Sensor development and radiometric correction for agricultural applications

Photogrammetric Engineering and Remote Sensing

Volumn 69, Issue 6, 2003, Pages 705-718

  Moran, S ^a   Fitzgerald, G ^b   Rango, A ^a   Walthall, C ^d   Barnes, E ^b,c   Bausch, W ^a   Clarke, T ^b   Daughtry, C ^d   Everitt, J ^e   Escobar, D ^e   Hatfield, J ^f   Havstad, K ^a   Jackson, T ^d   Kitchen, N ^g   Kustas, W ^d   McGuire, M ^a   Pinter Jr , P ^b   Sudduth, K ^g   Schepers, J ^h   Schmugge, T ^d   Starks, P ⁱ   Upchurch, D ^a   more..

^a U S DEPARTMENT OF AGRICULTURE   (United States)

^b AGRICULTURAL RESEARCH SERVICE   (United States)

^c Agricultural and Environmental Research Division   (United States)

^d AGRICULTURAL RESEARCH SERVICE   (United States)

^e KIKA DE LA GARZA SUBTROPICAL AGRICULTURAL RESEARCH CENTER   (United States)

^f USDA ARS National Laboratory for Agriculture and the Environment   (United States)

^g UNIVERSITY OF MISSOURI   (United States)

^h UNIVERSITY OF NEBRASKA LINCOLN   (United States)

ⁱ USDA ARS GRAZINGLANDS RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURE; ELECTRIC CONDUCTIVITY; FLUORESCENCE; RADIOMETRY; SOILS;

RADIOMETRIC CORRECTION;

SENSORS;

AGRICULTURAL APPLICATION; CALIBRATION; RADIOMETER; REMOTE SENSING; SENSOR;

EID: 0038240687     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.69.6.705     Document Type: Review

References (88)

