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The Study of Discrimination of Remotely Sensed Data for Designing the Separation Technique between Cassava and Sugarcane Farmland

机译:木薯和甘蔗农田在木薯和甘蔗农田分离技术辨别的研究

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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.
机译:木薯和甘蔗是泰国最重要的农作物。这些种植在作物季节,自然资源和气候中同样。几十年来,农民通常根据单价和政府补贴而转换他们的工厂。用于监测农田的遥感数据的使用已经遇到了植被指数的相似性和季节性变化的问题。在这项工作中,我们通过使用来自Sentinel-1和Sentinel-2卫星的两个传感器系统(光学和SAR传感器)的卫星数据来研究木薯和甘蔗种植园的显着差异。木薯采样场的结果表明,在同一年龄的情况下,生长的波动和Savi的平均值略低于甘蔗。萨维亚农田的Savi值似乎在超过11个月的年龄时接近甘蔗的均匀性。因此,应研究4-9个月之间年龄的生长阶段的木薯和甘蔗农田之间的差异。对于SAR极化,SAR后拍的VV,VH的VV在木薯和甘油中没有差异。当从Cassava和Sugarcane进行比较VV和VH的后拍值时,DB中的Sigma0值显示VV后拍的信号返回更高。由于信号目标的多样性,木薯和甘蔗的VH偏振的变化似乎难以识别。因此,通过使用SAR数据,在处理时间序列技术以进行作物调味术后,应考虑木薯和甘蔗之间的差异检测,以去除不需要的物体,直到仅留下木薯和甘蔗。从结果中,我们还发现,基于包裹的方法是与基于像素的基于像素相比将Cassava分离的更好的加工方法,并且需要描述统计,以区分每年的木薯和甘蔗。该方法需要两种农业种植园的信息。在收获和制备种植园时可能的处理过程是通过观察与某个区域的时间相关,以确定农田的边界。因此,由于泰国的种植特异性,需要对设计木薯和甘蔗农田之间的远程感测的数据的辨别。

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