ISSN 1068-3674, Russian Agricultural Sciences, 2017, Vol. 43, No. 6, pp. 461–465. © Allerton Press, Inc., 2017.
CROP PRODUCTION
Retrieval of Rice Crop Growth Variables Using Multi-Temporal RISAT-1 Remotely Sensed Data1 P. Kumara, R. Prasada, *, D. K. Guptaa, A. K. Vishwakarmaa, and A. Choudharyb a
Department of Physics, Indian Institute of Technology (BHU), Varanasi, India Department of Civil Engineering, Indian Institute of Technology Guwahati, India *e-mail:
[email protected]
b
Received July 27, 2017
Abstract—Microwave remote sensing sensors have great potential due to their capability to operate in any weather condition for the wide range of agricultural applications. The rice crop variables such as leaf area index (LAI) and plant height (PH) were retrieved for the monitoring of crop growth to improve crop production. The interaction of rice crop variables with medium spatial resolution (25 m) Radar Imaging Satellite-1 (RISAT-1) data for Varanasi district, India, was examined. The multi-temporal dual polarization (HH- and HV-) images having frequency 5.35 GHz at C-band were investigated. Crop growth profile derived from the analysis of temporal backscattering (July–October, 2013) showed 3–4 dB difference throughout its growth cycle. The rice crop variables were retrieved by the inversion of polynomial models and showed higher values of coefficient of determination (R 2) for HH-polarization in comparison to HV-polarization. Keywords: microwave remote sensing, rice crop, LAI, PH, C-band DOI: 10.3103/S1068367417060076
INTRODUCTION Rice crop is one of the most important crops in the world essential for the livelihood of the human beings. The economic growth of several countries depends on the production of rice [1]. So, it becomes essential to monitor full growth stages of rice crop continuously by acquiring accurate and timely information about the crop condition [2]. Spaceborne remote sensing has a vital role for the mapping and monitoring of agricultural crops due to its capability to provide permanent coverage over the larger areas [3–8]. The extraction of information from the optical satellite images is often incomplete and difficult due to atmospheric conditions. Due to these reasons and the limitation of temporal optical satellite images over a season, several researchers are using single date satellite data for the crop mapping and monitoring in Varanasi [9–12]. The frequent revisits and availability of high spatial and temporal resolution SAR time series images is a very useful data source for monitoring the agricultural crops in the tropical regions [5, 13–15]. SAR images are attractive due to its all-weather capability and available when optical sensors are inoperative. These sensors provide data highly sensitive to the canopy structure and moisture content [13, 14]. 1 The article is published in the original.
For several years various studies have shown the usefulness of microwave data for the retrieval of crop parameters [5, 16–18]. The multi-frequency (Ka, Ku, X, C and L) and full polarization (HH, HV, VV and VH) microwave data were analysed for the estimation of rice crop growth variables. Results have shown that LAI was found better correlated with HH- and cross polarization data at C-band [19]. Polarization of a microwave is sensitive to the shape, size and orientation of the target scattering elements. The horizontal polarization gives the measure of the horizontal dimension of the scattering elements; while the vertical dimension gives the measure of the vertical dimension [20]. The HH-polarization has shown high sensitivity in comparison to VV-polarization for rice crop variables using adaptive neuro-fuzzy inference system at X-band [21]. The Radarsat-2 and RISAT-1 datasets have been used for the study of several crops including rice crop and shown the utility of C-band [22]. The backscatter of C-band Radarsat-2 SAR data has shown highest correlation with LAI of paddy rice [8]. The HV-polarization was found more sensitive for LAI using RISAT-1 data for basmati and non-basmati rice [23]. The applications of SAR images for the estimation of crop growth variables are challenging, especially for the crop scattering geometry which mainly govern the interaction of microwave signal with the vegetation scattering elements [22]. However, very few studies have been reported for the
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Fig. 1. The temporal variation of back scattering coefficient at HH- and HV-polarizations for rice crop.
Fig. 2. Temporal behaviour of leaf area index.
RESULTS AND DISCUSSION mapping and monitoring of agricultural crops using RISAT-1 data [22–27]. The aim of the present study is to retrieve the rice crop variables using dual polarimetric multi-temporal RISAT-1 satellite data. Retrieval of rice crop growth variables is very essential for monitoring the rice crop growth stages in order to take timely measures for enhancing the production of the crop. RISAT-1 dual polarimetric (HH- and HV-) microwave remote sensing images at C-band (5.35 GHz) potentially overcome the ambiguity related to optical satellite data. MATERIAL AND METHODOLOGY The Varanasi district, in Uttar Pradesh, India, was selected as a study area. The field observations were done for the LAI and PH of rice crop at the same date of satellite pass during different crop growth stages. The LAI was measured using an instrument ACCUPAR LP-80 [2, 18]. The PH measurements were done manually using tape measurement in the rice field. The crop growth variables of rice crop were measured at its five different growth stages started from 15 July to 23 October, 2013 from the transplanting to maturity stage during Kharif season. The RISAT-1 satellite data was processed using SARscape software. The processing includes import of images and multi-looking were done before the filtering of images of the multi-temporal data. The image filtering was done using Lee filter. After the filtering of images, geocoding and radiometric calibration were done to obtain the backscattering values. The inversion of polynomial model of degree 2 was done for the retrieval of rice crop growth variables.
