A PRI-based water stress index combining structural and chlorophyll effects: Assessment using diurnal narrow-band airborne imagery and the CWSI thermal index

Remote Sensing of Environment

Volumn 138, Issue , 2013, Pages 38-50

  Zarco Tejada, P J ^a   Gonzalez Dugo V ^a   Williams, L E ^b   Suarez L ^a   Berni, J A J ^a   Goldhamer, D ^c   Fereres, E ^a,d  

^a INSTITUTO DE AGRICULTURA SOSTENIBLE   (Spain)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Airborne; CWSI; Grapevines; Narrow band; PRI; Stress detection; Thermal; UAV

Indexed keywords

AIRBORNE; CWSI; GRAPEVINES; NARROW BANDS; PRI; STRESS DETECTION; THERMAL;

CHLOROPHYLL; UNMANNED AERIAL VEHICLES (UAV);

PLANTS (BOTANY);

AIRBORNE SENSING; CANOPY; CHLOROPHYLL; COMPARATIVE STUDY; EXPERIMENTAL STUDY; PIGMENT; PIXEL; RADIATIVE TRANSFER; STOMATAL CONDUCTANCE; VINEYARD; WATER STRESS;

EID: 84882656099     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2013.07.024     Document Type: Article

References (63)

1. Barton C.V.M., North P.R.J. Remote sensing of canopy light use efficiency using the photochemical reflectance index. Model and analysis. Remote Sensing of Environment 2001, 78:264-273.
2. Berni J.A.J., Zarco-Tejada P.J., Sepulcre-Cantó G., Fereres E., Villalobos F. Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery. Remote Sensing of Environment 2009, 113:2380-2388.
3. Berni J.A.J., Zarco-Tejada P.J., Suárez L., Fereres E. Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing 2009, 47(3):722-738.
4. Damm A., Erler A., Hillen W., Meroni M., Schaepman M.E., Verhoef W., et al. Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence. Remote Sensing of Environment 2011, 115:1882-1892.
5. Farquhar G.D., Wong S.C. An empirical model of stomatal conductance. Australian Journal of Plant Physiology 1984, 11:191-210.
6. Fereres E., Cruz-Romero G., Hoffman G.F., Rawlins S.L. Recovery of orange trees following severe water stress. Journal of Applied Ecology 1979, 16:833-842.
7. Fereres E., Soriano M. Deficit irrigation for reducing agricultural water use. Journal of Experimental Botany 2007, 58:147-159.
8. Flexas J., Briantais J.M., Cerovic Z., Medrano H., Moya I. Steady-state and maximum chlorophyll fluorescence responses to water stress in grapevine leaves: A new remote sensing system. Remote Sensing of Environment 2000, 73:282-297.
9. 2 assimilation and stomatal conductance during water-stress in C-3 plants. Physiologia Plantarum 2002, 114(2):231-240.
10. Flexas J., Escalona J.M., Medrano H. Water stress induces different levels of photosynthesis and electron transport rate regulation in grapevines. Plant, Cell & Environment 1999, 22:39-48.
11. Gamon J.A., Peñuelas J., Field C.B. A narrow-wave band spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment 1992, 41:35-44.
12. Gonzalez-Dugo V., Zarco-Tejada P.J., Berni J.A., Suarez L., Goldhamer D., Fereres E. Almond tree canopy temperature reveals intra-crown variability that is water stress-dependent. Agricultural and Forest Meteorology 2012, 154-155:156-165.
13. Grimes D.W., Williams L.E. Irrigation effects on plant water relations and productivity of Thompson seedless grapevines. Crop Science 1990, 30:255-260.
14. Gueymard C.A. SMARTS code, version 2.9.5 user's manual solar consulting services Online PDF document from. http://www.nrel.gov/rredc/smarts/.
15. Guillén-Climent M.L., Zarco-Tejada P.J., Berni J.A.J., North P.R.J., Villalobos F.J. Mapping radiation interception in row-structured orchards using 3D simulation and high resolution airborne imagery acquired from a UAV. Precision Agriculture 2012, 13:473-500.
16. Haboudane D., Miller J.R., Tremblay N., Zarco-Tejada P.J., Dextraze L. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment 2002, 84:416-426.
17. Hall A.E., Camacho-B S.E., Kaufmann M.R. Regulation of water loss by citrus leaves. Physiologia Plantarum 1975, 33:62-65.
18. Hall F.G., Hilker T., Coops N.C., Lyapustin A., Huemmrich K.F., Middleton E.M., et al. Multi-angle remote sensing of forest light use efficiency by observing PRI variation with canopy shadow fraction. Remote Sensing of Environment 2008, 112:3201-3211.
19. Hernández-Clemente R., Navarro-Cerrillo R., Suárez L., Morales F., Zarco-Tejada P.J. Assessing structural effects on PRI for stress detection in conifer forests. Remote Sensing of Environment 2011, 115(9):2360-2375.
20. Hilker T., Coops N.C., Hall F.G., Black T.A., Wulder M.A., Nesic Z., et al. Separating physiologically and directionally induced changes in PRI using BRDF models. Remote Sensing of Environment 2008, 112:2777-2788.
