181 citations as recorded by crossref.

1. Vector radiative transfer code SORD: Performance analysis and quick start guide S. Korkin et al. https://doi.org/10.1016/j.jqsrt.2017.04.035
2. Predicting ground-level PM2.5 concentrations in the Beijing-Tianjin-Hebei region: A hybrid remote sensing and machine learning approach X. Li & X. Zhang https://doi.org/10.1016/j.envpol.2019.03.068
3. Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA A. Just et al. https://doi.org/10.3390/rs10050803
4. Spatiotemporal variability of Canadian High Arctic glacier surface albedo from MODIS data, 2001–2016 C. Mortimer & M. Sharp https://doi.org/10.5194/tc-12-701-2018
5. Intra-seasonal contrasting trends in clouds due to warming induced circulation changes S. Prijith et al. https://doi.org/10.1038/s41598-021-96246-2
6. Results From the Deep Convective Clouds-Based Response Versus Scan-Angle Characterization for the MODIS Reflective Solar Bands A. Angal et al. https://doi.org/10.1109/TGRS.2017.2759660
7. Estimating snow-cover trends from space K. Bormann et al. https://doi.org/10.1038/s41558-018-0318-3
8. Tightening of tropical ascent and high clouds key to precipitation change in a warmer climate H. Su et al. https://doi.org/10.1038/ncomms15771
9. A global moderate resolution dataset of gross primary production of vegetation for 2000–2016 Y. Zhang et al. https://doi.org/10.1038/sdata.2017.165
10. The regime of aerosol asymmetry parameter over Europe, the Mediterranean and the Middle East based on MODIS satellite data: evaluation against surface AERONET measurements M. Korras-Carraca et al. https://doi.org/10.5194/acp-15-13113-2015
11. Developing a Dust Emission Procedure for Central Asia L. Li & I. Sokolik https://doi.org/10.1177/1178622117711939
12. Validation of high‐resolution MAIAC aerosol product over South America V. Martins et al. https://doi.org/10.1002/2016JD026301
13. Validation and Accuracy Analysis of the Collection 6.1 MODIS Aerosol Optical Depth Over the Westernmost City in China Based on the Sun‐Sky Radiometer Observations From SONET G. Huang et al. https://doi.org/10.1029/2019EA001041
14. Changing surface–atmosphere energy exchange and refreezing capacity of the lower accumulation area, West Greenland C. Charalampidis et al. https://doi.org/10.5194/tc-9-2163-2015
15. An optimized semi-empirical physical approach for satellite-based PM2.5 retrieval: embedding machine learning to simulate complex physical parameters C. Jin et al. https://doi.org/10.5194/gmd-16-4137-2023
16. Exploring systematic offsets between aerosol products from the two MODIS sensors R. Levy et al. https://doi.org/10.5194/amt-11-4073-2018
17. Differences in monitoring vegetation dynamics between Moderate Resolution Imaging Spectroradiometer Collection 5 and Collection 6 vegetation index products on the Loess Plateau, China X. Liu et al. https://doi.org/10.1080/01431161.2019.1584928
18. Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes A. Sayer et al. https://doi.org/10.5194/amt-10-1425-2017
19. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China? M. Tao et al. https://doi.org/10.3390/rs9080800
20. An exploratory study on the aerosol height retrieval from OMI measurements of the 477  nm O2 − O2 spectral band using a neural network approach J. Chimot et al. https://doi.org/10.5194/amt-10-783-2017
21. A Comparison of Multi-Angle Implementation of Atmospheric Correction and MOD09 Daily Surface Reflectance Products From MODIS A. Lyapustin et al. https://doi.org/10.3389/frsen.2021.712093
22. Drought resistance enhanced by tree species diversity in global forests D. Liu et al. https://doi.org/10.1038/s41561-022-01026-w