1. Barnes, E.M., T.R. Clarke, S.E. Richards, P.D. Colaizzi, J. Haberland, M. Kostrzewski, P. Waller, C. Choi, E. Riley, T. Thompson, R.J. Lascano, H. Li, and M.S. Moran, 2000. Coincident detection of crop water stress, nitrogen status and canopy density using ground-based multispectral data, Proceedings of the Fifth International Conference on Precision Agriculture, 16-19 July, Bloomington, Minnesota (American Society of Agronomy, Madison, Wisconsin), unpaginated CD-Rom.
2. Bausch, W.C., 1995. Remote sensing of crop coefficients for improving the irrigation scheduling of corn, Agricultural Water Management, 27:55-68.
3. Bausch, W.C., D.M. Lund, and M.C. Blue, 1990. Robotic data acquisition of directional reflectance factors, Remote Sensing of Environment, 46:213-222.
4. Bausch, W.C., and H.R. Duke, 1996. Remote sensing of plant nitrogen status in corn, Transactions of the American Society of Agricultural Engineers (ASAE), 39(5):1869-1875.
5. Bausch, W.C., K. Diker, A.F.H. Goetz, and B. Curtiss, 1998. Hyperspectral Characteristics of Nitrogen Deficient Corn, American Society of Agricultural Engineers (ASAE) Paper No. 98-3061, 12-16 July, Orlando, Florida (American Society of Agricultural Engineers, St. Joseph, Michigan), 8 p.
6. Bausch, W.C., and K. Diker, 2001. Innovative remote sensing techniques to increase nitrogen use efficiency of corn, Communications in Soil Science and Plant Analysis, 32(7&8):1371-1390.
7. Blackmer, T.M., J.S. Schepers, and G.E. Meyer, 1995. Remote sensing to detect nitrogen deficiency in corn, Proceedings of Site-Specific Management for Agricultural Systems, 27-30 March 1994, Minneapolis, Minnesota (American Society of Agronomy, Madison, Wisconsin), pp. 505-512.
8. Blackmer, T.M., J.S. Schepers, G.E. Varvel, and E.A. Walter-Shea, 1996. Nitrogen deficiency detection of reflected shortwave radiation from irrigated corn canopies, Agronomy Journal, 88:1-5.
9. Bryant, R.B., and M.S. Moran, 1999. Determining crop water stress from crop temperature variability, Proceedings of the International Airborne Remote Sensing Conference, 21-24 June, Ottawa, Ontario, Canada, pp. 289-296.
10. Bryant, R., J. Qi, M.S. Moran, and W. Ni, 2003. Comparison of empirical models with a fuzzy inference system (FIS) for correction of bidirectional effects, Remote Sensing of Environment, (submitted).
11. Burke, J.J., J.R. Mahan, and J.L. Hatfield, 1988. Crop-specific thermal kinetic windows in relation to wheat and cotton biomass production, Agronomy Journal, 80:553-556.
12. Carter, L.M., J.D. Rhoades, and J.H. Chesson, 1993. Mechanization of soil salinity assessment for mapping, 1993 Water Meeting of the American Society of Agricultural Engineering, 12-17 December, Chicago, Illinois (American Society of Agricultural Engineering, St. Joseph, Michigan), 10 p.
13. Chappelle, E.W., C.S.T. Daughtry, and J.E. McMurtrey III, 1995. Method and Apparatus for Discriminating Materials Exhibiting Different Fluorescent Properties, U.S. Patent No. 5,412,219.
14. Clawson, K.L., and B.L. Blad, 1982. Infrared thermometry for scheduling irrigation of corn, Agronomy Journal, 74:311-316.
15. Daughtry, C.S.T., J.E. McMurtrey III, E.W. Chappelle, W.P. Dulaney, J.R. Irons, and M.B. Satterwhite, 1995. Potential for discriminating crop residues from soil by reflectance and fluorescence, Agronomy Journal, 87:165-171.
16. Doolittle, J.A., K.A. Sudduth, N.R. Kitchen, and S.J. Indorante, 1994. Estimating depths to claypans using electromagnetic induction methods, Journal of Soil and Water Conservation, 49(6):572-575.
17. Dymond, J.R., J.D. Shepherd, and J. Qi, 2001. A simple physical model of vegetation reflectance for standardizing optical satellite imagery, Remote Sensing of Environment, 77:230-239.
18. Escobar, D.E., J.H. Everitt, J.R. Noriega, M.R. Davis, and I. Cavazos, 1997. A true digital imaging system for remote sensing applications, Proceedings of the 16th Biennial Workshop on Videography and Color Photography in Resource Assessment, 29 April - 01 May, Weslaco, Texas (American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland), pp. 470-484.
