A landsat data tiling and compositing approach optimized for change detection in the conterminous United States

Photogrammetric Engineering and Remote Sensing

Volumn 81, Issue 7, 2015, Pages 573-586

  Nelson, Kurtis J ^a   Steinwand, Daniel ^a  

^a EARTH RESOURCES OBSERVATION AND SCIENCE EROS CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION;

AUTOMATED SYSTEMS; CHANGE DETECTION; CHANGE DETECTION ALGORITHMS; COMPOSITED; COMPOSITING; COSINE SIMILARITY; LANDSAT-5; VEGETATION CHANGE;

SIGNAL DETECTION;

ACCURACY ASSESSMENT; ALGORITHM; ANNUAL VARIATION; AUTOMATION; DATA ACQUISITION; LANDSAT; OPTIMIZATION; PIXEL; SATELLITE DATA; SOFTWARE; VEGETATION MAPPING;

UNITED STATES;

EID: 84934762452     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.81.7.573     Document Type: Article

References (43)

1. National Aeronautics and Space Administration, 2005. Landsat 7. Science Data Users Handbook, Goddard Space Flight Center, Greenbelt, Maryland, pp. 186.
2. Alexandridis, T.K., I. Cherif, C. Kalogeropoulos, S. Monachou, K. Eskridge, and N. Silleos, 2013. Rapid error assessment for quantitative estimations from Landsat 7 gap-filled images, Remote Sensing Letters, 4(9):920-928.
3. Aschbacher, J., and M.P. Milagro-Pérez, 2012. The European Earth Monitoring (GMES) programme: Status and perspectives, Remote Sensing of Environment, 120(1):3-8.
4. Boryan, C., Z. Yang, R. Mueller, and M. Craig, 2011. Monitoring US agriculture: The US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program, Geocarto International, 26(5):341-358.
5. Chander, G., C. Huang, L. Yang, C. Homer, and C. Larson, 2009. Developing consistent Landsat data sets for large area applications: The MRLC 2001 Protocol, IEEE Geoscience and Remote Sensing Letters, 6(4):777-781.
6. Deetz, C.H., and O.S. Adams, 1945. Elements of Map Projection with Applications to Map and Chart Construction, U.S. Government Printing Office, Special Publication Number 68, Fifth edition, Revised, 1944, Washington, D.C., pp. 226.
7. Flood, N., 2013. Seasonal composite Landsat TM/ETM+ images using the Medoid (a Multi-Dimensional Median), Remote Sensing, 5(12):6481-6500.
8. Fry, J.A., G. Xian, S. Jin, J.A. Dewitz, C.G. Homer, L. Yang, C.A. Barnes, N.D. Herold, and J.D. Wickham, 2011. Completion of the 2006 national land cover database for the conterminous United States, Photogrammetric Engineering & Remote Sensing, 77(9):858-864.
9. Goward, S.N., J.G. Masek, W. Cohen, G. Moisen, G.J. Collatz, S. Healey, R.A. Houghton, C. Huang, R. Kennedy, B. Law, S. Powell, D. Turner, and M.A. Wulder, 2008. Forest disturbance and North American carbon flux, Eos, 89(11):105-106.
10. Griffiths, P., S. Van Der Linden, T. Kuemmerle, and P. Hostert, 2013. A pixel-based Landsat compositing algorithm for large area land cover mapping, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(5):2088-2101.
11. Hansen, M.C., P.V. Potapov, R. Moore, M. Hancher, S.A. Turubanova, A. Tyukavina, D. Thau, S.V. Stehman, S.J. Goetz, T.R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C.O. Justice, and J.R.G. Townshend, 2013. High-resolution global maps of 21st-century forest cover change, Science, 342(6160):850-853.
12. Hansen, M.C., A. Egorov, P.V. Potapov, S.V. Stehman, A. Tyukavina, S.A. Turubanova, D.P. Roy, S.J. Goetz, T.R. Loveland, J. Ju, A. Kommareddy, V. Kovalskyy, C. Forsyth, and T. Bents, 2014. Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD), Remote Sensing of Environment, 140(1):466-484.
