Noise reduction of NDVI time series: An empirical comparison of selected techniques

Remote Sensing of Environment

Volumn 113, Issue 1, 2009, Pages 248-258

  Hird, Jennifer N ^a   McDermid, Gregory J ^a  

^a UNIVERSITY OF CALGARY   (Canada)

Author keywords

MODIS; NDVI time series; Noise reduction; Vegetation phenology

Indexed keywords

ACOUSTIC NOISE MEASUREMENT; FORESTRY; FUNCTIONS; REMOTE SENSING; SPACE OPTICS; VEGETATION;

ATMOSPHERIC CONDITIONS; EMPIRICAL COMPARISONS; FILTERING TECHNIQUES; FITTING METHODS; GAUSSIAN FUNCTIONS; MODEL-BASED; MODIS; NDVI DATUMS; NDVI TIME SERIES; NOISE LEVELS; NOISE REDUCTION; NOISE REDUCTIONS; REDUCTION TECHNIQUES; TIME SERIES; VEGETATION PHENOLOGIES; VEGETATION PHENOLOGY;

TIME SERIES ANALYSIS;

COMPARATIVE STUDY; DATA SET; ENVIRONMENTAL CONDITIONS; MODIS; NDVI; PHENOLOGY; REMOTE SENSING; TIME SERIES;

EID: 56949107790     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2008.09.003     Document Type: Article

References (44)

