Phenology-guided saltcedar (Tamarix spp.) mapping using Landsat TM images in western U.S.

Remote Sensing of Environment

Volumn 173, Issue , 2016, Pages 29-38

  Ji, Wenjie ^a   Wang, Le ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

End of Season Time (EoST); Landsat TM; Phenology; Saltcedar mapping

Indexed keywords

BIOLOGY; CLASSIFICATION (OF INFORMATION); IMAGE ACQUISITION; IMAGE RECONSTRUCTION; MAPPING; PIXELS; REMOTE SENSING; SPACE OPTICS;

CLASSIFICATION RESULTS; END OF SEASON-TIME (EOST); LANDSAT TM; PHENOLOGY; REMOTE SENSING IMAGERY; REMOTE SENSING IMAGES; SALTCEDAR; SPECTRAL SIGNATURE;

IMAGE PROCESSING;

COLOR; IMAGE ANALYSIS; IMAGE CLASSIFICATION; LANDSAT; MODIS; PHENOLOGY; PIXEL; REMOTE SENSING; RIVER; SATELLITE IMAGERY; SPATIOTEMPORAL ANALYSIS;

RIO GRANDE BASIN [NORTH AMERICA]; UNITED STATES;

TAMARIX;

EID: 84947768315     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2015.11.017     Document Type: Article

References (51)

