The remote sensing approach in broad-scale phenological studies

Applied Vegetation Science

Volumn 3, Issue 1, 2000, Pages 117-122

  Ricotta, C ^a   Avena, G C ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Advanced Very High Resolution Radiometer; Ecosystem seasonality; Maximum value compositing; Normalized difference vegetation index; Phenology

Indexed keywords

EID: 0034088199     PISSN: 14022001     EISSN: None     Source Type: Journal    
DOI: 10.2307/1478925     Document Type: Article

References (44)

1. Achard, F. & Estreguil, C. 1995. Forest classification of southeast Asia using NOAA AVHRR data. Remote Sens. Environ. 54: 198-208.
2. Andres, L., Salas, W.A. & Skole, D. 1994. Fourier analysis of multi-temporal AVHRR data applied to a land cover classification. Int. J. Remote Sens. 15: 1115-1121.
3. Anyamba, A. & Eastman, J.R. 1996. Interannual variability of NDVI over Africa and its relation to El Nino/Southern Oscillation. Int. J. Remote Sens. 17: 2533-2548.
4. Badhwar, G.D. & Henderson, K.E. 1985. Application of Thematic Mapper data to corn and soybean development stage estimation. Remote Sens. Environ. 17: 197-201.
5. Baret, F. & Guyot, G. 1986. Suivi de la maturation de couverts de blé par radiométrie dans les domaines visible et proche infra-rouge. Agronomie 6: 509-516.
6. Barnes, W.L., Pagano, T.S. & Solomonson, V.V. 1998. Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AMI. IEEE Trans. Geosci. Remote Sens. 36: 1088-1098.
7. Bergmeier, E. 1998. The phenological approach in Mediterranean landscape analysis. Phytocoenologia 28: 145-156.
8. Cross, A.M., Drake, N.A., Paivinen, R.T.M. & Settle, J.J. 1991. Sub-pixel measurement of tropical forest cover using AVHRR data. Int. J. Remote Sens. 12: 1119-1129.
9. Dierschke, H. 1990. Bibliographia symphaenologica. Excerpta Bot. Sect. B 28: 49-87.
10. Dierschke, H. 1994. Pflanzensoziologie. Grundlagen und Methoden. Ulmer, Stuttgart.
11. Eastman, J.R. & Fulk, M. 1993. Long sequence time series evaluation using standardized principal components. Photogramm. Engin. Remote Sens. 59: 991-996.
12. Ellenberg, H. & Ellenberg, C. 1956. Wuchsklimakarte von Südwest-Deutschland 1:200 000. Nördlicher und südlicher Teil. Reise- und Verkehrsverlag, Stuttgart.
13. Estes, J.E., Belward, A.S., Loveland, T.R., Scepan, J., Strahler, A., Townshend, J.R.C. & Justice, C.O. 1999. The way forward. Photogramm. Engin. Remote Sens. 65: 1089-1093.
14. Hirosawa, Y., Marsh, S.E. & Kliman, D.H. 1996. Application of standardized principal component analysis to landcover characterization using multitemporal AVHRR data. Remote Sens. Environ. 58: 267-281.
15. Holben, B.N. 1986. Characteristics of maximum-value composite images from temporal AVHRR data. Int. J. Remote Sens. 7: 1417-1434.
16. Kelly, M., Estes, J.E. & Knight, K.A. 1999. Image interpretation keys for validation of global land-cover data sets. Photogramm. Eng. Remote Sens. 65: 1041-1049.
17. Lambin, E.F. 1996. Change detection at multiple temporal scales: seasonal and annual variations in landscape variables. Photogramm. Engin. Remote Sens. 62: 931-938.
18. Lambin, E.F. & Strahler, A. 1994. Change-vector analysis in multitemporal space: a tool to detect and categorize landcover change processes using high temporal-resolution satellite data. Remote Sens. Environ. 48: 231-244.
19. Lieth, H. 1974. Phenology and seasonality modeling. Springer Verlag, Berlin.
20. Lloyd, D. 1990. A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery. Int. J. Remote Sens. 11: 2269-2279.
21. Los, S.O., Justice, C.O. & Tucker, C.J. 1994. A global 1° by 1° NDVI data set for climate studies derived from the GIMMS continental NDVI data. Int. J. Remote Sens. 15: 3493-3518.
22. Loveland, T.R., Merchant, J.W., Ohlen, D.O. & Brown, J.F. 1991. Development of a land-cover characteristics data-base for the conterminous U.S. Photogramm. Engin. Remote Sens. 57: 1453-1643.
23. Menenti, M., Azzali, S., Verhoef, W. & Van Swol, R. 1993. Mapping agro-ecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images. Adv. Space Res. 13: 233-237.