21. Idso S.B., Jackson R.D., Pinter P.J.J., Reginato R.J., Hatfield J.L. Normalizing the stress degree-day parameter for environmental variability. Agricultural Meteorology 1981, 24:45-55.
22. Idso S.B., Jackson R.D., Reginato R.J. Extending the "degree day" concept of plant phenological development to include water stress effects. Ecology 1978, 59:431-433.
23. Jackson R., Idso S., Reginato R., Pinter P.J. Canopy temperature as a crop water stress indicator. Water Resources Research 1981, 17:1133-1138.
24. Jones H.G. Plants and microclimate: A quantitative approach to environmental plant physiology 1992, Cambridge University Press, Cambridge.
25. Krause G.H., Weis E. Chlorophyll fluorescence as a tool in plant physiology. II. Interpretation of fluorescence signals. Photosynthesis Research 1984, 5:139-157.
26. Larcher W. Photosynthesis as a tool for indicating temperature stress events. Ecophysiology of photosynthesis 1994, 261-277. Springer, Berlin. E.D. Schulze, M.M. Caldwell (Eds.).
27. Leinonen I., Jones H.G. Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress. Journal of Experimental Botany 2004, 55(401):1423-1431.
28. Lichtenthaler H.K. The Kautsky effect: 60years of chlorophyll fluorescence induction kinetics. Photosynthetica 1992, 27:45-55.
29. Lichtenthaler H.K., Rinderle U. The role of chlorophyll fluorescence in the detection of stress conditions in plants. CRC Critical Reviews in Analytical Chemistry 1988, 19(Suppl. 1):529-585.
30. Meggio F., Zarco-Tejada P.J., Núñez L.C., Sepulcre-Cantó G., Gonzalez M.R., Martin P. Grape quality assessment in vineyards affected by iron deficiency chlorosis using narrow-band physiological remote sensing indices. Remote Sensing of Environment 2010, 114:1968-1986.
31. Meroni M., Colombo R., Cogliati S. High resolution leaf spectral signature for the detection of solar induced chlorophyll fluorescence. Proceedings of the 2nd ESA workshop on remote sensing of solar induced vegetation fluorescence, Montreal, Canada, 17-19 November 2004 2004.
32. Meroni M., Picchi V., Rossini M., Cogliati S., Panigada C., Nali C., et al. Leaf level early assessment of ozone injuries by passive fluorescence and PRI. International Journal of Remote Sensing 2008, 29(17):5409-5422.
33. Meroni M., Rossini M., Guanter L., Alonso L., Rascher U., Colombo R. Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications. Remote Sensing of Environment 2009, 113:2037-2051.
34. Meroni M., Rossini M., Picchi V., Panigada C., Cogliati S., Nali C., et al. Assessing steady-state fluorescence and PRI from hyperspectral proximal sensing as early indicators of plant stress: The case of ozone exposure. Sensors 2008, 8:1740-1754.
35. Middleton E.M., Cheng Y.B., Hilker T., Black T.A., Krishnan P., Coops N.C., et al. Linking foliage spectral responses to canopy level ecosystem photosynthetic light use efficiency at a Douglas-fir forest in Canada. Canadian Journal of Remote Sensing 2009, 35:166-188.
36. Miyashita K., Tanakamaru S., Maitani T., Kimura K. Recovery responses of photosynthesis, transpiration, and stomatal conductance in kidney bean following drought stress. Environmental and Experimental Botany 2005, 53:205-214.
37. Moran M.S., Clarke T.R., Inoue Y., Vidal A. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment 1994, 49:246-263.
38. Moya I., Camenen L., Evain S., Goulas Y., Cerovic Z.G., Latouche G. A new instrument for passive remote sensing 1. Measurements of sunlight-induced chlorophyll fluorescence. Remote Sensing of Environment 2004, 91:186-197.
39. Papageorgiou G. Chlorophyll fluorescence: An intrinsic probe of photosynthesis. Bioenergetics of photosynthesis 1975, 319-371. Academic Press, New York. Govindjee (Ed.).
40. Peguero-Pina J.J., Morales F., Flexas J., Gil-Pelegrín E., Moya I. Photochemistry, remotely sensed physiological reflectance index and de-epoxidation state of the xanthophyll cycle in Quercus coccifera under intense drought. Oecologia 2008, 156(1):1-11.
41. Rondeaux G., Steven M., Baret F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment 1996, 55:95-107.
42. Rougean J.-L., Breon F.M. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sensing of Environment 1995, 51:375-384.
43. Rouse J.W., Haas R.H., Schell J.A., Deering D.W., Harlan J.C. Monitoring the vernal advancements and retrogradation of natural vegetation. Nasa/Gsfc final report 1974, 371. U.G. MD (Ed.).
