Estimation of watershed-level distributed forest structure metrics relevant to hydrologic modeling using LiDAR and Landsat

Journal of Hydrology

Volumn 487, Issue , 2013, Pages 70-86

  Varhola, Andrés ^a   Coops, Nicholas C ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Airborne Laser Scanning; Distributed modeling; Hydrologic processes; Mountain pine beetle; Snow water equivalent; Spectral indices

Indexed keywords

AIRBORNE LASER SCANNING; DISTRIBUTED MODELING; HYDROLOGIC PROCESS; MOUNTAIN PINE BEETLE; SNOW WATER EQUIVALENT; SPECTRAL INDICES;

CATCHMENTS; EXTRAPOLATION; FORESTRY; LASER APPLICATIONS; MATHEMATICAL MODELS; OPTICAL RADAR; REMOTE SENSING; SNOW; VEGETATION; WATER SUPPLY; WATERSHEDS;

THREE DIMENSIONAL;

ABLATION; AIRBORNE SENSING; EVAPOTRANSPIRATION; FOREST; HYDROLOGICAL MODELING; LANDSAT; LANDSAT THEMATIC MAPPER; LANDSCAPE; LIDAR; REMOTE SENSING; SNOW ACCUMULATION; SPECTRAL RESOLUTION; VEGETATION STRUCTURE; WATERSHED;

HYDROLOGY; INSECTS; LASERS; REMOTE SENSING; SCANNING; SNOW; THREE DIMENSIONAL DESIGN; WATER SHEDS; WATER SUPPLY;

COLEOPTERA; HEXAPODA; PINUS MUGO;

EID: 84875663591     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2013.02.032     Document Type: Article

References (90)