19. Escobar, D.E., J.H. Everitt, J.R. Noriega, I. Cavazos, and M.R. Davis, 1998. A twelve-band airborne digital video imaging system (ADVIS), Remote Sensing of Environment, 66:122-128.
20. Escobar, D.E., J.H. Everitt, and M.R. Davis, 2000. The use of a twelve-band video system as a remote sensing research tool, Geocarto International, 15:37-44.
21. Everitt, J.H., D.E. Escobar, I. Cavazos, J.R. Noriega, and M.R. Davis, 1995. A three-camera multispectral digital video imaging system, Remote Sensing of Environment, 54:333-337.
22. Everitt, J.H., D.E. Escobar, J.R. Noriega, I. Cavazos, and M.R. Davis, 1997a. A video system capable of simulating Landsat TM 5, 4, 3 Imagery, Remote Sensing of Environment, 62:40-45.
23. Everitt, J.H., J.V. Richardson, J. Karges, M.A. Alaniz, M.R. Davis, and A. Gomez, 1997b. Detecting and mapping western pine beetle infestations with airborne ideography, global positioning system and geographic information system technologies, Southwestern Entomologist, 22:293-300.
24. Everitt, J.H., C. Yang, D.E. Escobar, C.F. Webster, R.I. Lonard, and M.R. Davis, 1999. Using remote sensing and spatial information technologies to detect and map two aquatic macrophytes, Journal of Aquatic Plant Management, 37:71-80.
25. Fitzgerald, G.J., 2001. Spider mite detection in cotton using hyperspectral remote sensing, American Society of Agronomy Abstracts, 22-25 October, Charlotte, North Carolina (American Society of Agronomy, Madison, Wisconsin), unpaginated CD-Rom.
26. Fitzgerald, G.J., S.J. Maas, and W.R. DeTar, 1999. Early detection of spider mites in cotton using multispectral remote sensing, Proceedings of the Beltwide Cotton Conference, 03-07 January, Orlando, Florida (National Cotton Council, Memphis, Tennessee), 2:1022-1024.
27. Fuchs, M., and C.B. Tanner, 1966. Infrared thermometry of vegetation, Agronomy Journal, 58:597-601.
28. Fujisada, H., 1998. ASTER Level-1 data processing slgorithm, IEEE Transactions on Geosciience and Remote Sensing, 36:1101-1112.
29. Gardner, B.R., B.L. Blad, and D.G. Watts, 1981a. Relationships between crop temperature, grain yield, evapotranspiration and phenological development in two hybrids of moisture stressed sorghum, Irrigation Science, 2:213-224.
30. Gardner, B.R., B.L. Blad, R.E. Maurer, and D.G. Watts, 1981b. Relationship between crop temperature and the physiological and phenological development of differentially irrigated corn, Agronomy Journal, 73:743-747.
31. Gillespie, A., S. Rokugawa, T. Matsunaga, J.S. Cothern, S. Hook and A.B. Kahle, 1998. A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, IEEE Transactions on Geoscience and Remote Sensing, 36:1113-1126.
32. Goodrich, D.C., A. Chehbouni, B. Goff, B. MacNish, T. Maddock III, M.S. Moran, W.J. Shuttleworth, D.G. Williams, C. Watts, L.H. Hipps, D.I. Cooper, J. Schieldge, Y.H. Kerr, H. Arias, M. Kirkland, R. Carlos, P, Cayrol, W. Kepner, B. Jones, R. Avissar, A. Begue, J-M. Bonnefond, G. Boulet, B. Branan, J.P. Brunel, L.C. Chen, T. Clarke, M.R. Davis, H. DeBruin, G. Dedieu, E. Elguero, W.E. Eichinger, J. Everitt, J. Garatuza-Payan, H. Gupta, C. Harlow, O. Hartogensis, M. Helfert, C. Holifield, D. Hymer, A. Kahle, T. Keefer, S. Krishnamoorthy, J-P. Lhomme, J-P. Lagouarde, D. Lo Seen, D. Laquet, R. Marsett, B. Monteny, W. Ni, Y. Nouvellon, R.T. Pinker, C. Peters, D. Pool, J. Qi, S. Rambal, J. Rodriguez, F. Santiago, E. Sano, S.M. Schaeffer, S. Schulte, R. Scott, X. Shao, K.A. Snyder, S. Sorooshian, C.L. Unkrich, M. Whitaker, and I. Yucel, 2000. Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program Special Issue, Journal of Agricultural and Forest Meteorology, 105(1-3):3-20.
33. Hanson, L.D., P.C. Robert, and M. Bauer, 1995. Mapping wild oats infestations using digital imagery for site-specific management, Proceedings of Site-Specific Management for Agricultural Systems, 27-30 March 1994, Minneapolis, Minnesota (ASA-CSSA-SSSA, Madison, Wisconsin), pp. 495-503.