13. Huang, C., S.N. Goward, J.G. Masek, F. Gao, E.F. Vermote, N. Thomas, K. Schleeweis, R.E. Kennedy, Z. Zhu, J.C. Eidenshink, and J.R.G. Townshend, 2009. Development of time series stacks of Landsat images for reconstructing forest disturbance history, International Journal of Digital Earth, 2(3):195-218.
14. Huang, C., S.N. Goward, J.G. Masek, N. Thomas, Z. Zhu, and J.E. Vogelmann, 2010a. An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks, Remote Sensing of Environment, 114(1):183-198.
15. Huang, C., N. Thomas, S.N. Goward, J.G. Masek, Z. Zhu, J.R.G. Townshend, and J.E. Vogelmann, 2010b. Automated masking of cloud and cloud shadow for forest change analysis using Landsat images, International Journal of Remote Sensing, 31(20):5449-5464.
16. Irish, R.R., J.L. Barker, S.N. Goward, and T. Arvidson, 2006. Characterization of the Landsat-7 ETM+ automated cloud-cover assessment (ACCA) algorithm, Photogrammetric Engineering & Remote Sensing, 72(10):1179-1188.
17. Jin, S., L. Yang, P. Danielson, C. Homer, J. Fry, and G. Xian, 2013. A comprehensive change detection method for updating the National Land Cover Database to circa 2011, Remote Sensing of Environment, 132(1):159-175.
18. Kennedy, R.E., Z. Yang, and W.B. Cohen, 2010. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr-Temporal segmentation algorithms, Remote Sensing of Environment, 114(12):2897-2910.
19. Luo, Y., A.P. Trishchenko, and K.V. Khlopenkov, 2008. Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over Canada and North America, Remote Sensing of Environment, 112(12):4167-4185.
20. Maiersperger, T.K., P.L. Scaramuzza, L. Leigh, S. Shrestha, K.P. Gallo, C.B. Jenkerson, and J.L. Dwyer, 2013. Characterizing LEDAPS surface reflectance products by comparisons with AERONET, field spectrometer, and MODIS data, Remote Sensing of Environment, 136(1):1-13.
21. Masek, J.G., E.F. Vermote, N.E. Saleous, R. Wolfe, F.G. Hall, K.F. Huemmrich, F. Gao, J. Kutler, and T.K. Lim, 2006. A Landsat surface reflectance dataset for North America, 1990-2000, IEEE Geoscience and Remote Sensing Letters, 3(1):68-72.
22. Nelson, K.J., J. Connot, B. Peterson, and C. Martin, 2013a. The LANDFIRE refresh strategy: Updating the national dataset, Fire Ecology, 9(2):80-101.
23. Nelson, K.J., J. Connot, B. Peterson, and J.J. Picotte, 2013b. LANDFIRE 2010-Updated data to support wildfire and ecological management, Earthzine, URL: http://www.earthzine. org/2013/09/15/landfire-2010-updated-data-to-support-wildfireand-ecological-management (last date accessed: 13 May 2015).
24. Oreopoulos, L., M.J. Wilson, and T. Varnai, 2011. Implementation on Landsat data of a Simple cloud-mask algorithm developed for MODIS land bands, IEEE Geoscience and Remote Sensing Letters, 8(4):597-601.
25. Potapov, P., S. Turubanova, and M.C. Hansen, 2011. Regionalscale boreal forest cover and change mapping using Landsat data composites for European Russia, Remote Sensing of Environment, 115(2):548-561.
26. Potapov, P.V., S.A. Turubanova, M.C. Hansen, B. Adusei, M. Broich, A. Altstatt, L. Mane, and C.O. Justice, 2012. Quantifying forest cover loss in Democratic Republic of the Congo, 2000-2010, with Landsat ETM+ data, Remote Sensing of Environment, 122(0):106-116.
27. Qian, G., S. Sural, Y. Gu, and S. Pramanik, 2004. Similarity between Euclidean and cosine angle distance for nearest neighbor queries, Proceedings of the 2004 ACM symposium on Applied Computing, Nicosia, Cyprus, Association for Computing Machinery, New York, pp. 1232-1237.
