Roy, David

Professor
Office Phone Number: 
605-688-5352
Email: 
david.roy@sdstate.edu

David Roy has research interests that include the development of remote sensing and advanced computing methods to integrate/fuse satellite sensor data and to map and characterize terrestrial change, Petabyte volume satellite data processing, and the causes and consequences of land cover and land use change.

He is co-lead of the USGS NASA Landsat Science team, a member of the NASA Land-Cover/Land-Use Change Science Team, and co-chair of the GOFC-GOLD Fire Implementation team. He is a member and former chair of the US Land Processes (LP) Distributed Active Archive Center (DAAC) User Working Group (UWG) and a member of the NASA Earth Exchange (NEX) UWG. He is a former member of the NASA MODIS and Suomi National Polar-orbiting Partnership (NPP) Land Science Teams.  

He has a Ph.D. from the Department of Geography, Cambridge University U.K. (1994), an M.Sc. degree in Remote Sensing and Image Processing from the Department of Meteorology, University of Edinburgh (1988), and a B.Sc. degree in Geophysics from the Department of Environmental Science, University of Lancaster (1987).

He held post-doctoral research fellowships at the U.K. Natural Environment Research Council Unit for Thematic Information Systems, University of Reading, and at the Space Applications Institute, Joint Research Centre of the European Commission, Ispra, Italy. Before moving to South Dakota State University he was a research scientist (and remains an Adjunct Professor) at the Department of Geographical Sciences, University of Maryland and led the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Data Operational Product Evaluation group at NASA's Goddard Space Flight Center for eight years.

He has an h-index > 45 and his research has been cited >15,000 times.

 

David Roy, Ph.D., Professor
Geospatial Sciences Center of Excellence
South Dakota State University
Wecota Hall, Box 506B
Brookings, SD 57007-3510
USA
Phone : (01) 605 688 5352
Fax : (01) 605 688 5227
Email : david.roy@sdstate.edu
Skype: david.p.roy
 

 

How to get here from the closest airport

 

Research Group

Dr. Alexey Egorov, Geospatial Analyst.

Dr. Haiyan Huang, Postdoctoral Fellow.

Dr. Zhongbin Li, Postdoctoral Fellow.

Dr. Lin Yan, Assistant Research Professor.

Dr. Hankui Zhang, Assistant Research Professor.

 

Graduate Students

Pedro Valle de Carvalho e Oliveira, Ph.D. Integrating airborne LiDAR, Landsat 8 and Sentinel-2 to map Brazilian Amazon Tropical Moist Forest (BATMF) canopy height [Funded by GSCE Graduate Research Assistantship and 2018 NASA Earth and Space Science Fellowship].

Herve Kashongwe, Geography Masters Degree, Assessment of Airborne LiDAR, Landsat-8 and Sentinel-2 data for forest characterization in Mai Ndombe Province, Democratic Republic of Congo, [funded by Dr. Roy's salary salvage].

Recent Ph.D.

Dr. Amadou Dieye, Land cover land use change and soil organic carbon under climate variability in  the semi-arid West African Sahel (1960-2050) [Funded by 2008 NASA Earth and Space Science Fellowship, Ph.D. April  2016].

Dr. Emma White, Changing field sizes of the Conterminous United States, a decennial assessment [Funded by 2010 GSCE Graduate Research Assistantship, Ph.D. November 2015].

Dr. Jason Stoker, A national-scale assessment of height above ground using disparate lidar collections [Funded by the USGS Land Remote Sensing Program, Ph.D. May 2015].

Dr. Sanath Kumar Sathyachandran, Fire type classification in the Brazilian Legal Amazon [Funded by 2010 NASA Earth and Space Science Fellowship, Ph.D. May 2014].

Dr. Chris Barnes, United States land cover land use change, albedo and radiative forcing: past and potential climate implications [Funded by 2007 NASA Earth and Space Science Fellowship, Ph.D. November 2010].

 

Recent Masters

Sam Cooper, Geography Masters Degree, Examination of the potential of Terrestrial Laser Scanning and Structure-from-Motion photogrammetry for rapid nondestructive field measurement of grass biomass, [Funded by GSCE Graduate Research Assistantship, Masters May  2017].

Marcelline Ndekelu, Geography Masters Degree, Remote sensing an improved census of Lemba commune, Kinshasa, Democratic Republic of the Congo [Funded by the Fulbright Foreign Student Program, Masters July 2015].

 

Currently Active Grants

Roy, D.P. (Principal Investigator), Yan, L., Zhang, H.K., Pathfinding near real time moderate resolution land surface monitoring, looking forward to an operational Landsat 9/10 Sentinel 2A/2B era, This proposal solicits membership to the Landsat Science Team for Dr. Roy and his team who have a proven capability in assessing, processing and developing products from Landsat and Sentinel-2 data. They will: (1) develop Landsat and Sentinel-2 processing, involving assessment and development of algorithms and development of Sentinel-2 ARD comparable to the Landsat ARD, and reflectance correction to nadir BRDF-adjusted reflectance (NBAR); (2) undertake quality assessment and characterization of the consistency of the Landsat and Sentinel-2 ARD; (3) investigate the utility of the data to develop annual land cover products using the state of the art non-parametric supervised classification approaches; (4) investigate the utility of the data to develop timely land cover mapping within the growing season and near-real time (NRT) change detection; (5) assess the expansion of tasks #1-4 to global scale, including making recommendations concerning the development of a global ARD, (6) through these integrative activities make informed recommendations for and provide feedback on planned Landsat-10 observational capabilities. This 5 year contract is funded by U.S. Department of Interior, U.S. Geological Survey, Solicitation G17PS00256.

Roy, D.P. (Principal Investigator), Boschetti, L, Prototyping a Landsat-8 Sentinel-2 Global Burned Area Product. This proposal will prototype a global burned area product by combination of NASA-USGS Landsat-8, ESA Sentinel-2A, and ESA Sentinel-2B data and is directly responsive to the primary focus of the call - developing algorithms and prototyping products for combined use of data from Landsat-8 and Sentinel-2 toward global land monitoring, and advances the virtual constellation paradigm for mid-resolution land imaging.  Product validation will be conducted by comparison with visually interpreted commercial high resolution data and will be endorsed by a regional network of African fire scientists and practitioners. The product will be compared with coarser resolution MODIS and VIIRS burned area products, and ESA funded burned area products, to assess product differences and at the validation sites to quantify their relative accuracies. This 3 year project is funded by NASA NNH14ZDA001N Land Cover/Land Use Change (LCLUC14-2): Multi-Source Land Imaging Science.

