Early Season Crop Acreage Estimation for Pigeon Pea using SAR Data: A Case Study of Kalaburagi District, Karnataka
DOI:
https://doi.org/10.58825/jog.2024.18.2.114Keywords:
Pigeon Pea, SAR data, Early Season Crop Acreage, Random Forest Classifier, Polarimetric AnalysisAbstract
Crop acreage estimates using space-based observations during mid-season and pre-harvest periods are operationally provided for major Kharif and Rabi crops in India. These are critical inputs for planning and decision-making concerning food security, storage, pricing, and procurement. This work explores the potential of Satellite C-band Synthetic Aperture Radar (SAR) data in VV and VH polarization, acquired during monsoon season, for early crop acreage assessment of Pigeon Pea. The present study evaluates two classification approaches based on multi-temporal SAR data to generate a spatial distribution map of the pigeon pea crop in the Kalaburagi region of Karnataka. The temporal profiles of sigma nought (backscatter coefficient) and Entropy vs. Alpha Angle were studied with reference to crop phenology. Random forest algorithm has been used to classify multi-temporal SAR Ground Range Detected (GRD) data from June to November 2019. Temporal SAR data from June to early November with VV+VH polarization was optimal for tur area assessment with 85% accuracy. This study also examines phase and intensity information from 3-date SAR Single Look Complex (SLC) data with an unsupervised Wishart Classification approach for improved crop acreage estimation. The results emphasize the effectiveness of dual-polarimetric SAR data for timely crop inventory of Pigeon Pea during the Kharif season.
References
Ainsworth T. L., J. Kelly and J. Lee (2009). Classification comparisons between dual-pol, compact polarimetric and quad-pol SAR imagery. ISPRS Journal of Photogrammetry and Remote Sensing,64,464-471, https://doi.org/10.1016/j.isprsjprs.2008.12.008
Bhagia N., G. D. Bairagi, S. Pandagre, G. Patel, S. P. Vyas, N. Kumar, R. Indal and P. Mesharam (2017). National Inventory of Rabi Pulses in India Using Remotely Sensed Data, J Indian Soc Remote Sens, 45(2): 285–295. https://doi.org/10.1007/s12524-016-0603-4
Chakraborty M., C. Patnaik, S. Panigrahy and J. S. Parihar (2006). Monitoring of wet season rice crop at state and national level in India using multi-date synthetic aperture radar data. Agriculture and Hydrology Applications of Remote Sensing. Proceedings of SPIE Volume 6411. https://doi.org/10.1117/12.693900
Cloude S. R. and E. Pottier (1997), "An entropy-based classification scheme for land applications of polarimetric SAR, IEEE Trans. Geosci. Remote Sens., Vol. 35, No. 1, 68–78. https://doi.org/10.1109/36.551935
Dadhwal V. K., R. P. Singh, S. Dutta and J. S. Parihar (2002). Remote sensing-based crop inventory: A review of Indian experience, Tropical Ecology 43(1): 107-122.