34. Hatfield, J.L., and P.J. Pinter, Jr., 1993. Remote sensing for crop protection, Crop Protection, 12:403-414.
35. Havstad, K.M., W.P. Kustas, A. Rango, J.C. Ritchie, and T.J. Schmugge, 2000. Jornada Experimental Range: A unique arid land location for experiments to validate satellite systems, Remote Sensing of Environment, 74:13-25.
36. Idso, S.B., 1982. Non-water-stressed baselines: A key to measuring and interpreting plant water stress, Agricultural Meteorology, 27:59-70.
37. Idso, S.B., R.D. Jackson, P.J. Pinter, Jr., R.J. Reginato, and J.L. Hatfield, 1981. Normalizing the stress-degree-day parameter for environmental variability, Agricultural Meteorology, 24:45-55.
38. Jackson, R.D., 1982. Canopy temperature and crop water stress, Advances in Irrigation, 1:43-85.
39. _, 1987. The Crop Water Stress Index: A second look, Proceedings of the International Conference on Measurement of Soil and Plant Water Stress, 06-10 July, Utah State University, Logan, Utah, 2:87-92.
40. _, 1990. The MAC Experiments, Remote Sensing of Environment, 32:77-79.
41. Jackson, R.D., R.J. Reginato, and S.B. Idso, 1977. Wheat canopy temperature: A practical tool for evaluating water requirements, Water Resources Research, 13:651-656.
42. Jackson, R.D., P.J. Pinter, Jr., R.J. Reginato, and S.B. Idso, 1980. Hand-Held Radiometry - Notes Developed for Use at the Workshop on Hand-Held Radiometry, 25-26 February, Phoenix, Arizona (USDA, Science and Education Administration, Agricultural Reviews and Manuals, Western Series, No. 19, Washington, D.C.), 66 p.
43. Jackson, R.D., D.B. Idso, R.J. Reginato, and P.J. Pinter, Jr., 1981. Canopy temperature as a crop water stress indicator, Water Resources Research, 17:1133-1138.
44. Jackson, R.D., M.S. Moran, P.N. Slater, and S.F. Biggar, 1987. Field calibration of reference reflectance panels, Remote Sensing of Environment, 22:145-158.
45. 4 reference reflectance panels, Remote Sensing of Environment, 40:231-239.
46. Jackson, T.J., 1997. Soil moisture estimation using special satellite microwave/imager satellite data over a grassland region, Water Resources Research, 33:1475-1484.
47. Jackson, T.J., D.M. Le Vine, A.Y. Hsu, A. Oldak, P.J. Starks, C.T. Swift, J.D. Isham, and M. Haken, 1999. Soil moisture mapping at regional scales using microwave radiometry: The Southern Great Plains hydrology experiment, IEEE Transactions on Geoscience and Remote Sensing, 37(5):2136-2151.
48. Jackson, T.J., E.G. Njoku, and V. Lakshmi, 2001. Introduction to the special issue on large scale passive microwave remote sensing of soil moisture, IEEE Transactions on Geoscience Remote Sensing, 39:1619-1620.
49. Jaynes, D.B., T.S. Colvin, and J. Ambuel, 1993. Soil Type and Crop Yield Determinations from Ground Conductivity Surveys, American Society of Agricultural Engineers, Paper 933552, American Society of Agricultural Engineers, St. Joseph, Michigan, 14 p.
50. Jaynes, D.B., J.M. Novak, T.B. Moorman, and C.A. Cambardella, 1995. Estimating herbicide partition coefficients from electromagnetic induction measurements, Journal of Environmental Quality, 24:36-41.
51. 2 enrichment (FACE) and soil nitrogen effects on energy balance and evapotranspiration of wheat, Water Resources Research, 35:1179-1190.
52. Kitchen, N.R., K.A. Sudduth, and S.T. Drummond, 1999. Soil electrical conductivity as a crop productivity measure for claypan soils, Journal of Production Agriculture, 12:607-617.
53. Kustas, W.P., and D.C. Goodrich, 1994. Preface to Monsoon'90 Multidisciplinary Experiment, Water Resources Research, 30:1211-1225.
54. Kustas, W.P., and J.M. Norman, 1996. Use of remote sensing for evapotranspiration monitoring over land surfaces, Hydrological Sciences Journal, 41:495-516.
55. Lesch, S.M., D.J. Strauss, and J.D. Rhoades, 1995a. Spatial prediction of soil salinity using electromagnetic induction techniques: 1. Statistical prediction models: A comparison of multiple linear regression and cokriging, Water Resources Research, 31:373-386.
