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Year 2021, Volume: 8 Issue: 1, 33 - 38, 07.03.2021
https://doi.org/10.30897/ijegeo.773860

Abstract

References

  • 1. Boken, V., Shaykewich, C.F., 2002. Improving an Operational Wheat Yield Model using Phenological Phase-based Normalized Difference Vegetation Index, International Journal of Remote Sensing, 23(20):4155-4168
  • 2. Doraiswamy, P.C., and Cook, P W., 1995. Spring Wheat Yield Assessment Using NOAA AVHRR Data, Canadian Journal of Remote Sensing, 21(1), 43-51
  • 3. Groten S.M.E., 1993. NDVI- monitoring and early yield assessment of Burkina Faso, International Journal of Remote Sensing, 14(8), 1495-1515
  • 4. Labus, M.P., Nielsen, G.A., Lawrence, R.L., Engel, R., Long, D.S., 2002. Wheat Yield Estimates using Multi-temporal NDVI Satellite Imagery, International Journal of Remote Sensing, 23(20): 4169-4180
  • 5. Patel, J. H., and Oza, M.P., 2014. Deriving Crop Calendar using NDVI Time-Series. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-8, 2014 ISPRS Technical Commission VIII Symposium, 09 – 12 December 2014, Hyderabad, India.
  • 6. Rajak, D., Ram, J., Rajesh K., and Ray, S. S., 2016. Early estimation of crop sown area by integrating multi-source data. Journal of Geomatics, Vol. 10 No. 1, April 2016, pp. 80 – 88.
  • 7. Quarmby, N.A., Milnes, M., Hindle, T. L., Silleos, N., 1993. The use of multi-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction, International Journal of Remote Sensing, 14(2), 199-210
  • 8. Tucker C.J., Elgin J.H., McMurtrey, 1980. Relationship of red and photographic infrared spectral data to alfalfa biomass, canopy cover and drought stress, International Journal of Remote Sensing, 1(1):(in press)
  • https://earthexplorer.usgs.gov/download/options/12267/LE70970682017017ASA00/

Winter Crop Growth Monitoring using Multi-Temporal NDVI Profiles in Kapadvanj Taluka, Gujarat State

Year 2021, Volume: 8 Issue: 1, 33 - 38, 07.03.2021
https://doi.org/10.30897/ijegeo.773860

Abstract

In the present study on winter crop growth monitoring in different villages in Kapadvanj Taluka of Kheda district was carried out using multi-temporal Sentinel-2 multi-spectral data (spatial resolution 10-m). Multi-temporal Sentinel-2 data covering study area for the winter crop period from November-2018 to March-2019 was downloaded from https://earthexplorer.usgs.gov/. The major objective of this study was to monitor site-specific crop growth in different villages of Kapadvanj Taluka by generating Normalized Difference Vegetation Index (NDVI) profiles of major winter crops. The spectral behavior of wheat, potato, bajara and castor crops during active growth stages was studied and it was observed that the spectral response of wheat and potato crops have quite distinct spectral behavior. However, castor and bajara crops do not show distinct spectral behavior. In this study, from the NDVI profiles of different crops it was observed that very distinct growth stages like early growth stage to flag leaf emergence which correspondence to rising of NDVI, followed by flag leaf emergence to flowering and grain filling stages which corresponds to maximum NDVI and finally physiological maturity stages corresponding to declining of NDVI of all the winter crops.

References

  • 1. Boken, V., Shaykewich, C.F., 2002. Improving an Operational Wheat Yield Model using Phenological Phase-based Normalized Difference Vegetation Index, International Journal of Remote Sensing, 23(20):4155-4168
  • 2. Doraiswamy, P.C., and Cook, P W., 1995. Spring Wheat Yield Assessment Using NOAA AVHRR Data, Canadian Journal of Remote Sensing, 21(1), 43-51
  • 3. Groten S.M.E., 1993. NDVI- monitoring and early yield assessment of Burkina Faso, International Journal of Remote Sensing, 14(8), 1495-1515
  • 4. Labus, M.P., Nielsen, G.A., Lawrence, R.L., Engel, R., Long, D.S., 2002. Wheat Yield Estimates using Multi-temporal NDVI Satellite Imagery, International Journal of Remote Sensing, 23(20): 4169-4180
  • 5. Patel, J. H., and Oza, M.P., 2014. Deriving Crop Calendar using NDVI Time-Series. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-8, 2014 ISPRS Technical Commission VIII Symposium, 09 – 12 December 2014, Hyderabad, India.
  • 6. Rajak, D., Ram, J., Rajesh K., and Ray, S. S., 2016. Early estimation of crop sown area by integrating multi-source data. Journal of Geomatics, Vol. 10 No. 1, April 2016, pp. 80 – 88.
  • 7. Quarmby, N.A., Milnes, M., Hindle, T. L., Silleos, N., 1993. The use of multi-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction, International Journal of Remote Sensing, 14(2), 199-210
  • 8. Tucker C.J., Elgin J.H., McMurtrey, 1980. Relationship of red and photographic infrared spectral data to alfalfa biomass, canopy cover and drought stress, International Journal of Remote Sensing, 1(1):(in press)
  • https://earthexplorer.usgs.gov/download/options/12267/LE70970682017017ASA00/
There are 9 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Disha Mehta 0000-0003-1331-698X

Shital H. Shukla This is me

Manik H. Kalubarme This is me

Publication Date March 7, 2021
Published in Issue Year 2021 Volume: 8 Issue: 1

Cite

APA Mehta, D., Shukla, S. H., & Kalubarme, M. H. (2021). Winter Crop Growth Monitoring using Multi-Temporal NDVI Profiles in Kapadvanj Taluka, Gujarat State. International Journal of Environment and Geoinformatics, 8(1), 33-38. https://doi.org/10.30897/ijegeo.773860