Current Science

Open Access Open Access  Restricted Access Subscription Access

Crop Phenology and Soil Moisture Applications of SCATSAT-1


Affiliations
1 Space Applications Centre, ISRO, Ahmedabad 380 015, India
2 Indian Institute of Remote Sensing, Dehradun 248 001, India
3 Vellore Institute of Technology, Vellore 632 014, India
4 M.P. Council of Science and Technology, Bhopal 462 003, India
5 Banaras Hindu University, Varanasi 221 005, India
6 Mahalanobis National Crop Forecast Centre, Delhi 110 012, India
 

SCATSAT-1 measures the backscattering coefficient over land surfaces, which is a function of vegetation structure, surface roughness, soil moisture content, incidence angle and dielectric properties of vegetation. Scatterometer image reconstruction techniques provide fine resolution data to explore the emerging applications over land by using ambiguous backscatter from land. In this paper, 2 km resolution products of ISRO’s scatterometer SCATSAT-1 are exploited for land target detection, rice crop phenology stages detection for kharif and rabi seasons and estimation of relative soil moisture over parts of India. Temporal and spatial backscatter changes are due to seasonal and changes in Land Use Land Cover. Crop phenology stages such as transplanting, maximum tillering, panicle emergence and physiological maturity stages are identified by analysing SCATSAT-1 time series along with NDVI and findings are supported by appropriate ground truth observations and crop cutting experiment (CCE) data. The relative soil moisture change detection is validated with in situ ground truth measurements using Hydraprobe, carried for SCATSAT-1 ascending and descending passes.

Keywords

Crop Phenology, Gamma-0, Rice, Sigma-0, Soil Moisture, Vegetation Dynamics.
User
Notifications
Font Size

  • Attema, E. P. W., The active microwave instrument on-board the ERS-1 satellite. Proc. IEEE, 1991, 79(6), 791–799.

  • Schanda, E., Physical Fundamentals of Remote Sensing, Springer Verlag, Berlin Heidelberg, etc., 1986, p. 187.

  • Kennett, R. G. and Li, F. K., Seasat over-land scatterometer data, part I: global overview of the Ku-band backscatter coefficients. IEEE Trans. Geosci. Remote Sensing, 1989, 27, 592–605.

  • Messeh, M. A. and Quegan, S., Variability in ERS scatterometer measurements over land. IEEE Trans. Geosci. Remote Sensing, 2000, 38, 1767–1776.

  • Ringelmann, N., Scipal, K., Bartalis, Z. and Wagner, W., Planting date estimation in semi-arid environments based on Ku-band radar scatterometer data. In IGARRS’2004, Anchorage, USA, 2004.

  • Oza, S. R. and Parihar, J. S., Evaluation of Ku-band QuikSCAT scatterometer data for rice crop growth stage assessment. Int. J. Remote Sensing, 2007, 28(16), 3447–3456.

  • Inoue, Y., Kurosu, T., Maeno, H., Uratsuka, S., Kozu, T., Dabrowsk-Zielinska, K and Qi, J., Season-long daily measurements of multi-frequency (Ka, Ku, X, C, and L) and fullpolarization backscatter signatures over paddy rice field and their relationship with biological variables. Remote Sensing Environ., 2002, 81, 194–204.

  • Schmugge, T., Remote sensing of soil moisture. In Hydrology Forecasting (eds Anderson, M. G. and Burt, T. P.), Wiley, New York, 1985, pp. 101–124.

  • Zhao, W. and Li, Z. L., Sensitivity study of soil moisture on the temporal evolution of surface temperature over bare surfaces. Int. J. Remote Sensing, 2013, 34, 3314–3331.

  • McCabe, M. and Wood, E., Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors. Remote Sensing Environ., 2006, 105(4), 271–285.

  • Wagnar, W., Noll J. Borgeaud and Rott, H., Monitoring soil moisture over the Canadian Prairies with ERS scatterometer. IEEE Trans. GeoSci. Remote Sensing, 1997, 37(1), 206–216.

  • Iliana Mladenova, Venkat Lakshmi, Jeffrey P. Walker and David G. Long, An assessment of QuikSCAT Ku-band scatterometer data for soil moisture sensitivity. IEEE Geosci. Remote Sensing Lett., 2009, 6(4), 640–643.

  • Bartalis et al., Initial soil moisture retrievals from Metop-A advanced scatterometer (ASCAT). Geophys. Res. Lett., 2007, 34, L20401.

  • Bindlish et al., Development and validation of the GCOMW AMSR2 soil moisture product, IGARSS 2016, pp. 1647–1650.

  • Kerr, Y. H., Waldteufel, P., Wigneron, J. P., Martinuzzi, J., Font, J. and Berger, M., Soil moisture retrieval from space: the soil moisture and ocean salinity (SMOS) mission. IEEE Trans. Geosci. Remote Sensing, 2001, 39, 1729–1735.