56. _, 1995b. Spatial prediction of soil salinity using electromagnetic induction techniques: 2. An efficient spatial sampling algorithm suitable for multiple linear regression model identification and estimation, Water Resources Research, 31:387-398.
57. Maas, S.J., G.J. Fitzgerald, and. W.R. DeTar, 2000. Determining cotton leaf canopy temperature using multispectral remote sensing, Proceedings of the Beltwide Cotton Conference, 04-09 January, San Antonio, Texas (National Cotton Council, Memphis, Tennessee), 1:623-626.
58. Moran, M.S., 2000. Image-based remote sensing for agricultural management - Perspectives of image providers, research scientists and users, Second International Conference on Geospatial Information in Agriculture and Forestry, 10-12 January, Orlando, Florida (Veridian ERIM International), 1:23-30.
59. Moran, M.S., T.R. Clarke, J. Qi, and P.J. Pinter, Jr., 1996. MADMAC: A test of multispectral airborne imagery as a farm management tool, Proceedings of the 26th International Symposium on Remote Sensing of the Environment, 25-29 March, Vancouver, B.C., Canada (International Center for Remote Sensing of Environment (ICRSE)), pp. 612-617.
60. Moran, M.S., Y. Inoue, and E.M. Barnes, 1997. Opportunities and limitations for image-based remote sensing in precision crop management, Remote Sensing of Environment, 61:319-346.
61. Moran, M.S., D.C. Hymer, J. Qi, and E.E. Sano, 2000a. Soil moisture evaluation using Synthetic Aperture Radar (SAR) and optical remote sensing in semiarid rangeland, Journal of Agricultural and Forest Meteorology, 105:69-80.
62. Moran, M.S., J. Qi, W. Ni, and D.T. Shannon, 2000b. Water Conservation Laboratory image and ground data archive (WIGDA99) for Arizona agricultural and rangeland regions, Second International Conference on Geospatial Information in Agriculture and Forestry, 10-12 January, Orlando, Florida (Veridian ERIM International), 2:229-236.
63. Moran, M.S., R.B. Bryant, T.R. Clarke, and J. Qi, 2001. Deployment and calibration of reference reflectance tarps for use with airborne cameras, Photogrammetric Engineering & Remote Sensing, 67:273-286.
64. Neale, C.M.U., W.C. Bausch, and D.F. Heermann, 1989. Development of reflectance-based crop coefficients for corn, Transactions of the ASAE, 32(6):1891-1899.
65. Nouvellon, Y., M.S. Moran, D. Lo Seen, R.B. Bryant, W. Ni, A. Begue, A.G. Chehbouni, W.E. Emmerich, P. Heilman, and J. Qi, 2001. Combining a grassland ecosystem model with Landsat TM imagery for a ten-year simulation of carbon and water budget, Remote Sensing of Environment, 78:131-149.
66. Osborne, S.L., J.S. Schepers, D.D. Francis, and M.R. Schlemmer, 2001. Use of spectral radiance to estimate in-season biomass and grain yield in nitrogen and water stressed corn, Crop Science, 42:165-171.
67. Ouaidrari, H., and E.F. Vermote, 1999. Operational atmospheric correction of Landsat TM data, Remote Sensing of Environment, 70:4-15.
68. Perry, E.M., and M.S. Moran, 1994. An evaluation of atmospheric corrections of radiometric surface temperatures for a semiarid rangeland watershed, Water Resource Research, 30:1261-1269.
69. Pinter, P.J., Jr., R.D. Jackson, and M.S. Moran, 1990. Bidirectional reflectance factors of agricultural targets: A comparison of ground-, aircraft- and satellite-based observations, Remote Sensing of Environment, 32:215-228.
70. Pinter, P.J., Jr., and M.S. Moran, 1994. Foreword: Remote sensing of soils and vegetation, Remote Sensing of Environment, 49:167-168.
71. Privette, J.L., G.P. Asner, J. Conel, K.F. Huemmrich, R. Olson, A. Rango, A.F. Rahman, K. Thome, and E.A. Walter-Shea, 2000. The EOS Prototype Validation Exercise (PROVE) at Jornada: Overview and lessons learned, Remote Sensing of Environment, 74:1-12.
72. Rango, A., M. Chopping, J. Ritchie, K. Havstad, W. Kustas, and T. Schmugge, 2000. Morphological characteristics of shrub coppice dunes in desert grasslands of southern New Mexico derived from scanning Lidar, Remote Sensing of Environment, 74:26-44.
