Field-based crop classification using SPOT4, SPOT5, IKONOS and QuickBird imagery for agricultural areas: A comparison study

International Journal of Remote Sensing

Volumn 32, Issue 24, 2011, Pages 9735-9768

  Turker, Mustafa ^a   Ozdarici, Asli ^b  

^a HACETTEPE UNIVERSITY   (Turkey)

^b MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

CROPS; IMAGE ENHANCEMENT; INFRARED DEVICES; SATELLITE IMAGERY;

AGRICULTURAL AREAS; AGRICULTURAL CROPS; CLIMATIC CONDITIONS; CROP CLASSIFICATION; CROP IDENTIFICATION; OVERALL ACCURACIES; QUICKBIRD IMAGERIES; SATELLITE POUR L'OBSERVATION DE LA TERRE;

IMAGE CLASSIFICATION;

ACCURACY ASSESSMENT; COMPARATIVE STUDY; CROP; FIELD METHOD; IKONOS; IMAGE CLASSIFICATION; MAPPING; NEAR INFRARED; QUICKBIRD; SATELLITE IMAGERY; SPOT;

TURKEY;

EID: 82155170603     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2011.576710     Document Type: Article

References (72)

1. APLIN, P. and ATKINSON, P.M., 2001, Sub-pixel land cover mapping for per-field classification. International Journal of Remote Sensing, 22, pp. 2853-2858.
2. APLIN, P. and ATKINSON, P.M., 2004, Predicting missing field boundaries to increase per-field classification accuracy. Photogrammetric Engineering and Remote Sensing, 70, pp. 141-149.
3. APLIN, P., ATKINSON, P.M. and CURRAN, P.J., 1999a, Fine spatial resolution simulated satellite sensor imagery for land cover mapping in the United Kingdom. Remote Sensing of Environment, 68, pp. 206-216.
4. APLIN, P., ATKINSON, P.M. and CURRAN, P.J., 1999b, Per-field classification of land use using the forthcoming very fine spatial resolution satellite sensors: problems and potential solutions. In Advances in Remote Sensing and GIS Analysis, P.M. Atkinson and N.J. Tate (Eds.), pp. 219-239 (Chichester: John Wiley & Sons).
5. BAN, Y., 2003, Synergy of multitemporal ERS-1 SAR and Landsat TM data for classification of agricultural crops. Canadian Journal of Remote Sensing, 29, pp. 518-526.
6. BAN, Y., TREITZ, P.M., HOWARTH, P.J., BRISCO, B. and BROWN, R.J., 1995, Improving the accuracy of synthetic aperture radar analysis for agricultural crop classification. Canadian Journal of Remote Sensing, 21, pp. 158-164.
7. BANNARI, A., PACHECO, A., STAENZ, K., MCNAIRN, H. and OMARI, K., 2006, Estimating and mapping crop residues cover on agricultural lands using hyperspectral and IKONOS data. Remote Sensing of Environment, 104, pp. 447-459.
8. BAUER, M.E., CIPRA, J.E., ANUTA, P.E. and ETHERIDGE, J.B., 1979, Identification and area estimation of agricultural crops by computer classification of LANDSAT MSS data. Remote Sensing of Environment, 8, pp. 77-92.
9. BERBEROGLU, S., LLOYD, C.D., ATKINSON, P.M. and CURRAN, P.J., 2000, The integration of spectral and textural information using neural networks for land cover mapping in the Mediterranean. Computers and Geosciences, 26, pp. 385-396.
10. BLAES, X., VANHALLEB, L. and DEFOURNY, P., 2005, Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment, 96, pp. 352-365.
11. BRISCO, B., BROWN, R.J. and MANORE, M.J., 1989, Early season crop discrimination with combined SAR and TM data. Canadian Journal of Remote Sensing, 15, pp. 44-54.
12. BÜTTNER, G. and CSILLAG, F., 1989, Comparative study of crop and soil mapping using multitemporal and multispectral SPOT and Landsat Thematic Mapper data. Remote Sensing of Environment, 29, pp. 241-249.
13. CAPOLSINI, P., ANDREFOUET, S., RION, C. and PAYRI, C., 2003, A comparison of Landsat ETM+, SPOT HRV, Ikonos, ASTER, and airborne MASTER data for coral reef habitat mapping in South Pacific islands. Canadian Journal of Remote Sensing, 29, pp. 187-200.