23. A geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 1: Evaluation over land surfaces using measurements from OMI at 466 nm W. Qin et al. https://doi.org/10.5194/amt-12-3997-2019
24. Large scale climate oscillation impacts on temperature, precipitation and land surface phenology in Central Asia K. de Beurs et al. https://doi.org/10.1088/1748-9326/aac4d0
25. Capturing rapid land surface dynamics with Collection V006 MODIS BRDF/NBAR/Albedo (MCD43) products Z. Wang et al. https://doi.org/10.1016/j.rse.2018.02.001
26. MODIS Collection 6 MAIAC algorithm A. Lyapustin et al. https://doi.org/10.5194/amt-11-5741-2018
27. Net primary productivity but not its remote‐sensing proxies predict mammal diversity in Andean‐Amazonian rainforests K. Holzmann et al. https://doi.org/10.1002/ecy.70059
28. Validation of MODIS Aerosol Optical Depth Retrieval over Mountains in Central China Based on a Sun-Sky Radiometer Site of SONET Y. Ma et al. https://doi.org/10.3390/rs8020111
29. Vegetation Dynamics and Their Response to the Urbanization of the Beijing–Tianjin–Hebei Region, China Y. Chang et al. https://doi.org/10.3390/su12208550
30. MISR empirical stray light corrections in high-contrast scenes J. Limbacher & R. Kahn https://doi.org/10.5194/amt-8-2927-2015
31. First Cross- and Inter-Band Calibrations of the Hyperspectral Imager Suite Using Off-Nadir Quasi-Simultaneous Overpass Counterparts H. Mizuochi et al. https://doi.org/10.1109/TGRS.2024.3444849
32. Dynamic estimation model of vegetation fractional coverage and drivers e. Shobairi https://doi.org/10.21833/ijaas.2018.03.009
33. A global aerosol classification algorithm incorporating multiple satellite data sets of aerosol and trace gas abundances M. Penning de Vries et al. https://doi.org/10.5194/acp-15-10597-2015
34. Global MODIS Fraction of Green Vegetation Cover for Monitoring Abrupt and Gradual Vegetation Changes F. Filipponi et al. https://doi.org/10.3390/rs10040653
35. Analysis of Spatial and Temporal Variability in Libya-4 with Landsat 8 and Sentinel-2 Data for Optimized Ground Target Location J. Rodrigo et al. https://doi.org/10.3390/rs11242909
36. Greening of India: Forests or Croplands? J. Kuttippurath & R. Kashyap https://doi.org/10.1016/j.apgeog.2023.103115
37. Continuity between NASA MODIS Collection 6.1 and VIIRS Collection 2 land products M. Román et al. https://doi.org/10.1016/j.rse.2023.113963
38. Drought Resilience Debt Drives NPP Decline in the Amazon Forest F. Machado‐Silva et al. https://doi.org/10.1029/2021GB007004
39. A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al. https://doi.org/10.5194/amt-13-373-2020
40. Short-term vegetation loss versus decadal degradation of grasslands in the Caucasus based on Cumulative Endmember Fractions K. Lewińska et al. https://doi.org/10.1016/j.rse.2020.111969
41. Evaluation of the MODIS (C6) Daily Albedo Products for Livingston Island, Antarctic A. Corbea-Pérez et al. https://doi.org/10.3390/rs13122357
42. Assessment of the impact of discontinuity in satellite instruments and retrievals on global PM2.5 estimates M. Hammer et al. https://doi.org/10.1016/j.rse.2023.113624
43. The global land shortwave cryosphere radiative effect during the MODIS era D. Singh et al. https://doi.org/10.5194/tc-9-2057-2015
44. Accuracy assessment of the latest generations of MODIS burned area products for mapping fire scars on a regional scale over Campos Amazônicos Savanna Enclave (Brazilian Amazon) D. Alves et al. https://doi.org/10.1117/1.JRS.12.026026
45. Amazon Forests’ Response to Droughts: A Perspective from the MAIAC Product J. Bi et al. https://doi.org/10.3390/rs8040356
