A Review: Soil Moisture Estimation Using Different Techniques Jitender Pandey, Vivek Chamoli and Rishi Prakash Abstract In this research paper, we have discussed about the different methods for estimation of soil moisture. Soil moisture is an imperative segment from a socioeco- nomical point of view. The importance and application of the soil moisture is seen in different fields like agriculture, forecasting of drought, geological application, etc. In this paper, we went over the points of interest and impediments of the different techniques to be examined and endeavor to dissect the best method for deciding the soil moisture content. Keywords Soil moisture · Hydrological · Remote sensing · Time domain reflectometry · Frequency domain reflectometry · Global navigation satellite system (GNSS) 1 Introduction Determining the moisture of the soil is one of the important things for various appli- cations for example in the case of large agricultural fields. The moisture content can be used as raw data for various applications like determining the health of the soil. Many methods have been put to arrive at a simple and accurate way of determining soil moisture. There are many types of ways for estimating the moisture of soil. Techniques like time domain reflectometry method are relatively faster. Other meth- ods like gravimetric techniques are somehow destructive, more time consuming, and laborious. However, the important thing is the spatial distribution of soil moisture which is used as an important parameter for various applications like metrological applications, agricultural applications, hydrological applications, forestry applica- tions, monitoring of flood and drought. Thus we need an upscale point measurement J. Pandey (B ) · V. Chamoli · R. Prakash Graphic Era (Deemed to Be University), Dehradun, India e-mail: jitenderpandey999@gmail.com V. Chamoli e-mail: vivekchamoli08@gmail.com © Springer Nature Singapore Pte Ltd. 2020 S. Choudhury et al. (eds.), Intelligent Communication, Control and Devices, Advances in Intelligent Systems and Computing 989, https://doi.org/10.1007/978-981-13-8618-3_12 105