Investigation of aggregation effects in vegetation condition monitoring at a national scale

International Journal of Geographical Information Science

Volumn 24, Issue 4, 2010, Pages 507-521

  Alexandridis, T K ^a   Katagis, T ^b   Gitas, I Z ^b   Silleos, N G ^a   Eskridge, K M ^c   Gritzas, G ^b  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^b ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^c UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Modifiable areal unit problem; Modis; Vegetation index; Vegetation monitoring; Zonation

Indexed keywords

MODIS; MONITORING SYSTEM; NDVI; PIXEL; RASTER; SATELLITE SENSOR; VEGETATION DYNAMICS; ZONATION;

GREECE; MEDITERRANEAN REGION;

EID: 77949530214     PISSN: 13658816     EISSN: 13623087     Source Type: Journal    
DOI: 10.1080/13658810902798107     Document Type: Article

References (44)

1. Alexandridis, T.K., Gitas, I.Z., and Silleos, N.G., 2008. An estimation of the optimum temporal resolution for monitoring vegetation condition on a nationwide scale using MODIS/Terra data. International Journal of Remote Sensing, 29, 3589-3607.
2. Asrar, G., et al., 1984. Estimating absorbed photosynthetic radiation and leaf-area index from spectral reflectance in wheat. Agronomy Journal, 76, 300-306.
3. Baret, F. and Guyot, G., 1991. Potentials and limits of vegetation indexes for LAI and APAR assessment. Remote Sensing of Environment, 35, 161-173.
4. Biggs, T.W., et al., 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, 4245-4266.
5. Cao, C. and Lam, N.S., 1997. Understanding the scale and resolution effects in remote sensing. In: D.A. Quattrochi and M.F. Goodchild, eds., Scale in remote sensing and GIS. Boca Raton, FL: CRC Press, Inc., 57-72.
6. Chemin, Y. and Alexandridis, T., 2006.Water productivity at different geographical scales in Zhanghe irrigation district, China. International Journal of Geoinformatics, 2, 9-19.
7. Chuvieco, E., et al., 2005. Assessment of multitemporal compositing techniques of MODIS and AVHRR images for burned land mapping. Remote Sensing of Environment, 94, 450-462.
8. Dall'Olmo, G. and Karnieli, A., 2002. Monitoring phenological cycles of desert ecosystems using NDVI and LST data derived from NOAA-AVHRR imagery. International Journal of Remote Sensing, 23, 4055-4071.
9. Deeming, J.E., et al., 1972. The national fire danger rating system. USDA forest service research paper RM-84, 165.
10. Droogers, P., 2002. Global irrigated area mapping: overview and recommendations, working paper 36. Colombo, Sri Lanka: International Water Management Institute.
11. EC, 2003. Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003, on the establishment of a common classification of territorial units for statistics (NUTS), L154/1-41.
12. FAO, 2000. The Global Information and Early Warning System on Food and Agriculture, GIEWS Information Booklet (ESCG) (Rome: FAO).
13. 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, 1837-1860.
14. Franklin, J. and Woodcock, C.E., 1997. Multiscale vegetation data for the mountains of Southern California: spatial and categorical resolutions. In: D.A. Quattrochi and M.F. Goodchild, eds., Scale in remote sensing and GIS. Boca Raton, FL: CRC Press, Inc., 141-168.
15. Gao, B.C., 1996. NDWI - a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257-266.
16. Gehlke, C.E. and Biehl, K., 1934. Certain effects of grouping upon the size of the correlation coefficient in census tract material. Journal of the American Statistical Association, 29, 169-170.
17. Gitas, I.Z., et al., 2004. Vegetation greenness mapping of Greece using MODIS imagery. In:Workshop on MODIS data and imagery: how to get and use them. Valladolid, Spain: University of Valladolid.
18. Griguolo, S. and Santacroce, P., 1996. Analysing, classifying and displaying time series of images pixel-by pixel: the package ADDAPIX. In: Co-ordination and harmonisation of databases and software for agroclimatic applications, FAO agrometeorology series working paper no. 13, 243-257. (Rome: FAO).