Roy, D.P (Principal Investigator), Nemani R., Hansen, M.C., Global Long-Term Multi-Sensor Web-Enabled Landsat Data Record. This new MEaSUREs proposal will (1) extend the CONUS and Alaska WELD Earth System Data Record back to 1982 when the first Landsat 30m data started to be acquired and (2) expand the WELD processing to global scale to provide Landsat 30m information for any terrestrial non-Antarctic location for six 3-year epochs spaced every 5 years from 1985 to 2010. Specifically, in collaboration with researchers at NASA AMES and the University of Maryland, the following combined multi-sensor (Landsat 4, 5 TM and 7 ETM+) 30m products will be generated: 1. Weekly, monthly, seasonal and annual products, CONUS and Alaska, 1982 to 2012, defined in the current WELD product Albers projection, generated at the PI's institution; 2. Annual percent land cover and 5-year land cover change products, CONUS, 1985 to 2010, Albers projection, generated at the PI's institution; 3. Monthly global products, for six epochs (1985, 1990, 1995, 2000, 2005, 2010), 36 months per epoch, defined in the MODIS Sinusoidal projection, generated on the NASA Earth Exchange (NEX) supercomputer at NASA AMES; and 4. Global percent land cover and change for each 36 month epoch (1985, 1990, 1995, 2000, 2005, 2010), MODIS Sinusoidal projection, generated on USGS global 30m land cover initiative hardware at the USGS EROS. This proposal directly supports the moderate global spatial resolution data needs of the climate and global change science communities and the needs of the applications community. This 5 year project is funded by NASA NNH12ZDA001N Making Earth System data records for Use in Research Environments (MEASURES).

Giglio, L. (Principal Investigator at University of Maryland), Boschetti, L., Schroder, W., Roy, D.P., Justice, C., Csiszar, I., MODIS Global Active Fire and Burned Area Product Maintenance and Validation, Data from the NASA MODIS Terra and Aqua satellites are being applied to the systematic mapping of fire; the MODIS Collection 6 Global Active Fire product (MOD14/MYD14) and Global Burned Area product (MCD45) provide a first generation multiyear data record for both research and applications from NASA’s Earth Observing System. This modestly priced 4 year proposal offers major savings by combining the maintenance of the two separate (but related) MODIS fire products into a single effort. Funded by NASA NNH13ZDA001N-TERAQEA Terra and Aqua – Algorithms – Existing Data Products.

 

Teaching

Remote Sensing (GEOG-484/584), David Roy (laboratory sessions, Pedro Valle de Carvalho e Oliveira), Undergraduate level course offered as part of the Geography degree and masters program, Fall 2010, Fall 2011, Fall 2012, Fall 2013, Fall 2014, Fall 2015, Spring 2017, Spring 2018. 

This course provides an overview and understanding of the technology, techniques and capabilities for remote sensing of the environment, through an investigation of the basic concepts of remote sensing and electromagnetic energy, interpretation of remotely sensed imagery, and key remote sensing applications.

GEOG 484-584 Syllabus and Schedule.pdf

 

Quantitative Remote Sensing for Terrestrial Monitoring (GSE/GEOG-741-S01), Graduate level course offered as part of the Geospatial Science and Engineering Ph.D. program, Fall 2006, Fall 2007, Spring 2009, Fall 2010, Spring 2013, Spring 2015, Fall 2016, Fall 2018. 

This course describes the science, algorithms, and computational approaches to generate and assess derived satellite products for long term Earth system monitoring. Emphasis is on the principles of optical remote sensing (400 to 1400 nm) and state-of-the-practice quantitative algorithms for estimating biophysical and geophysical land surface variables from remotely sensed observations. The course provides insights into how space agencies, and in particular NASA, goes about these tasks. Understanding of the fundamental principles of remote sensing, physics, calculus, statistics, and computer literacy is required.

 

Awards

NASA group achievement award, Group Achievement Award Aqua Mission Team, 2003.

NASA Goddard Space Flight Center group achievement award, Outstanding Teamwork Earth Observing (EOS) Aqua Mission Team, 2003.

NASA group achievement award, Group Achievement Award Moderate Resolution Imaging Spectroradiometer (MODIS) Support Team, 2001.

South Dakota State University F.O. Butler Award for Excellence in Research, 2013.

 

 

Book Chapters

Roy, D.P., Kovalskyy, V., Zhang, H., Yan, L., Kommareddy, I., The utility of Landsat data for global long term terrestrial monitoring, chapter in Remote Sensing Time Series  -  Revealing Land Surface Dynamics, Eds. Claudia Kuenzer, C., Dech, S.,  Wagner, W.,  Remote Sensing and Digital Image Processing, Volume 22, 2015, pp 289-305, Springer International, Switzerland.

Roy, D.P., Boschetti, L., Smith, A.M.S, 2013, Satellite remote sensing of fires, chapter 5 in Belcher, C.M. and Rein, G., eds., Fire Phenomena and the Earth System: An Interdisciplinary Guide to Fire Science, John Wiley & Sons, Ltd., Chichester, England, DOI: 10.1002/9781118529539.ch5

Justice C.O., Csiszar, I., Boschetti, L., Korontzi, S., Schroeder, W., Giglio, L., Vadrevu, K.P., Roy, D.P., 2013, Satellite Monitoring and Inventory of Global Vegetation Fires, chapter 20 in Goldammer, J.G. ed., 2013, Vegetation Fires and Global Change – Challenges for Concerted International Action, A White Paper directed to the United Nations and International Organizations, A publication of the Global Fire Monitoring Center (GFMC), Kessel Publishing House, ISBN 978-3-941300-78-1.