Directorate of Economics & Statistics (2021). Agricultural Statistics at a Glance 2021. Accessed from http:// eands.dacnet.nic.in, Ministry of Agriculture & Farmers Welfare, Directorate of Economics & Statistics, p.272
DPD Report (2020), Kharif Pulses Prospects 2020-21, (accessed from http://dpd.gov.in), Directorate of Pulses Development, Ministry of Agriculture & Farmers Welfare
Geographical Indications Registry (2019). Geographical Indications Journal, Advertised under Rule 41 (1) of Geographical Indications of Goods (Registration & Protection) Rules, 2002, Geographical Indications Registry, Intellectual Property Rights, Journal No.120, April 12, 2019, 37-43
Gumma M.K., T. W. Tsusaka, I. Mohammed, G. Chavula, N. V. P. R.Ganga Rao, P. Okori, C. o. Ojiewo, R. Varshney, M. Siambi and A. Whitbread (2019), Monitoring Changes in the Cultivation of Pigeon pea and Groundnut in Malawi Using Time Series Satellite Imagery for Sustainable Food Systems. Remote Sens. 2019, 11, 1475. https://doi.org/10.3390/rs11121475
Haldar D., C. Patnaik and M. Chakraborty (2014) Jute Crop Discrimination and Biophysical Para-meter Monitoring Using Multi-Parametric SAR Data in West Bengal, India. Open Access Library Journal, 1: e817
Harfenmeister K, S. Itzerott, C. Weltzien and D. Spengler (2021), Agricultural Monitoring Using Polarimetric Decomposition Parameters of Sentinel-1 Data. Remote Sensing. 2021; 13(4):575. https://doi.org/10.3390/rs13040575
Inglada J., A. Vincent, M. Arias and C. Marais-Sicre (2016), Improved early crop type identification by joint use of high temporal resolution SAR and optical image time series, Remote Sensing, vol. 8, no. 5, 362, 2016. https://doi.org/10.3390/rs8050362
Jong-Sen L., M. R. Grunes, T. L. Ainsworth, Li-Jen Du, D. L. Schuler and S. R. Cloude (1999), Unsupervised classification using polarimetric decomposition and the complex Wishart classifier, IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 5, pp. 2249-2258, Sept. 1999, doi: 10.1109/36.789621.
Kaoneka S. R., R. K. Saxena, S. N. Silim, D. A. Odeny, N. V. P. R. Ganga Rao, H. A. Shimelis, M. Siambi and R. K. Varshney (2016), Pigeon pea breeding in eastern and southern Africa: challenges and opportunities. Plant Breed, 135: 148-154. https://doi.org/10.1111/pbr.12340
Mandal D., D. S. Vaka, N. Bhogapurapu, V.S. K. Vanama, V. Kumar, Y. S. Rao and A. Bhattacharya (2019). Sentinel-1 SLC Preprocessing Workflow for Polarimetric Applications: A Generic Practice for Generating Dual-pol Covariance Matrix Elements in SNAP S-1 Toolbox, https://doi.org/10.20944/preprints201911.0393.v1
Marawar M.W. and V. V. Ujjainkar (2019). Role of Pigeonpea in Indian Food Security. Remarking an Analisation 2019;4(2): E-461-466
Natteshan N.V.S. and N. S. Kumar (2020). Effective SAR image segmentation and classification of crop areas using MRG and CDNN techniques, European Journal of Remote Sensing, 53:sup1, 126-140, https://doi.org/10.1080/22797254.2020.1727777
Parihar J. S., M. Chakraborty, K.R. Manjunath and S> Panigrahy. (1998). Synthetic aperture radar data as a sustainable system for monitoring the Cropping system - an analysis, Page(s) 245-255, ISPRS Archives – Volume XXXII Part 1, 1998, ISPRS Symposium on Earth Observation System for Sustainable Development, Technical Commission I: Sensors, Platforms, and Imagery, 2-27 February 1998
Parihar J. S. and V. K. Dadhwal (2002). Crop production forecasting using remote sensing data: Indian experience. Proceedings of the ISPRS Comm. VII Symposium “Resource and Environmental Monitoring”, Hyderabad, India during Dec. 3-6 2002, IAPRS & GIS, vol. 34, Part 7, 1-6.
Parihar J. S. and K. R. Manjunath (2013). Agricultural Applications: Evolution during last 25 Years. NNRMS Bulletin. March 2013, 58–75.
Parihar J. S. and M. P. Oza (2004). Remote Sensing for Crop Production Forecasting: Indian Experience. Twentieth Session of the Asia and Pacific Commission on Agricultural Statistics, Sept 2004
Parihar J. S. and M. P. Oza (2006). FASAL: an integrated approach for crop assessment and production forecasting, Agriculture and Hydrology Applications of Remote Sensing, edited by Robert J. Kuligowski, Proc. of SPIE Vol. 6411, 641101.