14. CHEN, D., STOW, D.A. and GONG, P., 2004, Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case. International Journal of Remote Sensing, 25, pp. 2177-2192.
15. CHENG, P., TOUTIN, T. and TOM, V., 2000, Unlocking the potential for Landsat 7 Data. Earth Observation Magazine, February, pp. 28-31.
16. CIHLAR, J., BEAUBIEN, J., XIAO, Q., CHEN, J. and LI, Z., 1997, Land cover of the Boreas region from AVHRR and Landsat data. Canadian Journal of Remote Sensing, 23, pp. 163-175.
17. CONGALTON, R.G., BALOGH, M., BELL, C., GREEN, K., MILLIKEN, J.A. and OTTMAN, R., 1998, Mapping and monitoring agricultural crops and other land cover in the lower Colorado River Basin. Photogrammetric Engineering and Remote Sensing, 64, pp. 1107-1113.
18. CONRAD, C., FRITSCH, S., ZEIDLER, J., RÜCKER, G. and DECH, S., 2010, Per-field irrigated crop classification in arid Central Asia using SPOT and ASTER data. Remote Sensing, 2, pp. 1035-1056.
19. CUSHNIE, J.L., 1987, The interactive effect of spatial resolution and degree of internal variability within land-cover types on classification accuracies. International Journal of Remote Sensing, 8, pp. 15-29.
20. DE WIT, A.J.W. and CLEVERS, J.G.P.W., 2004, Efficiency and accuracy of per-field classification for operational crop mapping. International Journal of Remote Sensing, 25, pp. 4091-4112.
21. DIGITALGLOBE, 2009, Digital Globe Corporation, Longmont, CO. Available online at: http://www.digitalglobe.com (accessed 12 December 2009).
22. DUTTA, S., PATEL, N.K., MEDHAVY, T.T., SRIVASTAVA, S.K., MISHRA, N. and SINGH, K.R.P., 1998, Wheat crop classification using multidate IRS LISS-I data. Journal of the Indian Society of Remote Sensing, 26, pp. 7-14.
23. DUTTA, S., SHARMAA, S.A., KHERA, A.P., AJAI, M.Y., HOODA, R.S., MOTHIKUMAR, K.E. and MANCHANDAB, M.L., 1994, Accuracy assessment in cotton acreage estimation using Indian remote sensing satellite data. ISPRS Journal of Photogrammetry and Remote Sensing, 49, pp. 21-26.
24. EARTH SEARCH SCIENCES INC., 2009, The Probe aircraft platform, Montana. Available online at: http://www.earthsearch.com/technology (accessed 4 May 2010).
25. EIDENSHINK, J.C. and FAUNDEEN, J.L., 1994, The 1 km AVHRR global land data set: first stages in implementation. International Journal of Remote Sensing, 15, pp. 3443-3462.
26. FULLER, R.M., GROOM, G.B. and JONES, A.R., 1994, The land cover map of Great Britain: an automated classification of Landsat Thematic Mapper data. Photogrammetric Engineering and Remote Sensing, 60, pp. 553-562.
27. GAO, J., 1999, A comparative study on spatial and spectral resolutions of satellite data in mapping mangrove forests. International Journal of Remote Sensing, 20, pp. 2823-2833.
28. GAO, J. and SKILLCORN, D., 1998, Capability of SPOT XS data in producing detailed land cover maps at the urban-rural periphery. International Journal of Remote Sensing, 19, pp. 2877-2891.
29. GEOEYE, 2009, GeoEye Corporation, Dulles, VA. Available online at: http://www.geoeye.com/CorpSite/ (accessed 12 December 2009).
30. GONZALEZ, R.C. and WOODS, R.E. (Eds.), 2007, Digital Image Processing (London: Pearson Education Ltd.).
31. GUERSCHMAN, J.P., PARUELO, J.M., DI BELLA, C., GIALLORENZI, M.C. and PACIN, F., 2003, Land cover classification in the Argentine Pampas using multi-temporal Landsat TM data. International Journal of Remote Sensing, 24, pp. 3381-3402.
32. HANUSCHAK, G.A., SIGMAN, R., CRAIG, M.E., OZGA, M., LUEBBE, R.C., COOK, P.W., KLEWENO, D.D. and MILLER, C.E., 1980, Crop-area estimates from Landsat: transition from research and development to timely results. IEEE Transactions on Geoscience and Remote Sensing, GE-18, pp. 160-166.
