Accuracy, objectivity and efficiency of remote sensing for agricultural statistics

Agricultural Survey Methods

Volumn , Issue , 2010, Pages 193-211

  Gallego, Javier ^a   Carfagna, Elisabetta ^b   Baruth, Bettina ^a  

^a JOINT RESEARCH CENTRE   (Italy)

^b UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Agricultural statistics; Cost efficiency; Crop yield forecasting; GEOSS; Remote sensing

Indexed keywords

EID: 84886045513     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470665480.ch12     Document Type: Chapter

References (82)

1. Allen, J.D. (1990) A look at the Remote Sensing Applications Program of the National Agricultural Statistics Service. Journal of Official Statistics, 6, 393-409.
2. Battese, G.E., Harter, R.M. and Fuller, W.A. (1988) An error-components model for prediction of county crop areas using survey and satellite data. Journal of the American Statistical Association, 83, 28-36.
3. Blaes, X. and Defourny, P. (2003) Retrieving crop parameters based on tandem ERS 1/2 interferometric coherence images. Remote Sensing of Environment, 88, 374-385.
4. Boryan, C., Craig, M. and Lindsay, M. (2008) Deriving essential dates of AWiFS and MODIS data for the identification of corn and soybean fields in the U.S. heartland. Pecora 17 - The Future of Land Imaging. Going Operational, Denver, Colorado, 18-20 November.
5. Bouman, B.A.M. (1992) Accuracy of estimating the leaf area index from vegetation indices derived from crop reflectance characteristics: a simulation study. International Journal of Remote Sensing, 13, 3069-3084.
6. Carfagna, E. (2001) Cost-effectiveness of remote sensing in agricultural and environmental statistics. In Proceedings of the Conference on Agricultural and Environmental Statistical Applications in Rome (CAESAR), 5-7 June, Vol 3, pp. 617-627. http://www. ec-gis.org/document.cfm?id = 427&db = document.
7. Carfagna, E. and Gallego, F.J. (2005) Using remote sensing for agricultural statistics. International Statistical Review, 73, 389-404.
8. Carfagna, E. and Marzialetti, J. (2009a) Sequential design in quality control and validation of land cover data bases. Journal of Applied Stochastic Models in Business and Industry, 25, 195-205.
9. Carfagna, E. and Marzialetti, J. (2009b) Continuous innovation of the quality control of remote sensing data for territory management. In P. Erto (ed.), Statistics for Innovation, pp. 172-188. New York: Springer.
10. Cochran, W. (1977) Sampling Techniques, 3rd edition. New York: John Wiley & Sons. Inc.
11. Congalton, R.G. and Green, K. (1999) Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, FL: Lewis.
12. Dadhwal, V.K., Singh, R.P., Dutta, S. and Parihar, J.S. (2002) Remote sensing based crop inventory:A review of Indian experience. Tropical Ecology, 43, 107-122.
13. Dong, Q., Eerens, H. and Chen, Z. (2008) Crop area assessment using remote sensing on the North China Plain. In Proceedings ISPRS, Vol. 37, Part B8, pp. 957-962.
14. Doorenbos, J. (ed.) (1986) Yield response to water. FAO irrigation and drainage paper, 33.
15. Doraiswamy, P.C., Moulin, S., Cook, P.W. and Stern, A. (2003) Crop yield assessment from remote sensing. Photogrammetric Engineering and Remote Sensing, 69, 665-674.
16. 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, 548-559.
17. Doraiswamy, P.C., Sinclair, T.R., Hollinger, S., Akhmedov, B., Stern, A. and Prueger, J. (2005) Application of MODIS derived parameters for regional crop yield assessment. Remote Sensing of Environment, 97, 192-202.
18. Dorigo, W.A., Zurita-Milla, R., de Wit, A.J.W., Brazile, J., Singh, R. and Schaepman, M.E. (2007) A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling. International Journal of Applied Earth Observation and Geoinformation, 9, 165-193.
19. Eerens, H. and Swinnen, E. (2009) Crop mapping with MODIS 250m over Europe: first results of the hard and soft classifications. MARSOP3 interim report, JRC Ispra.
20. Fang, H., Liang, S., Hoogenboom, G., Teasdale, J. and Cavigelli, M. (2008) Corn-yield estimation through assimilation of remotely sensed data into the CSM-CERES-maize model. International Journal of Remote Sensing, 29, 3011-3032.
