Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Remote Sensing of Environment

Volumn 114, Issue 5, 2010, Pages 1053-1068

  Powell, Scott L ^a   Cohen, Warren B ^b   Healey, Sean P ^c   Kennedy, Robert E ^d   Moisen, Gretchen G ^c   Pierce, Kenneth B ^e   Ohmann, Janet L ^b  

^a MONTANA STATE UNIVERSITY   (United States)

^b PACIFIC NORTHWEST RESEARCH STATION   (United States)

^c ROCKY MOUNTAIN RESEARCH STATION   (United States)

^d OREGON STATE UNIVERSITY   (United States)

^e WASHINGTON DEPARTMENT OF FISH AND WILDLIFE   (United States)

Author keywords

Biomass; Curve fitting; Disturbance; FIA; Landsat; Random forests

Indexed keywords

ABOVEGROUND TREE BIOMASS; ARIZONA; BIOMASS DYNAMICS; BIOMASS MEASUREMENTS; CARBON DYNAMICS; EMPIRICAL MODELING; EXPLICIT KNOWLEDGE; FIA; FIELD DATA; FIELD INVENTORIES; FOREST BIOMASS; FOREST DISTURBANCES; FOREST INVENTORY AND ANALYSIS; LANDSAT; LANDSAT SATELLITE; MAJOR AXIS; MINNESOTA; NEAREST NEIGHBOR IMPUTATION; NORTH AMERICAN; RANDOM FORESTS; REGRESSION TREES; REGROWTH PROCESS; STATISTICAL TECHNIQUES; SUN ANGLE; TEMPORAL INFORMATION; TIME FRAME;

CURVE FITTING; DYNAMICS; FORECASTING; FORESTRY; LOCATION; MOBILE TELECOMMUNICATION SYSTEMS; SATELLITE IMAGERY; TIME SERIES ANALYSIS; WEATHER SATELLITES;

BIOMASS;

ABOVEGROUND BIOMASS; CARBON CYCLE; COMPARATIVE STUDY; DATA SET; DISTURBANCE; EMPIRICAL ANALYSIS; FOREST INVENTORY; LANDSAT; PHENOLOGY; REGROWTH; SATELLITE IMAGERY; TIME SERIES;

BIOMASS; FORECASTS; FORESTRY; FORESTS; IMAGE ANALYSIS; SATELLITES;

ARIZONA; MINNESOTA; UNITED STATES;

EID: 76049083444     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2009.12.018     Document Type: Article

References (72)