  • Entakhabi et al., Soil moisture active and passive (SMAP) mission. Proc. IEEE, 2010, 98(5), 704–716.

  • Das, N. et al., An algorithm for merging SMAP radiometer and radar data for high resolution soil moisture retrieval. IEEE Trans. GeoSci. Remote Sensing, 2011, 49(5), 1504–1512.

  • Ujjwal Narayan and Venkat Lakshmi, A simple method for spatial disaggregation of radiometer derived soil moisture using higher resolution radar observations. Progress in Electromagnetics Research Symposium 2005, Hangzhou, China, 22–26 August.

  • Long, D. G. and Daum, D., Spatial resolution enhancement of SSM/I data. IEEE Trans. Geosci. Remote Sensing, 1997, 36, 407– 417.

  • Jalpa, M. and Kirti, P., Generation of high resolution sigma-0 through algebraic reconstruction, Scientific report/SAC/SIPA/ DPSG/AIPD/TN-09/Jul., 2015.

  • Jalpa, M., Evaluation of OSCAT high resolution sigma-0 products generated at SAC Scientific report, SAC/SIPG/MDPD/SCATDP/ TN-01/Mar. 2016, 2016.

  • Ray, S. S. and Dubey, S., Space technology use in crop insurance. In E-Agriculture in Action: Drones for Agriculture (ed. Sylvester, G.), Food and Agriculture Organization of the United Nations and International Telecommunication Union. Bangkok, 2017, pp. 65– 70.

  • Chaurasia et al., Assessment of the AMSR-E soil moisture product over India. Int. J. Remote Sensing, 2011, 32(23), 7955–7970.

  • Lehrsch, G. A., Whisler, F. D. and Römkens, M. J. M., Spatial variation of parameters describing soil surface roughness. Soil Sci. Soc. Am. J., 1988, 52, 311–319.

  • Wild, A., Soil and the Environment: An Introduction, Cambridge University Press, Cambridge, 1993, p. 287.

  • Lehrsch, G. A., Whisler, F. D. and Römkens, M. J. M., Soil surface roughness as influences by selected soil physical properties. Soil Till. Res., 1987, 10, 197–212.

  • Lehrsch, G. A., Whisler, F. D. and Römkens, M. J. M., Selection of a parameter describing soil surface roughness. Soil Sci. Soc. Am. J., 1988, 52, 1439–1445.

  • Ellis, S. and Mellor, A., Soils and Environment, Routledge, London, 1995, p. 364.

  • Ujjwal Singh, P. K. et al., Assessment of ScatSat-1 backscattering by using the state of the art water cloud model. International Conference on Geomatics in Civil Engineering (ICGCE-2018), 5–6 April 2018, IIT Roorkee, 2018.


Abstract Views: 383

PDF Views: 131




  • Crop Phenology and Soil Moisture Applications of SCATSAT-1

Abstract Views: 383  |  PDF Views: 131

Authors

Nilima R. Chaube
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Sasmita Chaurasia
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Rojalin Tripathy
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Dharmendra Kumar Pandey
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Arundhati Misra
Space Applications Centre, ISRO, Ahmedabad 380 015, India
B. K. Bhattacharya
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Prakash Chauhan
Indian Institute of Remote Sensing, Dehradun 248 001, India
Kiran Yarakulla
Vellore Institute of Technology, Vellore 632 014, India
G. D. Bairagi
M.P. Council of Science and Technology, Bhopal 462 003, India
Prashant Kumar Srivastava
Banaras Hindu University, Varanasi 221 005, India
Preeti Teheliani
Mahalanobis National Crop Forecast Centre, Delhi 110 012, India
S. S. Ray
Mahalanobis National Crop Forecast Centre, Delhi 110 012, India

Abstract


SCATSAT-1 measures the backscattering coefficient over land surfaces, which is a function of vegetation structure, surface roughness, soil moisture content, incidence angle and dielectric properties of vegetation. Scatterometer image reconstruction techniques provide fine resolution data to explore the emerging applications over land by using ambiguous backscatter from land. In this paper, 2 km resolution products of ISRO’s scatterometer SCATSAT-1 are exploited for land target detection, rice crop phenology stages detection for kharif and rabi seasons and estimation of relative soil moisture over parts of India. Temporal and spatial backscatter changes are due to seasonal and changes in Land Use Land Cover. Crop phenology stages such as transplanting, maximum tillering, panicle emergence and physiological maturity stages are identified by analysing SCATSAT-1 time series along with NDVI and findings are supported by appropriate ground truth observations and crop cutting experiment (CCE) data. The relative soil moisture change detection is validated with in situ ground truth measurements using Hydraprobe, carried for SCATSAT-1 ascending and descending passes.

Keywords


Crop Phenology, Gamma-0, Rice, Sigma-0, Soil Moisture, Vegetation Dynamics.

References





DOI: https://doi.org/10.18520/cs%2Fv117%2Fi6%2F1022-1031