1. Akasheh O.Z., Neale C.M.U., Jayanthi H. Detailed mapping of riparian vegetation in the middle Rio Grande using high resolution multi-spectral airborne remote sensing. Journal of Arid Environments 2008, 72(9):1734-1744.
2. Archetti M., Richardson A.D., O'Keefe J., Delpierre N. Predicting climate change impacts on the amount and duration of autumn colors in a New England forest. PloS One 2013, 8(3).
3. Bateman H.L., Merritt D.M., Glenn E.P., Nagler P.L. Indirect effects of biocontrol of an invasive riparian plant (Tamarix) alters habitat and reduces herpetofauna abundance. Biological Invasions 2014, 17(1):87-97.
4. Bradley B.A., Mustard J.F. Identifying land cover variability distinct from land cover change: Cheatgrass in the Great Basin. Remote Sensing of Environment 2005, 94(2):204-213.
5. Carter G.A., Lucas K.L., Blossom G.A., Lassitter C.L., Holiday D.M., Mooneyhan D.S., Griffith J.A. Remote sensing and mapping of tamarisk along the Colorado River, USA: A comparative use of summer-acquired Hyperion, Thematic Mapper and QuickBird data. Remote Sensing 2009, 1(3):318-329.
6. Cleverly J.R., Dahm C.N., Thibault J.R., Gilroy D.J., Coonrod J.E.A. Seasonal estimates of actual evapo-transpiration from Tamarix ramosissima stands using three-dimensional eddy covariance. Journal of Arid Environments 2002, 52(2):181-197.
7. Dennison P.E., Nagler P.L., Hultine K.R., Glenn E.P., Ehleringer J.R. Remote monitoring of tamarisk defoliation and evapotranspiration following saltcedar leaf beetle attack. Remote Sensing of Environment 2009, 113(7):1462-1472.
8. Delbart N., Kergoat L., Le Toan T., Lhermitte J., Picard G. Determination of phenological dates in boreal regions using normalized difference water index. Remote Sensing of Environment 2005, 97(1):26-38.
9. DiTomaso J.M. Impact, biology, and ecology of saltcedar (Tamarix spp.) in the Southwestern United States. Weed Technology 1998, 12(2):326-336.
10. Evangelista P.H., Stohlgren T.J., Morisette J.T., Kumar S. Mapping invasive tamarisk (Tamarix): A comparison of single-scene and time-series analyses of remotely sensed data. Remote Sensing 2009, 1(3):519-533.
11. Everitt B.L. Chronology of the spread of tamarisk in the central Rio Grande. Wetlands 1998, 18(4):658-668.
12. Everitt J.H., Deloach C.J. Remote sensing of Chinese tamarisk (Tamarix chinensis) and associated vegetation. Weed Science 1990, 38(3):273-278.
13. Fisher J., Mustard J.F., Vadeboncoeur M.A. Green leaf phenology at Landsat resolution: scaling from the field to the satellite. Remote Sensing of Environment 2006, 100(2):265-279.
14. Frazier A.E., Wang L. Characterizing spatial patterns of invasive species using sub-pixel classifications. Remote Sensing of Environment 2011, 115(8):1997-2007.
15. Friedman J.M., Auble G.T., Shafroth P.B., Scott M.L., Merigliano M.F., Freehling M.D., Griffin E.R. Dominance of no-native riparian trees in western USA. Biological Invasions 2005, 7(4):747-751.
16. Friedman J.M., Roelle J.E., Cade B.S. Genetic and environmental influences on leaf phenology and cold hardiness of native and introduced riparian tress. International Journal of Biometeorology 2011, 55(6):775-787.
17. Gao F., Masek J., Schwaller M., Hall F. On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. IEEE Transactions on Geoscience and Remote Sensing 2006, 44(8):2207-2218.
18. Ge S., Carruthers R., Gong P., Herrera A. Texture analysis for mapping Tamarix parviflora using aerial photographs along the Cache Creek, California. Environmental Monitoring and Assessment 2006, 114(1-3):65-83.
19. Glenn E.P., Nagler P.L. Comparative ecophysiology of Tamarix ramosissima and native trees in western U.S. riparian zones. Journal of Arid Environments 2005, 61(3):419-446.
20. Hamada Y., Stow D.A., Coulter L.L., Jafolla J.C., Hendricks L.W. Detecting tamarisk species (Tamarix spp.) in riparian habitats of Southern California using high spatial resolution hyperspectral imagery. Remote Sensing of Environment 2007, 109(2):237-248.
21. Howe W.H., Knopf F.L. On the imminent decline of Rio Grande cottonwoods in central New Mexico. The Southwestern Naturalist 1991, 36(2):218-224.
22. Hufkens K., Friedl M., Sonnentag O., Braswell B.H., Milliman T., Richardson A.D. Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology. Remote Sensing of Environment 2012, 117:307-321.
23. Hultine K.R., Belnap J., van Riper C., Ehleringer J.R., Dennison P.E., Lee M.E., West J.B. Tamarisk biocontrol in the western United States: Ecological and societal implications. Frontiers in Ecology and the Environment 2010, 8(9):467-474.
24. Ji W., Wang L. Discriminating saltcedar (Tamarix ramosissima) from sparsely distributed cottonwood (Populus euphratica) using a summer season satellite image. Photogrammetric Engineering & Remote Sensing 2015, 81(10):795-806.
25. Lass L.W., Carson H.W., Callihan R.H. Detection of yellow starthistle (Centaurea solstitialis) and common St. Johnswort (Hypericum perforatum) with multispectral digital imagery. Weed Technology 1996, 10(3):466-474.
