Assessing water stress of desert tamarugo trees using in situ data and very high spatial resolution remote sensing

Remote Sensing

Volumn 5, Issue 10, 2013, Pages 5064-5088

  Chávez, Roberto O ^a   Clevers, Jan G P W ^a   Herold, Martin ^a   Acevedo, Edmundo ^b   Ortiz, Mauricio ^b,c  

^a WAGENINGEN UNIVERSITY   (Netherlands)

^b UNIVERSITY OF CHILE   (Chile)

^c Centro de Estudios Avanzados en Fruticultura (CEAF)   (Chile)

Author keywords

Arid ecosystems; Green canopy fraction; Groundwater depletion; Lai; Pulvinar movement; Satellite images; Vegetation indices; Water stress

Indexed keywords

ARID ECOSYSTEMS; GREEN CANOPY; GROUNDWATER DEPLETION; LAI; PULVINAR MOVEMENT; SATELLITE IMAGES; VEGETATION INDEX; WATER STRESS;

FORESTRY; GROUNDWATER; SATELLITE IMAGERY;

TREES (MATHEMATICS);

ECOSYSTEMS; FOREST CANOPY; GROUND WATER; IMAGES; PLANTS; SATELLITES;

EID: 84887804201     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs5105064     Document Type: Article

References (53)