Csiszar, I.A., Justice, C.O., Goldammer, J.G., Lynham, T. , de Groot, W.J, Prins, E.M., Elvidge, C.D., Oertel, D., Lorenz, E., Bobbe, T., Quayle, B., Davies, D., Roy, D., Boschetti, L. Korontzi, S., Ambrose, S., Stephens, G., 2014, The GOFC/GOLD Fire Mapping and Monitoring theme: assessment and strategic plans, in “Remote Sensing Modeling and Applications to Wildland Fires”, Qu, J.J.; Sommers, W.; Yang, R.; Riebau, A.; Kafatos, M. (Eds.), Springer Verlag, 550p, ISBN 978-3-642-32529-8.

Roy, D.P., Boschetti, L., Giglio, L., 2011, Remote Sensing of Global Savanna Fire Occurrence, Extent and Properties, chapter 12 in Michael J. Hill and Niall P. Hanan, eds., Ecosystem Function in Global Savannas: Measurement and Modeling at Landscape to Global Scales, CRC/Taylor and Francis, p. 239-254.

Boschetti, L., Roy, D.P. and Justice C.O., 2011, Daily global mapping of vegetation biomass burning from MODIS satellite data, chapter 8 in Maselli, F., Menenti, M., Brivio, P.A., eds., Optical observation of vegetation properties and characteristics, Research Signpost, Trivandrum, p. 189-202.

Masuoka, E., Roy, D.P., Wolfe, R., Morisette, J., Sinno, S., Teague, M., Saleous, N., Devadiga, S., Justice, C., and Nickeson, J., 2011, MODIS land data products-”generation, quality assurance and validation, chapter 22 in Ramachandran, B., Justice, C.O., and Abrams, M.J., eds., Land remote sensing and global environmental change-”NASA's Earth Observing System and the science of ASTER and MODIS, New York, Springer, p. 511-534.

Justice, C.O., Giglio, L., Roy, D.P., Boschetti, L., Csiszar, I., Davies, D., Korontzi, S., Schroeder, W., O'Neal, K., and Morisette, J., 2010, MODIS-derived global fire products, chapter 29 in Ramachandran, B., Justice, C.O., and Abrams, M.J., eds., Land remote sensing and global environmental change-”NASA's Earth Observing System and the science of ASTER and MODIS, New York, Springer, p. 663-682.

Roy, D.P and Justice, C.O., 2007, A burning question -“ the changing role of fire on Earth- in Our Changing Planet: A View From Space , Cambridge University Press, September 30th 2007, Editors Michael D. King, Claire L. Parkinson, Kim C. Partington, Robin G. Williams, 266-273.

 

Other

Shortboard

Longboard

Lake wind

 

 

 

Global WELD monthly 30m Landsat 5 TM and Landsat 7 ETM+ proof of concepts generated on the NASA Earth Exchange (NEX) supercomputer. See product documentation at http://globalmonitoring.sdstate.edu/projects/weldglobal/gweld.html

 

Global WELD Version 3.0 products now three global years available:

GeoTiff format products at http://globalweld.cr.usgs.gov

HDF format products at http://globalweld.cr.usgs.gov/collections

Native resolution visualizations at http://go.nasa.gov/2kLcKto 

 

Annual WELD 30m Landsat 7 ETM+ mosaic of the conterminous USA (CONUS). Ten years of WELD Landsat satellite data products are freely available for the CONUS and Alaska, providing improved opportunities for the generation of large-area, long-term, high spatial resolution data records and for terrestrial analysis and monitoring. Now 1900+ registered users. See http://globalmonitoring.sdstate.edu/projects/weld/

 

WELD Landsat 8 image mosaic of Chesapeake Bay on NASA web site.   

WELD Landsat 8: WIRED and Slate magazine images

Landsat 8: South Dakota NPR Radio Interview

 

Conterminous United States (CONUS) field extraction. An automated computational methodology to extract cropland fields from WELD processed Landsat 5 TM and Landsat 7 ETM+ time series was developed. In 2010 for all the CONUS a total of 4,182,777 fields were extracted with mean and median field sizes of 0.193 km2 and 0.278 km2 respectively. Download data and project information

 

A daily acquisition of MODIS 1km data from Sept. 7, 2000. Creating internally consistent global composites over time requires rigorous production and quality assessment protocols. See NASA MODIS QA browse site https://landweb.nascom.nasa.gov/cgi-bin/browse/browseMODIS.cgi

 

Fire-affected areas detected using MODIS satellite data within a 650km by 500km region encompassing the southern border of Zambia, the northern border of Zimbabwe, and western borders of Mozambique (borders shown in white). The location and approximate day of burning is mapped over 5 months of the dry season from May 1st (Blue) to October 31st (Red) 2002. Lakes Kariba and Cahora Bassa are shown as grey. See MODIS Fire product site http://modis-fire.umd.edu/pages/BurnedArea.php

 

Recent (2017+) Journal Publications

Giglio, L., Boschetti, L., Roy, D.P., Humber, M.L., Justice, C.O., 2018, The Collection 6 MODIS burned area mapping algorithm and product, Remote Sensing of Environment. 217, 72-85. (https://doi.org/10.1016/j.rse.2018.08.005)

Dwyer, J.L., Roy, D.P., Sauer, B., Jenkerson, C.B., Zhang, H.K., Lymburner, L., 2018, Analysis Ready Data: Enabling analysis of the Landsat archive, Remote Sensing, 10(9), 1363.  (http://www.mdpi.com/2072-4292/10/9/1363)

Roy, D.P. and Yan, L., 2018, Robust Landsat-based crop time series modelling, Remote Sensing of Environment. In Press. (https://doi.org/10.1016/j.rse.2018.06.038)

Helder, D., Markham, B., Morfitt, R., Storey, J., Barsi, J., Gascon, F, Clerc, S., LaFrance, B., Masek, J., Roy, D.P., Lewis, A., Pahlevan, N., 2018, Observations and recommendations for the calibration of Landsat 8 OLI and Sentinel 2 MSI for improved data interoperability. Remote Sensing, 10(9), 1340. (http://www.mdpi.com/2072-4292/10/9/1340)