The whole life of rice crop was divided into three different major growth stages like vegetative stage, reproductive stage and ripening stage. At the vegetative stage, the backscattering coefficients (σ0) were found dominant due to major contribution of stems and the interaction between the stems and water underneath the rice crop. During vegetative to reproductive stage, the scattering coefficients were found to increase until leaves became large and dense. However, the backscattering coefficients were found to increase slowly due to random scattering by vertical leaves during vegetative to reproductive stage. The increase in the size of leaves cause to cover most of the spaces between plants resulted to quench the contributions from the stems and the water underneath. At the ripening stage, the color of leaves was found changed from green to yellow and density of leaves was decreased. At this stage, the backscattering showed its decreasing behaviour [2, 16, 28]. The temporal variation of backscattering at HH- and HV-polarizations is shown in Fig. 1. LAI is defined as the one-sided green leaf area per unit ground surface area. It is a dimensionless quantity [29]. The LAI and PH were found increasing from vegetative to reproductive stages and then started slight decreasing from the maturity stage (23 October, 2013) for both HH- and HV-polarizations. The temporal behaviour of LAI and PH are shown in Figs. 2 and 3 respectively. The rice crop variables were retrieved by the inversion of polynomial model. The higher value of coefficient of determination (R 2 = 0.8827) was obtained between the observed and retrieved values of LAI at HH-polarization, whereas the lesser value (R 2 = 0.8265) was found at
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20 0 2013 9-08-2013 3-0 9-2013 8-0 9-2013 3-10-2013 2 15-072 0 0 Date of data acquisition Fig. 3. Temporal behaviour of plant height.
HV-polarization. The retrieval of LAI is shown in the Fig. 4 for (a) HH- and (b) HV-polarizations, respectively. The polynomial regression models were inverted to estimate the PH for HH- and HV-polarizations. The value of coefficient of determination for PH with σ0 was found higher (R 2 = 0.9083) in comparison to LAI at HH-polarization. The lesser value of R 2 = 0.7992 was found for the PH at HV-polarization in comparison to HH-polarization. The above analysis shows that HH-polarization is more suitable for the retrieval of rice crop growth variables in comparison to HV-polarization. Polynomial models, variation of coefficient of determination (R 2) and root mean square error (RMSE) for LAI and PH at HH- and HV-polarization are summarized in Table 1. The Fig. 5 shows the observed and retrieved values of PH for HH- and HV-polarizations respectively.
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Fig. 4. Retrieval of leaf area index for (a) HH- and (b) HV-polarization.
scattering values were found more sensitive in comparison to HV-polarization for the LAI and PH rice crop variables. The retrieved values of LAI and PH were found very close to the observed values using inversion of polynomial regression models. The results
CONCLUSIONS The significant temporal variations of σ0 were found for the rice crop variables using dual polarimetric RISAT-1 satellite data. The HH-polarized back-
Table 1. Polynomial models, variation of R2 and RMSE for LAI and PH at HH- and HV-polarizations Crop growth variables LAI, m2/m2 PH (cm)
Polarizations
Polynomial models for LAI and PH at HH- and HV-polarizations
R2
RMSE
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y = –0.4215x2 – 4.9079x – 11.577
0.8827
0.0023
HV-
y = –0.1876x2 – 2.0033x – 2.5068
0.8265
0.0058
HH-
y = –14.470x2 – 163.83x – 359.37
0.9083
0.0053
0.7992
0.0106
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Fig. 5. Retrieval of plant height for (a) HH- and (b) HV-polarization.
show that the C-band, RISAT-1 microwave satellite data may be useful for the accurate retrieval of rice crop variables to monitor its growth stages. ACKNOWLEDGMENTS The authors wish to acknowledge Prof. Rajeev Sangal, Director, Indian Institute of Technology (BHU), Varanasi, for the financial support to procure software Environment for Visualizing Images (ENVI) version 5.1 with the SAR scape module. REFERENCES 1. Wang, L., Kong, J.A., Ding, K.H., Toan, T.L., RibbesBaillarin, F., and Foury, N., Electromagnetic scattering model for rice canopy based on Monte Carlo simulation, Prog. Electromagn. Res. B, 2005, vol. 52, pp. 153–171. 2. Gupta, D.K., Kumar, P., Mishra, V.N., Prasad, R., Dikshit, P.K.S., Dwivedi, S.B., Ohri, A., Singh, R.S., and Srivastava, V., Bistatic measurements for the estimation of rice crop variables using artificial neural network, Adv. Space Res., 2015, vol. 55, pp. 1613–1626. 3. Panigrahy, S., Manjunath, K.R., Chakraborty, M., Kundu, N., and Parihar, J.S., Evaluation of RADARSAT Standard Beam data for identification of potato and rice crops in India, ISPRS J. Photogramm. Remote Sens., 1999, vol. 54, pp. 254–262. 4. Oza, S.R., Panigrahy, S., and Parihar, J.S., Concurrent use of active and passive microwave remote sensing data for monitoring of rice crop, Int. J. Appl. Earth Obs. Geoinf., 2008, vol. 10, pp. 296–304. 5. Baghdadi, N., Boyer, N., Todoroff, P., Hajj, M.E., and Bégué, A., Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island, Remote Sens. Environ., 2009, vol. 113, pp. 1724–1738.
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