1. Bechtold W.A., and Scott C.T. The Forest Inventory and Analysis Plot Design. In: Bechtold W.A., and Patterson P.L. (Eds). The enhanced Forest Inventory and Analysis Program-National sampling design and estimation procedures. Gen. Tech. Rep. SRS-80 (2005), U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, N.C 27-42
2. Berterretche M., Hudak A.T., Cohen W.B., Maiersperger T.K., Gower S.T., and Dungan J. Comparison of regression and geostatistical methods for mapping Leaf Area Index (LAI) with Landsat ETM + data over a boreal forest. Remote Sensing of Environment 96 (2005) 49-61
3. Blackard J.A., Finco M.V., Helmer E.H., Holden G.R., Hoppus M.L., Jacobs D.M., et al. Mapping US forest biomass using nationwide forest inventory data and moderate resolution information. Remote Sensing of Environment 112 (2008) 1658-1677
4. Breiman L. Random forests. Machine Learning 45 (2001) 5-32
5. Canty M.J., Nielson A.A., and Schmidt M. Automatic radiometric normalization of multitemporal satellite imagery. Remote Sensing of Environment 91 3-4 (2004) 441-451
6. Chambers J.Q., Fisher J.I., Zeng H., Chapman E.L., Baker D.B., and Hurtt G.C. Hurricane Katrina's carbon footprint on U.S. Gulf Coast forests. Science 318 (2007) 1107
7. Cihlar J., Heimann M., Olson R., Alexandrov G., Belward A., Brown L., et al. Terrestrial carbon observation-The Frascati report on in situ carbon data and information. Environment and Natural Resources Service Sustainable Development Department vol. 5 (2002), Food and Agricultural Organization of the United Nations, Rome 120 pp
8. Cohen W.B., and Goward S.N. Landsat's role in ecological applications of remote sensing. BioScience 54 (2004) 535-545
9. Cohen W.B., Harmon M.E., Wallin D.O., and Fiorella M. Two decades of carbon flux from forests of the Pacific Northwest. Bioscience 46 11 (1996) 836-844
10. Cohen W.B., Spies T.A., Alig R.J., Oetter D.R., Maiersperger T.K., and Fiorella M. Characterizing 23 years (1972-1995) of stand replacement disturbance in western Oregon forests with Landsat imagery. Ecosystems 5 (2002) 122-137
11. Cohen W.B., Maiersperger T.K., Gower S.T., and Turner D.P. An improved strategy for regression of biophysical variables and Landsat ETM + data. Remote Sensing of Environment 84 (2003) 561-571
12. Crist E.P. A TM tasseled cap equivalent transformation for reflectance factor data. Remote Sensing of Environment 17 (1985) 301-306
13. Cutler D.R., Edwards T.C., Beard K.H., Cutler A., and Hess K.T. Random forests for classification in ecology. Ecology 88 (2007) 2783-2792
14. Drake J.B., Dubayah R.O., Clark D.B., Knox R.G., Blair J.B., Hofton M.A., et al. Estimation of tropical forest structural characteristics using large-footprint lidar. Remote Sensing of Environment 79 (2002) 305-319
15. Duane, M. V., Cohen, W. B., Campbell, J. L., Hudiburg, T., Turner, D. P., and Weyermann, D. (in press). Implications of alternative field-sampling designs on Landsat-based mapping of stand age and carbon stocks in Oregon forests. Forest Science.
16. Falkowski M.J., Evans J.S., Martinuzzi S., Gessler P.E., and Hudak A.T. Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA. Remote Sensing of Environment 113 (2009) 946-956
17. Fazakas Z., Nilsson M., and Olsson H. Regional forest biomass and wood volume estimation using satellite data and ancillary data. Agricultural and Forest Meteorology 98-99 (1999) 417-425
18. Foody G.M., Boyd D.S., and Cutler M.E.J. Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions. Remote Sensing of Environment 85 (2003) 463-474
19. Franco-Lopez H., Ek A.R., and Bauer M.E. Estimation and mapping of forest stand density, volume, and cover type using the k-nearest neighbors method. Remote Sensing of Environment 77 (2001) 251-274
20. Freeman, E. A. and Frescino, T. A. (2009). ModelMap: An R package for modeling and map production using Random Forest and Stochastic Gradient Boosting. USDA Forest Service, Rocky Mountain Research Station, 507 25th St., Ogden, UT, USA. Eafreeman@fs.fed.us, URL: http://CRAN.R-project.org
21. Goetz S.J., Baccini A., Laporte N.T., Johns T., Walker W., Kellndorfer J., et al. Mapping and monitoring carbon stocks with satellite observations: A comparison of methods. Carbon Balance and Management 4 (2009) 2 10.1186/1750-0680-4-2
22. Goward S.N., Arvidson T., Williams D., Faundeen J., Irons J., and Franks S. Historical record of Landsat global coverage: Mission operations, NSLRSDA, and International cooperator stations. Photogrammetric Engineering and Remote Sensing 72 10 (2006) 1155-1169
23. Goward S.N., Masek J.G., Cohen W., Moisen G., Collatz G.J., Healey S., et al. Forest disturbance and North American carbon flux. EOS 89 11 (2008) 105-106
24. Hall F.G., Shimabukuro Y.E., and Huemmrich K.F. Remote-sensing of forest biophysical structure using mixture decomposition and geometric reflectance models. Ecological Applications 5 4 (1995) 993-1013