Zhang, H.K., Roy, D.P., Yan, L., Li, Z., Huang, H., Vermote, E., Skakun, S., Roger, J-C, 2018, Characterization of Sentinel-2A and Landsat-8 top of atmosphere, surface, nadir BRDF adjusted reflectance and NDVI differences, Remote Sensing of Environment. 215, 482-494. (https://doi.org/10.1016/j.rse.2018.04.031)

Yan, L., Roy, D.P., Li, Z., Zhang, H.K., Huang, H., 2018, Sentinel-2A multi-temporal misregistration characterization and an orbit-based sub-pixel registration methodology, Remote Sensing of Environment. 215, 495-506.  (https://doi.org/10.1016/j.rse.2018.04.021

Wulder, M.A., Coops, N.C., Roy, D.P., White, J.C., Hermosilla, T., 2018, Land Cover 2.0, International Journal of Remote Sensing, 39(12), 4254-4284.(https://www.tandfonline.com/doi/full/10.1080/01431161.2018.1452075)

Yan, L. and Roy, D.P., 2018, Robust large-area gap filling of Landsat reflectance time series by spectral-angle-mapper based spatio-temporal similarity (SAMSTS), Remote Sensing, 10(4), 609.  (http://www.mdpi.com/2072-4292/10/4/609

Li, F., Zhang, X., Kondragunta, S., Roy, D.P., 2018, Investigation of the fire radiative energy biomass combustion coefficient: A comparison of polar and geostationary satellite retrievals over the Conterminous United States. Journal of Geophysical Research: Biogeosciences, 123, 722–739. (http://onlinelibrary.wiley.com/doi/10.1002/2017JG004279/epdf)

Egorov, A.V., Roy, D.P., Zhang, H.K., Hansen, M.C., Kommareddy, A., 2018, Demonstration of percent tree cover classification using Landsat analysis ready data (ARD) and sensitivity analysis with respect to Landsat ARD processing level, Remote Sensing, 10(2), 209. (http://www.mdpi.com/2072-4292/10/2/209)

Kumar S.S. and Roy D.P., 2018, Global Operational Land Imager (GOLI) Landsat-8 reflectance based active fire detection algorithm, International Journal of Digital Earth, 11(2), 154-178.  (http://www.tandfonline.com/doi/full/10.1080/17538947.2017.1391341)

Roy, D.P., Li, Z., Zhang, H.K., 2017, Adjustment of Sentinel-2 multi-spectral instrument (MSI) red-edge band reflectance to nadir BRDF adjusted reflectance (NBAR) and quantification of red-edge band BRDF effects, Remote Sensing, 9(12), 1325. (http://www.mdpi.com/2072-4292/9/12/1325)

Li, J. and Roy, D.P., 2017, A global analysis of Sentinel-2A, Sentinel-2B and Landsat-8 data revisit intervals and implications for terrestrial monitoring, Remote Sensing. 9(9), 902. (http://www.mdpi.com/2072-4292/9/9/902

Li, Z., Zhang H.K., Roy D.P., Yan L., Huang H., Li J., Li Z., 2017, Landsat 15 m panchromatic assisted downscaling (LPAD) of 30 m reflective wavelength data to Sentinel-2 20 m resolution, Remote Sensing. 9(7), 755. (http://www.mdpi.com/2072-4292/9/7/755

Roy, D.P, Li, J., Zhang, H.K., Yan, L., Huang, H., 2017, Examination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance, Remote Sensing of Environment.  199, 25-38. (https://doi.org/10.1016/j.rse.2017.06.019

Zhang, H.K. and Roy, D.P,  2017, Using the 500 m MODIS land cover product to derive a consistent continental scale 30 m Landsat land cover classification, Remote Sensing of Environment. 197, 15-34. (https://doi.org/10.1016/j.rse.2017.05.024)

Cooper, S.D., Roy, D.P., Schaaf, C.B., Paynter, I., 2017, Examination of the potential of Terrestrial Laser Scanning and Structure-from-Motion photogrammetry for rapid nondestructive field measurement of grass biomass, Remote Sensing. 9 (6), 531. (http://www.mdpi.com/2072-4292/9/6/531)

Roy, D.P.  and  Kumar, S.S., 2017, Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome, International Journal of Digital Earth. 10(1), 54-84.  (http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1208686

 

Submitted Publications

Mathieu, R., Main, R., Roy, D.P., Naidoo, L., Yang, H., Detection of burned areas in southern African savannahs using time series of C-band Sentinel-1 data, Remote Sensing of Environment.

Li, Z., Zhang, H.K., Roy, D.P., Investigation of Sentinel-2 bidirectional reflectance hot-spot sensing conditions, IEEE Transactions on Geoscience and Remote Sensing. ​

Helder, D., Markham, B.,  Morfitt, R., Storey, J., Barsi, J., Gascon, F, Clerc, S., LaFrance, B., Masek, J., Roy, D., Lewis, A., Pahlevan, N., Observations and recommendations for the calibration of Landsat 8 OLI and Sentinel 2 MSI for improved data interoperability. Remote Sensing.

 

Select Journal Publications (110+)

Huang, H., Roy, D.P., Boschetti, B., Zhang, H.K., Yan, L., Kumar, S.S., Gomez-Dans, J., Li, J., 2016, Separability analysis of Sentinel-2A multi-spectral instrument (MSI) data for burned area discrimination, Remote Sensing. 8(10), 873.  (http://www.mdpi.com/2072-4292/8/10/873)

Wessels, K., Van Den Bergh, F., Roy, D.P., Salmon, B., Steenkamp, K., MacAlister, B., Swanepoel, D., Jewitt, D., 2016, Rapid land cover map updates using change detection and robust Random Forest classifiers, Remote Sensing. 8(11), 888. (http://www.mdpi.com/2072-4292/8/11/888

Boschetti, L., Stehman, S.V., Roy, D.P., 2016, A stratified random sampling design in space and time for regional to global scale burned area product validation, Remote Sensing of Environment, 186, 465-478. (http://dx.doi.org/10.1016/j.rse.2016.09.016). 