1. Alila Y., KuraŚ P.K., Schnorbus M., Hudson R. Forests and floods: a new paradigm sheds light on age-old controversies. Water Resour. Res. 2009, 45(8):1-24.
2. Andersen J., Dybkjaer G., Jensen K., Refsgaard J., Rasmussen K. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model. J. Hydrol. 2002, 264(1-4):34-50.
3. Andreadis K., Lettenmaier D.P. Assimilating remotely sensed snow observations into a macroscale hydrology model. Adv. Water Resour. 2006, 29(6):872-886.
4. Beven K. Calibration, validation and equifinality in hydrological modelling: a continuing discussion. Model Validation: Perspectives in Hydrological Science 2001, John Wiley & Sons, pp. 43-55. M.G. Anderson, P.D. Bates (Eds.).
5. Bewley D., Alila Y., Varhola A. Variability of snow water equivalent and snow energetics across a large catchment subject to Mountain Pine Beetle infestation and rapid salvage logging. J. Hydrol. 2010, 388:464-479.
6. Biftu G.F., Gan T.Y. Semi-distributed, physically based, hydrologic modeling of the Paddle River Basin, Alberta, using remotely sensed data. J. Hydrol. 2001, 244(3-4):137-156.
7. Boon, S., 2007a. Infestation and Salvage Harvesting on Seasonal Snow Melt and Runoff. Canadian Forest Service, 28 pp.
8. Boon S. Snow accumulation and ablation in a beetle-killed pine stand in Northern Interior British Columbia. BC J. Ecosyst. Manage. 2007, 8(3):1-13.
9. Boon S. Snow ablation energy balance in a dead forest stand. Hydrol. Process. 2009, 23:2600-2610.
10. Brooks K., Ffolliot P., Gregersen H., DeBano L. Hydrology and the Management of Watersheds 2003, Iowa State University Press, Ames, IA. third ed.
11. Burges S.J. Invited perspective: why I am an optimist. Water Resour. Res. 2011, 47:1-14.
12. Chavez P.S. Image-based atmospheric corrections: revisited and improved. Photogram. Eng. Remote Sensing 1996, 62:1025-1036.
13. Chen J.M., Chen X., Ju W., Geng X. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs. J. Hydrol. 2005, 305(1-4):15-39.
14. Chen J.M., Rich P.M., Gower S.T., Norman J.M., Plummer S. Leaf area index of boreal forests: theory, techniques, and measurements. J. Geophys. Res. 1997, 102(D24):29429-29443.
15. Chen X., Vierling L., Rowell E., DeFelice T. Using lidar and effective LAI data to evaluate IKONOS and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest. Remote Sens. Environ. 2004, 91(1):14-26.
16. Coops N.C., Varhola A., Bater C.W., Teti P., Boon S. Assessing differences in tree and stand structure following beetle infestation using LiDAR data. Can J. Remote Sens. 2009, 35(6):497-508.
17. Donoghue D., Watt P. Using LiDAR to compare forest height estimates from IKONOS and Landsat ETM+ data in Sitka spruce plantation forests. Int. J. Remote Sens. 2006, 27(11):2161-2175.
18. Dozier J. Mountain hydrology, snow color, and the fourth paradigm. Eos 2011, 92(43):373-384.
19. Droogers P., Kite G. Remotely sensed data used for modelling at different hydrological scales. Hydrol. Process. 2002, 16:1543-1556.
20. Ellis C.R., Pomeroy J.W., Brown T., MacDonald J. Simulation of snow accumulation and melt in needleleaf forest environments. Hydrol. Earth Syst. Sci. 2010, 14(6):925-940.
21. Essery R., Pomeroy J.W., Ellis C.R., Link T.E. Modelling longwave radiation to snow beneath forest canopies using hemispherical photography or linear regression. Hydrol. Process. 2008, 22:2788-2800.
22. Fang X., Pomeroy J.W., Westbrook C.J., Guo X., Minke A.G., Brown T. Prediction of snowmelt derived streamflow in a wetland dominated prairie basin. Hydrol. Earth Syst. Sci. 2010, 14:991-1006.
23. Field A. Discovering Statistics using SPSS 2005, Sage Publications. second ed.
24. Franklin S.E. Forest structure estimation. Remote Sensing for Sustainable Forest Management 2001, 251-285. Lewis Publishers. S.E. Franklin (Ed.).
25. Franklin S.E. Remote Sensing for Sustainable Forest Management 2001, Lewis Publishers.
26. Franklin S.E. Mountain pine beetle red-attack forest damage classification using stratified Landsat TM data in British Columbia, Canada. Photogramm. Eng. Remote Sens. 2003, 69(3):283.
27. Frazer, G.W., Canham, C.D., Lertzman, K.P., 1999. Gap Light Analyzer (GLA): Version 2.0: Imaging Software to Extract Canopy Structure and Gap Light Transmission Indices from True-colour Fisheye Photographs. Users Manual and Program Documentation, Version 2.0. Simon Fraser University, Institute of Ecosystem Studies, 36 pp.
28. Gill T., Phinn S., Armston J., Pailthorpe B. Estimating tree-cover change in Australia: challenges of using the MODIS vegetation index product. Int. J. Remote Sens. 2009, 30(6):1547-1565.
29. Hennon P.E., D'Amore D.V., Witter D.T. Influence of forest canopy and snow on microclimate in a declining yellow-cedar forest of Southeast Alaska. Northwest Sci. 2010, 84(1):73-87.
30. Hyyppä J., Hyyppä H., Leckie D., Gougeon F., Yu X., Maltamo M. Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. Int. J. Remote Sens. 2008, 29:1339-1366.
31. Immerzeel W.W., Droogers P., de Jong S.M., Bierkens M.F.P. Large-scale monitoring of snow cover and runoff simulation in Himalayan river basins using remote sensing. Remote Sens. Environ. 2009, 113(1):40-49.
