Multi-year monitoring of rice crop phenology through time series analysis of MODIS images

International Journal of Remote Sensing

Volumn 30, Issue 18, 2009, Pages 4643-4662

  Boschetti, M ^a,b   Stroppiana, D ^a   Brivio, P A ^a   Bocchi, S ^b  

^a INSTITUTE FOR ELECTROMAGNETIC SENSING OF THE ENVIRONMENT   (Italy)

^b UNIVERSITY OF MILAN   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CROPS; CULTIVATION; RADIOMETERS; REMOTE SENSING; SATELLITES; SPATIAL DISTRIBUTION; SPECTROMETERS;

DISTRIBUTED INFORMATION; GROWING DEGREE DAYS; MODERATE RESOLUTION IMAGING SPECTROMETERS; NORMALIZED DIFFERENCE VEGETATION INDEX; REMOTE SENSING SATELLITES; REMOTELY SENSED DATA; RICE CROPPING SYSTEMS; SEASONAL ANALYSIS;

TIME SERIES ANALYSIS;

AGRONOMY; CROP PRODUCTION; CROPPING PRACTICE; ESTIMATION METHOD; MODELING; MODIS; MONITORING SYSTEM; NDVI; PHENOLOGY; PRECISION; REMOTE SENSING; RICE; SATELLITE DATA; SEASONAL VARIATION; SENESCENCE; SOWING DATE; TIME SERIES ANALYSIS;

EURASIA; EUROPE; ITALY; SOUTHERN EUROPE;

EID: 70449381068     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160802632249     Document Type: Article

References (30)