Zhang, H. K. and Roy, D.P., 2016, Landsat 5 Thematic Mapper reflectance and NDVI 27-year time series inconsistencies due to satellite orbit change, Remote Sensing of Environment, 186, 217–233. (http://dx.doi.org/10.1016/j.rse.2016.08.022).

Storey, J., Roy, D.P., Masek, J., Gascon, F., Dwyer, J., Choate, M., 2016, A note on the temporary mis-registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery, Remote Sensing of Environment, 186, 121-122; (http://dx.doi.org/10.1016/j.rse.2016.08.025).

Roy, D.P., Li, J., Zhang, H.K., Yan, L., 2016, Best practices for the reprojection and resampling of Sentinel-2 Multi Spectral Instrument Level 1C data, Remote Sensing Letters, 7(11), 1023-1032. (http://www.tandfonline.com/doi/full/10.1080/2150704X.2016.1212419)

Yan, L., Roy, D.P., Zhang, H.K., Li, J., Huang, H., 2016, An automated approach for sub-pixel registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery, Remote Sensing, 8(6), 520. (http://www.mdpi.com/2072-4292/8/6/520).  

Roy, D.P., Zhang, H. K., Ju, J., Gomez-Dans, J. L., Lewis, P.E., Schaaf C.B., Sun, Q., Li, J., Huang, H., Kovalskyy, V., 2016, A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance, Remote Sensing of Environment, 176, 255-271. (http://www.sciencedirect.com/science/article/pii/S0034425716300220)

Zhang, H. K. and Roy, D.P., 2016, Computationally inexpensive Landsat 8 Operational Land Imager (OLI) pansharpening, Remote Sensing, 8(3), 180; doi:10.3390/rs8030180. (http://www.mdpi.com/2072-4292/8/3/180)

Roy, D.P., Kovalskyy, V., Zhang, H.K., Vermote, E.F., Yan, L., Kumar, S.S, Egorov, A., 2016, Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity, Remote Sensing of Environment, 185, 57-70.(http://dx.doi.org/10.1016/j.rse.2015.12.024)

Zhang, H. K., Roy, D.P., Kovalskyy, V., 2016, Optimal solar geometry definition for global long term Landsat time series bi-directional reflectance normalization, IEEE Transactions on Geoscience and Remote Sensing. 54(3), 1410-1418. doi: 10.1109/TGRS.2015.2480684.  Note, the right hand side of Equation 2 should be: (1.36292×10^(-9)×α^5 - 3.15403×10^(-8)×α^4 - 3.15819614×10^(-6)×α^3 + 0.0000652685643×α^2 + 0.0120604786763×α + 10.06).  (oops, sorry).

Wulder, M.A, White, J.C., Loveland, T.R., Woodcock, C.E., Belward, A.S., Cohen, W.B., Fosnight, G., Shaw, J.,  Masek,  J.G., Roy, D.P., 2016, The global Landsat archive: Status, consolidation, and direction, Remote Sensing of Environment. 185, 271-283. (http://dx.doi.org/10.1016/j.rse.2015.11.032)

Yan, L. and Roy, D.P., 2016, Conterminous United States crop field size quantification from multi-temporal Landsat data, Remote Sensing of Environment, 172, 67-86. (http://www.sciencedirect.com/science/article/pii/S0034425715301851)

White, E. and Roy, D.P., 2015, A contemporary decennial examination of changing agricultural field sizes using Landsat time series data, Geo: Geography and Environment, 2: 33–54, DOI: 10.1002/geo2.4 (http://onlinelibrary.wiley.com/doi/10.1002/geo2.4/full)

Egorov A.V., Hansen, M.C., Roy, D.P., Kommareddy, A., Potapov, P.V., 2015, Image interpretation-guided supervised classification using nested segmentation, Remote Sensing of Environment, 165, 135–147. (http://www.sciencedirect.com/science/article/pii/S0034425715001649)

Boschetti, L., Roy, D.P., Justice, C.O., Humber, M., 2015, MODIS-Landsat fusion for large area 30m burned area mapping, Remote Sensing of Environment, 161, 27-42. (http://www.sciencedirect.com/science/article/pii/S0034425715000401)

Yan, L. and Roy, D.P., 2015, Improved time series land cover classification by missing-observation-adaptive nonlinear dimensionality reduction, Remote Sensing of Environment, 158, 478-491. (http://www.sciencedirect.com/science/article/pii/S0034425714004763)

Kovalskyy, V. and Roy, D.P., 2015, A one year Landsat 8 conterminous United States study of cirrus and non-cirrus clouds, Remote Sensing, 7, 564-578; doi:10.3390/rs70100564 (http://www.mdpi.com/2072-4292/7/1/564)

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., 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., 2014, Landsat-8: science and product vision for terrestrial global change research, Remote Sensing of Environment, 145, 154–172. (http://www.sciencedirect.com/science/article/pii/S003442571400042X)

Zhang, X., Kondragunta, S., Roy, D.P., 2014, Interannual variation in biomass burning and fire seasonality derived from Geostationary satellite data across the contiguous United States from 1995 to 2011, Journal of Geophysical Research: Biogeosciences, 119, 1147–1162.

Kumar, S.S., Roy, D.P., Cochrane, M.A., Souza JR, C.M., Barber, C., Boschetti, L., 2014, A quantitative study of the proximity of satellite detected active fires to roads and rivers in the Brazilian tropical moist forest biome, International Journal of Wildland Fire, 23(4), 532-543. http://www.publish.csiro.au/?paper=WF13106

Freeborn, P.H., Wooster, M.J., Roy, D.P., Cochrane, M.A., 2014, Quantification of MODIS fire radiative power (FRP) measurement uncertainty for use in satellite-based active fire characterization and biomass burning estimation, Geophysical Research Letters, 41, doi:10.1002/2013GL059086.