21. FAO (2008) The State of Food and Agricultural Statistical Systems in Africa - 2007, RAF publication 2008E. Accra: FAO Regional Office for Africa.
22. Friedl, M.A., McIver, D.K., Hodges, J.C.F., Zhang, X.Y., Muchoney, D., Strahler, A.H., Woodcock, C.E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F. and Schaaf, C. (2002) Global land cover mapping from MODIS: Algorithms and early results. Remote Sensing of Environment, 83, 287-302.
23. Gallego, F.J. (2004) Remote sensing and land cover area estimation. International Journal of Remote Sensing, 25, 3019-3047.
24. Gallego, F.J. (2006) Review of the main remote sensing methods for crop area estimates. In B. Baruth, A. Royer and G. Genovese (eds), Remote Sensing Support to Crop Yield Forecast and Area Estimates ISPRS archives, Vol. 36, Part 8/W48, pp. 65-70. http://www.isprs. org/publications/PDF/ISPRS_Archives_WorkshopStresa2006.pdf.
25. Genovese, G., Vignolles, C., Negre, T. and Passera, G. (2001) A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study on Spain. Agronomie, 21, 91-111.
26. Gentle, J., Perry, C. and Wigton, W. (2006) Modeling nonsampling errors in agricultural surveys. In Proceedings of the Section on Survey Research Methods, American Statistical Association, 3035-3041.
27. GEOSS (2009) Best practices for crop area estimation with Remote Sensing. Ispra, 5-6 June 2008. http://www.earthobservations.org/geoss.shtml.
28. Hammond, T.O. and Verbyla, D.L. (1996) Optimistic bias in classification accuracy assessment. International Journal of Remote Sensing, 17, 1261-1266.
29. Hannerz, F. and Lotsch, A. (2008) Assessment of remotely sensed and statistical inventories of African agricultural fields. International Journal of Remote Sensing, 29, 3787-3804.
30. Hansen, M.H., Hurwitz, W.N. and Madow, W.G. (1953) Sample Survey Methods and Theory. New York: John Wiley & Sons, Inc.
31. Hanuschak, G., Hale, R., Craig, M., Mueller, R. and Hart, G. (2001) The new economics of remote sensing for agricultural statistics in the United States. Proceedings of the Conference on Agricultural and Environmental Statistical Applications in Rome (CAESAR), 5-7 June, Vol. 2, pp. 427-437.
32. Hanuschak, G.A., Sigman, R., Craig, M.E., Ozga, M., Luebbe, R.C., Cook, P.W. et al. (1980) Crop-area estimates from LANDSAT: Transition from research and development timely results. IEEE Transactions on Geoscience and Remote Sensing, GE-18, 160-166.
33. Heydorn, R.P. (1984) Using satellite remotely sensed data to estimate crop proportions. Communications in Statistics - Theory and Methods, 23, 2881-2903.
34. Hilker, T., Coops, N.C., Wulder, M.A., Black, T.A. and Guy, R.D. (2008) The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements. Science of the Total Environment, 404, 411-423.
35. Im, J. and Jensen, J.R. (2008) Hyperspectral remote sensing of vegetation. Geography Compass, 2, 1943-1961.
36. Ippoliti-Ramilo, G.A., Epiphanio, J.C.N. and Shimabukuro, Y.E. (2003) Landsat-5 thematic mapper data for pre-planting crop area evaluation in tropical countries. International Journal of Remote Sensing, 24, 1521-1534.
37. Johnson, D.M. (2008) A comparison of coincident landsat-5 TM and resourcesat-1 AWiFS imagery for classifying croplands. Photogrammetric Engineering and Remote Sensing, 74, 1413-1423.
38. Kalubarme, M.H., Potdar, M.B., Manjunath, K.R., Mahey, R.K. and Siddhu, S.S. (2003) Growth profile based crop yield models: A case study of large area wheat yield modelling and its extendibility using atmospheric corrected NOAA AVHRR data. International Journal of Remote Sensing, 24, 2037-2054.
39. Kancheva, R., Borisova, D. and Georgiev, G. (2007) Spectral predictors of crop development and yield. In Proceedings of the 3rd International Conference on Recent Advances in Space Technologies (RAST 2007), article number 4283987, pp. 247-251. Piscataway, NJ: Institute of Electrical and Electronics Engineers.
40. Kastens, J.H., Kastens, T.L., Kastens, D.L.A., Price, K.P., Martinko, E.A. and Lee, R. (2005) Image masking for crop yield forecasting using AVHRR NDVI time series imagery. Remote Sensing of Environment, 99, 341-356.
