Recent Publications

February 2015

Byrd, K., Ratliff, J., Bliss, N.B., Wein, A., Sleeter, B., Sohl, T.L., and Li, Z., 2015, Quantifying climate change mitigation potential in the United States Great Plains wetlands for three greenhouse gas emission scenarios: Mitigation and Adaptation Strategies for Global Change, v. 20, no. 3, p. 439-465, at http://dx.doi.org/10.1007/s11027-013-9500-0.

Ji, L., Wylie, B.K., Nossov, D.R., Peterson, B.E., Alexander, H.D., Mack, M.C., Rover, J.A., Waldrop, M.P., McFarland, J.W., Chen, X., and Pastick, N.J., 2015, Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska: International Journal of Remote Sensing, v. 36, no. 4, p. 939-953, at http://dx.doi.org/10.1080/01431161.2015.1004764.

McNally, A., Husak, G.J., Brown, M.E., Carroll, M., Funk, C.C., Yatheendradas, S., Arsenault, K., Peters-Lidard, C., and Verdin, J.P., 2015, Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture: Journal of Hydrometeorology, v. 16, no. 1, p. 295-305, at http://dx.doi.org/10.1175/JHM-D-14-0049.1.

Pervez, M.S., and Henebry, G.M., 2014, Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes—implications for flooding and drought: Natural Hazards and Earth System Sciences, v. 2, no. 1, p. 147-162, 2015, at http://dx.doi.org/10.5194/nhess-15-147-2015.

Rengarajan, R., Sampath, A., Storey, J.C., and Choate, M.J., 2015, Validation of geometric accuracy of Global Land Survey (GLS) 2000 data: Photogrammetric Engineering and Remote Sensing, v. 81, no. 2, p. 131-141, at http://dx.doi.org/10.14358/PERS.81.2.131.

 

January 2015

Boyte, S.P., Wylie, B.K., Major, D.J., and Brown, J.F., 2015, The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth: International Journal of Digital Earth, v. 8, no. 2, p. 116-130, at http://dx.doi.org/10.1080/17538947.2013.860196.

Funk, C.C., Hoell, A., Shukla, S., Bladé, I., Liebmann, B., Roberts, J.B., Robertson, F.R., and Husak, G., 2014, Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices: Hydrology and Earth System Sciences, v. 18, no. 12, p. 4965-4978, at http://dx.doi.org/10.5194/hessd-11-3111-2014.

Loveland, T.R., and Mahmood, R., 2014, A design for a sustained assessment of climate forcing and feedbacks related to land use and land cover change: Bulletin of the American Meteorological Society, v. 95, no. 10, p. 1563-1572, at http://dx.doi.org/10.1175/BAMS-D-12-00208.1.

Senay, G.B., Velpuri, N.M., Bohms, S., Budde, M.E., Young, C.J., Rowland, J.D., and Verdin, J.P., 2014, Drought monitoring and assessment—remote sensing and modeling approaches for the Famine Early Warning Systems Network, chap. 9 in Paolo, P., and Baldassarre, G.D., eds., Hydro-meteorological hazards, risks, and disasters: Amsterdam, Elsevier, p. 233-262, at http://dx.doi.org/10.1016/B978-0-12-394846-5.00009-6.

Senay, G.B., Velpuri, N.M., Bohms, S., Demissie, Y., and Gebremichael, M., 2014, Understanding the hydrologic sources and sinks in the Nile Basin using multi-source climate and remote sensing datasets: Water Resources Research, v. 50, no. 11, p. 8625-8650, at http://dx.doi.org/10.1002/2013WR015231.

Tadesse, T., Wardlow, B.D., Brown, J.F., Svoboda, M.D., Hayes, M.J., Fuchs, B., and Gutzmer, D., 2014, Assessing the vegetation condition impacts of the 2011 drought across the U.S. Southern Great Plains using the Vegetation Drought Response Index (VegDRI): Journal of Applied Meteorology and Climatology, v. 54, no. 1, p. 153-169, at http://dx.doi.org/10.1175/JAMC-D-14-0048.1.