73. Renard, K.G., L.J. Lane, J.R. Simanton, W.E. Emmerich, J.J. Stone, M.A. Weltz, D.C. Goodrich, and D.S. Yakowitz, 1993. Agricultural impacts in an arid environment: Walnut Gulch case study, Hydrological Science and Technology, 9:145-190.
74. Rhoades, J.D., and R.D. Ingvalson, 1971. Determining salinity in field soils with soil resistance measurements, Soil Science Society of America Proceedings, 35:54-60.
75. Rhoades, J.D., and D.L. Corwin, 1981. Determining soil electrical conductivity-depth relations using an inductive electromagnetic soil conductivity meter, Soil Science Society of America Journal, 45:255-260.
76. Schmugge, T., A.N. French, J.C. Ritchie, and A. Rango, 2002a. ASTER observations of the spectral emissivity over New Mexico, Proceedings of SPIE EurOpto 8th International Symposium on Remote Sensing, 17-21 September 2001, Toulouse, France (SPIE Vol. 4542), pp. 207-213.
77. Schmugge, T., A.N. French, J.C. Ritchie, A. Rango, and H. Pelgrum, 2002b. Temperature and emissivity separation from multispectral thermal infrared observations, Remote Sensing of Environment, 79:189-198.
78. Schott, J.R., J.A. Barsi, B.L. Nordgren, N.G. Raqueño, and D. de Alwis, 2001. Calibration of Landsat thermal data and application to water resource studies, Remote Sensing of Environment, 78:108-117.
79. Shanahan, J.F., J.S. Schepers, D.D. Francis, G.E. Varvel, W.W. Wilhelm, J.S. Tringe, M.R. Schlemmer, and D.J. Major, 2001. Use of remote sensing imagery to estimate corn grain yield, Agronomy Journal, 93:583-589.
80. Slater, P.N., S.F. Biggar, R.G. Holm, R.D. Jackson, Y. Mao, M.S. Moran, J.M. Palmer, and B. Yuan (1986). Absolute radiometric calibration of the Thematic Mapper, Proceedings of the Society of Photo-Optical Instrumentation Engineers, 660:2-8.
81. Sudduth, K.A., N.R. Kitchen, D.F. Hughes, and S.T. Drummond, 1995. Electromagnetic induction sensing as an indicator of productivity on claypan soils, Proceedings of Site-Specific Management for Agricultural Systems, 27-30 March 1994, Minneapolis, Minnesota (ASA-CSSA-SSSA, Madison, Wisconsin), pp. 671-681.
82. Sudduth, K.A., S.T. Drummond, and N.R. Kitchen, 2001. Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture, Computers and Electronics in Agriculture, 31:239-264.
83. Walthall, C.L., S.E. Loechel, C.S.T. Daughtry, W.P. Dulaney, and L.J. Watson, 1999. Assessing sources of corn field variability using airborne imagery coincident with surface measurements, Proceedings of the 4th International Airborne Remote Sensing Conference/21st Canadian Symposium on Remote Sensing, 21-24 June, Ottawa, Ontario, Canada, P. II:367-374.
84. Webster, C.F., R.L. Repic, J.H. Everitt, D.E. Escobar, and M.R. Davis, 2000. Airborne videography for the inventory and mapping of point and nonpoint source discharges into the Rio Grand and Arroyo Colorado of subtropical south Texas, Geocarto International, 15:45-50.
85. Wiegand, C.L., and L.N. Namken, 1966. Influences of plant moisture stress, solar radiation and air temperature on cotton leaf temperature, Agronomy Journal, 58:552-556.
86. Yamaguchi, Y., A.B. Kahle, H. Tsu, T. Kawakami, and M. Pniel, 1998. Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), IEEE Transactions on Geoscience and Remote Sensing, 36:1062-1071.
87. Yang, C., and G.L. Anderson, 1996. Determining within-field management zones for grain sorghum using aerial videography, 26th International Symposium on Remote Sensing of the Environment, 25-29 March, Vancouver, B.C., Canada (International Center for Remote Sensing of Environment (ICRSE)), pp. 606-611.
88. Yang, C., J.H. Everitt, and C. Mao, 2001. An airborne hyperspectral imaging system for agricultural applications, Proceedings of the 18th Biennial Workshop on Color Aerial Photography and Videography in Resource Assessment, 16-18 May, Amherst, Massachusetts (American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland), unpaginated CD-Rom.