Yan, L. and Roy, D.P., 2014, Automated crop field extraction from multi-temporal Web Enabled Landsat Data, Remote Sensing of Environment, 144, 42-64. (http://dx.doi.org/10.1016/j.rse.2014.01.006)

Roy, D.P., Qin, Y., Kovalskyy, V. , Vermote, E.F., Ju, J., Egorov, A., Hansen, M.C., Kommareddy, I., Yan, L., 2014, Conterminous United States demonstration and characterization of MODIS-based Landsat ETM+ atmospheric correction, Remote Sensing of Environment, 140, 433-449. (http://www.sciencedirect.com/science/article/pii/S0034425713003337#)

Hansen, M.C., Egorov, A., Potapov, P.V., Stehman, S.V., Tyukavina, A., Turubanova, S.A., Roy, D.P., Goetz, S.J., Loveland, T.R., Ju, J., Kommareddy, A., Kovalskyy, V., Forsythe, C., Bents, T., 2014, Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD), Remote sensing of Environment, 140, 466-484.

Stoker, J.M., Cochrane, M.A., Roy, D.P., 2014, Integrating disparate Lidar data at the national scale to assess the relationships between height above ground, land cover and ecoregions, Photogrammetric Engineering & Remote Sensing, 80, 1, 59-70.

Smith, A.M.S., Tinkham, W.T., Roy, D.P., Boschetti, L., Kremens, R.L., Kumar, S.S., Sparks, A., Falkowski, M.J., 2013, Quantification of fuel moisture effects on biomass consumed derived from fire radiative energy retrievals, Geophysical Research Letters, 40, 6298-6302, doi:10.1002/2013GL058232.

Heward, H., Smith, A.M.S., Roy, D.P., Hoffman, C.M., Tinkham, W.T., Morgan, P., 2013, Is burn severity related to fire intensity? Observations from landscape scale remote sensing, International Journal of Wildland Fire, 22, 910-918.

Kovalskyy, V., Henebry, G.M., Roy, D.P., Adusei, B., Hansen, M., Senay, G.B., Mocko, D.M., 2013, Evaluation of a coupled event driven phenology and evapotranspiration model for croplands in the United States northern Great Plains, Journal of Geophysical Research – Atmospheres, 118, 11, 5065-5081.

Yanmin, S., Schaaf, C., Xiaoyang, Z., Strahler, A., Roy, D.P., Morisette, J., Wang, Z., Nightingale, J., Nickeson, J., Richardson, A.D., Xie, D., Wang, J., Li, X., Strabala, K., Davies, J., 2013, Daily 500m MODIS reflectance anisotropy direct broadcast (DB) products for monitoring vegetation phenology dynamics, International Journal of Remote Sensing , 34, 5997-6016.

Kovalskyy, V. and Roy, D.P., 2013, The global availability of Landsat 5 TM and Landsat 7 ETM+ land surface observations and implications for global 30m Landsat data product generation, Remote Sensing of Environment, 130, 280-293. (http://www.sciencedirect.com/science/article/pii/S0034425712004609).

Barnes, C., Roy, D.P., Loveland, T., 2013, Projected Surface Radiative Forcing due to 2000 to 2050 Land Cover Land Use Albedo Change over the Eastern United States, Journal of Land Use Science, 8, 369-382( http://www.tandfonline.com/doi/abs/10.1080/1747423X.2012.667453 ).

Ju, J., Roy, D.P., Vermote, E., Masek, J., Kovalskyy, V., 2012, Continental-scale validation of MODIS-based and LEDAPS Landsat ETM+ atmospheric correction methods, Remote Sensing of Environment, 122, 175-184. ( PDF file, 1.29MB )

Dieye, A.M., Roy, D.P., 2012, A study of rural Senegalese attitudes and perceptions of their behavior to changes in the climate, Environmental Management, 50, 5, 929-941. (http://dx.doi.org/10.1007/s00267-012-9932-4)

Dieye, A. M., Roy, D.P., Hanan, N.P., Liu, S., Hansen, M., Toure, A., 2012, Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal, Biogeosciences , 9, 631-648.

Kovalskyy, V., Roy, D.P., Zhang, X., Ju, J., 2012, The suitability of multi-temporal Web-Enabled Landsat Data (WELD) NDVI for phenological monitoring - a comparison with flux tower and MODIS NDVI, Remote Sensing Letters, 3:4, 325-334.

Kumar, S.S., Roy, D.P., Boschetti, L., Kremens, R., 2011, Exploiting the power law distribution properties of satellite fire radiative power retrievals - a method to estimate fire radiative energy and biomass burned from sparse satellite observations, Journal of Geophysical Research, 116, D19303, doi:10.1029/2011JD015676. ( PDF file, 1.27MB )

Disney, M.I., Lewis, P., Gomez-Dans, J., Roy, D.P., Wooster, M., Lajas, D., 2011, 3D radiative transfer modelling of fire impacts on a two-layer savanna system, Remote Sensing of Environment, 115, 1866-1881. ( PDF file, 3.1MB )

Wulder, M.A., White, J.C., Masek, J.G., Dwyer, J., Roy, D.P., 2011, Continuity of Landsat observations: Short term considerations, Remote Sensing of Environment, 115: 747-751. ( PDF file, 142K )

Tulbure, M.G., Wimberly, M.C., Roy, D.P., Henebry, G.M., 2011, Spatial and temporal heterogeneity of agricultural fires in the central United States in relation to land cover and land use. Landscape Ecology , 26, 211-224.

Hansen, M.C., Egorov, A., Roy, D.P., Potapov, P., Ju, J., Turubanova, S., Kommareddy, I., Loveland, T.R., 2011, Continuous fields of land cover for the conterminous United States using Landsat data: first results from the Web-Enabled Landsat Data (WELD) project. Remote Sensing Letters , 2, 279-288.

Barnes, C.A. and Roy D.P., 2010, Radiative forcing over the conterminous United States due to contemporary land cover land use change and sensitivity to snow and interannual albedo variability, J. Geophys. Res., 115, G04033, doi:10.1029/2010JG001428. ( PDF file, 2.3MB ).

Roy D.P., Boschetti, L., Maier, S.W., Smith, A.M.S., 2010, Field estimation of ash and char color-lightness using a standard gray scale, International Journal of Wildland Fire, 19:698-704.

Boschetti, L., Roy, D.P., Justice, C., Giglio, L., 2010, Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product, International Journal of Wildland Fire , 19:705-709.

Archibald, S., Scholes, R.J, Roy, D.P., Roberts, G. Boschetti, L., 2010, Southern African fire regimes as revealed by remote sensing, International Journal of Wildland Fire , 19:861-878.