 

December 2014

Giri, C.P., Long, J.B., Abbas, S., Murali, R.M., Qamer, F.M., Pengra, B.W., and Thau, D., 2015, Distribution and dynamics of mangrove forests of South Asia: Journal of Environmental Management, v. 148, p. 101-111, at http://dx.doi.org/10.1016/j.jenvman.2014.01.020.

Howard, S.M., Picotte, J.J., and Coan, M.J., 2014, Utilizing multi-sensor fire detections to map fires in the USGS, in Toth, C., Holm, T.M., and Jutzi, B., eds., Sustaining land imaging...UAS to satellites, ASPRS 2014, Pecora 19, in conjunction with the Joint Symposium of ISPRS Technical Commission I and IAG Commission 4, Denver, Colo., 17-20 November 2014, The International Archives of the Photogrammetry, Remote Sensing, and Spatial Information Sciences, XL-1: Lemmer, Netherlands, International Society for Photogrammetry and Remote Sensing, p. 161-166, at http://dx.doi.org/10.5194/isprsarchives-XL-1-161-2014.

Liebmann, B., Hoerling, M.P., Funk, C.C., Bladé, I., Dole, R.M., Allured, D., Quan, X., Pegion, P., and Eischeid, J.K., 2014, Understanding recent eastern Horn of Africa rainfall variability and change: Journal of Climate, v. 27, no. 23, p. 8630-8645, at http://dx.doi.org/10.1175/JCLI-D-13-00714.1.

Mishra, N., Haque, M.O., Leigh, L., Aaron, D.B., Helder, D.L., and Markham, B.L., 2014, Radiometric cross calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+): Remote Sensing, v. 6, no. 12, p. 12619-12638, at http://dx.doi.org/10.3390/rs61212619.

Peterson, B.E., and Nelson, K.J., 2014, Mapping forest height in Alaska using GLAS, Landsat composites, and airborne LiDAR: Remote Sensing, v. 6, no. 12, p. 12409-12426, at http://dx.doi.org/10.3390/rs61212409.

Worstell, B.B., Poppenga, S.K., Evans, G.A., and Prince, S.A., 2014, Lidar point density analysis—Implications for identifying water bodies: U.S. Geological Survey Scientific Investigations Report 2014-5191, 19 p., at http://dx.doi.org/10.3133/sir20145191.

 

November 2014

Auch, R.F., and Laingen, C., in press, Having it both ways? Land use change in a U.S. midwestern agricultural ecoregion: The Professional Geographer, p. 1-14. (Also available online at http://dx.doi.org/10.1080/00330124.2014.921015.)

Giri, C.P., and Long, J.B., 2014, Land cover characterization and mapping of South America for the year 2010 using Landsat 30m satellite data: Remote Sensing, v. 6, no. 10, p. 9494-9510, available only online at http://dx.doi.org/10.3390/rs6109494.  

Harriman, L.M., 2014, Climate change implications and use of early warning systems for global dust  storms, chap. 8 of Singh, A., and Zommers, Z., eds., Reducing disasters—early warning systems for climate  change: Dordrecht, Netherlands, Springer, p. 153-165. (Also available online at http://dx.doi.org/10.1007/978-94-017-8598-3_8.)

Pervez, M.S., and Henebry, G.M., in press, Assessing the impacts of climate and land use and land cover change on the freshwater availability in the Brahmaputra River basin: Journal of Hydrology - Regional Studies, p. 0-0. (Also available online at http://dx.doi.org/10.1016/j.ejrh.2014.09.003.)

Singh, R.K., Senay, G.B., Velpuri, N.M., Bohms, S., and Verdin, J.P., 2014, On the downscaling of actual evapotranspiration maps based on combination of MODIS and Landsat-based actual evapotranspiration estimates: Remote Sensing, v. 6, no. 11, p. 10483-10509, available only online at http://dx.doi.org/10.3390/rs61110483.

Storey, J.C., Choate, M.J., and Lee, K., 2014, Landsat 8 Operational Land Imager on-orbit geometric calibration and performance: Remote Sensing, v. 6, no. 11, p. 11127-11152, at http://dx.doi.org/10.3390/rs61111127.