32. Jackson S.I., Prowse T.D. Spatial variation of snowmelt and sublimation in a high-elevation semi-desert basin of western Canada. Hydrol. Process. 2009, 23:2611-2627.
33. Jensen J.R. Remote Sensing of the Environment 2007, Pearson Prentice Hall, Upper Saddle River, NJ. second ed.
34. Jones H.G., Vaughan R.A. Remote Sensing of Vegetation 2010, Oxford University Press, New York, NY.
35. Jost G., Moore R.D., Weiler M., Gluns D., Alila Y. Use of distributed snow measurements to test and improve a snowmelt model for predicting the effect of forest clear-cutting. J. Hydrol. 2009, 376(1-2):94-106.
36. Kauth, R.J., Thomas, G.S., 1976. The tasselled cap-a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. In: 2nd International Symposium of Remotely Sensed Data, Purdue University, West Lafayette, IN, p. 159.
37. Kraus K., Pfeifer N. Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS J. Photogramm. Remote Sens. 1998, 53(4):193-203.
38. KuraŚ P.K., Alila Y., Weiler M. Forest harvesting effects on the magnitude and frequency of peak flows can increase with return period. Water Resour. Res. 2012, 48(1):1-19.
39. Leblanc S.G., Chen J.M., Fernandes R., Deering D.W., Conley A. Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests. Agric. For. Meteorol. 2005, 129(3-4):187-207.
40. Lim K., Treitz P., Wulder M., St-Onge B., Flood M. LiDAR remote sensing of forest structure. Prog. Phys. Geog. 2003, 27(1):88-106.
41. Liston G.E. Interrelationships among snow distribution, snowmelt, and snow cover depletion: Implications for atmospheric, hydrologic, and ecologic modeling. J. Appl. Meteorol. 1999, 38:1474-1488.
42. Liston G.E., Elder K. A distributed snow-evolution modeling system (SnowModel). J. Hydrometeor. 2006, 7(6):1259-1275.
43. Liu T., Willems P., Feng X.W., Li Q., Huang Y., Bao A.M., Chen X., Veroustraete F., Dong Q.H. On the usefulness of remote sensing input data for spatially distributed hydrological modelling: case of the Tarim River basin in China. Hydrol. Process. 2012, 26:335-344.
44. Luce C.H., Tarboton D.G., Cooley K.R. The influence of the spatial distribution of snow on basin-averaged snowmelt. Hydrol. Process. 1998, 12:1671-1683.
45. McGaughey, R.J., 2010. FUSION/LDV: Software for LIDAR data Analysis and Visualization. US Department of Agriculture, 150 pp.
46. McMillan A.M.S., Goulden M.L. Age-dependent variation in the biophysical properties of boreal forests. Global Biogeochem. Cycles 2008, 22(2):1-14.
47. Miller J.B. A formula for average foliage density. Aust. J. Bot. 1967, 15:141-144.
48. Mitchell R.G., Preisler H.K. Fall rate of lodgepole pine killed by the mountain pine beetle in central Oregon. West. J. Appl. For. 1998, 13(1):23-26.
49. Montes F., Rubio A., Barbeito I., Cañellas I. Characterization of the spatial structure of the canopy in Pinus silvestris L. stands in Central Spain from hemispherical photographs. Forest Ecol. Manag. 2008, 255(3-4):580-590.
50. Morsdorf F., Kötz B., Meier E., Itten K., Allgöwer B. Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction. Remote Sens. Environ. 2006, 104(1):50-61.
51. Murphy P.N., Ogilvie J., Meng F.-R., Arp P. Stream network modelling using lidar and photogrammetric digital elevation models: a comparison and field verification. Hydrol. Process. 2008, 22:1747-1754.
52. Ngigi T.G., Tateishi R., Gachari M. Global mean values in linear spectral unmixing: double fallacy!. Int. J. Remote Sens. 2009, 30(5):1109-1125.
53. Nolin A.W. Recent advances in remote sensing of seasonal snow. J. Glaciol. 2011, 56(200):1141-1150.
54. Néelz S., Pender G., Villanueva I., Wilson M., Wright N.G., Bates P., Mason D., Whitlow C. Using remotely sensed data to support flood modelling. Water Manage. 2006, 159(1):35-43.
55. Petroselli A. LiDAR data and hydrological applications at the basin scale. GISci. Remote Sens. 2012, 49(1):139-162.
56. Pomeroy J.W., Dion K. Winter radiation extinction and reflection in a boreal pine canopy: measurements and modelling. Hydrol. Process. 1996, 10(12):1591-1608.
57. Pomeroy J.W., Gray D., Brown T., Hedstrom N., Quinton W., Granger R., Carey S. The cold regions hydrological model: a platform for basing process representation and model structure on physical evidence. Hydrol. Process. 2007, 21:2650-2667.
58. Pomeroy J.W., Gray D., Hedstrom N., Janowicz J. Prediction of seasonal snow accumulation in cold climate forests. Hydrol. Process. 2002, 16(18):3543-3558.
59. Pomeroy J.W., Marks D., Link T., Ellis C.R., Hardy J.P., Rowlands A., Granger R. The impact of coniferous forest temperature on incoming longwave radiation to melting snow. Hydrol. Process. 2009, 23(17):2513-2525.
60. Pugh E., Gordon E. A conceptual model of water yield impacts from beetle-induced tree death in snow-dominated lodgepole pine forests. Hydrol. Process. 2012, 10.1002/hyp. 9312.
61. Roth B.E., Slatton K.C., Cohen M.J. On the potential for high-resolution lidar to improve rainfall interception estimates in forest ecosystems. Front. Ecol. Environ. 2012, 5(8):421-428.