Roy, D.P., Ju, J., Mbow, C., Frost, P., Loveland, T.R., 2010, Accessing Free Landsat Data via the Internet: Africa's Challenge, Remote Sensing Letters , 1:111-117.

Roy, D.P., Ju, J., Kline, K., Scaramuzza, P.L., Kovalskyy, V., Hansen, M.C., Loveland, T.R., Vermote, E.F., Zhang, C., 2010, Web-enabled Landsat Data (WELD): Landsat ETM+ Composited Mosaics of the Conterminous United States, Remote Sensing of Environment, 114: 35-49. ( PDF file, 1.2MB )

Ju, J., Roy, D.P., Shuai, Y., Schaaf, C., 2010, Development of an approach for generation of temporally complete daily nadir MODIS reflectance time series, Remote Sensing of Environment, 114: 1-20. ( PDF file, 3.7MB )

Bwangoy, J.R., Hansen, M.C., Roy, D.P., De Grandi, G., Justice, C.O., 2010, Wetlands mapping in the Congo Basin using optical and radar remotely sensed data and derived topographical indices, Remote Sensing of Environment, 114:73-86. ( PDF file, 732 KB )

Boschetti L. and Roy, D.P., 2009, Strategies for the fusion of satellite fire radiative power with burned area data for fire radiative energy derivation, Journal of Geophysical Research Atmospheres, 114, D20302, doi:10.1029/2008JD011645. ( PDF file, 457KB )

Roy, D.P. and Boschetti, L., 2009, Southern Africa Validation of the MODIS, L3JRC and GLOBCARBON Burned Area Products, IEEE Transactions on Geoscience and Remote Sensing, 47, 4, 1032-1044, doi:10.1109/TGRS.2008.2009000.( PDF file, 1.4MB )

Archibald, S., Roy, D.P., Van Wilgen, B.W., Scholes, R.J., 2009, What Limits Fire?: An examination of drivers of burnt area in sub-equatorial Africa, Global Change Biologyspecial issue on Fire Ecology and Climate Change, 15, 613-630, doi: 10.1111/j.1365-2486.2008.01754.x.

Giglio, L., Loboda, T., Roy, D.P., Quayle, B., Justice, C.O., 2009, An active-fire based burned area mapping algorithm for the MODIS sensor, Remote Sensing of Environment, 113: 408-420. ( PDF file 4.8MB )

Boschetti, L. and Roy, D.P., 2008, Defining a fire year for reporting and analysis of global inter-annual fire variability, Journal of Geophysical Research, 113, G03020, doi:10.1029/2008JG000686. ( PDF file 2.5MB )

Lindquist, E., Hansen, M.C., Roy, D.P., Justice, C.O., 2008, The suitability of decadal image data sets for mapping tropical forest cover change in the Democratic Republic of Congo: implications for the mid-decadal global land survey, International Journal of Remote Sensing, 29: 7269-7275 ( PDF file 250KB ).

Roy, D.P., Boschetti, L., Justice C.O., Ju, J., 2008, The Collection 5 MODIS Burned Area Product - Global Evaluation by Comparison with the MODIS Active Fire Product, Remote Sensing of Environment,112: 3690-“3707. ( PDF file 4,5MB )

Roy, D.P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M., Lindquist, E., 2008, Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data, Remote Sensing of Environment, 112:3112-3130. ( PDF file 6MB )

Boschetti, L., Roy, D.P., Justice, C.O., 2008, Using NASA's World Wind Virtual Globe for Interactive Internet Visualisation of the Global MODIS Burned Area Product, International Journal of Remote Sensing,29 (11):3067-3072. ( PDF file, 355 KB ).

Barnes, C.A. and Roy, D.P., 2008, Radiative forcing over the conterminous United States due to contemporary land cover land use albedo change, Geophysical Research Letters, 35, L09706, doi:10.1029/2008GL033567. ( PDF file, 315KB ), AGU Journal Highlight, EOS, 89, 24, 10th June 2008, p 221.

Hansen, M.C., Roy, D.P., Lindquist, E., Adusei , B., Justice, C.O., Altstaat, A., 2008, A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change and preliminary results for Central Africa, Remote Sensing of Environment, 112:2495-2513. ( PDF file, 4.6MB )

Ju, J. and Roy, D.P., 2008, The Availability of Cloud-free Landsat ETM+ data over the Conterminous United States and Globally, Remote Sensing of Environment, 112:1196-1211.( PDF file, 2.1MB )

Boschetti, L., Roy, D.P., Barbosa, P., Boca, R., Justice, C., 2008, A MODIS assessment of the summer 2007 extent burned in Greece, International Journal of Remote Sensing, 29:2433-2436. ( PDF file, 300KB )

Myneni, R.B., Wenze Yang, W., Nemani, R.R., Huete, A.R., Dickinson, R.E., Knyazikhin, Y., Didan, K., Fu, R., Negrón Juárez, R.I., Saatchi, S.S., Hashimoto, H., Ichii, K., Shabanov, N.V., Tan, B., Ratana, P., Privette, J.L., Morisette, J.T., Vermote, E.F., Roy, D.P., Wolfe, R.E., Friedl, M.A., Running, S.W., Votava, P., Saleous, N., Devadiga, S., Su, Y., Salomonson , V.V., 2007, Large Seasonal Swings in Leaf Area of Amazon Rainforests, Proceedings of the National Academy of Sciences, March 13 2007; doi:10.1073/pnas.0611338104 ( PDF file, 2.6MB )

Trigg, S.N and Roy D.P., 2007, A focus group study of factors that promote and constrain the use of satellite derived fire products by resource managers in southern Africa, Journal of Environmental Management, 82:95-110 ( PDF file, 512KB )

Roy, D.P., Lewis, P., Schaaf, C., Devadiga, S., Boschetti, L., 2006, The global impact of cloud on the production of MODIS bi-directional reflectance model based composites for terrestrial monitoring, IEEE Geoscience & Remote Sensing Letters, 3:452-456. ( PDF file, 254KB )

