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IETE Technical Review Volume 39, 2022 - Issue 1
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Articles

Forest Change Detection Using an Optimized Convolution Neural Network

Radha SenthilkumarDepartment of Information Technology, Anna University, Madras Institute of Technology Campus, Chennai, IndiaView further author information
,
V. SrinidhiDepartment of Information Technology, Anna University, Madras Institute of Technology Campus, Chennai, IndiaCorrespondence[email protected]
View further author information
,
S. NeelavathiDepartment of Information Technology, Anna University, Madras Institute of Technology Campus, Chennai, IndiaView further author information
&
S. Renuga DeviDepartment of Information Technology, Anna University, Madras Institute of Technology Campus, Chennai, IndiaView further author information
Pages 135-142 | Published online: 11 Oct 2020

References

  • M. Schultz, J. Clevers, and S. Carter, “Performance of vegetation indices from Landsat time series in deforestation monitoring,” Int. J. Appl. Earth Obs. Geoinf., Vol. 52, pp. 318–27, 2016. ISSN 0303-2434. DOI: https://doi.org/10.1016/j.jag.2016.06.020.
  • R. R. Irish, “Landsat 7 automatic cloud cover assessment,” in Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral imagery VI, 23 August 2000.
  • Z. Zhu, and C. E. Woodcock, “Object-based cloud and cloud shadow detection in Landsat imagery,” Remote Sens. Environ., Vol. 118, pp. 83–94, 2011. ISSN 0034-4257. DOI: https://doi.org/10.1016/j.rse.2011.10.028.
  • D. S. Candra, S. Phinn, and P. Scarth, “Cloud and cloud shadow removal of Landsat 8 images using Multitemporal cloud removal method,” in 2017 6th International Conference on Agro-Geoinformatics, IEEE, 2017.
  • M. Sahana, H. Sajjad, and R. Ahmed, “Assessing spatio-temporal health of forest cover using forest canopy density model and forest fragmentation approach in Sundarban reserve forest, India,” Model. Earth Syst. Environ. 2015. DOI: https://doi.org/10.1007/s40808-015-0043-0.
  • E. L. Bullock, C. E. Woodcock, and P. Olofsson, “Monitoring tropical forest degradation using spectral unmixing and Landsat time series analysis,” Remote Sens. Environ., Vol. 238, 2018. ISSN 0034-4257. DOI: https://doi.org/10.1016/j.rse.2018.11.011.
  • F. Gao, T. Hilker, and X. Zhu, “Fusing Landsat and MODIS data for vegetation monitoring,” IEEE Geosci. Remote Sens. Mag., Vol. 3, no. 3, pp. 47–60, 2015. DOI: https://doi.org/10.1109/MGRS.2015.2434351.
  • M. Das, and S. K. Ghosh, “A deep-learning-based forecasting ensemble to predict missing data for remote sensing analysis,” IEEE Geosci. Remote Sens. Lett., Vol. 10, no. 12, pp. 5228–36, 2017. DOI: https://doi.org/10.1109/JSTARS.2017.2760202.
  • C. Manikanta, and V. Mamatha Jadav, “Evaluation of modified PLS regression method to fill the missing values in training dataset,” in International Conference on Smart Sensors and Systems (IC-SSS), 2015.
  • Z. Zhu, “Change detection using Landsat time series: a review of frequencies, preprocessing algorithms and applications,” ISPRS. J. Photogramm. Remote. Sens., Vol. 130, pp. 370–84, 2017. ISSN 0924-2716. DOI: https://doi.org/10.1016/j.isprsjprs.2017.06.013.
  • A. Singh, and K. K. Singh, “Unsupervised change detection in remote sensing images using fusion of spectral and statistical indices,” Egypt. J. Remote Sens. Space Sci., Vol. 21, no. 3, pp. 345–51, 2018. ISSN 1110-9823. DOI: https://doi.org/10.1016/j.ejrs.2018.01.006.
  • S. H. Khan, X. He, F. Porikli, and M. Bennamoun, “Forest change detection in incomplete satellite images with deep neural networks,” IEEE Trans. Geo Sci. Remote Sens., Vol. 55, no. 9, pp. 5407–23, 2017. DOI: https://doi.org/10.1109/TGRS.2017.2707528.
  • https://earthexplorer.usgs.gov

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