1. Badeck F.-W., Bondeau A., Böttcher K., Doktor D., Lucht W., Schaber J., et al. Responses of spring phenology to climate change. New Phytologist 162 (2004) 295-309
2. Beck P., Atzberer C., Høgda K., Johansen B., and Skidmore A. Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI. Remote Sensing of Environment 100 (2006) 321-334
3. Beck P., Jönsson P., Høgda K., Karlsen S., Eklundh L., and Skidmore A. A ground-validated NDVI dataset for monitoring vegetation dynamics and mapping phenology in Fennoscandia and the Kola peninsula. International Journal of Remote Sensing 28 (2007) 4311-4330
4. Bradley B., Jacob R., Hermance J., and Mustard J. A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data. Remote Sensing of Environment 106 (2007) 137-145
5. Carreiras J., Pereira J., Shimabukuro Y., and Stroppiana D. Evaluation of compositing algorithms over the Brazilian Amazon using SPOT-4 VEGETATION data. International Journal of Remote Sensing 24 (2003) 3427-3440
6. Chen J., Jönsson P., Tamura M., Gu Z., Matsushita B., and Eklundh L. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sensing of Environment 91 (2004) 332-334
7. DeFries R., and Townshend J. NDVI-derived land cover classification at a global scale. International Journal of Remote Sensing 15 (1994) 3567-3586
8. DeFries R., Hansen M., and Townshend J. Global discrimination of land cover types from metrics derived from AVHRR Pathfinder data. Remote Sensing of Environment 54 (1995) 209-222
9. EOS. Land Processes Data Active Archive Center Earth Observing System Data Gateway (2006). http://lpdaac.usgs.gov Available online at: http://lpdaac.usgs.gov
10. Filipova-Racheva D., and Hall-Beyer M. Smoothing of NDVI time series curves for monitoring of vegetation changes in time. Ecological Monitoring and Assessment Network National Science Meeting 2000, Toronto, Ontario, Canada, January 17-22, 2000. (2000). http://www.eman-rese.ca/eman/reports/meetings/national2000/toc_posters.html Available online at: http://www.eman-rese.ca/eman/reports/meetings/national2000/toc_posters.html
11. Goward S., Markham B., and Dye D. Normalized difference vegetation index measurements from the advanced very high resolution radiometer. Remote Sensing of Environment 35 (1991) 257-277
12. Gutman G. Vegetation indices from AVHRR: An update and future prospects. Remote Sensing of Environment 35 (1991) 121-136
13. Hebblewhite M., Merrill E., and McDermid G.J. A multi-scale test of the forage maturation hypothesis in a partially migratory ungulate population. Ecological Monographs 78 (2008) 141-166
14. Holben B. Characteristics of maximum-value composite images from temporal AVHRR data. International Journal of Remote Sensing 7 (1986) 1417-1434
15. Hoblen B., and Fraser R.S. Red and near-infrared response to off-nadir viewing. International Journal of Remote Sensing 5 (1984) 145-460
16. Huete A. A soil-adjusted vegetation index (SAVI). Remote Sensing of Evironment 25 (1988) 295-309
17. Huete A., Justice C., and van Leeuwen. MODIS Vegetation Index (MOD13) Algorithm Theoretical Basis Document, Version 3 (1999). http://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf Available at: http://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf
18. Hurlbert A.H., and Haskell J.P. The effect of energy and seasonality on avian species richness and community composition. The American Naturalist 16 (2003) 83-97
19. Jönsson P., and Eklundh L. Seasonality extraction by function-fitting to time series of satellite sensor data. IEEE Transactions on Geoscience and Remote Sensing 40 (2002) 1824-1832
20. Jönsson P., and Eklundh L. TIMESAT - A program for analyzing time-series of satellite sensor data. Computers and Geoscience 30 (2004) 833-845
21. Jönsson P., and Eklundh L. TIMESAT - A program for analyzing time-series of satellite sensor data: User's Guide for TIMESAT 2.3 (2006), Malmö and Lund, Sweden 3-10
22. Jordan C. Derivation of leaf area index from quality of light on the forest floor. Ecology 50 (1969) 663-666
23. Kaufman Y., and Tanré D. Atmospherically resistant vegetation index (ARVI) for EOS-MODIS. IEEE Transactions on Geoscience and Remote Sensing 30 (1992) 261-270
24. Kobayashi H., and Dye D. Atmospheric conditions for monitoring the long-term dynamics in the Amazon using normalized difference vegetation index. Remote Sensing of Environment 97 (2005) 519-525
25. LP DAAC. MODIS Vegetation Indices QA Science Data Sets (2005). http://lpdaac.usgs.gov/modis/moyd13_qa_v4.asp Available at: http://lpdaac.usgs.gov/modis/moyd13_qa_v4.asp
26. Li Z., and Strahler A. Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing. IEEE Transactions on Geoscience and Remote Sensing 30 (1992) 376-292
27. Lovell J., and Graetz R. Filtering pathfinder AVHRR land NDVI data for Australia. International Journal of Remotes Sensing 22 (2001) 2649-2654
28. Ma M., and Veroustraete F. Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China. Advances in Space Research 37 (2006) 835-840
29. Moody A., and Johnson D. Land-surface phenologies from AVHRR using the discrete fourier transform. Remote Sensing of Environment 75 (2001) 305-323
30. Myneni R., Hall F., Sellers P., and Marshak A. The interpretation of spectral vegetation indexes. IEEE Transactions on Geoscience and Remote Sensing 33 (1995) 481-486
31. Natural Regions Committee. Natural regions and subregions of Alberta (2006), Government of Alberta, Alberta 1-162 Pub. No. T/852
32. Qi J., Chehbouni A., Huete A., Kerr Y., and Sorooshian S. A modified soil adjusted vegetation index. Remote Sensing of Environment 48 (1994) 119-126
33. Rabiner L., Sambur M., and Schmidt C. Applications of a nonlinear smoothing algorithm to speech processing. IEEE Transactions on Acoustics, Speech, and Signal Processing 23 (1975) 552-557
34. Reed B., Brown J., VanderZee D., Loveland T., Merchant J., and Ohlen D. Measuring phenological variability from satellite imagery. Journal of Vegetation Science 5 (1994) 703-714
35. Reed B., White M., and Brown J. Remote Sensing Phenology. In M. D. Schwartz (Ed.), Phenology: An Integrative Environmental Science (pp. 365-381) (2003), Dordrecht, Netherlands: Kluwer Academic Publishers
36. Roerink G., Menenti M., and Verhoef W. Reconstructing cloudfree NDVI composites using Fourier analysis of time series. International Journal of Remote Sensing 21 (2000) 1911-1917
37. Savitzky A., and Golay M. Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry 36 (1964) 1627-1639
38. Sellers P., Tucker C., Collatz G., Los S., Justice C., Dazlich D., et al. A global 10 by 10 NDVI data set for global studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI. International Journal of Remote Sensing 15 (1994) 3519-3545
39. Swets D., Reed B., Rowland J., and Marko S. A weighted least-squares approach to temporal smoothing of NDVI. 1999 ASPRS Annual Conference, From Image to Information, Portland, Oregon, May 17-21, 1999, Proceedings: Bethesda, Maryland (1999), American Society for Photogrammetry and Remote Sensing
40. van Dijk A., Callis S., Sakamoto C., and Decker W. Smoothing vegetation index profiles: An alternative method for reducing radiometric disturbance in NOAA/AVHRR data. Photogrammetric Engineering and Remote Sensing 53 (1987) 1059-1067
41. Velleman P. Definition and comparison of robust nonlinear data smoothing algorithms. Journal of the American Statistical Association 75 (1980) 609-615
42. Viovy N., Arino O., and Velward A. The Best Index Slope Extraction (BISE): A method for reducing noise in NDVI time-series. International Journal of Remote Sensing 13 (1992) 1585-1590
43. Wang Q., Adiku S., Tenhunen J., and Granier A. On the relationship of NDVI with leaf area index in a deciduous forest site. Remote Sensing of Environment 94 (2005) 244-255
44. Willmott C. Some comments on the evaluation of model performance. Bulletin American Meteorological Society 63 (1982) 1309-1313