1. Ezcurra, E. Global Deserts Outlook; United Nations Environment Programme: Nairobi, Kenya, 2006.
2. Blaschke, T. Object based image analysis for remote sensing. ISPRS J Photogram. Remote Sens. 2010, 65, 2-16.
3. Laliberte, A.S.; Rango, A.; Havstad, K.M.; Paris, J.F.; Beck, R.F.; McNeely, R.; Gonzalez, A.L. Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico. Remote Sens. Environ. 2004, 93, 198-210.
4. Laliberte, A.S.; Fredrickson, E.L.; Rango, A. Combining decision trees with hierarchical object-oriented image analysis for mapping arid rangelands. Photogram. Eng. Remote Sens. 2007, 73, 197-207.
5. Gibbes, C.; Adhikari, S.; Rostant, L.; Southworth, J.; Qiu, Y., Application of object based classification and high resolution satellite imagery for savanna ecosystem analysis. Remote Sens. 2010, 2, 2748-2772.
6. Asner, G.P.; Wessman, C.A.; Bateson, C.A.; Privette, J.L. Impact of tissue, canopy, and landscape factors on the hyperspectral reflectance variability of arid ecosystems. Remote Sens. Environ. 2000, 74, 69-84.
7. Borzuchowski, J.; Schulz, K. Retrieval of leaf area index (LAI) and soil water content (WC) using hyperspectral remote sensing under controlled glass house conditions for spring barley and sugar beet. Remote Sens. 2010, 2, 1702-1721.
8. Chávez, R.O.; Clevers, J.G.P.W.; Herold, M.; Ortiz, M.; Acevedo, E. Modelling the spectral response of the desert tree Prosopis tamarugo to water stress. Int. J. Appl. Earth Obs. Geoinf. 2013, 21, 53-65.
9. Taiz, L.; Zeiger, E. Plant Physiology; Sinauer Associates: Sunderland, MA, USA, 2010.
10. Kimes, D.S.; Kirchner, J.A. Diurnal variations of vegetation canopy structure. Int. J. Remote Sens. 1983, 4, 257-271.
11. Moran, M.S.; Pinter, P.J., Jr; Clothier, B.E.; Allen, S.G. Effect of water stress on the canopy architecture and spectral indices of irrigated alfalfa. Remote Sens. Environ. 1989, 29, 251-261.
12. Verhoef, W.; Bach, H. Coupled soil-leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data. Remote Sens. Environ. 2007, 109, 166-182.
13. Rojas, R.; Dassargues, A. Groundwater flow modelling of the regional aquifer of the Pampa del Tamarugal, Northern Chile. Hydrogeol. J. 2007, 15, 537-551.
14. Romero, H.; Méndez, M.; Smith, P. Mining development and environmental injustice in the Atacama Desert of Northern Chile. Environ. Justice 2012, 5, 70-76.
15. Gajardo, R. La Vegetación Natural de Chile Clasificación y Distribución Geográfica; Editorial Universitaria: Santiago, Chile, 1994.
16. CONAMA. Biodiversidad de Chile, Patrimonio Y Desafíos; Ocho Libros Editores: Santiago, Chile, 2008.
17. CONAF. Plan de Manejo Reserva Nacional Pampa del Tamarugal; Corporación Nacional Forestal (CONAF). Ministerio de Agricultura: Gobierno, Chile, 1997; p. 110.
18. Estades, C.F. Natural history and conservation status of the Tamarugo Conebill in northern Chile. Wilson Bull. 1996, 108, 268-279.
19. Ramírez-Leyton, G.; Pincheira-Donoso, D. Fauna del Altiplano y Desierto de Atacama. Vertebrados de la Provncia de El Loa; Phrynosaura Ediciones: Calama, Chile, 2005.
20. Oyarzún, J.; Oyarzún, R. Sustainable development threats, inter-sector conflicts and environmental policy requirements in the arid, mining rich, Northern Chile territory. Sustain. Dev. 2011, 19, 263-274.
21. Burkart, A. A monograph of the genus Prosopis (Leguminosae subfam. Mimosoideae). J. Arnold. Arbor. 1976, 57, 219-249.
22. Altamirano, H. Prosopis tamarugo Phil. Tamarugo. In Las especies arbóreas de los bosques templados de Chile y Argentina. Autoecología; Donoso, C., Ed.; Marisa Cuneo Ediciones: Valdivia,Chile, 2006; pp 534-540.
23. Riedemann, P.; Aldunate, G.; Teillier, S. Flora nativa de valor ornamental. Chile, Zona Norte. Identificación y propagación; Productora Gráfica Andros Ltda: Santiago, Chile, 2006; p. 404.
24. Acevedo, E.; Ortiz, M.; Franck, N.; Sanguineti, P. Relaciones hídricas de Prosopis tamarugo Phil. Uso de isótopos estables; Universidad de Chile: Santiago, Chile, 2007; p. 82.
25. Sudzuki, F. Environmental Influence on Foliar Anatomy of Prosopis Tamarugo Phil. In The Current State of Knowledge on Prosopis Tamarugo; Habit, M., Ed.; FAO: Rome, Italy, 1985.
26. DICTUC. Anexo VIII.2 Modelación de la Evolución del Nivel de la Napa en la Pampa del Tamarugal. In EIA proyecto Pampa Hermosa; Dirección de Investigaciones Científicas y Tecnológicas Universidad Católica de Chile, Santiago, Chile, 2008; p 169.