19. Hahn, C.P., 1969. Testing homogeneity of variances in a two-way classification. Biometrics, 25, 153-158.
20. Hay, G.J., et al., 2001. A multiscale framework for landscape analysis: object-specific analysis and upscaling. Landscape Ecology, 16, 471-490.
21. Heywood, I., 1998. An introduction to geographical information systems (NewYork:Wentley Longman).
22. Huete, A., et al., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195-213.
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, 37-53.
24. Jelinski, D.E. and Wu, J.G., 1996. The modifiable areal unit problem and implications for landscape ecology. Landscape Ecology, 11, 129-140.
25. Lambin, E.F. and Ehrlich, D., 1995. Combining vegetation indices and surface temperature for land-cover mapping at broad spatial scales. International Journal of Remote Sensing, 16, 573-579.
26. Loukas, A., et al., 2001. Rainfall-frequency mapping for Greece. Physics and chemistry of the earth, part B: hydrology, oceans and atmosphere, 26, 669-674.
27. Marceau, D.J., 1999. The scale issue in the social and natural sciences. Canadian Journal of Remote Sensing, 25, 347-356.
28. Maselli, F., 2004. Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data. Remote sensing of environment, 89, 423-433.
29. Ministry of Environment, Spatial Planning and Public Works of Greece [MINENV], 2004. CORINE land cover 2000 map [online]. European Environment Agency, Available from: http://dataservice.eea.europa.eu/dataservice/.
30. Moulin, S., et al., 1997. Global-scale assessment of vegetation phenology using NOAA/AVHRR satellite measurements. Journal of Climate, 10, 1154-1170.
31. Openshaw, S., 1983. The modifiable areal unit problem. Concepts & Techniques in Modern Geography, no. 38 (Norwich: Geo Books).
32. Openshaw, S. and Taylor, P.J., 1979. The modifiable areal unit problem. In Quantitative Geography: A British View, N. Wrigley, R.J. Bennett (Eds) (London: Routledge), 61-69.
33. Plante, M., et al., 2004. Studying deer habitat on Anticosti Island, Quebec: relating animal occurrences and forest map information. Ecological Modelling, 174, 387-399.
34. Ramsey, R.D., Falconer, A., and Jensen, J.R., 1995. The relationship between NOAA-AVHRR NDVI and ecoregions in Utah. Remote Sensing of Environment, 53, 188-198.
35. Senay, G.B. and Elliott, R.L., 2000. Combining AVHRR-NDVI and landuse data to describe temporal and spatial dynamics of vegetation. Forest Ecology and Management, 128, 83-91.
36. Silleos, N., Perakis, K., and Petsanis, G., 2002. Assessment of crop damage using space remote sensing and GIS. International Journal of Remote Sensing, 23, 417-427.
37. Song, D.W.S., 2003. Spatial decomposition of segregation indices: a framework toward measuring segregation at multiple levels. Geographical Analysis, 35, 179-194.
38. Tucker, C.J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127-150.
39. Van Beurden, A.U.C.J. and Douven, W.J.A.M., 1999. Aggregation issues of spatial information in environmental research. International Journal of Geographical Information Science, 13, 513-527.
40. Vermote, E.F., El Saleous, N.Z., and Justice, C.O., 2002. Atmospheric correction of MODIS data in the visible to middle infrared: first results. Remote Sensing of Environment, 83, 97-111.
41. Wan, Z., Wang, P., and Li, X., 2004. Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA. International Journal of Remote Sensing, 25, 61-72.
42. 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, 217-234.
43. Wicks, T.E., Smith, G.M., and Curran, P.J., 2002. Polygon-based aggregation of remotely sensed data for regional ecological analyses. International Journal of Applied Earth Observation and Geoinformation, 4, 161-173.
44. Zhang, X.Y., et al., 2003. Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84, 471-475.