The Pharma Innovation Journal 2019; 8(6): 360-362 ISSN (E): 2277- 7695 ISSN (P): 2349-8242 NAAS Rating: 5.03 Estimation of soil moisture from sentinel-1a TPI 2019; 8(6): 360-362 © 2019 TPI synthetic aperture radar (SAR) in Perambalur www.thepharmajournal.com Received: 01-04-2019 district of Tamil Nadu Accepted: 05-05-2019 Selvaprakash Ramalingam Selvaprakash Ramalingam, Jagadeeswaran Ramasamy, Pazhanivelan Department of Remote Sensing and GIS, Tamil Nadu sellaperumal, Kumaraperumal Ramalingam, Sivakumar Karthikeyan Agricultural University, and GA Deepagaran Coimbatore, Tamil Nadu, India Jagadeeswaran Ramasamy Abstract Agricultural College & Research An attempt was made to estimate and map soil moisture in Perambalur district of Tamil Nadu using Institute, TNAU, sentinel – 1A Synthetic Aperture Radar (SAR) Data. Sentinel -1A C band data with VV and VH Kudumiyanmalai, Tamil Nadu, polarization were acquired for the study area during September 2018 to January 2019 at monthly interval. India Ground truth collections were performed to estimate in-situ soil moisture both by gravimetric method and using TDR probe at the time of satellite pass. Images were processed using SNAP toolbox and Pazhanivelan sellaperumal backscattering co-efficient (σ0) were generated for each pixel. The backscattering co-efficient value for Department of Remote Sensing and GIS, Tamil Nadu VV polarization for different dates varied from -14.28 to -2.47 and for VH polarization it was -21.84 to - Agricultural University, 9.04 since the backscattering co-efficient has a direct relationship with volumetric soil moisture, the same Coimbatore, Tamil Nadu, India was correlated with in-situ soil moisture. The correlation value is maximum, minimum in the study period dates of (0.62 to -0.49) and (0.69 to -0.72) represented for VH and VV polarization. The negative Kumaraperumal Ramalingam correlation occurring dates are dense vegetation occurring the field. Department of Remote Sensing and GIS, Tamil Nadu Keywords: Soil moisture, SAR data, VV, VH, backscattering, polarization Agricultural University, Coimbatore, Tamil Nadu, India Introduction Sivakumar Karthikeyan Soil moisture is majorly contributing the agricultural crop planning (the time of sowing, Department of Remote Sensing flowering, and maturity stages). Fresh water is mostly used in (75%) the agriculture crop and GIS, Tamil Nadu production. As there is an increase in the fresh water demand, it is important to make optimal Agricultural University, use of water resources with improved agricultural productivity through accurate information Coimbatore, Tamil Nadu, India provided by remote sensing (Lakhankar et al., 2009) [5]. Knowledge about the spatial GA Deepagaran distribution and temporal variation of soil moisture in a region is a pre-requisite for effective Agro Climate Research Centre, crop planning, in-season drought assessment, irrigation management and soil conservation Tamil Nadu Agricultural programme. The conventional method of measuring soil moisture using neutron probe, TDR University, Coimbatore, Tamil probe and gravimetric methods are not appropriate for understanding of the spatial and Nadu, India temporal dynamics of soil moisture due to variation in topography, soil type and land use pattern. The advances in microwave remote sensing both passive and active have demonstrated the potential to map the spatial extent of soil moisture at different scales (Khedikar et al., 2014) [4]. Recent advances in microwave remote sensing have demonstrated the potential toquantitatively measure the soil moisture on bare and short-vegetated surfaces (Engman and Chauhan et al., 1995) [1]. Despite the importance of soil moisture information, widespread and continuous measurement of soil moisture is also possible. The remote sensing challenges are top few centimetres of surface soil. Soil penetration depth mainly depends on the wave frequency of the radiation and the condition of the target. At all weather conditions (cloud, rain, storms) microwave penetrates into the soil for 5cm orup to 15cm root zone level of volumetric analysis. Polarimetric radar systems having both soil moisture and surface roughness have been successfully retrieved from a quad-polarimetric radar data set. Oh et al., [6] (1992) developed an empirical polarimetric scattering model using a database of scatter meter measurements, which was used to simultaneously retrieve surface root-mean-square Correspondence (RMS) height and soil moisture contents. It was using C-band ENVISAT ASAR data that is Jagadeeswaran Ramasamy sensitive to soil moisture studies in C-HH polarization data. C-band data is horizontally Agricultural College & Research Institute, TNAU, polarized data channel in conjunction with ancillary data on vegetation. The objective of this Kudumiyanmalai, Tamil Nadu, study is to map soil moisture distribution of Perambalur District of Tamil Nadu using the data India ~ 360 ~ The Pharma Innovation Journal value of new generation satellite of Sentinel-1ASynthetic the 185 mm. the Perambalur district having a semi-arid Aperture Radar (SAR) data. climate and contains high humidity. Various land forms occurring in the area such as structural hills, erosional plains, Materials and Methods residual hills rolling uplands and pediments of different facies Study area belonging to the denotational and structural land forms. These Perambalur district boundary on the north by Cuddalore and district major areas occupy the black soil, and minimum areas Salem districts, south by Tiruchirappalli, east by Ariyalur only occupy red loam and alluvial soils. district, west by Tiruchirappalli and Salem districts. The Though, the cropping intensity is very high in irrigated district has an area of 1,756 sq. km. Perambalur District lies in systems there is an uncertainty of judicious supply of water in the geographical co-ordinates of longitude 78° 52' 47.9892'' E canal i.e., turn system is in practice. Poor distribution of and latitude11° 13' 48.0000'' N showed on the (fig. 1) .The rainfall is a matter of concern to plan for a better cropping period of 1901 – 1970 rainfall ranges from 843.5 to 1123.3 programme in rainfed areas. Thus, the monitoring and mm. The highest average temperature is 31.7oC in the month mapping of moisture zones will certainly help to identify the of May, 24.9oC in the month of lowest average temperature. potential cropping zones in this region and manage irrigation During the year, the average temperatures vary by 6.8 °C. The source effectively. precipitation variation between driest and wettest months is Fig 1: Map showing the study area Satellite data Ground truth data The Sentinel-1A SAR data with a spatial resolution Ground truth verification was carried out in the study area to of(20*5m) with 12days temporal resolution Interferometric estimate the in-situ soil moisture during different dates which Wide swath (IW) mode was downloaded from the European coincides with date of pass of the satellite (between space agency website and utilized for the study. The September, 2018 and January, 2019). Soil sampling was done characteristics of the sensor are presented in Table 1. to represent various types of lands (irrigated, rainfed and crop (Annonymous, 2019) lands). (https://sentinel.esa.int/web/sentinel/technical-guides/sentinel- 1-sar/sar-instrument/acquisition-modes) [3]. Data analysis Image preprocessing of Sentinel-1A IW GRDH dataset was Table 1: IW Data Characteristics carried out in order to reduce orbital errors, radiometric Characteristic Value distortion, geometric distortion and speckle noise. Orbital Swath width 250 km correction was done using precise orbit files that are available [2] Incidence angle range 29.1° - 46.0° in https://qc.sentienl1.eo.esa.int/ which could be directly Sub-swaths 3 downloaded to SNAP toolbox for the orbital correction of the Azimuth steering angle ± 0.6° data. Radiometric Correction is a progressive reduction in Dual HH+HV, VV+VH, brightness over images from near to far range (Rosich et al., Polarisation options Single HH, VV 2004) [7]. Geo-coding converts an image from Ground Range Maximum Noise Equivalent Sigma -22 dB or Slant Range geometry into a map coordinate system. In Zero (NESZ) SNAP toolbox, the terrain correction will be carried out using ~ 361 ~ The Pharma Innovation Journal SRTM 3sec DEM which is automatically downloaded from September 2018 to January 2019. The dB value for ground the servers. truth point (D1) varied from -22.40 to -14.32, -15.10 -5.88and similar for all the dates VH, VV polarization. Where in Post – processing of the satellite data satellite pass date wise minimum, maximum, radar Speckle filter exploits the space varying temporal correlation backscattering values (dB) presented. The minimum value of speckle between images to significantly reduce the noise. during the period (D1 to D5) ranged from -22.40 to -18.46 Refined Lee Sigma filter averages the image while preserving and maximum ranged from -14.32 dB to -9.03 dB, the edges was used to reduce the noise in the data. The respectively (Table.2). The dB value comparatively good for intensity values are converted to dB values using the linear to D1 and D2 date of both VH and VV polarizations. The date dB conversion tool in SNAP and stored for further processing. wise dB values indicate the low moisture during the non-rainy Derive sigma naught is a fraction which describes the amount date of SAR data collection and increases in moisture for of reflectivity of an object is normalized with respect to a unit during the rainy dates. The correlation vales range -0.49 to area on the horizontal ground plane in the field (Khedikar et 0.62 in VH and -0.72 to 0.69 in VV polarizations occurred. al., 2014) [4]. This function is also involves the physical and The correlation value is high in D1, D2 and D5for correlation electrical properties of the incident material. of VV polarization comparatively high in VH polarizations, respectively (Table. 3). D3 and D4 dates are mostly Result and Discussion interpreted on high vegetation so can’t be correlated on the The soil moisture retrieved for the study area from the C – soil moisture and satellite dB value.