NASA's Black Marble nighttime lights product suite

[1]  Alan H. Strahler,et al.  An algorithm for the retrieval of the clumping index (CI) from the MODIS BRDF product using an adjusted version of the kernel-driven BRDF model , 2018 .

[2]  C. Schaaf,et al.  Capturing rapid land surface dynamics with Collection V006 MODIS BRDF/NBAR/Albedo (MCD43) products , 2018 .

[3]  Jean-Claude Roger,et al.  Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring , 2018, International journal of remote sensing.

[4]  Chuanrong Li,et al.  Stability Monitoring of the VIIRS Day/Night Band over Dome C with a Lunar Irradiance Model and BRDF Correction , 2018, Remote. Sens..

[5]  Lei Ma,et al.  Identifying industrial heat sources using time-series of the VIIRS Nightfire product with an object-oriented approach , 2018 .

[6]  T. Lauvaux,et al.  Assessing uncertainties in gridded emissions: A case study for fossil fuel carbon dioxide (FFCO2) emission data , 2017 .

[7]  Crystal B. Schaaf,et al.  Evaluation of the VIIRS BRDF, Albedo and NBAR products suite and an assessment of continuity with the long term MODIS record , 2017 .

[8]  M. Roman,et al.  Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records , 2017 .

[9]  Crystal B. Schaaf,et al.  Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet , 2017 .

[10]  Zhan Li,et al.  Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[11]  Noam Levin,et al.  The impact of seasonal changes on observed nighttime brightness from 2014 to 2015 monthly VIIRS DNB composites , 2017 .

[12]  M. Roman,et al.  Overview of NASA's MODIS and VIIRS Snow-Cover Earth SystemData Records , 2017 .

[13]  M. Bennett,et al.  Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics , 2017 .

[14]  Robert E. Griffin,et al.  Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas , 2017, Remote. Sens..

[15]  Noam Levin,et al.  A global analysis of factors controlling VIIRS nighttime light levels from densely populated areas , 2017 .

[16]  A. Kokhanovsky,et al.  Atmospheric Aerosols: Life Cycles and Effects on Air Quality and Climate , 2017 .

[17]  Xiaoxiong Xiong,et al.  Impact of Spatial Sampling on Continuity of MODIS–VIIRS Land Surface Reflectance Products: A Simulation Approach , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Alan H. Strahler,et al.  Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners , 2016 .

[19]  Alan H. Strahler,et al.  A Method for Improving Hotspot Directional Signatures in BRDF Models Used for MODIS , 2016 .

[20]  Hanqing Shi,et al.  Inversion of Nighttime PM2.5 Mass Concentration in Beijing Based on the VIIRS Day-Night Band , 2016 .

[21]  Kenneth J. Mackin,et al.  Detection limit of fishing boats by the day night band (DNB) on VIIRS , 2016, Optical Engineering + Applications.

[22]  Arun Malik,et al.  Using VIIRS Day/Night Band to Measure Electricity Supply Reliability: Preliminary Results from Maharashtra, India , 2016, Remote. Sens..

[23]  Karen C. Seto,et al.  A Robust Method to Generate a Consistent Time Series From DMSP/OLS Nighttime Light Data , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[24]  C. Elvidge,et al.  The new world atlas of artificial night sky brightness , 2016, Science Advances.

[25]  Steven D. Miller,et al.  Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method , 2016 .

[26]  M. Vaughan,et al.  An overview of the CATS level 1 processing algorithms and data products , 2016 .

[27]  Noam Levin,et al.  Quantifying urban light pollution — A comparison between field measurements and EROS-B imagery , 2016 .

[28]  Ryutaro Tateishi,et al.  Global mapping of urban built-up areas of year 2014 by combining MODIS multispectral data with VIIRS nighttime light data , 2016, Int. J. Digit. Earth.

[29]  Bo Jiang,et al.  Retrieval of Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from VIIRS Time-Series Data , 2016, Remote. Sens..

[30]  Crystal B. Schaaf,et al.  Estimating the effective spatial resolution of the operational BRDF, albedo, and nadir reflectance products from MODIS and VIIRS , 2016 .

[31]  Steven D. Miller,et al.  VIIRS Day/Night Band - Correcting Striping and Nonuniformity over a Very Large Dynamic Range , 2016, J. Imaging.

[32]  Frank Bickenbach,et al.  Night lights and regional GDP , 2016 .

