selected for analysis of soil moisture variability in relation to the distribution of rice cropping systems. The spatial distribution of rice cropping systems was obtained from classification of the time-series MODIS NDVI 250-m data acquired in 2002 and 2006. DAta were processed using the empirical mode decomposition (EMD) method for noise filtering of the time-series NDVI data. Soft and hard classification algorithms, namely linear mixture model (LMM) and support vector machine (SVMs), were used for classifying rice cropping systems. These two classification algorithms were used for the sake of comparing their classification performance. Various spatial and non-spatial data were also gathered for accuracy assessment of the TVDI and classification results. The results showed that the LST-NDVI space was well-defined. The pixels in each scatter plot could form a triangle. This indicated a wide range of surface soil moisture in the study area. The TVDI validation results were achieved by comparing TVDI values with daily rainfall throughout the study area The comparisons results revealed good agreement and sensitivity between TVDI and daily rainfall data. The areas with low soil moisture were mainly distributed in coastal areas from 2002 to 2005, but expanded into the middle region in 2006 and 2007. The largest area of low soil moisture was observed in 2006, reflecting the fact that the MD was faced with drought in 2006 because the amount of water in the Mekong and Bassac Rivers in the dry season was reduced drastically. In a case study of rice crop phenology detection, the comparison results between the estimated sowing/heading dates and field survey data indicated that the use of smooth time profiles extracted from the EMD-based filtered time-series MODIS NDVI 250-m data for detecting phenological dates gave better results than the wavelet transform. These, NDVI patterns reflected the seasonal changes in crop phenology of rice cropping systems, which was important for understanding the temporal NDVI responses of different rice fields of cropping patterns in the study area. The LMM and SVMs were applied to the EMD-based filtered data for classification of rice cropping systems in the region. The classification maps for 2002 and 2006 were compared with the ground truth data and government rice area statistics. The comparison results indicated that both classification methods (LMM and SVMs) were promising for rice crop mapping in the region. The comparison results between the classification results and the ground truth data indicated that the SVMs gave slightly better classification results than the LMM. The overall accuracy and Kappa coefficient achieved by the SVMs for the year 2002 data were 84.0% and 0.79, while the values for the LMM were 81.8% and 0.76, respectively. Similarly, the overall accuracy and Kappa coefficient achieved by the SVMs for the year 2006 data were 85.1% and 0.80, and those for the LMM were 81.8% and 0.76, respectively. These comparison results reaffirmed good agreement between the MODIS-derived rice areas with the government rice area statistics at the provincial level (R2>0.85 in all cases). However, a significance test of difference between two classification methods using Z-test method revealed that the classification accuracy between these two classification (i.e. LMM and SVMs) were not statistically significant different. The Z-test values between the classification methods reported for the year 2002 and 2006 data were 0.299 and 0.275, respectively. These values were smaller than the critical value of 1.96. To relate surface soil moisture variations with rice cropping systems, the composite soil moisture maps (considering dry and very dry classes) were aggregated with the rice crop maps for the years 2002 and 2006. The results indicated a remarkable increase in the area of double and triple irrigated rice cropping systems in areas of low soil moisture (i.e dry and very dry conditions) during this period. Approximately, 6.3% and 9.9% of the area of double and triple irrigated rice cropping system identified as low soil moisture in 2002 increased to 14.9% and 16.3% in 2006, respectively. This study has demonstrated merits of using MODIS data for studying soil moisture variability in relation to rice cropping system, which is important for crop and water management.