24. Monteith, J.L. 1977. Climate and efficiency of crop production in Britain. Phil. Trans. R. Soc. Lond. B 271: 277-294.
25. Muchoney, D., Strahler, A., Hodges, J. & Locastro, J. 1999. The IGP DISCover confidence sites and the system for terrestrial ecosystem parametrization: Tools for describing and validating global land-cover data. Photogramm. Engin. Remote Sens. 65: 1061-1067.
26. Odenweller, J.B. & Johnson, K.I. 1984. Crop identification using Landsat temporal-spectral profiles. Remote Sens. Environ. 14: 39-54.
27. Primack, R.B. 1985. Patterns of flowering phenology in communities, populations, individuals, and single flowers. In: White, J. (ed.) The population structure of vegetation, pp. 571-593. Junk, Dordrecht.
28. Ramsey, R.D., Falconer, A. & Jensen, J.R. 1995. The relationship between NOAA-AVHRR NDVI and Ecoregions in Utah. Remote Sens. Environ. 53: 188-198.
29. Rast, M., Bézy, J.L. & Bruzzi, S. 1999. The ESA Medium Resolution Imaging Spectrometer MERIS - a review of the instrument and its mission. Int. J. Remote Sens. 20: 1681-1702.
30. Rathcke, B. & Lacey, E.P. 1985. Phenological patterns of terrestrial plants. Annu. Rev. Ecol. Syst. 16: 179-214.
31. Reed, B.C. & Sayler, K. 1998. A method for deriving phenological metrics from satellite data, Colorado 1991-1995. In: Proceedings of the Northern Great Plains Regional Workshop on Climate Change and Climate Variability, pp. 47-55. University of North Dakota Press, Grand Forks, ND.
32. Reed, B.C., Brown, J.F., VanderZee, D., Loveland, T.R., Merchant, J.W. & Ohlen, D.O. 1994. Measuring phenological variability from satellite imagery. J. Veg. Sci. 5: 703-714.
33. Rouse, J.W., Haas, R.H., Schell, J.A. & Deering, D.W. 1974. Monitoring vegetation systems in the Great Plains with ERTS. In: Proceedings of the Third Earth Resources Technology Satellite-1 Symposium, pp: 309-317. Goddard Space Flight Center, NASA SP-351, Science and Technical Information Office, NASA, Washington, DC.
34. Ruimy, A., Saugier, B. & Dedieu, G. 1994. Methodology for the estimation of terrestrial net primary production from remotely sensed data. J. Geophys. Res. D 99: 5263-5283.
35. Running, S.W., Loveland, T.R. & Pierce, L.L. 1994. A vegetation classification logic based on remote sensing for use in global biogeochemical models. Ambio 23: 77-81.
36. Samson, S.A. 1993. Two indices to characterize temporal patterns in the spectral response of vegetation. Photogramm. Engin. Remote Sens. 59: 511-517.
37. Sellers, P.J., Tucker, C.J., Collatz, G.J., Los, S.O., Justice, C.O., Dazlich, D.A. & Randall, D.A. 1994. A global 1° by 1° NDVI data set for climate studies. Part 2: the generation of global fields of terrestrial biophysical parameters from the NDVI. Int. J. Remote Sens. 15: 3519-3545.
38. Taddei, R. 1997. Maximum value interpolated (MVI): a maximum value composite method improvement in vegetation index profile analysis. Int. J. Remote Sens. 18: 2365-2370.
39. Townshend, J.R.G., Goff, T.E. & Tucker, C.J. 1985. Multitemporal dimensionality of images of normalized difference vegetation index at continental scales. IEEE Trans. Geosci. Remote Sens. 23: 888-895.
40. Trichon, V., Ducrot, D. & Gastellu-Etchegorry, J.P. 1999. SPOT4 potential for the monitoring of tropical vegetation. A case study in Sumatra. Int. J. J. Remote Sens. 20: 2761-2785.
41. Tucker, C.J, Holben, B.N., Elgin, J.H. & McMurtrey, J.E. 1981. Remote sensing of total dry-matter accumulation in winter wheat. Remote Sens. Environ. 11: 171-189.
42. Tucker, C.J, Townshend, J.R.G. & Goff, T.E. 1985. African land-cover classification using satellite data. Science 227: 369-375.
43. van Leeuwen, W.J.D., Huete, A.R. & Laing, T.W. 1999. MODIS vegetation index compositing approach: a prototype with AVHRR data. Remote Sens. Environ. 69: 264-280.
44. Woodwell, G.M., Houghton, R.A., Stone, T.A., Nelson, R.F. & Kovalick, W. 1987. Deforestation in the tropics: new measurements in the Amazon basin using Landsat and NOAA AVHRR imagery. J. Geophys. Res. 92: 2157-2163.