27. Geohidrología-SQM. Informe Semestral 2. In Plan de Segumiento Ambiental Hidrogeológico Proyecto Pampa Hermosa; Geohidrología: Santiago, Chile, 2012; p. 118.
28. Meyer, W.S.; Ritchie, J.T. Resistance to water flow in the Sorghum plant. Plant. Physiol. 1980, 65, 33-39.
29. Scholander, P.F.; Hammel, H.T.; Bradstreet, E.D.; Hemmingsen, E.A. Sap pressure in vascular plants. Science 1965, 148, 339-346.
30. Lichtenthaler, H.K.; Wellburn, A.R. Determination of total carotenoids and chlorophyll a and b of leaf extract in different solvents. Biochem. Soc. Trans. 1983, 591-592.
31. LI-COR. LAI-2000 Plant Canopy Analyser. Instruction Manual; LICOR: Lincoln, NE, USA, 1992.
32. Jonckheere, I.; Fleck, S.; Nackaerts, K.; Muys, B.; Coppin, P.; Weiss, M.; Baret, F. Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agric. For. Meteorol. 2004, 121, 19-35.
33. Peper, P.J.; McPherson, E.G. Evaluation of four methods for estimating leaf area of isolated trees. Urban. For. Urban. Green. 2003, 2, 19-29.
34. Ortiz, M.; Silva, P.; Acevedo, E. Leaf Water Parameters in Prosopis Tamarugo Phil. Subject to a Lowering of the Water Table. In Nivel freático en la Pampa del Tamarugal y Crecimiento de Prosopis tamarugo Phil; Tesis para optar al Grado Académico de Doctor en Ciencias Silvoagrpecuarias y Veterinarias: Santiago, Chile, 2010; pp. 15-42.
35. Updike, T.; Comp, C. Radiometric Use of WorldView2 Imagery; Technical Note; Revision 1; DigitalGlobe, Inc.: Longmont, CO, USA, 2010; p. 17.
36. Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8, 127-150.
37. Gitelson, A.A.; Keydan, G.P.; Merzlyak, M.N. Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophys. Res. Lett. 2006, 33, L11402.
38. Pastenes, C.; Pimentel, P.; Lillo, J. Leaf movements and photoinhibition in relation to water stress in field-grown beans. J. Exp. Bot. 2005, 56, 425-433.
39. Liu, C.C.; Welham, C.V.J.; Zhang, X.Q.; Wang, R.Q. Leaflet movement of Robinia pseudoacacia in response to a changing light environment. J. Integr. Plant. Biol. 2007, 49, 419-424.
40. Pastenes, C.; Porter, V.; Baginsky, C.; Norton, P.; González, J. Paraheliotropism can protect water-stressed bean (Phaseolus vulgaris L.) plants against photoinhibition. J. Plant. Physiol. 2004, 161, 1315-1323.
41. Ortega, A.; Escobar, R.; Colle, S.; de Abreu, S.L. The state of solar energy resource assessment in Chile. Renewable Energy 2010, 35, 2514-2524.
42. Hirschmann, R.J. Records on solar radiation in Chile. Solar Energy 1973, 14, 129-138.
43. Schmidhalter, U. The gradient between pre-dawn rhizoplane and bulk soil matric potentials, and its relation to the pre-dawn root and leaf water potentials of four species. Plant. Cell. Environ. 1997, 20, 953-960.
44. Veste, M.; Staudinger, M.; Küppers, M. Spatial and temporal variability of soil water in drylands: Plant water potential as a diagnostic tool. Forestry Studies China 2008, 10, 74-80.
45. Richter, H. Water relations of plants in the field: some comments on the measurement of selected parameters. J. Exp. Bot. 1997, 48, 1-7.
46. Boochs, F.; Kupfer, G.; Dockter, K.; Kuhbauch, W. Shape of the red edge as vitality indicator for plants. Int. J. Remote Sens. 1990, 11, 1741-1753.
47. Filella, I.; Penuelas, J. The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status. Int. J. Remote Sens. 1994, 15, 1459-1470.
48. Horler, D.N.H.; Dockray, M.; Barber, J. The red edge of plant leaf reflectance. Int. J. Remote Sens. 1983, 4, 273-288.
49. Carter, G.A.; Knapp, A.K. Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. Am. J. Bot. 2001, 88, 677-684.
50. Malenovský, Z.; Bartholomeus, H.M.; Acerbi-Junior, F.W.; Schopfer, J.T.; Painter, T.H.; Epema, G.F.; Bregt, A.K. Scaling dimensions in spectroscopy of soil and vegetation. Int. J. Appl. Earth Obs. Geoinf. 2007, 9, 137-164.
51. Moorthy, I.; Miller, J.R.; Noland, T.L. Estimating chlorophyll concentration in conifer needles with hyperspectral data: An assessment at the needle and canopy level. Remote Sens. Environ. 2008, 112, 2824-2838.
52. o zenith angle: Theoretical considerations based on 3D architecture models and application to wheat crops. Agric. For. Meteorol. 2010, 150, 1393-1401.
53. Liu, J.; Pattey, E.; Admiral, S. Assessment of in situ crop LAI measurement using unidirectional view digital photography. Agric. For. Meteorol. 2013, 169, 25-34.