[33]  Jun Wang,et al.  Improving Nocturnal Fire Detection With the VIIRS Day–Night Band , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[34]  Jun Wang,et al.  Potential application of VIIRS Day/Night Band for monitoring nighttime surface PM 2.5 air quality from space , 2016 .

[35]  Mikhail Zhizhin,et al.  Methods for Global Survey of Natural Gas Flaring from Visible Infrared Imaging Radiometer Suite Data , 2015 .

[36]  Xiaoxiong Xiong,et al.  Suomi-NPP VIIRS day–night band on-orbit calibration and performance , 2015 .

[37]  Steven D. Miller,et al.  An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band , 2015 .

[38]  Jia Yue,et al.  Upper atmospheric gravity wave details revealed in nightglow satellite imagery , 2015, Proceedings of the National Academy of Sciences.

[39]  Wei Guo,et al.  Mapping Impervious Surface Distribution with Integration of SNNP VIIRS-DNB and MODIS NDVI Data , 2015, Remote. Sens..

[40]  Jinpei Ou,et al.  Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO2 Emissions: A Comparison with DMSP-OLS Nighttime Light Data , 2015, PloS one.

[41]  Eleanor C. Stokes,et al.  Holidays in lights: Tracking cultural patterns in demand for energy services , 2015, Earth's future.

[42]  Xi Chen,et al.  A Test of the New VIIRS Lights Data Set: Population and Economic Output in Africa , 2015, Remote. Sens..

[43]  Jianping Wu,et al.  Estimating House Vacancy Rate in Metropolitan Areas Using NPP-VIIRS Nighttime Light Composite Data , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[44]  Chuanmin Hu,et al.  Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico , 2015 .

[45]  Christopher D. Elvidge,et al.  Automatic Boat Identification System for VIIRS Low Light Imaging Data , 2015, Remote. Sens..

[46]  Jianping Wu,et al.  Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the County Level in China , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[47]  Steven D. Miller,et al.  Utilization of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band for Arctic Ship Tracking and Fisheries Management , 2015, Remote. Sens..

[48]  Xiaoxiong Xiong,et al.  A New Method for Suomi-NPP VIIRS Day–Night Band On-Orbit Radiometric Calibration , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[49]  Xiaoxiong Xiong,et al.  The S-NPP VIIRS Day-Night Band On-Orbit Calibration/Characterization and Current State of SDR Products , 2014, Remote. Sens..

[50]  Changyong Cao,et al.  Quantitative Analysis of VIIRS DNB Nightlight Point Source for Light Power Estimation and Stability Monitoring , 2014, Remote. Sens..

[51]  Karen C. Seto,et al.  Chapter 12 - Human settlements, infrastructure and spatial planning , 2014 .

[52]  Yang Yang,et al.  Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review , 2014, Remote. Sens..

[53]  K. Gaston,et al.  Mapping artificial lightscapes for ecological studies , 2014 .

[54]  Christopher O. Justice,et al.  Early evaluation of the VIIRS calibration, cloud mask and surface reflectance Earth data records , 2014 .

[55]  J. Butler,et al.  VIIRS on‐orbit calibration methodology and performance , 2014 .

[56]  J. Wolch,et al.  Urban green space, public health, and environmental justice: The challenge of making cities ‘just green enough’ , 2014 .

[57]  C. Folke,et al.  Reconnecting Cities to the Biosphere: Stewardship of Green Infrastructure and Urban Ecosystem Services , 2014, AMBIO.

[58]  Jianping Wu,et al.  Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas , 2014 .

[59]  Richard A. Frey,et al.  The VIIRS Cloud Mask: Progress in the first year of S‐NPP toward a common cloud detection scheme , 2014 .

[60]  T. Pei,et al.  Responses of Suomi-NPP VIIRS-derived nighttime lights to socioeconomic activity in China’s cities , 2014 .

[61]  D. Haase,et al.  Green justice or just green? Provision of urban green spaces in Berlin, Germany , 2014 .

[62]  C. Woodcock,et al.  Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods , 2014 .

[63]  Simone Bastianoni,et al.  A Thermodynamic Geography: Night-Time Satellite Imagery as a Proxy Measure of Emergy , 2014, AMBIO.

[64]  Steven D. Miller,et al.  The expected performance of cloud optical and microphysical properties derived from Suomi NPP VIIRS day/night band lunar reflectance , 2013 .

[65]  Steven D. Miller,et al.  Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band , 2013, Remote. Sens..