44. Schreiber U., Bilger W. Rapid assessment of stress effects on plant leaves by chlorophyll fluorescence measurements. Plant response to stress 1987, 27-53. Springer-Verlag, Berlin, Germany. J.D. Tenhunen, E.M. Catarino (Eds.).
45. Schreiber U., Bilger W., Neubauer C. Chlorophyll fluorescence as a non-intrusive indicator for rapid assessment of in vivo photosynthesis. Ecological studies 1994, vol. 100:49-70. Springer, Berlin Heidelberg New York. E.D. Schulze, M.M. Caldwell (Eds.).
46. Sepulcre-Cantó G., Zarco-Tejada P.J., Jiménez-Muñoz J.C., Sobrino J.A., Miguel E.D., Villalobos F.J. Detection of water stress in an olive orchard with thermal remote sensing imagery. Agricultural and Forest Meteorology 2006, 136(1-2):31-44.
47. Sepulcre-Cantó G., Zarco-Tejada P.J., Jiménez-Muñoz J.C., Sobrino J.A., Soriano M.A., Fereres E., et al. Monitoring yield and fruit quality parameters in open-canopy tree crops under water stress. Implications for ASTER. Remote Sensing of Environment 2007, 107:455-470.
48. Stagakis S., González-Dugo V., Cid P., Guillén-Climent M.L., Zarco-Tejada P.J. Monitoring water stress and fruit quality in an orange orchard under regulated deficit irrigation using narrow-band structural and physiological remote sensing indices. ISPRS Journal of Photogrammetry and Remote Sensing 2012, 71:47-61.
49. Suarez L., Zarco-Tejada P.J., Berni J.A.J., González-Dugo V., Fereres E. Modelling PRI for water stress detection using radiative transfer models. Remote Sensing of Environment 2009, 113:730-744.
50. Suarez L., Zarco-Tejada P.J., González-Dugo V., Berni J.A.J., Sagardoy R., Morales F., et al. Detecting water stress effects on fruit quality in orchards with time-series PRI airborne imagery. Remote Sensing of Environment 2010, 114:286-298.
51. Suarez L., Zarco-Tejada P.J., Sepulcre-Cantó G., Pérez-Priego O., Miller J.R., Jiménez-Muñoz J.C., et al. Assessing canopy PRI for water stress detection with diurnal airborne imagery. Remote Sensing of Environment 2008, 112:560-575.
52. Thenot F., Méthy M., Winkel T. The Photochemical Reflectance Index (PRI) as a water-stress index. International Journal of Remote Sensing 2002, 23(23):5135-5139.
53. Villalobos F.J., Testi L., Moreno-Perez M.F. Evaporation and canopy conductance of citrus orchard. Agricultural Water Management 2008, 96(4):565-573.
54. Williams L.E., Araujo F. Correlations among predawn leaf, midday leaf, and midday stem water potential and their correlations with other measures of soil and plant water status in Vitis vinifera L. Journal of the American Society for Horticultural Science 2002, 127:448-454.
55. Williams L.E., Baeza P., Vaughn P. Midday measurements of leaf water potential and stomatal conductance are highly correlated with daily water use of Thompson Seedless grapevines. Irrigation Science 2012, 30(3):201-212.
56. Williams L.E., Grimes D.W., Phene C.J. The effects of applied water at various fractions of measured evapotranspiration on water relations and vegetative growth of Thompson Seedless. Irrigation Science 2010, 28:221-232.
57. Williams L.E., Phene C.J., Grimes D.W., Trout T.J. Water use of mature Thompson Seedless grapevines in California. Irrigation Science 2003, 22(1):11-18.
58. Williams L.E., Trout T.J. Relationships among vine and soil based measures of water status in a Thompson Seedless vineyard in response to high frequency drip irrigation. American Journal of Enology and Viticulture 2005, 56:357-366.
59. Zarco-Tejada P.J., Catalina A., González M.R., Martín P. Relationships between net photosynthesis and steady-state chlorophyll fluorescence retrieved from airborne hyperspectral imagery. Remote Sensing of Environment 2013, 136:247-258.
60. Zarco-Tejada P.J., González-Dugo V., Berni J.A.J. Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sensing of Environment 2012, 117:322-337.
61. Zarco-Tejada P.J., Guillén-Climent M.L., Hernández-Clemente R., Catalina A., González M.R., Martín P. Estimating leaf carotenoid content in vineyards using high resolution hyperspectral imagery acquired from an unmanned aerial vehicle. Agricultural and Forest Meteorology 2013, 171-172:281-294.
62. Zarco-Tejada P.J., Miller J.R., Mohammed G.H., Noland T.L. Chlorophyll fluorescence effects on vegetation apparent reflectance: I. Leaf-level measurements and model simulation. Remote Sensing of Environment 2000, 74(3):582-595.
63. Zarco-Tejada P.J., Miller J.R., Mohammed G.H., Noland T.L., Sampson P.H. Vegetation stress detection through chlorophyll a+b estimation and fluorescence effects on hyperspectral imagery. Journal of Environmental Quality 2002, 31:1433-1441.