33. HIXSON, M.M., BAUER, M.E. and SCHOLZ, D.K., 1982, An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans. Remote Sensing of Environment, 12, pp. 123-128.
34. HUTCHINSON, C.F., 1982, Techniques for combining Landsat and ancillary data for digital classification improvement. Photogrammetric Engineering and Remote Sensing, 48, pp. 123-130.
35. IOKA, M. and KODA, M., 1986, Performance of Landsat-5 TM data in land-cover classification. International Journal of Remote Sensing, 7, pp. 1715-1728.
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, pp. 1521-1534.
37. JANSSEN, L.L.F., JAARSMA, M.N. and VAN DER LINDEN, E.T.M., 1990, Integrating topographic data with remote sensing for land-cover classification. Photogrammetric Engineering and Remote Sensing, 56, pp. 1503-1506.
38. JANSSEN, L.L.F. and MOLENAAR, M., 1995, Terrain objects, their dynamics and their monitoring by the integration of GIS and remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 33, pp. 749-758.
39. JEWELL, N., 1989, An evaluation of multi-date SPOT data for agriculture and land use mapping in the United Kingdom. International Journal of Remote Sensing, 10, pp. 939-951.
40. 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, pp. 1413-1423.
41. JUSTICE, C.O. and TOWNSHEND, J.R.G., 1994, Data sets for global remote sensing: lessons learnt. International Journal of Remote Sensing, 15, pp. 3621-3639.
42. KUROSU, T., FUJITA, M. and CHIBA, K., 1997, The identification of rice fields using multitemporal ERS-1 C band SAR data. International Journal of Remote Sensing, 18, pp. 2953-2965.
43. LANJERI, S., MELIÁ, J. and SEGARRA, D., 2001, A multi-temporal masking classification method for vineyard monitoring in central Spain. International Journal of Remote Sensing, 22, pp. 3167-3186.
44. LOBO, A., CHIC, O. and CASTERAD, A., 1996, Classification ofMediterranean crops with multisensor data: per-pixel versus per-object statistics and image segmentation. International Journal of Remote Sensing, 17, pp. 2385-2400.
45. LOVELAND, T.R., MERCHANT, J.W., OHLEN, D.O. and BROWN, J.F., 1991, Development of a land-cover characteristics database for the conterminous US. Photogrammetric Engineering and Remote Sensing, 57, pp. 1453-1463.
46. MARACCI, G. and AIFADOPOULOU, D., 1990, Multi-temporal remote sensing study of spectral signatures of crops in the Thessaloniki test site. International Journal of Remote Sensing, 11, pp. 1609-1615.
47. MCCAULEY, S. and GOETZ, S.J., 2004, Mapping residential density patterns using multitemporal Landsat data and a decision-tree classifier. International Journal of Remote Sensing, 25, pp. 1077-1094.
48. MCNAIRN, H., CHAMPAGNE, C., SHANG, J., HOLMSTROM, D. and REICHERT, G., 2009, Integration of optical and synthetic aperture radar (SAR) imagery for delivering operational annual crop inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 64, pp. 434-449.
49. MORAIN, S.A. and WILLIAMS, D.L., 1975, Wheat production estimates using satellite images. Agronomy Journal, 67, pp. 361-364.
50. MUMBY, P.J. and EDWARDS, A.J., 2002, Mapping marine environments with IKONOS imagery: enhanced spatial resolution can deliver greater thematic accuracy. Remote Sensing of Environment, 82, pp. 248-257.
51. MURAKAMI, T., OGAWA, S., ISHITSUKA, N., KUMAGAI, K. and SAITO, G., 2001, Crop discrimination with multitemporal SPOT/HRV data in the Saga Plains, Japan. International Journal of Remote Sensing, 22, pp. 1335-1348.
52. MURTHY, C.S., RAJU, P.V. and BADRINATH, K.V.S., 2003, Classification of wheat crop with multi-temporal images: performance of maximum likelihood and artificial neural networks. International Journal of Remote Sensing, 24, pp. 4871-4890.