[66]  Bruce I. Hauss,et al.  Suomi NPP VIIRS day‐night band on‐orbit performance , 2013 .

[67]  Robert E. Wolfe,et al.  Suomi NPP VIIRS prelaunch and on‐orbit geometric calibration and characterization , 2013 .

[68]  Stephen P. Mills,et al.  VIIRS day/night band (DNB) stray light characterization and correction , 2013, Optics & Photonics - Optical Engineering + Applications.

[69]  Jürgen Fischer,et al.  Temperature Stability of the Sky Quality Meter , 2013, Sensors.

[70]  Lawrence A. Corp,et al.  NASA Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager , 2013, Remote. Sens..

[71]  Donghui Xie,et al.  Daily MODIS 500 m reflectance anisotropy direct broadcast (DB) products for monitoring vegetation phenology dynamics , 2013 .

[72]  Thomas Esch,et al.  Urban Footprint Processor—Fully Automated Processing Chain Generating Settlement Masks From Global Data of the TanDEM-X Mission , 2013, IEEE Geoscience and Remote Sensing Letters.

[73]  Xi Shao,et al.  Detecting Light Outages After Severe Storms Using the S-NPP/VIIRS Day/Night Band Radiances , 2013, IEEE Geoscience and Remote Sensing Letters.

[74]  Donald W. Hillger,et al.  First-Light Imagery from Suomi NPP VIIRS , 2013 .

[75]  Zhuosen Wang,et al.  Use of In Situ and Airborne Multiangle Data to Assess MODIS- and Landsat-Based Estimates of Directional Reflectance and Albedo , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[76]  Xi Li,et al.  Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China , 2013, Remote. Sens..

[77]  Kathleen A. Powell,et al.  CALIOP and AERONET aerosol optical depth comparisons: One size fits none , 2013 .

[78]  C. Elvidge,et al.  Citizen Science Provides Valuable Data for Monitoring Global Night Sky Luminance , 2013, Scientific Reports.

[79]  Steven D. Miller,et al.  Preliminary investigations toward nighttime aerosol optical depth retrievals from the VIIRS Day/Night Band , 2013 .

[80]  J. Rockström,et al.  Policy: Sustainable development goals for people and planet , 2013, Nature.

[81]  Andrew Molthan,et al.  Satellite Observations Monitor Outages From Superstorm Sandy , 2013 .

[82]  C. Woodcock,et al.  Measuring Gap Fraction, Element Clumping Index and LAI in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar , 2012 .

[83]  Stephen P. Mills,et al.  Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities , 2012, Proceedings of the National Academy of Sciences.

[84]  Jerry Y. Pan,et al.  Intercomparison of MODIS albedo retrievals and in situ measurements across the global FLUXNET network , 2012 .

[85]  A. Strahler,et al.  Global clumping index map derived from the MODIS BRDF product , 2012 .

[86]  Steven D. Miller,et al.  Assessing Moonlight Availability for Nighttime Environmental Applications by Low-Light Visible Polar-Orbiting Satellite Sensors , 2012 .

[87]  Crystal B. Schaaf,et al.  Dynamics of vegetation indices in tropical and subtropical savannas defined by ecoregions and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover , 2012 .

[88]  C. Woodcock,et al.  Evaluation of Moderate-resolution Imaging Spectroradiometer (MODIS) snow albedo product (MCD43A) over tundra , 2012 .

[89]  Michael D. King,et al.  Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements , 2011 .

[90]  Steven D. Miller,et al.  Automated Lightning Flash Detection in Nighttime Visible Satellite Data , 2011 .

[91]  Robert E. Wolfe,et al.  An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics From MODIS Data , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[92]  Franz Hölker,et al.  Cloud Coverage Acts as an Amplifier for Ecological Light Pollution in Urban Ecosystems , 2011, PloS one.

[93]  Christopher D. Elvidge,et al.  Spectral Identification of Lighting Type and Character , 2010, Sensors.

[94]  Feng Gao,et al.  Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes , 2010 .

[95]  Charles S. Zender,et al.  MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland , 2009 .

[96]  K. Davis,et al.  The MODIS (Collection V005) BRDF/albedo product: Assessment of spatial representativeness over forested landscapes , 2009 .

[97]  Steven D. Miller,et al.  A Dynamic Lunar Spectral Irradiance Data Set for NPOESS/VIIRS Day/Night Band Nighttime Environmental Applications , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[98]  Eric Vermote,et al.  Atmospheric correction for the monitoring of land surfaces , 2008 .