Paul S. and D. N. Kumar (2019). Comparison of Landsat-8 and Sentinel-2 Data for Classification of Rabi Crops over Karnataka, India, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences; Vol. XLII-3/W6, Gottingen: Copernicus GmbH. (2019): 579-584. https://doi.org/10.5194/isprs-archives-XLII-3-W6-579-2019
Ramamurthy V., D. M. Mamatha, K. V. Niranjan, V. Ramakrishnappa, K. Ranjitha, C. Marigowda and S. Singh (2019). Suitability evaluation for pigeon pea in southern transition zone of Karnataka Plateau, India. Legume Research - An International Journal. https://doi.org/10.18805/LR-4047
Ranjan A. K. and B. R. Parida (2019). Paddy acreage mapping and yield prediction using sentinel-based optical and SAR data in Sahibganj district, Jharkhand (India). Spatial Information Research, 27, 399–410 (2019). https://doi.org/10.1007/s41324-019-00246-4
Ray S.S., N. M. Sanapala and S. Gupta (2014). Use of Remote Sensing in Crop Forecasting and Assessment of Impact of Natural Disasters: Operational Approaches in India. In Conference Proceedings: FAO Expert Meeting on Crop Monitoring for Improved Food Security, Vientiane, Lao PDR, 111-121.
Sentinel-1 Product Specification (2020). Doc No.S1-RS-MDA-52-7441, ESA, 27/02/2020
Shaik Salma, N. Keerthana and B.M. Dodamani (2022), Target decomposition using dual-polarization sentinel-1 SAR data: Study on crop growth analysis,Remote Sensing Applications: Society and Environment,Volume 28,2022,100854,ISSN 2352-9385
Siddayya S., A. Dandekar and S. Kammar (2016). Adoption pattern of improved pigeon pea varieties in Gulbarga district, Karnataka, India. Agricultural Science Digest - A Research Journal. 1-36. https://doi.org/10.18805/asd.v36i4.6465
Silim S. N., G. Mergeai and P. M. Kimani (eds) (2001). PIGEONPEA Status and Potential in Eastern and Southern Africa, Proceedings of a Regional Workshop Nairobi, Kenya, 12-15 Sep 2000. International Crop Research Institute for Semi Arid Tropics , Patancheru, Andhra Pradesh, India. ISBN 92-9066-432-0, 1-232.
Singh J., A. Mahapatra, S. Basu and B. Banerjee (2019). "Assessment of Sentinel-1 and Sentinel-2 Satellite Imagery for Crop Classification in Indian Region During Kharif and Rabi Crop Cycles," IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, 3720-3723, https://doi.org/10.1109/IGARSS.2019.8900491
Tiwari A.K. and A. K. Shivhare (2019). Pulses in India: Retrospect and Prospects – 2018. Directorate of Pulses Development, GoI, Bhopal (MP), India, 1-346.
Tiwari S.K, M. L. Prasad Rao and G. P. Rao (2021). Paddy crop acreage assessment using Sentinel-1 (C-band) SAR data in Andhra Pradesh state, India, Journal of Crop and Weed, 17(2): 10-18 (2021)
Uppala D., K. Ramana, S. Poloju, S. Mullapudi and V. K. Dadhwal (2015). Rice crop discrimination using single date RISAT1 Hybrid (RH, RV) polarimetric data. Photogrammetric Engineering and Remote Sensing. 81. 557-563. https://doi.org/10.14358/PERS.81.7.557
Verma A., A. Kumar and K. Lal (2019). Kharif crop characterization using combination of SAR and MSI Optical Sentinel Satellite datasets. J Earth Syst Sci 128, 230. https://doi.org/10.1007/s12040-019-1260-0
Xianfeng Jiao, M. K. John, J. Shang, H. McNairn, D. Walters, B. Ma and X. Geng (2014), Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data,ISPRS Journal of Photogrammetry and Remote Sensing,Volume 96,2014,Pages 38-46,ISSN 0924-2716.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Geomatics
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
