PE&RS July 2015 - page 525

PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
July 2015
525
Acknowledgement
Support for this effort was provided by the following NASA
programs: making Earth Science Data Records for Use in Re-
search Environment (NNH06ZDA001N-MEASURES), Land
Cover and Land Use Change (NNH07ZDA001N-LCLUC),
NASA ACCESS (NH11ZDA001N-ACCESS) and NASA Indi-
cators (NNH12ZDA001N-INCA). We would also like to thank
Linda Jonescheit Owen for providing the GLS data–distribu-
tion values from the USGS EROS Data Center.
References
Feng, M., C. Huang, S. Channan, E.F. Vermote, J.G. Masek,
& J.R. Townshend, 2012. Quality assessment of Landsat
surface reflectance products using MODIS data.
Computers
& Geosciences
,
38
(1), 9–22. doi:10.1016/j.cageo.2011.04.011
Feng, M., J. O. Sexton, C. Huang, J. G. Masek, E. F. Ver-
mote, F. Gao, R. Narashimhan, S. Channan, R.E. Wolfe,
J.R. Townshend, 2013. Global surface reflectance products
from Landsat: Assessment using coincident MODIS obser-
vations.
Remote Sensing of Environment
,
134
, 276–293.
doi:10.1016/j.rse.2013.02.031
Feng, M., J. O. Sexton, S. Channan, J. R. Townshend, 2015.
A global, high-resolution (30-m) inland water body data-
set for 2000: first results of a topographic-spectral classi-
fication algorithm. International Journal of Digital Earth.
(accepted)
Franks, S., J. G. Masek, R. M. K. Headley, J. Gasch, and
T. Arvidson, 2009. Large Area Scene Selection Interface
(LASSI): Methodology of Selecting Landsat Imagery for the
Global Land Survey 2005.
Photogrammetric Engineering
and Remote Sensing
,
75
, 1287–1296.
Gutman, G., R. Byrnes, J. G. Masek, S. Covington, C. O. Jus-
tice, S. Franks, and R. Headley, 2008. Towards monitor-
ing land-cover and land-use changes at a global scale: The
Global Land Survey 2005.
Photogrammetric Engineering
and Remote Sensing
,
74
(1), 6–10.
Gutman, G., C. Huang, G. Chander, P. Noojipady, J. G.
Masek, J. G., (2013). Assessment of the NASA–USGS Glob-
al Land Survey (GLS) datasets.
Remote Sensing of Envi-
ronment
,
134
, 249–265. doi:10.1016/j.rse.2013.02.026
Holben, B. N., (1986). Characteristics of maximum-value
composite images from temporal AVHRR data.
Inter-
national Journal of Remote Sensing
,
7
(11), 1417–1434.
doi:10.1080/01431168608948945
Huang,C.,N. Thomas, S.N.Goward, J.G.Masek, Z. Zhu, J.R.G.
Townshend, & J.E. Vogelmann, (2010). Automated mask-
ing of cloud and cloud shadow for forest change analysis us-
ing Landsat images.
International Journal of Remote Sens-
ing
,
31
(20), 5449–5464. doi:10.1080/01431160903369642
Irish, R. R., J.L. Barker, S.N. Goward, & T. Arvidson, (2006).
Characterization of the Landsat-7 ETM+ Automated
Cloud-Cover Assessment ( ACCA ) Algorithm.
Photogram-
metric Engineering & Remote Sensing
,
72
(10), 1179–1188.
Kim, D. H., R. Narashiman, J.O. Sexton, C. Huang & J.R.
Townshend, (2011, July). Methodology to select phenolog-
ically suitable Landsat scenes for forest change detection.
In
Geoscience and Remote Sensing Symposium (IGARSS),
2011 IEEE International
(pp. 2613-2616). IEEE.
Kim, D.-H., J.O. Sexton, P. Noojipady, C. Huang, A. Anand,
S. Channan, M. Feng, J.R. Townshend, (2014). Global,
Landsat-based forest-cover change from 1990 to 2000.
Re-
mote Sensing of Environment
,
155
, 178–193. doi:10.1016/j.
rse.2014.08.017
Lindquist, E. J., M.C. Hansen, D.P. Roy & C.O Justice,
(2008). The suitability of decadal image data sets for map-
ping tropical forest cover change in the Democratic Repub-
lic of Congo: implications for the global land survey.
Inter-
national Journal of Remote Sensing
,
29
(24), 7269–7275.
doi:10.1080/01431160802275890
Roy, D. P., J. Ju, J, K. Kline, P.L. Scaramuzza, V. Kovalskyy,
M. Hansen, C. Zhang, (2010). Web-enabled Landsat Data
(WELD): Landsat ETM+ composited mosaics of the con-
terminous United States.
Remote Sensing of Environment
,
114
(1), 35–49. doi:10.1016/j.rse.2009.08.011
Sexton, J. O., X.-P. Song, M. Feng, P. Noojipady, A. Anand,
C. Huang, D. Kim, K.M. Collins, S. Channan., C. DiMiceli,
J.R.G. Townshend, (2013). Global, 30-m resolution continu-
ous fields of tree cover: Landsat-based rescaling of MODIS
Vegetation Continuous Fields with lidar-based estimates
of error.
International Journal of Digital Earth
, (April),
130321031236007. doi:10.1080/17538947.2013.786146
Storey, J., P. Scaramuzza, G. Schmidt, & J. Barsi, (2005).
Landsat 7 scan line corrector-off gap filled product develop-
ment.
In Proceedings of Pecora
,
16
, 23–27.
Wulder, M. A., J.G. Masek, W. B. Cohen, T.R. Loveland, &
C.E. Woodcock, (2012). Opening the archive: How free data
has enabled the science and monitoring promise of Landsat.
Remote Sensing of Environment
,
122
, 2–10. doi:10.1016/j.
rse.2012.01.010
Authors
Saurabh Channan, Min Feng, Do-Hyung Kim, Joseph
Owen Sexton, Xiao-Peng Song, Dan-Xia Song, Kathrine
Collins,
and
John R. Townshend
are with the Global
Land Cover Facility, Department of Geographical Sciences,
University of Maryland, College Park, MD 20742, USA.
Praveen Noojipady
is with the Global Land Cover
Facility, Department of Geographical Sciences, University of
Maryland, College Park, MD 20742, USA and the National
Wildlife Federation, National Advocacy Center, Washington,
DC 20004, USA.
Anupam Anand
is with the Global Land Cover Facility,
Department of Geographical Sciences, University of
Maryland, College Park, MD 20742, USA and the Global
Environment Facility, Washington, DC 20433, USA.
515...,516,517,518,519,520,521,522,523,524 526,527,528,529,530,531,532,533,534,535,...602
Powered by FlippingBook