25. Hall R.J., Skakun R.S., Arsenault E.J., and Case B.S. Modeling forest stand structure attributes using Landsat ETM + data: Application to mapping of aboveground biomass and stand volume. Forest Ecology and Management 225 (2006) 378-390
26. Hansen M.C., DeFries R.S., Townshend J.R.G., Sohlberg R., Dimiceli C., and Carroll M. Towards an operational MODIS continuous field of percent tree cover algorithm: Examples using AVHRR and MODIS data. Remote Sensing of Environment 83 (2002) 303-319
27. Harmon M.E., Ferrell W.K., and Franklin J.F. Effects on carbon storage of conversion of old-growth forests to young forests. Science 247 4943 (1990) 699-702
28. Healey S.P., Cohen W.B., Zhiqiang Y., and Krankina O. Comparison of Tasseled Cap-based Landsat data structures for forest disturbance detection. Remote Sensing of Environment 97 (2005) 301-310
29. Healey S.P., Yang Z., Cohen W.B., and Pierce D.J. Application of two regression-based methods to estimate the effects of partial harvest on forest structure using Landsat data. Remote Sensing of Environment 101 (2006) 115-126
30. Healey S.P., Cohen W.B., Spies T.A., Moeur M., Pflugmacher D., Whitley M.G., et al. The relative impact of harvest and fire upon landscape-level dynamics of older forests: Lessons from the Northwest Forest Plan. Ecosystems 11 7 (2008) 1106-1119
31. Houghton R.A. Aboveground forest biomass and the global carbon balance. Global Change Biology 11 (2005) 945-958
32. Huang C., Goward S.N., Masek J.G., Gao F., Vermote E.F., Thomas N., et al. Development of time series stacks of Landsat images for reconstructing forest disturbance history. International Journal of Digital Earth 2 (2009) 195-218
33. Huang C., Goward S.N., Masek J.G., Thomas N., Zhu Z., and Vogelmann J.E. An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks. Remote Sensing of Environment 114 (2010) 183-198
34. Jakubauskas M.E., and Price K.P. Empirical relationships between structural and spectral factors of Yellowstone lodgepole pine forests. Photogrammetric Engineering and Remote Sensing 63 (1997) 1375-1381
35. Jenkins J.C., Chojnacky D.C., Heath L.S., and Birdsey R.A. National-scale biomass equations for United States tree species. Forest Science 49 1 (2003) 12-35
36. Kellndorfer J.M., Walker W.S., Pierce L.E., Dobson M.C., Fites J., Hunsaker C., et al. Vegetation height derivation from Shuttle Radar Topography Mission and National Elevation data sets. Remote Sensing of Environment 93 3 (2004) 339-358
37. Kennedy R.E., Cohen W.B., and Schroeder T.A. Trajectory-based change detection for automated characterization of forest disturbance dynamics. Remote Sensing of Environment 110 (2007) 370-386
38. Kennedy, R. E., Yang, Z., and Cohen, W. B. (in review). Detecting trends in disturbance and recovery using yearly Landsat Thematic Mapper stacks: 1. Processing and analysis algorithm. Remote Sensing of Environment.
39. Labrecque S., Fournier R.A., Luther J.E., and Piercey D. A comparison of four methods to map biomass from Landsat-TM and inventory data in western Newfoundland. Forest Ecology and Management 226 (2006) 129-144
40. Larsson H. Linear regression for canopy cover estimation in Acacia woodlands using Landsat-TM, -MSS, and SPOT HRV XS data. International Journal of Remote Sensing 14 (1993) 2129-2136
41. Lawrence R.L., Wood S.D., and Sheley R.L. Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications (RandomForest). Remote Sensing of Environment 100 (2006) 356-362
42. Lefsky M.A., Cohen W.B., and Spies T.A. An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon. Canadian Journal of Forest Research 31 (2001) 78-87
43. Lefsky M.A., Cohen W.B., Parker G.G., and Harding D.J. Lidar remote sensing for ecosystem studies. Bioscience 52 (2002) 19-30
44. Lu D. The potential and challenge of remote sensing-based biomass estimation. International Journal of Remote Sensing 27 (2006) 1297-1328
45. Masek J.G., and Collatz G.J. Estimating forest carbon fluxes in a disturbed southeastern landscape: Integration of remote sensing, forest inventory, and biogeochemical modeling. Journal of Geophysical Research 111 (2006) G01006 10.1029/2005JG000062
46. Masek J.G., Vermote E.F., Saleous N., Wolfe R., Hall F.G., Huemmrich F., et al. Landsat surface reflectance data set for North America, 1990-2000. Geoscience and Remote Sensing Letters 3 (2006) 68-72
47. Moisen G.G., and Frescino T.S. Comparing five modeling techniques for predicting forest characteristics. Ecological Modelling 157 (2002) 209-225
48. Myneni R.B., Nemani R.R., and Running S.W. Estimation of global leaf area index and absorbed par using radiative transfer models. IEEE Transactions on Geoscience and Remote Sensing 35 6 (1997) 1380-1393