28. Rollins, M.G., 2009. LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment, International Journal of Wildland Fire, 18(3):235-249.
29. Roy, D.P., J. Ju, K. Kline, P.L. Scaramuzza, V. Kovalskyy, M. Hansen, T.R. Loveland, E. Vermote, and C. Zhang, 2010. Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States, Remote Sensing of Environment, 114(1):35-49.
30. Ryan, K.C., and T.S. Opperman, 2013. LANDFIRE-A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning, Forest Ecology and Management, 294(1):208-216.
31. Scaramuzza, P.L., M.A. Bouchard, and J.L. Dwyer, 2012. Development of the Landsat data continuity mission cloud-cover assessment algorithms, IEEE Transactions on Geoscience and Remote Sensing, 50(4):1140-1154.
32. Schmidt, G., C. Jenkerson, J. Masek, E. Vermote, and F. Gao, 2013. Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) Algorithm Description, US Geological Survey, Open File Report 2013-1057, Reston, Virginia, pp. 27.
33. Sebastiani, F., 2002. Machine learning in automated text categorization, ACM Computing Surveys, 34(1):1-47.
34. Snyder, J.P., 1987. Map Projection: A Working Manual, US Geological Survey, Professional Paper 1395, Washington, D.C., pp. 383.
35. Storey, J., P. Scaramuzza, G. Schmidt, and J. Barsi, 2005. Landsat 7 scan line corrector-off gap-filled product development, Proceedings of Pecora 16 Global Priorities in Land Remote Sensing, Sioux Falls, South Dakota, American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, pp. 23-27.
36. Storey, J.C., and M.J. Choate, 2004. Landsat-5 bumper-mode geometric correction, IEEE Transactions on Geoscience and Remote Sensing, 42(12):2695-2703.
37. United States Geological Survey, 2014. Earth Resources Observation and Science Center Science Processing Architecture On Demand Interface User Guide, URL: http://landsat.usgs.gov/documents/ espa_odi_userguide.pdf (last date accessed: 13 May 2015). Vogelmann, J.E., J.R. Kost, B. Tolk, S. Howard, K. Short, X. Chen, C.
38. Vogelmann, J.E., J.R. Kost, B. Tolk, S. Howard, K. Short, X. Chen, C. Huang, K. Pabst, and M.G. Rollins, 2011. Monitoring landscape change for LANDFIRE using multi-temporal satellite imagery and ancillary data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4(2):252-264.
39. Wijedasa, L.S., S. Sloan, D.G. Michelakis, and G.R. Clements, 2012. Overcoming limitations with Landsat imagery for mapping of peat swamp forests in Sundaland, Remote Sensing, 4(12):2595-2618.
40. Woodcock, C.E., R. Allen, M. Anderson, A. Belward, R. Bindschadler, W. Cohen, F. Gao, S.N. Goward, D. Helder, E. Helmer, R. Nemani, L. Oreopoulos, J. Schott, P.S. Thenkabail, E.F. Vermote, J. Vogelmann, M.A. Wulder, and R. Wynne, 2008. Free access to Landsat imagery, Science, 320(5879):1011.
41. Wulder, M.A., S.M. Ortlepp, J.C. White, and S. Maxwell, 2008. Evaluation of Landsat-7 SLC-off image products for forest change detection, Canadian Journal of Remote Sensing, 34(2):93-99.
42. Zhu, Z., B. Bergmaschi, R. Bernknopf, D. Clow, D. Dye, S. Faulkner, W. Forney, R. Gleason, T. Hawbaker, J. Liu, S. Liu, S. Prisley, B. Reed, M. Reeves, M. Rollins, B. Sleeter, T. Sohl, S. Stackpoole, S. Stehman, R. Striegl, and A. Wein, 2010. A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios, U.S. Geological Survey, Scientific Investigations Report 2010-5233, Reston, Virginia, pp. 188.
43. Zhu, Z., and C.E. Woodcock, 2012. Object-based cloud and cloud shadow detection in Landsat imagery, Remote Sensing of Environment, 118(1):83-94.