An estimation of the optimum temporal resolution for monitoring vegetation condition on a nationwide scale using MODIS/Terra data

International Journal of Remote Sensing

Volumn 29, Issue 12, 2008, Pages 3589-3607

  Alexandridis, T K ^a   Gitas, I Z ^a   Silleos, N G ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; QUALITY CONTROL; RADIOMETERS; TIME SERIES ANALYSIS; VEGETATION;

AUTOCORRELATION ANALYSIS; MEDITERRANEAN REGION; NORMALIZED DIFFERENCE VEGETATION INDEX; OPERATIONAL MONITORING; REMOTELY SENSED DATA; VEGETATION CATEGORIES; VEGETATION CONDITION; VEGETATION MONITORING;

CONDITION MONITORING;

AUTOCORRELATION; DATA SET; ESTIMATION METHOD; MODIS; MONITORING; NDVI; QUALITATIVE ANALYSIS; SATELLITE DATA; SATELLITE IMAGERY; SMOOTHING; SPECTRAL REFLECTANCE; TIME SERIES ANALYSIS; VEGETATION MAPPING;

MEDITERRANEAN REGION; MEDITERRANEAN SEA;

EID: 46349091158     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160701564618     Document Type: Article

References (51)

1. Asrar, G., Fuchs, M., Kanemasu, E. T. and Hatfield, J. L. (1984) Estimating absorbed photosynthetic radiation and leaf-area index from spectral reflectance in wheat. Agronomy Journal, 76, pp. 300-306.
2. Atkinson, P. M. (1991) Optimal ground-based sampling for remote-sensing investigations-estimating the regional mean. International Journal of Remote Sensing, 12, pp. 559-567.
3. Baret, F. and Guyot, G. (1991) Potentials and limits of vegetation indexes for LAI and APAR assessment. Remote Sensing of Environment, 35, pp. 161-173.
4. Bian, L. (1997) Multiscale nature of spatial data in scaling up environmental methods. Scale in Remote Sensing and GIS, pp. 13-26. CRC Press Inc., Boca Raton, FL
5. Biggs, T. W., Thenkabail, P. S., Gumma, M. K., Scott, C. A., Parthasaradhi, G. R. and Turral, H. N. (2006) Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India. International Journal of Remote Sensing, 27, pp. 4245-4266.
6. Cao, C. and Lam, N. S. (1997) Understanding the scale and resolution effects in remote sensing. Scale in Remote Sensing and GIS, pp. 57-72. CRC Press Inc., Boca Raton, FL
7. Chuvieco, E., Ventura, G., Martin, M. P. and Gomez, I. (2005) Assessment of multitemporal compositing techniques of MODIS and AVHRR images for burned land mapping. Remote Sensing of Environment, 94, pp. 450-462.
8. Cihlar, J., Manak, D. and Dapos Iorio, M. (1994) Evaluation of compositing algorithms for AVHRR data over land. IEEE Transactions on Geoscience and Remote Sensing, 32, pp. 427-437.
9. Curran, P. J. and Atkinson, P. M. (1998) Geostatistics and remote sensing. Progress in Physical Geography, 22, pp. 61-78.
10. Durbin, J. and Watson, G. S. (1971) Testing for serial correlation in least squares regression. 3. Biometrika, 58, pp. 1-42.
11. EC (1999) Council Regulation (EC) No 1251/1999 of 17 May 1999 establishing a support system for producers of certain arable crops. Official Journal, pp. 1-14.
12. EC (1999) European Council Regulation (EC) No 1257/1999 of 17 May 1999 on support for rural development from the European Agricultural Guidance and Guarantee Fund (EAGGF) and amending and repealing certain regulations. Official Journal, pp. 80-101.
13. EC (2003) Regulation (EC) No 2152/2003 of the European Parliament and of the Council of 17 November 2003 concerning monitoring of forests and environmental interactions in the community (Forest Focus). Official Journal, pp. 1-8.
14. Eubank, R. L. (1988) Spline Smoothing and Nonparametric Regression, Marcel Dekker Inc., New York
15. Ferraz, S. F. D., Capao, L. and Vettorazzi, C. A. (2006) Temporal scale and spatial resolution effects on Amazon forest fragmentation assessment in Rondonia. International Journal of Remote Sensing, 27, pp. 459-472.
16. Ferreira, L. G. and Huete, A. R. (2004) Assessing the seasonal dynamics of the Brazilian Cerrado vegetation through the use of spectral vegetation indices. International Journal of Remote Sensing, 25, pp. 1837-1860.
17. Gao, B. C. (1996) NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, pp. 257-266.
18. Gardner, E. S. (1985) Exponential smoothing-the state of the art. Journal of Forecasting, 4, pp. 1-28.
19. Gitas, I. Z., Mitri, G., Avyikou, I. and Diamanti, E. (2004) Vegetation greenness mapping of Greece using MODIS imagery. Workshop on MODIS Data and Imagery: How to Get and Use Them
20. Goodchild, M. F. and Quattrochi, D. A. (1997) Introduction: Scale, multiscaling, remote sensing, and GIS. Scale in Remote Sensing and GIS, pp. 1-13. CRC Press Inc., Boca Raton, FL
21. Gumpertz, M. L., Wu, C. and Pye, J. M. (2000) Logistic regression for southern pine beetle outbreaks with spatial and temporal autocorrelation. Forest Science, 46, pp. 95-107.
22. Hoffer, R. M. (1978) Biological and physical considerations in applying computer-aided analysis techniques to remote sensor data. Remote Sensing: The Quantitative Approach, pp. 227-289. McGraw-Hill International Book Co., London
23. Huete, A. R., Jackson, R. D. and Post, D. F. (1985) Spectral response of a plant canopy with different soil backgrounds. Remote Sensing of Environment, 17, pp. 37-53.
24. Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X. and Ferreira, L. G. (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, pp. 195-213.
25. Intriligator, M. D., Bodkin, R. G. and Xiao, Z. (1996) Econometric Models, Techniques and Applications, Prentice-Hall International, Upper Saddle River, N.J.
26. Jupp, D. L. B., Strahler, A. H. and Woodcock, C. E. (1988) Auto-correlation and regularization in digital images. 1. Basic theory. IEEE Transactions on Geoscience and Remote Sensing, 26, pp. 463-473.
27. Kohyama, T., Kubo, T. and Macklin, E. (2005) Effect of temporal autocorrelation on apparent growth rate variation in forest tree census data and an alternative distribution function of tree growth rate. Ecological Research, 20, pp. 11-15.
28. Kriegler, F. J., Malila, W. A., Nalepka, R. F. and Richardson, W. (1969) Preprocessing transformations and their effects on multispectral recognition. Proceedings of 6th International Symposium on Remote Sensing of Environment, pp. 97-131.
29. Loukas, A., Vasiliades, L., Dalezios, N. R. and Domenikiotis, C. (2001) Rainfall-frequency mapping for Greece. Physics and Chemistry of the Earth Part B-Hydrology Oceans and Atmosphere, 26, pp. 669-674.
30. Lunetta, R. S., Johnson, D. M., Lyon, J. G. and Crotwell, J. (2004) Impacts of imagery temporal frequency on land-cover change detection monitoring. Remote Sensing of Environment, 89, pp. 444-454.
31. Marceau, D. J., Gratton, D. J., Fournier, R. A. and Fortin, J. P. (1994) Remote-sensing and the measurement of geographical entities in a forested environment. 2. The optimal spatial-resolution. Remote Sensing of Environment, 49, pp. 105-117.
32. Marshall, H. E. (1999) Sensitivity analysis. The Technology Management Handbook, p. 8/59. CRC Press Inc., Boca Raton, FL
33. Maselli, F. (2004) Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data. Remote Sensing of Environment, 89, pp. 423-433.
34. McGarigal, K. and Marks, B. J. (1994) FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure, Version 2.0, Forest Science Department, Oregon State University, Corvallis, OR
35. Moulin, S., Kergoat, L., Viovy, N. and Dedieu, G. (1997) Global-scale assessment of vegetation phenology using NOAA/AVHRR satellite measurements. Journal of Climate, 10, pp. 1154-1170.
36. N'Kanza, S. and Naizot, T. (1993) A method for the structural analysis of degraded images. Photo-interpretation, 1, pp. 5-16.
37. Perrier, E. R. and Wilding, L. P. (1986) An evaluation of computational methods for field uniformity studies. Advances in Agronomy, 39, pp. 265-312.
38. Qi, J., Huete, A. R., Hood, J. and Kerr, Y. (1993) Compositing multi-temporal remote sensing data sets. Pecora 12, pp. 206-213. American Society of Photogrammetry and Remote Sensing, Sioux Falls, SD
39. Reinsch, C. (1967) Smoothing by spline functions. Numerische Mathematik, 10, pp. 177-183.
40. Rouse, J. W. Jr., Hase, R. H., Schell, J. A. and Deering, D. W. (1973) Monitoring vegetation systems in the great plain with ERTS. Proceedings of 3rd ERTS Symposium, 1, pp. 309-317.
41. Roy, D. P., Borak, J. S., Devadiga, S., Wolfe, R. E., Zheng, M. and Descloitres, J. (2002) The MODIS land product quality assessment approach. Remote Sensing of Environment, 83, pp. 62-76.
42. Shannon, C. and Weaver, W. (1949) The Mathematical Theory of Communication, University of Illinois Press, Urbana
43. Silleos, N., Perakis, K. and Petsanis, G. (2002) Assessment of crop damage using space remote sensing and GIS. International Journal of Remote Sensing, 23, pp. 417-427.
44. Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P. and Macomber, S. A. (2001) Classification and change detection using Landsat TM data: when and how to correct atmospheric effects?. Remote Sensing of Environment, 75, pp. 230-244.
45. Sousa, A. M. O., Pereira, J. M. C. and Silva, J. M. N. (2003) Evaluating the performance of multitemporal image compositing algorithms for burned area analysis. International Journal of Remote Sensing, 24, pp. 1219-1236.
46. Townshend, J. R. G. and Justice, C. O. (2002) Towards operational monitoring of terrestrial systems by moderate-resolution remote sensing. Remote Sensing of Environment, 83, pp. 351-359.
47. van Leeuwen, W. J. D., Huete, A. R. and Laing, T. W. (1999) MODIS vegetation index compositing approach: A prototype with AVHRR data. Remote Sensing of Environment, 69, pp. 264-280.
48. White, K. J. (1992) The Durbin-Watson test for autocorrelation in nonlinear models. Review of Economics and Statistics, 74, pp. 370-373.
49. White, M. A., Thornton, P. E. and Running, S. W. (1997) A continental phenology model for monitoring vegetation responses to interannual climatic variability. Global Biogeochemical Cycles, 11, pp. 217-234.
50. Wooldridge, J. M. (2000) Introductory Econometrics: A Modern Approach, South-Western College Publishing, Cincinnati, OH
51. Zhang, X. Y., Friedl, M. A., Schaaf, C. B., Strahler, A. H., Hodges, J. C. F., Gao, F., Reed, B. C. and Huete, A. (2003) Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84, pp. 471-475.