Storey, J.C., Choate, M.J., and Moe, D., 2014, Landsat 8 thermal infrared sensor geometric characterization and calibration: Remote Sensing, v. 6, no. 11, p. 11153-11181, at http://dx.doi.org/10.3390/rs61111153.

 

2014

Funk, C.C., Hoell, A., Shukla, S., Bladé, I., Liebmann, B., Roberts, J.B., Robertson, F.R., and Husak, G., 2014, Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices: Hydrology and Earth System Sciences, v. 11, no. 3, p. 3111-3136, available only online at http://dx.doi.org/10.5194/hessd-11-3111-2014.

Gallant, A.L., Kaya, S., White, L., Brisco, B., Roth, M.F., Sadinski, W.J., and Rover, J.A., 2014, Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data: Water, v. 6, no. 3, p. 694-722, available only online at http://dx.doi.org/10.3390/w6030694.

Long, J.B., Napton, D.E., Giri, C.P., and Graesser, J., 2014, A mapping and monitoring assessment of the Philippines’ mangrove forests from 1990 to 2010: Journal of Coastal Research, v. 30, no. 2, p. 260-271. (Also available online at http://dx.doi.org/10.2112/JCOASTRES-D-13-00057.1.)

Loveland, T.R., Wulder, M.A., and Irons, J.R., Landsat Science Team meeting—first Landsat 8 evaluations: The Earth Observer, v. 26, no. 2, p. 24-28. (Also available online at http://eospso.gsfc.nasa.gov/earth-observer-archive/.)

Pastick, N.J., Rigge, M.B., Wylie, B.K., Jorgenson, M.T., Rose, J.R., Johnson, K.D., and Ji, L., 2014, Distribution and landscape controls of organic layer thickness and carbon within the Alaskan Yukon River Basin: Geoderma, v. 230-231, p. 79-94. (Also available online at http://dx.doi.org/10.1016/j.geoderma.2014.04.008.)

Pervez, M.S., Budde, M.E., and Rowland, J.D., 2014, Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI: Remote Sensing of Environment, v. 149, p. 155-165. (Also available online at http://dx.doi.org/10.1016/j.rse.2014.04.008.)

Pervez, M.S., and Henebry, G.M., 2014, Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes—implications for flooding and drought: Natural Hazards and Earth System Sciences Discussions, v. 2, no. 2, p. 1671-1692. (Also available online at http://dx.doi.org/10.5194/nhessd-2-1671-2014.)

Poppenga, S.K., Gesch, D.B., and Worstell, B.B., 2013, Hydrography change detection—three-dimensional analysis of lidar data for updating mapped hydrography: Access, v. 16, no. 1, available only online at http://www.usgs.gov/core_science_systems/access/.

Roy, D.P., Wulder, M.A., Loveland, T.R., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D.L., Irons, J.R., Johnson, D.M., Kennedy, R., 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.E., Wynne, R.H., and Zhu, Z., 2014, Landsat-8—science and product vision for terrestrial global change research: Remote Sensing of Environment, v. 145, p. 154-172. (Also available online at http://dx.doi.org/10.1016/j.rse.2014.02.001.)

Sampath, A., Heidemann, H.K., Stensaas, G.L., and Christopherson, J.B., 2014, ASPRS research on quantifying the geometric quality of lidar data: Photogrammetric Engineering and Remote Sensing, v. 80, no. 3, p. 201-205.  (Also available online at http://www.asprs.org/a/publications/pers/2014journals/March_2014_Flippin....)

U.S. Geological Survey, 2014, Landsat surface reflectance climate data records: U.S. Geological Survey Fact Sheet 2013-3117, 1 p., available only online at http://pubs.er.usgs.gov/publication/fs20133117.

U.S. Geological Survey, 2014, Tracking change over time—River flooding: U.S. Geological Survey General Information Product 133-A, variously paged, available only online at http://dx.doi.org/10.3133/10.3133/gip133A.