46. AOD trends during 2001–2010 from observations and model simulations A. Pozzer et al. https://doi.org/10.5194/acp-15-5521-2015
47. Spatiotemporal Patterns of Vegetation Greenness Change and Associated Climatic and Anthropogenic Drivers on the Tibetan Plateau during 2000–2015 L. Li et al. https://doi.org/10.3390/rs10101525
48. Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States “Gigafire” P. Makkaroon et al. https://doi.org/10.1029/2022JD037298
49. Dynamics of the island mass effect – Part 1: Detecting the extent G. Bourdin et al. https://doi.org/10.5194/bg-22-3207-2025
50. Analysis of Surface Water Trends for the Conterminous United States Using MODIS Satellite Data, 2003–2019 R. Petrakis et al. https://doi.org/10.1029/2021WR031399
51. Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance R. Levy et al. https://doi.org/10.5194/amt-8-4083-2015
52. Can MODIS detect trends in aerosol optical depth over land? X. Fan et al. https://doi.org/10.1007/s00376-017-7017-2
53. Increasing sensitivity of alpine grasslands to climate variability along an elevational gradient on the Qinghai-Tibet Plateau L. Li et al. https://doi.org/10.1016/j.scitotenv.2019.04.399
54. The Variations and Trends of MODIS C5 & C6 Products’ Errors in the Recent Decade over the Background and Urban Areas of North China Q. Zhang et al. https://doi.org/10.3390/rs8090754
55. Heterogeneous patterns of abundance of epigeic arthropod taxa along a major elevation gradient J. Röder et al. https://doi.org/10.1111/btp.12403
56. Evaluation of MODIS Albedo Product over Ice Caps in Iceland and Impact of Volcanic Eruptions on Their Albedo S. Gascoin et al. https://doi.org/10.3390/rs9050399
57. Multi‐model analysis of climate impacts on plant photosynthesis in China during 2000–2015 H. Yan et al. https://doi.org/10.1002/joc.6170
58. Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds T. Krisna et al. https://doi.org/10.5194/acp-18-4439-2018
59. Consistency of vegetation index seasonality across the Amazon rainforest E. Maeda et al. https://doi.org/10.1016/j.jag.2016.05.005
60. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. https://doi.org/10.3390/rs12182900
61. Spatio-temporal quality distribution of MODIS vegetation collections 5 and 6: implications for forest-non-forest separability D. Panuju et al. https://doi.org/10.1080/01431161.2019.1641758
62. Remote Sensing of Pasture Degradation in the Highlands of the Kyrgyz Republic: Finer-Scale Analysis Reveals Complicating Factors M. Tomaszewska & G. Henebry https://doi.org/10.3390/rs13173449
63. Scaled RTLS BRDF model extended to high zenith angles A. Lyapustin et al. https://doi.org/10.3389/frsen.2025.1533803
64. Warming, Sheep and Volcanoes: Land Cover Changes in Iceland Evident in Satellite NDVI Trends M. Raynolds et al. https://doi.org/10.3390/rs70809492
65. GEOV2: Improved smoothed and gap filled time series of LAI, FAPAR and FCover 1 km Copernicus Global Land products A. Verger et al. https://doi.org/10.1016/j.jag.2023.103479
66. Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada J. Thomas et al. https://doi.org/10.1002/2017GL073701
67. Uncertainty of Remote Sensing Data in Monitoring Vegetation Phenology: A Comparison of MODIS C5 and C6 Vegetation Index Products on the Tibetan Plateau Z. Zheng & W. Zhu https://doi.org/10.3390/rs9121288
68. Evaluation of VIIRS and MODIS Snow Cover Fraction in High-Mountain Asia Using Landsat 8 OLI K. Rittger et al. https://doi.org/10.3389/frsen.2021.647154
69. Cloud responses to climate variability over the extratropical oceans as observed by MISR and MODIS A. Geiss & R. Marchand https://doi.org/10.5194/acp-19-7547-2019
70. Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S. X. Ye et al. https://doi.org/10.3390/rs14236113
71. Effects of climate change and ozone on vegetation phenology on the Tibetan Plateau Y. Bao et al. https://doi.org/10.1016/j.scitotenv.2024.172780
72. Evaluation and comparison of MODIS and VIIRS aerosol optical depth (AOD) products over regions in the Eastern Mediterranean and the Black Sea P. Ettehadi Osgouei et al. https://doi.org/10.1016/j.atmosenv.2021.118784
73. The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation J. Chen et al. https://doi.org/10.5194/essd-14-3489-2022
74. Differences between the MODIS Collection 6 and 5.1 aerosol datasets over the greater Mediterranean region A. Georgoulias et al. https://doi.org/10.1016/j.atmosenv.2016.10.014
75. Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures A. Adolph et al. https://doi.org/10.5194/tc-12-907-2018
76. Comparison and evaluation of the MODIS Collection 6 aerosol data in China M. Tao et al. https://doi.org/10.1002/2015JD023360
77. Comparison of NASA Harmonized Landsat and Sentinel-2 (HLS) surface reflectance products with MODIS NBAR Q. Zhou et al. https://doi.org/10.1016/j.rse.2026.115717
78. Detection, mapping, and interpretation of the main drivers of the Arctic GPP change from 2001 to 2019 D. Ma et al. https://doi.org/10.1007/s00382-023-06935-z
79. Impact of spring phenology variation on GPP and its lag feedback for winter wheat over the North China Plain L. Guo et al. https://doi.org/10.1016/j.scitotenv.2020.138342
80. Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression D. Zhang et al. https://doi.org/10.3390/rs13173442
81. Dark ice dynamics of the south-west Greenland Ice Sheet A. Tedstone et al. https://doi.org/10.5194/tc-11-2491-2017
82. Regional sulfate drives long-term rise in AOD over megacity Kolkata, India P. Rawat et al. https://doi.org/10.1016/j.atmosenv.2019.04.031
83. Satellite Observations of the Contrasting Response of Trees and Grasses to Variations in Water Availability S. Walther et al. https://doi.org/10.1029/2018GL080535
84. Daily and Hourly Surface PM2.5 Estimation From Satellite AOD H. Zhang & S. Kondragunta https://doi.org/10.1029/2020EA001599
85. The main inherent uncertainty sources in trend estimation based on satellite remote sensing data J. Wen et al. https://doi.org/10.1007/s00704-022-04312-0
86. Global dynamic habitat indices (DHIs) based on MODIS and VIIRS vegetation products D. Liu et al. https://doi.org/10.1016/j.rse.2025.115099
87. Spatiotemporal variability and contribution of different aerosol types to the aerosol optical depth over the Eastern Mediterranean A. Georgoulias et al. https://doi.org/10.5194/acp-16-13853-2016
88. Satellite Observations of the Recovery of Forests and Grasslands in Western China C. Gang et al. https://doi.org/10.1029/2019JG005198
89. Temporally corrected long-term satellite solar-induced fluorescence leads to improved estimation of global trends in vegetation photosynthesis during 1995–2018 S. Wang et al. https://doi.org/10.1016/j.isprsjprs.2022.10.018
90. A new approach developed to study variability in North African dust transport routes over the Atlantic during 2001–2015 L. Meng et al. https://doi.org/10.1002/2017GL074478
91. Deep learning based winter wheat mapping using statistical data as ground references in Kansas and northern Texas, US L. Zhong et al. https://doi.org/10.1016/j.rse.2019.111411
92. Assessment of the Radiometric Calibration Consistency of Reflective Solar Bands between Terra and Aqua MODIS in Upcoming Collection-7 L1B A. Wu et al. https://doi.org/10.3390/rs15194730
