A LandTrendr multispectral ensemble for forest disturbance detection

Remote Sensing of Environment

Volumn 205, Issue , 2018, Pages 131-140

  Cohen, Warren B ^a   Yang, Zhiqiang ^b   Healey, Sean P ^a   Kennedy, Robert E ^b   Gorelick, Noel ^c  

^a USDA FOREST SERVICE   (United States)

^b OREGON STATE UNIVERSITY   (United States)

^c GOOGLE   (Switzerland)

Author keywords

Disturbance signal to noise ratio; Forest disturbance; Landsat time series; Multispectral change detection; Stacking ensemble

Indexed keywords

CALIBRATION; DECISION TREES; INFRARED DEVICES; LANDSAT; REFLECTION; SIGNAL TO NOISE RATIO; TIME SERIES;

CHANGE DETECTION; DISTURBANCE SIGNAL-TO-NOISE RATIO; DISTURBANCE SIGNALS; FOREST DISTURBANCES; LANDSAT TIME SERIES; MULTI-SPECTRAL; MULTISPECTRAL CHANGE DETECTION; SPECTRAL INDICES; STACKING ENSEMBLE; STACKINGS;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; CALIBRATION; DETECTION METHOD; DISTURBANCE; ERROR ANALYSIS; FOREST ECOSYSTEM; LANDSAT; MULTISPECTRAL IMAGE; PERFORMANCE ASSESSMENT; SIGNAL-TO-NOISE RATIO; TIME SERIES ANALYSIS;

EID: 85034865511     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2017.11.015     Document Type: Article

References (37)