1. BOCCHI, S., CALLEGARIN, A. and MAGGIORE, T., 2002, The rice crop in Italy, a geographical analysis for spatial database construction. In Proceedings of the 2nd International Temperate Rice Conference, June 1999, Sacramento, J.E. Hill and B. Hardy (Eds), (Los Baños, Philippines: International Rice Research Institute), pp. 627-629.
2. BOCCHI, S., CALLEGARIN, A. and BALDI, G., 2003, Rice production system in Italy and its sustainability. In Proceeding of the 3rd International Temperate Rice Conference, 10-13 March 2003, Punta del Este Uruguay (Uruguay: INIA), pp. 19-22.
3. BOSCHETTI, M., CONFALONIERI, R., STROPPIANA, D., BOCCHI, S. and BRIVIO, P.A., 2005, Agroecological modelling for monitoring rice productions: contribution of field experiment and multi-temporal EO data. Proceedings SPIE, 5976, pp. 1-11.
4. CHEN, J., JÖNSSON, P., TAMURA, M., GU, Z., MATSUSHITA, B. and EKLUNDH, L., 2004, A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sensing of Environment, 91, pp. 332-344.
5. CONFALONIERI, R. and BOCCHI, S., 2005, Evaluation of CropSyst for simulating the yield of flooded rice in northern Italy. European Journal of Agronomy, 23, pp. 315-326.
6. DORAISWAMY, P.C., HATFIELD, J.L., JACKSON, T.J., AKHMEDOV, B., PRUEGER, J. and STERN, A., 2004, Crop condition and yield simulations using Landsat and MODIS. Remote Sensing of Environment, 92, pp. 548-559.
7. GOBRON, N. and PINTY, B., 2005, The state of vegetation in Europe following the 2003 drought. International Journal of Remote Sensing, 26, pp. 2013-2020.
8. HUETE, A., JUSTICE, C., and LEEUWEN, W., 1999, MODIS Vegetation Index (MOD13), Algorithm Theoretical Basis Document. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf.
9. 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.
10. JÖNSSON, P. and EKLUNDH, L., 2004, TIMESAT: a program for analyzing time-series of satellite sensor data. Computers and Geosciences, 30, pp. 833-845
11. JUSTICE, C.O., TOWNSHEND, J.R.G., HOLBEN, B.N. and TUCKER, C.J., 1985, Analysis of the phenology of global vegetation using meteorological satellite data. International Journal of Remote Sensing, 6, pp. 1271-1318.
12. KINIRY, J.R., BEAN, B., XIE, Y. and CHEN, P., 2004, Maize yield potential: critical processes and simulation modeling in a high-yielding environment. Agricultural Systems, 82, pp. 45-56.
13. LOAGUE, K.M. and GREEN, R.E., 1991, Statistical and graphical methods for evaluating solute transport models: overview and application. Journal of Contaminant Hydrology, 7, pp. 51-73.
14. MEIER, U., 1997, Growth stages of monoand dicotyledonous plants: BBCH-Monograph, Blackwell Science, Berlin.
15. 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.
16. MOULIN, S., BONDEAU, A. and DELECOLLE, R., 1998, Combining agricultural crop model and satellite observation: from field to regional scales. International Journal of Remote Sensing, 19, pp. 1021-1036.
17. MYNENI, R.B., HALL, F.G., SELLERS, P.J. and MARSHAK, A.L., 1995, The interpretation of spectral vegetation indicies. IEEE Transactions on Geoscience and Remote Sensing 33, pp. 481-486.
18. POTTER, C., TAN, P., STEINBACH, M., KLOOSTER, S., KUMAR, V. and MYNENI, R. 2003, Major disturbance events in terrestrial ecosystems detected using global satellite data sets. Global Change Biology, 9, pp. 1005-1021.
19. REED, B.C. and BROWN, J.F., 2002, Issues in characterizing phenology from satellite observations. In Proceedings of Use of Earth Observation Data for Phenological Monitoring, 12-13 December 2002, Joint Research Centre, Ispra, Italy, EUR 20675 EN, European Commission, (Ispra: Joint Research Centre), pp. 23-26.
20. REED, B.C., BROWN, J.F., VAN DER ZEE, D., LOVELAND, T.R., MERCHANT, J.W. and OHLEN, D.O., 1994, Measuring phenological variability from satellite imagery. Journal of Vegetation Science, 5, pp. 703-714.
21. REICHSTEIN, M., CIAIS, P., PAPALE, D., VALENTINI, R., RUNNING, S., VIOVY, N., CRAMER, W., GRANIER, A., OGÉE, J., ALLARD, V., AUBINET, M., BERNHOFER, Chr., BUCHMANN, N., CARRARA, A., GRÜNWALD, T., HEIMANN, M., HEINESCH, B., KNOHL, A., KUTSCH, W., LOUSTAU, D., MANCA, G., MATTEUCCI, G., MIGLIETTA, F., OURCIVAL, J.M., PILEGAARD, K., PUMPANEN, J., RAMBAL, S., SCHAPHOFF, S., SEUFERT, G., SOUSSANA, J.F., SANZ, M.J., VESALA, T. and ZHAO, M., 2007, Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis. Global Change Biology, 13, pp. 634-651.
22. SAKAMOTO, T., YOKOZAWA, M., TORITANI, H., SHIBAYAMA, M., ISHITSUKA, N. and OHNO, H., 2006, A crop phenology detection method using time-series MODIS data. Remote Sensing of Environment, 96, pp. 366-374.
23. SCHÄR, C., VIDALE, P.L., LUTHI, D., FREI, C., HABERLI, C., LINIGER, M.A. and APPENZELLER, C., 2004, The role of increasing temperature variability in European summer heatwaves. Nature, 427, pp. 332-336.
24. STROPPIANA, D., BOSCHETTI, M., CONFALONIERI, R., BOCCHI, S. and BRIVIO, P.A., 2006, Evaluation of LAI-2000 for leaf area index monitoring in paddy rice. Field Crop Research, 99, pp. 167-170.
25. TUCKER, C.J., VANPRAET, C.L., SHARMAN, M.J., and VAN ITTERSUN, G., 1985, Satellite remote sensing of total herbaceous production in the Senegalese Sahel 1980-1984. Remote Sensing of Environment, 17, pp. 232-249.
26. TURNER, D.P., GOWER, S.T., COHEN, M.W.B. and MAIERSPERGER, G.T.K., 2002, Effects of spatial variability in light use efficiency on satellite-based NPP monitoring. Remote Sensing of Environment, 80, pp. 397-405.
27. WHITE, M.A. and NEMANI, R.R., 2006, Real-time monitoring and short-term forecasting of land surface phenology. Remote Sensing of Environment, 104, pp. 43-49.
28. 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 Cycle, 11, pp. 217-234.
29. XIN, J., YU, Z., VAN LEEUWEN, L. and DRIESSEN, P.M., 2002, Mapping crop key phenological stages in the North China Plain using NOAA time series images. International Journal of Applied Earth Observation and Geoinformation, 4, pp. 109-117.
30. ZHANG, X., FRIEDL, M.A., SCHAAF, C.B., STRAHLER, A.H., HODGESA, J.C.F., GAO, F., REED, R.C. and HUETE, A., 2003, Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84, pp. 471-475.