Relationships Between Rice Growth Parameters and Remote Sensing Data

Abstract

Rice is an agricullure planis thai has the specific characlerislic in the life stage due to the growth stage having different proportion of vegetation, water, and soil. Vegetation index is one of the satellite remote sensing parameter that is widely used to monitor the global vegetation cover. The objective of the study is to know the spectral characteristic of rice plant in the life stage and find the relationship between the rice growth parameters and the remote sensing data by the Landsat ETM* data using the correlation and regression analysis. The result of study shows that the spectral characteristic of the rice before one month of age is different comparing after one inonlh. All of the examined vegetation index has close linear relationship with rice coverage. Difference Vegetation Index (DVI) is the best vegetation index which estimates rice coverage with equation y = 1.762x + 2.558 and R 2 value was 0.946. Rice age has a high quadratic relationship with all of evaluated vegetation index. Transformed Vegetation Index (TV1) is the best vegetation to predict the age of the rice. Formula y = O.OI3x z -1.625x + 145.8 is the relationship form between the rice age and the TV1 with R ; = 0.939. Peak of the vegetation index of rice is in the rice age of 2 months. This period is the transition of vegetative and generative stages.

Rice Yield Prediction Using MODIS - NDVI (MOD13Q1) and Land Based Observations

“…Then, a relationship between rice age and rice NDVI was performed. Nuarsa and Nishio (2007), suggested that the quadratic equation is the best relationship between rice age and rice NDVI. From the quadratic equation, 3 variables were calculated i.e., maximum NDVI value (NDVI max ) attained during crop period, the age of the rice plant when the NDVI peak is achieved (Age NDVImax ), and summation of the rice NDVI during observation (∑ NDVI) as illustrated in Figure 4.…”

Relationship between Rice Spectral and Rice Yield Using Modis Data

“…According to the results of our previous research (Nuarsa and Nishio, 2007), the quadratic equation best describes the relationship between rice age and the NDVI. From the quadratic equation, the maximum NDVI (NDVI max ), the age of the rice plant at the NDVI max (Age NDVImax ), and the total NDVI (∑ NDVI) was calculated, as shown in Figure 2.…”

A comparative analysis of multitemporal MODIS EVI and NDVI data for large-scale rice yield estimation

“…The statistics of crop yields were considered as the dependent variable, determined by an independent variable of either EVI or NDVI. In this study, the quadratic regression model, which produces more accurate results in establishing the relationship between remotely sensed vegetation indices and crop yields (Hayes and Decker, 1998;Nuarsa and Nishio, 2007;Son et al, 2013c), was used to examine the effectiveness of EVI and NDVI for estimating rice crop yields in the study region. The model can be expressed using the following equation:…”