Abstract
Water is the main resource for agriculture. Management of water in agricultural field is a challenging process. To manage the water content in the agricultural field, smart irrigation system has been proposed by using fuzzy based decision support system on Hyperspectral Image benchmark dataset. Hyperspectral images are the process of collected and processed the images from electromagnetic spectrum. Recent studies show that hyperspectral images are very accurate in collecting the soil moistures value. Dataset is collected in five-day field of campaign the soil is the type of clayey slit and it is non vegetation. Hyperspectral datasets which consist of range value between 454 to 598 nm. Value is gathered from the 285 hyperspectral snapshot camera recording images with 125 spectral bands with the spectral resolution of 4 nm. Experimental results of this method achieve the accuracy of 0.98. Hence the proposed method reduces the water wastage to an extent.
Highlights
In recent years, the efficient utilization of water in agriculture is the most important challenges in modern agriculture (Polak et al, 2017)
There are many other influencing factors like roughness, texture, mineral content is present in soil to analyze the soil moisture value but the result of soil moisture value is considered in the top layer of 5 cm (Zhong et al, 2006)
Data are collected from the experienced farmers as well as the researchers
Summary
The efficient utilization of water in agriculture is the most important challenges in modern agriculture (Polak et al, 2017). Hyperspectral imaging widely used in remote sensing applications, which involves complex surface measurements and detection of identical materials having fine spectral signatures (Palacios-Orueta and Ustin, 1998) This fuzzy system cannot be focus only on water management it can be supported for selected crops. Decision Tree is a statistical/machine learning technique for classification and regression It is mainly used for interaction between the variables and new data. Support Vector Machine is a selection method that compares the standard parameter set of discrete values, called the candidate set and takes the one that has the best classification accuracy. RMSE and R2valuehas been compared for 285 hyperspectral snapshots This comparison gives the best and worst fit regression value from the band datasets.
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