Roy, D.P., Trigg, S.N., Bhima, R., Brockett, B., Dube, O., Frost, P., Govender, N., Landmann, T., Le Roux, J., Lepono, T., Macuacua, J., Mbow, C., Mhwandangara,K., Mosepele, B., Mutanga, O., Neo-Mahupeleng, G., Norman, M., Virgilo,S., 2006, The utility of satellite fire product accuracy information - perspectives and recommendations from the southern Africa fire network, IEEE Transactions on Geoscience and Remote Sensing,44:1928-1930. ( PDF file, 63KB )

Roy, D.P., Boschetti, L., Trigg, S., 2006, Remote Sensing of Fire Severity: Assessing the performance of the Normalized Burn Ratio, IEEE Geoscience and Remote Sensing Letters, 3:112-116. ( PDF file, 201KB )

Jin, Y. and Roy, D.P., 2005, Fire-induced albedo change and its radiative forcing at the surface in northern Australia, Geophys. Res. Lett., 32, L13401, doi:10.1029/2005GL022822. ( PDF file, 210KB )

Roy, D.P., Frost, P., Justice, C., Landmann, T., Le Roux, J., Gumbo, K., Makungwa, S., Dunham, K., Du Toit, R., Mhwandagara, K., Zacarias, A, Tacheba, B., Dube, O., Pereira, J., Mushove, P., Morisette, J., Santhana Vannan, S., Davies, D., 2005, The Southern Africa Fire Network (SAFNet) regional burned area product validation protocol, International Journal of Remote Sensing, 26:4265-4292. ( PDF file, 1.4MB )

Roy, D.P. and Landmann, T., 2005, Characterizing the surface heterogeneity of fire effects using multi-temporal reflective wavelength data, International Journal of Remote Sensing, 26:4197-4218. ( PDF file, 490 KB )

Privette, J.L. and Roy, D.P., 2005, Southern Africa as a remote sensing testbed: the SAFARI 2000 special issue overview, International Journal of Remote Sensing, 26:4141-“4158. ( PDF file, 362KB )

Roy, D.P., Jin, Y., Lewis, P.E., Justice, C.O., 2005, Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data, Remote Sensing of Environment, 97: 137-162. ( PDF file, 4MB )

Trigg, S.N., Roy, D.P., Flasse, S.P., 2005, An in situ study of the effects of surface anisotropy on the remote sensing of burned savannah , International Journal of Remote Sensing, 26:4869-4876. ( PDF file, 429KB )

Korontzi, S., Roy, D.P., Justice C.O., Ward, D.E., 2004, Modeling and sensitivity analysis of fire emissions in southern African during SAFARI 2000, Remote Sensing of Environment, 92:255-275.( PDF file, 1.9MB )

Roy, D., Lewis, P., Justice, C., 2002, Burned area mapping using multi-temporal moderate spatial resolution data - a bi-directional reflectance model-based expectation approach, Remote Sensing of Environment, 83:263-286. ( PDF file, 2.3 MB )

Vermote E. and Roy D., 2002, Land surface hot-spot observed by MODIS over Central Africa, International Journal of Remote Sensingcover and letter, 23: 2141-2143. ( PDF, 562 KB )

Roy, D., Borak, J, Devadiga, S., Wolfe, R., Zheng, M., Descloitres, J., 2002, The MODIS land product quality assessment approach, Remote Sensing of Environment, 83:62-76. ( PDF, 1MB )

Wolfe, R., Nishihama, M., Fleig, A., Kuyper, J., Roy, D., Storey, J., Patt, F., 2002, Achieving sub-pixel geolocation accuracy in support of MODIS land science, Remote Sensing of Environment, 83:31-49. ( PDF, 1MB )

Justice, C., Townshend, J., Vermote, E., Masuoka, E., Wolfe, R., Saleous, N., Roy, D., Morisette, J. 2002, An overview of MODIS Land data processing and product status, Remote Sensing of Environment, 83:3-15. ( PDF, 359KB )

Schaaf, C., Gao, F., Strahler, A., Lucht, W., Li, X., Tsang, T., Strugnell, N., Zhang, X., Jin, Y., Muller, J-P., Lewis, P., Barnsley, M., Hobson, P., Disney, M., Roberts, G., Dunderdale, M., d'Entremont, R., Hu, B., Liang, S., Privette, J., Roy, D., 2002, First operational BRDF, albedo and nadir reflectance products from MODIS, Remote Sensing of Environment, 83: 135-148. ( PDF, 1.3MB )

Roy, D.P., 2000, The impact of misregistration upon composited wide field of view satellite data and implications for change detection, IEEE Transactions on Geoscience and Remote Sensing, 38:2017-2032. ( PDF, 436KB )

Roy, D., Giglio, L., Kendall, J., Justice, C., 1999, Multitemporal active-fire based burn scar detection algorithm, International Journal of Remote Sensing, 20:1031-1038. ( PDF, 418KB )

Wolfe, R., Roy, D., Vermote, E., 1998, The MODIS land data storage, gridding and compositing methodology: L2 Grid, IEEE Transactions on Geoscience and Remote Sensing,36:1324-1338. ( PDF, 321KB )

Justice, C., Vermote, E., Townshend, J., Defries, R., Roy, D., Hall, D., Salomonson, V., Privette, J., Riggs, G., Strahler, A., Lucht, W., Myneni, R., Knyazikhin, Y., Running, S., Nemani, R., Wan, Z., Huete, A., van Leeuwen, W., Wolfe, R., Giglio, L., Muller, J-P., Lewis, P., Barnsley, M., 1998, The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research, IEEE Transactions on Geoscience and Remote Sensing,36:1228-1249. ( PDF, 480KB )

Roy, D.P.,1997, Investigation of the maximum normalised difference vegetation index (NDVI) and the maximum surface temperature (Ts) AVHRR compositing procedures for the extraction of NDVI and Ts over forest, International Journal of Remote Sensing, 18:2383-2401. ( PDF, 285KB)

Roy, D.P., Devereux, B., Grainger, B., White, S., 1997, Parametric geometric correction of airborne thematic mapper imagery, International Journal of Remote Sensing, 18:1865-1887. (PDF, 7.5MB)

     
Last modified: 
Aug 30, 2018