41. Kogan, F.N. (1990) Remote sensing of weather impacts on vegetation in non-homogeneous areas. International Journal of Remote Sensing, 11, 1405-1419.
42. Lathrop, R. (2006) The application of a ratio estimator to determine confidence limits on land use change mapping. International Journal of Remote Sensing, 27, 2033-2038.
43. Lessler, V.M. and Kalsbeek, W.D. (1999) Nonsampling errors in environmental surveys. Journal of Agricultural, Biological, and Environmental Statistics, 4, 473-488.
44. Manjunath, K.R., Potdar, M.B. and Purohit, N.L. (2002) Large area operational wheat yield model development and validation based on spectral and meteorological data. International Journal of Remote Sensing, 23, 3023-3038.
45. Marriot, F.H.C. (1990) A Dictionary of Statistical Terms, 5th edition. Harlow: Longman.
46. Mueller, R. and Seffrin, R. (2006) New methods and satellites: A program update on the NASS cropland data layer acreage program. In B. Baruth, A. Royer and G. Genovese (eds), Remote Sensing Support to Crop Yield Forecast and Area Estimates ISPRS archives, Vol. 36, Part 8/W48, pp. 97-102. http://www.isprs.org/publications/PDF/ISPRS_Archives_WorkshopStresa2006.pdf.
47. Mutanga, O. and Skidmore, A.K. (2004) Narrow band vegetation indices overcome the saturation problem in biomass estimation. International Journal of Remote Sensing, 25, 3999-4014.
48. Myneni, R.B. and Williams, D.L. (1994) On the relationship between FAPAR and NDVI. Remote Sensing of Environment, 49, 200-211.
49. Navalgund, R.R., Jayaraman, V. and Roy, P.S. (2007) Remote sensing applications: An overview. Current Science, 93, 1747-1766.
50. Nieuwenhuis, G.J.A., de Wit, A.J.W., van Kraalingen, D.W.G., van Diepen, C.A. and Boogaard, H.L. (2006) Monitoring crop growth conditions using the global water satisfaction index and remote sensing. Paper presented to ISPRS Conference on Remote Sensing:From Pixels to Processes, Enschede. http://www.itc.nl/external/isprsc7/ symposium/proceedings/TS23_4.pdf.
51. Nunes de Lima, M.V. (ed.) (2005) CORINE Land Cover Updating for the Year 2000. Image2000 and CLC2000: Products and Methods, Report EUR 21757 EN. Ispra, Italy: JRC. http://www.ec-gis.org/sdi/publist/pdfs/nunes2005eur2000.pdf.
52. Parihar, J.S. and Oza, M.P. (2006) FASAL: An integrated approach for crop assessment and production forecasting. Proceedings of SPIE, the International Society for Optical Engineering, 6411, art. no. 641101.
53. Pettorelli, N., Vik, J.O., Mysterud, A., Gaillard, J.M., Tucker, C.J. and Stenseth, N.C. (2005) Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution, 20, 503-510.
54. Piccard, I., van Diepen, C.A., Boogaard, H.L., Supit, I., Eerens, H. and Kempeneers, P. (2002) Other yield forecasting systems: description and comparison with the MARS Crop Yield Forecasting System. Internal report, JRC Ispra.
55. Pinty, B. and Verstraete, M.M. (1992) GEMI: A non-linear index to monitor global vegetation from satellites. Vegetatio, 101, 15-20.
56. Pinty, B., Leprieur, C. and Verstraete, M. (1993) Towards a quantitative interpretation of vegetation indices. Part 1: Biophysical canopy properties and classical indices. Remote Sensing Reviews, 7, 127-150.
57. Pontius Jr., R.G. and Cheuk, M.L. (2006) A generalized cross-tabulation matrix to compare soft-classified maps at multiple resolutions. International Journal of Geographical Information Science, 20, 1-30.
58. Prasad, A.K., Chai, L., Singh, R.P. and Kafatos, M. (2006) Crop yield estimation model for Iowa using remote sensing and surface parameters. International Journal of Applied Earth Observation and Geoinformation, 8, 26-33.
59. Quinlan, J.R. (1996) Improved use of continuous attributes in C4.5. Journal of Artificial Intelligence Research, 4, 77-90.
60. Rama Rao, N. (2008) Development of a crop-specific spectral library and discrimination of various agricultural crop varieties using hyperspectral imagery. International Journal of Remote Sensing, 29, 131-144.
61. Rasmussen, M.S. (1998) Developing simple, operational, consistent NDVI-vegetation models by applying environmental and climatic information. Part II: Crop yield assessment. International Journal of Remote Sensing, 19, 119-139.