1. Allen, C.D., Breshears, D.D., McDowell, N.G., On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere 6 (2015), 1–55.
2. Breiman, L., Random forests. Mach. Learn. 45 (2001), 5–32.
3. Brooks, E.B., Wynne, R.H., Thomas, V.A., Blinn, C.E., Coulston, J.W., On-the-fly massively multitemporal change detection using statistical quality control charts and Landsat data. IEEE Trans. Geosci. Remote Sens. 52 (2014), 3316–3332.
4. Cohen, W.B., Spies, T.A., Alig, R.J., Oetter, D.R., Maiersperger, T.K., Fiorella, M., Characterizing 23 years (1972–1995) of stand replacement disturbance in western Oregon forests with Landsat imagery. Ecosystems 5 (2002), 122–137.
5. Cohen, W.B., Yang, Z., Kennedy, R.E., Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync - Tools for calibration and validation. Remote Sens. Environ. 114 (2010), 2911–2924.
6. Cohen, W.B., Yang, Z., Stehman, S.V., Schroeder, T.A., Bell, D.M., Masek, J.G., Huang, C., Meigs, G.W., Forest disturbance in the conterminous US from 1985–2012: the emerging dominance of forest decline. For. Ecol. Manag. 360 (2016), 242–252.
7. Cohen, W.B., Healey, S.P., Yang, Z., Stehman, S.V., Brewer, C.K., Brooks, E.B., Gorelick, N., Huang, C., Hughes, M.J., Kennedy, R.E., Loveland, T.R., Moisen, G.G., Schroeder, T.A., Vogelmann, J.E., Woodcock, C.E., Yang, L., Zhu, Z., How similar are forest disturbance maps derived from different Landsat time series algorithms?. Forests, 8, 2017, 98, 10.3390/f8040098.
8. Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., Lambin, E., Digital change detection methods in ecosystem monitoring: a review. Int. J. Remote Sens. 25 (2004), 1565–1596.
9. Crist, E.P., A TM Tasseled Cap equivalent transformation for reflectance factor data. Remote Sens. Environ. 17 (1985), 301–306.
10. DeVries, B., Verbesselt, J., Kooistra, L., Herold, M., Robust monitoring of small-scale forest disturbances in a tropical montane forest using Landsat time series. Remote Sens. Environ. 161 (2015), 107–121.
11. Hansen, M.C., Potapov, P.V., Moore, R. et al., High-resolution global maps of 21st-century forest cover change. Science 342 (2013), 850–853 with supplementary materials www.sciencemag.org/content/342/6160/850/suppl/DC1.
12. Healey, S.P., Cohen, W.B., Zhiqiang, Y., Krankina, O., Comparison of Tasseled Cap-based Landsat data structures for forest disturbance detection. Remote Sens. Environ. 97 (2005), 301–310.
13. Healey, S.P., Cohen, W.B., Spies, T.A., Moeur, M., Pflugmacher, D., Whitley, M.G., Lefsky, M.A., The relative impact of harvest and fire upon landscape-level dynamics of older forests: lessons from the Northwest Forest plan. Ecosystems 11 (2008), 1106–1119.
14. Healey, S.P., Cohen, W.B., Yang, Z., Brewer, C.K., Brooks, E.B., Gorelick, N., Hernandez, A.J., Huang, C., Hughes, M.J., Kennedy, R.E., Loveland, T.R., Moisen, G.G., Schroeder, T.A., Stehman, S.V., Vogelmann, J.E., Woodcock, C.E., Yang, L., Zhu, Z., Mapping forest change using stacked generalization: an ensemble approach. Remote Sens. Environ., 2017, 10.1016/j.rse.2017.09.029 (in press).
15. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sens. Environ. 158 (2015), 220–234.
16. Huang, C., Goward, S.N., Masek, J.G., Thomas, N., An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. Remote Sens. Environ. 114 (2010), 183–198.
17. Hughes, M.J., Kaylor, S.D., Hayes, D.J., Patch-based forest change detection from Landsat time series. Forests, 8, 2017, 166, 10.3390/f8050166.
18. Kennedy, R.E., Yang, Z., Cohen, W.B., Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr - temporal segmentation algorithms. Remote Sens. Environ. 114 (2010), 2897–2910.
19. Kennedy, R.E., Yang, Z., Cohen, W.B., Pfaff, E., Braaten, J., Nelson, P., Spatial and temporal patterns of forest disturbance and regrowth within the area of the Northwest Forest Plan. Remote Sens. Environ. 122 (2012), 117–133.
20. Key, C.H., Benson, N.C., Landscape assessment: remote sensing of severity, the normalized burn ratio. Lutes, D.C., (eds.) FIREMON: Fire Effects Monitoring, and Inventory System, 2005, USDA Forest Service, Rocky Mountain Research, Station, Ogden, UT.
21. Kim, D.-H., Sexton, J.O., Noojipady, P., Huang, C., Anand, A., Channan, S., Feng, M., Townshend, J.R., Global, Landsat-based forest-cover change from 1990 to 2000. Remote Sens. Environ. 155 (2014), 178–193.
22. Kissinger, G., Herold, M., De Sy, V., Drivers of Deforestation and Forest Degradation: A Synthesis Report for REDD + Policymakers. August 2012, Lexeme Consulting, Vancouver Canada.
23. Masek, J.G., Huang, C., Cohen, W.B., Kutler, J., Hall, F.G., Wolfe, R., Nelson, P., North American forest disturbance mapped from a decadal Landsat record: methodology and initial results. Remote Sens. Environ. 112 (2008), 2914–2926.
24. McDowell, N., Coops, N.C., Beck, P.S.A., Chambers, J.Q., Gangodagamage, C., Hicke, J.A., Huang, C.-Y., Kennedy, R.E., Krofcheck, D.J., Litvak, M., Meddens, A.J.H., Muss, J., Negrón-Juarez, R., Peng, C., Schwantes, A.M., Swenson, J.J., Vernon, L.J., Williams, A.P., Xu, C., Zhao, M., Running, S.W., Allen, C.D., Global satellite monitoring of climate-induced vegetation disturbances. Trends Plant Sci. 20 (2015), 114–123.
25. Meddens, A.J.H., Hicke, J.A., Spatial and temporal patterns of Landsat-based detection of tree mortality caused by a mountain pine beetle outbreak in Colorado, USA. For. Ecol. Manag. 322 (2014), 78–88.
26. Meigs, Garrett, Kennedy, R.E., Cohen, W.B., A Landsat time series approach to characterize bark beetle and defoliator impacts on tree mortality and surface fuels in conifer forests. Remote Sens. Environ. 115 (2011), 3707–3718.
27. Mildrexler, D., Yang, Z., Cohen, W.B., A forest vulnerability index based on drought and high temperatures. Remote Sens. Environ. 173 (2016), 314–325.
28. Moeur, M., Ohmann, J.L., Kennedy, R.E., Cohen, W.B., Gregory, M.J., Yang, Z., Roberts, H.M., Spies, T.A., Fiorella, M., Northwest Forest Plan–the first 15 years (1994–2008): status and trends of late-successional and old-growth forests. Gen. Tech. Rep. PNW-GTR-853, 2011, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland, OR 48 p.
29. Pohmann, R., Speck, O., Scheffler, K., Signal-to-noise ratio and MR tissue parameters in human brain imaging at 3, 7, and 9.4 Tesla using current receive coil arrays. Magn. Reson. Med. 75 (2016), 801–809.
30. Powell, S.L., Cohen, W.B., Healey, S.P., Kennedy, R.E., Moisen, G.G., Pierce, K.B., Ohmann, J.L., Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: a comparison of empirical modeling approaches. Remote Sens. Environ. 114 (2010), 1053–1068.
31. Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W., Monitoring vegetation systems in the Great Plains with ERTS. Freden, S.C., Mercanti, E.P., Becker, M., (eds.) Third Earth Resources Technology Satellite–1 Symposium. Volume I: Technical Presentations, 1974, NASA SP-351, NASA, Washington, D.C., 309–317.
32. Roy, D.P., Wulder, M.A., Loveland, T.R., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D., Irons, J.R., Johnson, D.M., Kennedy, R.E., Scambos, T.A., Schaaf, C.B., Schott, J.R., Sheng, Y., Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao, F., Hipple, J.D., Hostert, P., Huntington, J., Justice, C.O., Kilic, A., Kovalskyy, V., Lee, Z.P., Lymburner, L., Masek, J.G., McCorkel, J., Shuai, Y., Trezza, R., Vogelmann, J., Wynne, R.H., Zhu, Z., Landsat-8: science and product vision for terrestrial global change research. Remote Sens. Environ. 145 (2014), 154–172.
33. Schultz, M., Clevers, J.G.P.W., Carter, S., Verbesselt, J., Avitabile, V., Quang, H.V., Herold, M., Performance of vegetation indices from Landsat time series in deforestation monitoring. Int. J. Appl. Earth Obs. Geoinf. 52 (2016), 318–327.
34. Trenberth, K.E., Signal versus noise in the southern oscillation. Mon. Weather Rev. 112 (1984), 326–332.
35. Vogelmann, J.E., Xian, G., Homer, C., Tolk, B., Monitoring gradual ecosystem change using Landsat time series analyses: case studies in selected forest and rangeland ecosystems. Remote Sens. Environ. 122 (2012), 92–105.
36. Wilson, E.H., Sader, S.A., Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sens. Environ. 80 (2002), 385–396.
37. Wulder, M.A., Skakun, R.S., Kurz, W.A., White, J.C., Estimating time since forest harvest using segmented Landsat ETM + imagery. Remote Sens. Environ. 93 (2004), 179–187.