62. Roy A., Royer A., Turcotte R. Improvement of springtime streamflow simulations in a boreal environment by incorporating snow-covered area derived from remote sensing data. J. Hydrol. 2010, 390:35-44.
63. Schmugge T., Kustas W., Ritchie J., Jackson T., Rango A. Remote sensing in hydrology. Adv. Water Resour. 2002, 25(8-12):1367-1385.
64. Service R. As the west goes dry. Science 2004, 303:1124-1127.
65. Shengli H., Young C., Feng M., Heidemann K., Cushing M., Mushet D.M., Shuguang L. Demonstration of a conceptual model for using LiDAR to improve the estimation of floodwater mitigation potential of Prairie Pothole Region wetlands. J. Hydrol. 2011, 405(3-4):417-426.
66. Shook K.R., Pomeroy J.W. Memory effects of depressional storage in Northern Prairie hydrology. Hydrol. Process. 2011, 25(25):3890-3898.
67. Sicart J.E., Essery R., Pomeroy J.W., Hardy J.P., Link T.E., Marks D. A sensitivity study of daytime net radiation during snowmelt to forest canopy and atmospheric conditions. J. Hydrometeor. 2004, 5(5):774-784.
68. Silleos N.G., Alexandridis T.K., Gitas I.Z., Perakis K. Vegetation indices: advances made in biomass estimation and vegetation monitoring in the last 30 years. Geocarto Int. 2006, 21(4):21-28.
69. Singh V., Woolhiser D. Mathematical modeling of watershed hydrology. J. Hydrol. Eng. 2002, 7(4):270-292.
70. Skakun R.S., Wulder M.A., Franklin S.E. Sensitivity of the thematic mapper enhanced wetness difference index to detect mountain pine beetle red-attack damage. Remote Sens. Environ. 2003, 86(4):433-443.
71. Solberg S., Næsset E., Hanssen K.H., Christiansen E. Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning. Remote Sens. Environ. 2006, 102:364-376.
72. Stenberg P., Linder S., Smolander H., Flower-Ellis J. Performance of the LAI-2000 plant canopy analyzer in estimating leaf area index of some Scots pine stands. Tree Physiol. 1994, 14:981-995.
73. Storck, P., 2000. Trees, Snow and Flooding. An Investigation of Forest Canopy Effects on Snow Accumulation and Melt at the Plot and Watershed Scales in the Pacific Northwest. In: Water Resources Series, Technical Report 161. University of Washington, Seattle, WA, 176 pp.
74. Tang Q., Gao H., Lu H., Lettenmaier D.P. Remote sensing: hydrology. Prog. Phys. Geog. 2009, 33(4):490-509.
75. Teti, P., 2008. Effects of Overstory Mortality on Snow Accumulation and Ablation. Ministry of Forests and Range, Williams Lake, British Columbia. 41 pp.
76. Toomey M., Vierling L.A. Multispectral remote sensing of landscape level foliar moisture: techniques and applications for forest ecosystem monitoring. Can. J. For. Res. 2005, 35(5):1087-1097.
77. Varhola A., Coops N.C., Bater C.W., Teti P., Boon S., Weiler M. The influence of ground- and lidar-derived forest structure metrics on snow accumulation and ablation in disturbed forests. Can. J. For. Res. 2010, 40(4):812-821.
78. Varhola A., Coops N.C., Weiler M., Moore R.D. Forest canopy effects on snow accumulation and ablation: an integrative review of empirical results. J. Hydrol. 2010, 392:219-233.
79. Varhola A., Frazer G.W., Teti P., Coops N.C. Estimation of forest structure metrics relevant to hydrologic modeling using coordinate transformation of airborne laser scanning data. Hydrol. Earth Syst. Sci. 2012, 16(10):3749-3766.
80. Vetter M., Höfle B., Mandlburger G., Rutzinger M. Estimating changes of riverine landscapes and riverbeds by using airborne LiDAR data and river cross-sections. Z. Geomorphol. 2011, 55(2):51-65.
81. Wagner W., Verhoest N., Ludwig R., Tedesco M. Remote sensing in hydrological sciences. Hydrol. Earth Syst. Sci. 2009, 13:813-817.
82. Wang J., Sammis T.W., Gutschick V.P., Gebremichael M., Dennis S.O., Harrison R.E. Review of satellite remote sensing use in forest health studies. Open Geog. J. 2010, 3:28-42.
83. Watson D.J. Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and within. Ann. Bot. 1947, XI(41):41-76.
84. Welles J.M., Norman J.M. Instrument for indirect measurement of canopy architecture. Agron. J. 1991, 83(5):818-825.
85. Wigmosta M., Vail L., Lettenmaier D.P. A distributed hydrology-vegetation model for complex terrain. Water Resour. Res. 1994, 30(6):1665-1679.
86. Williams D.L. A comparison of spectral reflectance properties at the needle, branch, and canopy level for selected conifer species. Remote Sens. Environ. 1991, 35(2-3):79-93.
87. Wolter P., Townsend P., Sturtevant B. Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data. Remote Sens. Environ. 2009, 113(9):2019-2036.
88. Wulder M.A., Dymond C.C., White J.C., Leckie D.G., Carroll A.L. Surveying mountain pine beetle damage of forests: a review of remote sensing opportunities. Forest Ecol. Manag. 2006, 221:27-41.
89. Wulder M.A., Bater C.W., Coops N.C., Hilker T., White J.C. The role of LiDAR in sustainable forest management. Forest. Chron. 2008, 84(6):807-826.
90. Zhang Y., Chen J.M., Miller J.M., Noland T.L. Retrieving chlorophyll content in conifer needles from hyperspectral measurements. Can J. Remote Sens. 2008, 34(3):296-310.