[99]  Steven Platnick,et al.  MODIS-Derived Spatially Complete Surface Albedo Products: Spatial and Temporal Pixel Distribution and Zonal Averages , 2008 .

[100]  B. Thaiutsa,et al.  Urban green space, street tree and heritage large tree assessment in Bangkok, Thailand , 2008 .

[101]  Robert E. Wolfe,et al.  Vegetation Phenology Metrics Derived from Temporally Smoothed and Gap-Filled MODIS Data , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.

[102]  Robert E. Wolfe,et al.  An Algorithm to Produce Temporally and Spatially Continuous MODIS-LAI Time Series , 2008, IEEE Geoscience and Remote Sensing Letters.

[103]  Steven D. Miller,et al.  Twenty thousand leagues over the seas: the first satellite perspective on bioluminescent ‘milky seas’ , 2006 .

[104]  Ranga B. Myneni,et al.  The impact of gridding artifacts on the local spatial properties of MODIS data : Implications for validation, compositing, and band-to-band registration across resolutions , 2006 .

[105]  Nik Heynen,et al.  The Political Ecology of Uneven Urban Green Space , 2006 .

[106]  T. Painter,et al.  Reflectance quantities in optical remote sensing - definitions and case studies , 2006 .

[107]  Mark J. Chopping,et al.  Progress in Retrieving Canopy Structure Parameters from NASA Multi-Angle Remote Sensing , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[108]  Steven D Miller,et al.  Detection of a bioluminescent milky sea from space. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[109]  R. Lacaze,et al.  Canada-wide foliage clumping index mapping from multiangular POLDER measurements , 2005 .

[110]  J. Chen,et al.  Global mapping of foliage clumping index using multi-angular satellite data , 2005 .

[111]  Per Jönsson,et al.  TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..

[112]  C.Y. Jim.  Green-space preservation and allocation for sustainable greening of compact cities , 2004 .

[113]  Per Jönsson,et al.  Seasonality extraction by function fitting to time-series of satellite sensor data , 2002, IEEE Trans. Geosci. Remote. Sens..

[114]  D. Roy,et al.  Achieving sub-pixel geolocation accuracy in support of MODIS land science , 2002 .

[115]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[116]  Julienne C. Stroeve,et al.  Development and validation of a snow albedo algorithm for the MODIS instrument , 2002, Annals of Glaciology.

[117]  Roselyne Lacaze,et al.  Retrieval of vegetation clumping index using hot spot signatures measured by POLDER instrument , 2002 .

[118]  Robert E. Wolfe,et al.  MODIS level 2 grid with the ISIN map projection , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[119]  N. C. Strugnell,et al.  A global albedo data set derived from AVHRR data for use in climate simulations , 2001 .

[120]  W. Lucht,et al.  Considerations in the parametric modeling of BRDF and albedo from multiangular satellite sensor observations , 2000 .

[121]  Boulder,et al.  The artificial night sky brightness mapped from DMSP satellite Operational Linescan System measurements , 2000, astro-ph/0003412.

[122]  J. Muller,et al.  MODIS BRDF / Albedo Product : Algorithm Theoretical Basis Document Version 5 . 0 , 1999 .

[123]  S. Running,et al.  MODIS Leaf Area Index (LAI) And Fraction Of Photosynthetically Active Radiation Absorbed By Vegetation (FPAR) Product , 1999 .

[124]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[125]  David P. Roy,et al.  MODIS land data storage, gridding, and compositing methodology: Level 2 grid , 1998, IEEE Trans. Geosci. Remote. Sens..

[126]  Michael J. Barnsley,et al.  Global retrieval of bidirectional reflectance and albedo over land , 1997 .

[127]  J. Roujean,et al.  A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data , 1992 .

[128]  Alan H. Strahler,et al.  Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effect of crown shape and mutual shadowing , 1992, IEEE Trans. Geosci. Remote. Sens..

[129]  J. Chen,et al.  Measuring leaf area index of plant canopies with branch architecture , 1991 .

[130]  J. Monteith,et al.  The Radiation Regime and Architecture of Plant Stands. , 1983 .

[131]  F. E. Nicodemus,et al.  Geometrical considerations and nomenclature for reflectance , 1977 .

[132]  T. Nilson.  A theoretical analysis of the frequency of gaps in plant stands , 1971 .

[133]  CATS Algorithm Theoretical Basis Document Level 1 and Level 2 Data Products Primary , 2022 .