26. Lobell D.B., Asner G.P. Cropland distributions from temporal unmixing of MODIS data. Remote Sensing of Environment 2004, 93(3):412-422.
27. Lobell D.B., Asner G.P., Ortiz-Monasterio J.I., Benning T.L. Remote sensing of regional crop production in the Yaqui Valley, Mexico: estimates and uncertainties. Agriculture, Ecosystems and Environment 2003, 94(2):205-220.
28. Meng R., Dennison P.E., Jamison L.R., van Riper C., Nagler P.L., Hultine K.R., Dudley T. Detection of Tamarix defoliation by the Northern Tamarisk beetle based on multitemporal Landsat 5 Thematic Mapper imagery. GIScience & Remote Sensing 2012, 49(4):510-537.
29. Merritt D.M., Copper D.J. Riparian vegetation and channel change in response to river regulation: a comparative study of regulated and unregulated streams in the Green River Basin, USA. Regulated Rivers: Research & Management 2000, 16(6):543-564.
30. Merritt D.M., Poff N.L. Shifting dominance of riparian Populus and Tamarix along gradients of flow alteration in western North American rivers. Ecological Application 2010, 20(1):135-152.
31. Mooney H.A., Cleland E.E. The evolutionary impact of invasive species. Proceedings of the National Academy of Sciences of the United States of America 2001, 98(10):5446-5451.
32. Morisett J.T., Jarnevich C.S., Ulah A., Cai W., Pedelty J.A., Gentle J.E., Schnase J.L. A tamarisk habitat suitability map for the continental United States. Frontiers in Ecology and the Environment 2006, 4(1):11-17.
33. Nagler P.L., Brown T., Hultine K.R., van Riper C., Bean D.W., Dennison P.E., Glenn E.P. Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods. Remote Sensing of Environment 2012, 118:227-240.
34. Nagler P.L., Cleverly J.R., Glenn E.P., Lampkin D., Huete A., Wan Z. Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data. Remote Sensing of Environment 2005, 94(1):17-30.
35. Nagler P.L., Glenn E.P., Didan K., Osterberg J., Jordan F., Cunningham J. Wide-area estimates of stand structure and water use of Tamarix spp. On the Lower Colorado River: Implications for restoration and water management projects. Restoration Ecology 2008, 16(1):136-145.
36. Nagler P.L., Glenn E.P., Jarnevich C.S., Shafroth P.B. Distribution and abundance of saltcedar and Russian olive in the western United States. Critical Reviews in Plant Sciences 2011, 30(6):508-523.
37. Nagler P.L., Pearlstein S., Glenn E.P., Brown T.B., Bateman H.L., Bean D.W., Hultine K.R. Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations. Remote Sensing of Environment 2014, 140:206-219.
38. O'Keefe, J. (2000). Phenology of Woody Species at Harvard Forest since 1990. Long Term Ecological Research Network. Retrieved from. doi:10.6073/pasta/d2bd66e9f08298167d0213e719dffabe.
39. Resasco J., Hale A.N., Henry M.C., Gorchov D.L. Detecting an invasive shrub in a deciduous forest understory using late-fall Landsat sensor imagery. International Journal of Remote Sensing 2007, 28(16):3739-3745.
40. Richardson A.D., Bailey A.S., Denny E.G., Martin C.W., O'Keefe J. Phenology of a northern hardwood forest canopy. Global Change Biology 2006, 12(7):1174-1188.
41. Richardson A.D., Braswell B.H., Hollinger D.Y., Jenkins J.P., Olinger S.V. Near-surface remote sensing of spatial and temporal variation in canopy phenology. Ecological Applications 2009, 19(6):1417-1428.
42. Robinson T.W. Introduction, Spread and Areal Extent of Saltcedar (Tamarix) in the Western States 1965, US Government Printing Office.
43. Shafroth P.B., Cleverly J.R., Dudley T.L., Taylor J.P., van Riper C., Weeks E.P., Stuart J.N. Control of Tamarix in the western United States: Implications of water salvage, wildlife use, and riparian restoration. Environmental Management 2005, 35(3):231-246.
44. Silván-Cárdenas J.L., Wang L. Retrieval of subpixel Tamarix canopy cover from Landsat data along the Forgotten River using linear and nonlinear spectral mixture models. Remote Sensing of Environment 2010, 114(8):1777-1790.
45. Stromberg J.C., Chew M.K., Nagler P.L., Glenn E.P. Changing perceptions of change: The role of scientists in Tamarix and river management. Restoration Ecology 2009, 17(2):177-186.
46. US Environmental Protection Agency NHDPlus Version 2 Retrieved from. http://horizon-systems.com/nhdplus/.
47. Wang L., Silván-Cárdenas J.L., Yang J., Frazier A.E. Invasive saltcedar (Tamarisk spp.) distribution mapping using multiresolution remote sensing imagery. The Professional Geographer 2013, 65(1):1-15.
48. Wang L., Zhang S. Incorporation of texture information in a SVM method for classifying Saltcedar in Western China. Remote Sensing Letters 2014, 5(6):501-510.
49. Wardle D.A., Bardgett R.D., Callaway R.M., Van der Putten W.H. Terrestrial ecosystem responses to species gains and losses. Science 2011, 332(6035):1273-1277.
50. Yang C., Everitt J.H., Fletcher R.S. Evaluating airborne hyperspectral imagery for mapping saltcedar infestations in west Texas. Journal of Applied Remote Sensing 2013, 7(1):073556.
51. Zhang X., Goldberg M.D. Monitoring fall foliage coloration dynamics using time-series satellite data. Remote Sensing of Environment 2011, 115(2):382-391.