Authors:
Anuphao Aobpaet
and
Soravis Supavetch
Affiliation:
Department of Civil Engineering, Kasetsart University, Bangkok and Thailand
Keyword(s):
Cassava, Sugarcane, Remote Sensing for Agriculture.
Abstract:
Cassava and sugarcane are the most important agricultural crops in Thailand. The cultivations of those are similarly in crop season, natural resources, and climate. For decades, the farmers usually switch their plant depending on unit price and government subsidy. The use of remote sensing data for monitoring change in farmland has encountered a problem on the similarity of vegetation index and the seasonal variation. In this work, we investigate the significant differences between cassava and sugarcane plantation by using satellite data from two sensors systems (Optical and SAR sensor) from Sentinel-1 and Sentinel-2 satellites. The result of the sampling fields of cassava shows the fluctuation of the growth and the mean of SAVI is slightly lower than sugarcane at the same age. SAVI values over the cassava farmland seem to approach the homogeneity of sugarcane when the age of more than 11 months. Thus, the difference between cassava and sugarcane farmland using this method should be
investigated on the growth stage of the age between 4-9 months. For SAR polarization, the VV, VH of SAR backscatters have little difference in cassava and sugarcane. When compare the backscatters value of VV and VH from cassava and sugarcane, the sigma0 values in dB show that VV backscatters have a higher signal return. The variation of VH polarization of cassava and sugarcane seem difficult to identify due to the diversity of signal targets. Therefore, by using SAR data, the detection of the difference between cassava and sugarcane should be considered after working on time series techniques for crop seasoning to remove unwanted objects until only cassava and sugarcane remain. From the results, we also found that the parcel-based method is a better processing approach to separate cassava from sugarcane compared to pixel-based, and it requires descriptive statistics to distinguish between cassava and sugarcane at each age. This method requires the information of two agricultural plantations boundaries. The possible handling process when harvesting and preparation of the plantation are by observing time-related over an area to determine the boundary of the farmland. Therefore, the discrimination of remotely sensed data for designing the decomposition technique between cassava and sugarcane farmland is necessary because of the specificity of cultivation in Thailand.
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