49. Nelson M.D., Healey S.P., Moser W.K., and Hansen M.H. Combining satellite imagery with forest inventory data to assess damage severity following a major blowdown event in northern Minnesota, USA. International Journal of Remote Sensing 30 (2009) 5089-5108
50. Ohmann J.L., and Gregory M.J. Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, USA. Canadian Journal of Forest Research 32 (2002) 725-741
51. Pacala S., Birdsey R.A., Bridgham S.D., Conant R.T., Davis K., and Hales B. The North American carbon budget past and present. In: King A.W., et al. (Ed). The first State of the Carbon Cycle Report (SOCCR) (2007), NOAA Natl. Clim. Data Cent, Asheville, N.C.
52. Pierce K.B., Lookingbill T., and Urban D.L. A simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis. Landscape Ecology 20 (2005) 137-147
53. Pierce Jr. K.B., Ohmann J.L., Wimberly M.C., Gregory M.J., and Fried J.S. Mapping wildland fuels and forest structure for land management: A comparison of nearest neighbor imputation and other methods. Canadian Journal of Forest Research 39 (2009) 1901-1916
54. Potter C., Gross P., Klooster S., Fladeland M., and Genovese V. Storage of carbon in U.S. forests predicted from satellite data, ecosystem modeling, and inventory summaries. Climate Change 90 3 (2008) 269-282
55. Powell S.L., Cohen W.B., Yang Z., Pierce J.D., and Alberti M. Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972-2006. Remote Sensing of Environment 112 (2008) 1895-1908
56. Powell S.L., Hansen A.J., and Cohen W.B. Mapping the extent and distribution of conifer cover increase in the Greater Yellowstone Ecosystem. In: Dupont A., and Jacobs H. (Eds). Landscape ecology research trends (2008), Nova Science Publishers, Hauppauge, New York 27-43
57. Prasad A.M., Iverson L.R., and Liaw A. Newer classification and regression tree techniques: Bagging and Random Forests for ecological prediction. Ecosystems 9 (2006) 181-199
58. Rahman M.M., Csaplovics E., and Koch B. Satellite estimation of forest carbon using regression models. International Journal of Remote Sensing 29 (2008) 6917-6936
59. Ruefenacht B., Finco M.V., Nelson M.D., Czaplewski R., Helmer E.H., Blackard J.A., et al. Conterminous U.S. and Alaska forest type mapping using Forest Inventory and Analysis data. Photogrammetric Engineering and Remote Sensing 74 (2008) 1379-1389
60. Schroeder T.A., Cohen W.B., Song C., Canty M.J., and Yang Z. Radiometric calibration of Landsat data for characterization of early successional forest patterns in western Oregon. Remote Sensing of Environment 103 (2006) 16-26
61. Schroeder T.A., Cohen W.B., and Yang Z. Patterns of forest regrowth following clearcutting in western Oregon as determined from a Landsat time-series. Forest Ecology and Management 243 (2007) 259-273
62. Steininger M.K. Satellite estimation of tropical secondary forest above-ground biomass: Data from Brazil and Bolivia. International Journal of Remote Sensing 21 (2000) 1139-1157
63. Thomas, N. E., Huang, C., Goward, S. N., Powell, S., Rishmawi, K., Schleeweis, K. et al. (in review). Assessment of NAFD forest change products derived from Landsat Time Series Stacks (LTSS). Remote Sensing of Environment.
64. Thompson J.R., and Spies T.A. Vegetation and weather explain variation in crown damage within a large mixed-severity wildfire. Forest Ecology and Management 258 (2009) 1684-1694
65. Thornton P.E., Running S.W., and White M.A. Generating surfaces of daily meteorological variables over large regions of complex terrain. Journal of Hydrology 190 (1997) 214-251
66. Tomppo E.O., Gagliano C., De Natale F., Katila M., and McRoberts R.E. Predicting categorical forest variables using an improved k-nearest neighbor estimator and Landsat imagery. Remote Sensing of Environment 113 (2009) 500-517
67. Townshend J.R.G., and Justice C.O. Unsupervised classification of MSS Landsat data for mapping spatially complex vegetation. International Journal of Remote Sensing 1 2 (1980) 105-120
68. Turner D.P., Cohen W.B., Kennedy R.E., Fassnacht K.S., and Briggs J.M. Relationship between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites. Remote Sensing of Environment 70 (1999) 52-68
69. Wofsy S.C., and Harris R.C. The North American Carbon Program (NACP): Report of the NACP Committee of the U.S. Interagency Carbon Cycle Science Program (2002), U.S. Global Change Research Program, Washington, D.C.
70. Woodbury P.B., Smith J.E., and Heath L.S. Carbon sequestration in the U.S. forest sector from 1990 to 2010. Forest Ecology and Management 241 (2007) 14-27
71. Woodcock C.A., Allen R., Anderson M., Belward A., Bindschadler R., Cohen W., et al. Free access to Landsat imagery. Science 320 5879 (2008) 1011
72. Zheng D., Rademacher J., Chen J., Crow T., Bresee M., Le Moine J., et al. Estimating aboveground biomass using Landsat ETM + data across a managed landscape in northern Wisconsin, USA. Remote Sensing of Environment 93 (2004) 402-411