53. OETTERA, D.R., COHENB, W.B., BERTERRETCHEA, M., MAIERSPERGERA, T.K. and KENNEDYA, R.E., 2000, Land cover mapping in an agricultural setting using multiseasonal Thematic Mapper data. Remote Sensing of Environment, 76, pp. 139-155.
54. OKAMOTO, K. and KAWASHIMA, H., 1999, Estimation of rice-planted area in the tropical zone using a combination of optical andmicrowave satellite sensor data. International Journal of Remote Sensing, 20, pp. 1045-1048.
55. PANIGRAHY, S. and SHARMA, S.A., 1997, Mapping of crop rotation using multidate Indian remote sensing satellite digital data. ISPRS Journal of Photogrammetry and Remote Sensing, 52, pp. 85-91.
56. PCI, 2003, Software Users Manual (Richmond Hill, ON: PCI Geomatics Enterprises Inc.).
57. PEDLEY, M.I. and CURRAN, P.J., 1991, Per-field classification: an example using SPOT HRV imagery. International Journal of Remote Sensing, 12, pp. 2181-2192.
58. RAPTIS, V.S., VAUGHAN, R.A. and WRIGHT, G.G., 2003, The effect of scaling on land cover classification from satellite data. Computers & Geosciences, 29, pp. 705-714.
59. RYERSON, R.A., DOBBINS, R.N. and THIBAULT, C., 1985, Timely crop area estimates from Landsat. Photogrammetric Engineering and Remote Sensing, 51, pp. 1735-1743.
60. SHAO, Y., FAN, X., LIU, H., XIAO, J., ROSS, S., BRISCO, B., BROWN, R. and STAPLES, G., 2001, Rice monitoring and production estimation usingmultitemporal RADARSAT. Remote Sensing of Environment, 76, pp. 310-325.
61. SIMONETT, D.S., 1983, The development and principles of remote sensing. In Manual of Remote Sensing, 2nd ed., R.N. Colwell (Ed.), pp. 1-35 (Falls Church, VA: American Society of Photogrammetry).
62. SMITH, G.M. and FULLER, R.M., 2001, An integrated approach to land cover classification: an example in the Island of Jersey. International Journal of Remote Sensing, 22, pp. 3123-3142.
63. TREITZ, P.M., HOWARTH, P.J. and GONG, P., 1992, Application of satellite and GIS technologies for land-cover and land-use mapping at the rural-urban fringe: a case study. Photogrammetric Engineering and Remote Sensing, 58, pp. 439-448.
64. TSO, B. and MATHER, P.M., 1999, Crop discrimination using multi-temporal SAR imagery. International Journal of Remote Sensing, 20, pp. 2443-2460.
65. TURKER, M. and ARIKAN, M., 2005, Sequential masking classification of multi-temporal Landsat7 ETM+ images for field-based crop mapping in Karacabey, Turkey. International Journal of Remote Sensing, 26, pp. 3813-3830.
66. TURKER, M. and DERENYI, E., 2000, GIS assisted change detection using remote sensing. Geocarto International, 15, pp. 49-54.
67. TURNER, M.D. and CONGALTON, R.G., 1998, Classification of multi-temporal SPOT-XS satellite data for mapping rice fields on a West African floodplain. International Journal of Remote Sensing, 19, pp. 21-41.
68. WANG, L., SOUSA, W.P., GONG, P. and BIGING, G.S., 2004, Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sensing of Environment, 91, pp. 432-440.
69. WILLIAMS, V.L., PHILIPSON, W.R. and PHILPOT, W.D., 1987, Identifying vegetable crops with Landsat Thematic Mapper data. Photogrammetric Engineering and Remote Sensing, 53, pp. 187-191.
70. XAVIER, B., VANHALLEB, L. and DEFOURNYA, P., 2005, Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment, 96, pp. 352-365.
71. YANG, C., EVERITT, J.H., FLETCHER, R.S. and MURDEN, D., 2007, Using high resolution QuickBird imagery for crop identification and area estimation. Geocarto International, 22, pp. 219-233.
72. ZHANG, Q., WANG, J., GONG, P. and SHI, P., 2003, Study of urban spatial patterns from SPOT panchromatic imagery using textural analysis. International Journal of Remote Sensing, 24, pp. 4137-4160.