62. Reynolds, C. (2001) Input data sources, climate normals, crop models, and data extraction routines utilized by PECAD. Paper presented to Third International Conference on Geospatial Information in Agriculture and Forestry, Denver, Colorado, 5-7 November.
63. Rojas, O. (2007) Operational maize yield model development and validation based on remote sensing and agro-meteorological data in Kenya. International Journal of Remote Sensing, 28, 3775-3793.
64. Salazar, L., Kogan, F. and Roytman, L. (2008) Using vegetation health indices and partial least squares method for estimation of corn yield. International Journal of Remote Sensing, 29, 175-189.
65. Shi, Z., Ruecker, G.R., Mueller, M. et al. (2007) Modeling of cotton yields in the Amu Darya river floodplains of Uzbekistan integrating multitemporal remote sensing and minimum field data. Agronomy Journal, 99, 1317-1326.
66. Sielken R.L., Gbur E.E. (1984) Multiyear, through the season, crop acreage estimation using estimated acreage in sample segments. Communications in Statistics - Theory and Methods, 23, 2961-2974.
67. Stehman, S.V. and Milliken, J.A. (2007) Estimating the effect of crop classification error on evapotranspiration derived from remote sensing in the lower Colorado river basin, USA. Remote Sensing of Environment, 106, 217-227.
68. Strahler, A.S., Boschetti, L., Foody, G.M., Friedl, M.A., Hansen, M.C. and Herold, M. (2006) Global land cover validation recommendations for evaluation and accuracy assessment of Global Land Cover Maps. EUR Report 22156, JRC Ispra.
69. Taylor, J., Sannier, C., Delincé, J, Gallego, F.J. (1997) Regional crop inventories in Europe assisted by remote sensing: 1988-1993. Synthesis Report, EUR 17319 EN, JRC Ispra.
70. Taylor, T.W. (1996) Agricultural analysis for a worldwide crop assessment. In Proceedings of the SPOT Conference, Paris, 15-18 April, pp. 485-488.
71. Thompson, S.K. and Seber, G.A.F. (1996) Adaptive Sampling. New York: John Wiley & Sons, Inc.
72. USDA/NASS (2006) The yield forecasting program of NASS. SMB Staff Report 06-01. http://www.nass.usda.gov/Education_and_Outreach/Understanding_Statistics/yldfrcst2006.pdf.
73. Van Leeuwen, W.J.D., Hutchinson, C.F., Doorn, B., Sheffner, E. and Kaupp, V.H. (2006) Integrated crop production observations and information system. In Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3506-3508.
74. Verbeiren, S., Eerens, H., Piccard, I., Bauwens, I. and Van Orshoven, J. (2008) Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium. International Journal of Applied Earth Observation and Geoinformation, 10, 486-497.
75. Verbyla, D.L. and Boles, S.H. (2000) Bias in land cover change estimates due to misregistration. International Journal of Remote Sensing, 21, 3553-3560.
76. Verbyla, D.L. and Hammond, T.O. (1995) Conservative bias in classification accuracy assessment due to pixel-by-pixel comparison of classified images with reference grids. International Journal of Remote Sensing, 16, 581-587.
77. Wall, L., Larocque, D. and Léger, P. (2008) The early explanatory power of NDVI in crop yield modelling. International Journal of Remote Sensing, 29, 2211-2225.
78. Weissteiner, C.J., Braun, M. and Kuhbauch, W. (2004) Regional yield predictions of malting barley by remote sensing and ancillary data. Proceedings of SPIE, the International Society for Optical Engineering, 5232, 528-539.
79. Wood, S., Sebastian, K. and Scherr, S.J. (2000) Pilot Analysis of Global Ecosystems: Agroecosystems. Washington, DC: World Resources Institute and International Food Policy Research Institute.
80. Woodcock, C.E. and Gopal, S. (2000) Fuzzy set theory and thematic maps: Accuracy assessment and area estimation. International Journal of Geographical Information Science, 14, 153-172.
81. Yuping, M., Shili, W., Li, Z. et al. (2008) Monitoring winter wheat growth in North China by combining a crop model and remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 10, 426-437.
82. Zurita-Milla, R., Kaiser, G., Clevers, J.G.P.W., Schneider, W. and Schaepman, M.E. (2009) Downscaling time series of MERIS full resolution data to monitor vegetation seasonal dynamics. Remote Sensing of Environment, 113, 1874-1885.