93. Estimation of the Land Surface Albedo Changes in the Broader Mediterranean Area, Based on 12 Years of Satellite Observations N. Benas & N. Chrysoulakis https://doi.org/10.3390/rs71215816
94. Spatiotemporal Variations of Global Terrestrial Typical Vegetation EVI and Their Responses to Climate Change from 2000 to 2021 C. Li et al. https://doi.org/10.3390/rs15174245
95. Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency A. Sayer et al. https://doi.org/10.1002/2015JD023878
96. Performance stability of the MODIS and VIIRS LAI algorithms inferred from analysis of long time series of products K. Yan et al. https://doi.org/10.1016/j.rse.2021.112438
97. Weather specific evaluation of satellite retrieved aerosol optical depth over drylands of the Southwest United States H. Dhaliwal & S. Pal https://doi.org/10.1016/j.atmosres.2026.108932
98. Was the extreme Northern Hemisphere greening in 2015 predictable? A. Bastos et al. https://doi.org/10.1088/1748-9326/aa67b5
99. Different Satellite Products Revealing Variable Trends in Global Gross Primary Production Y. Bai et al. https://doi.org/10.1029/2022JG006918
100. Degradation of the FY-3D MERSI-II: Cross-Calibration With MODIS and Its Impact on Aerosol Retrieval X. Su et al. https://doi.org/10.1109/TGRS.2026.3668309
101. Unraveling the Multiple Drivers of Greening-Browning and Leaf Area Variability in a Socioeconomically Sensitive Drought-Prone Region K. Bageshree et al. https://doi.org/10.3390/cli10050070
102. Grid-cell aerosol direct shortwave radiative forcing calculated using the SBDART model with MODIS and AERONET observations: An application in winter and summer in eastern China Y. Fu et al. https://doi.org/10.1007/s00376-017-6226-z
103. Updated MISR dark water research aerosol retrieval algorithm – Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections J. Limbacher & R. Kahn https://doi.org/10.5194/amt-10-1539-2017
104. Can Indirect Evaluation Methods and Their Fusion Products Reduce Uncertainty in Actual Evapotranspiration Estimates? X. Shao et al. https://doi.org/10.1029/2021WR031069
105. Quantifying the Dependence of Satellite Cloud Retrievals on Instrument Uncertainty Y. Shea et al. https://doi.org/10.1175/JCLI-D-16-0429.1
106. Evaluation of the MODIS collections 5 and 6 for change analysis of vegetation and land surface temperature dynamics in North and South America E. Heck et al. https://doi.org/10.1016/j.isprsjprs.2019.07.011
107. Validation of MODIS-Aqua Aerosol Products C051 and C006 over the Beijing-Tianjin-Hebei Region K. Wang et al. https://doi.org/10.3390/atmos8090172
108. Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening? Y. Zhang et al. https://doi.org/10.1016/j.rse.2016.12.018
109. Contrasting Performance of the Remotely-Derived GPP Products over Different Climate Zones across China Y. Chen et al. https://doi.org/10.3390/rs11161855
110. Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index S. Wang et al. https://doi.org/10.1016/j.rse.2018.08.026
111. A Comparative Study of Cross-Product NDVI Dynamics in the Kilimanjaro Region—A Matter of Sensor, Degradation Calibration, and Significance F. Detsch et al. https://doi.org/10.3390/rs8020159
112. Regional‐Scale Wilting Point Estimation Using Satellite SIF, Radiative‐Transfer Inversion, and Soil‐Vegetation‐Atmosphere Transfer Simulation: A Grassland Study T. Kiyono et al. https://doi.org/10.1029/2022JG007074
113. Predominantly positive XCO2 anomalies in the Caatinga biome highlight carbon vulnerability L. Silva et al. https://doi.org/10.1038/s41598-026-37629-1
114. On the relative stability of CERES reflected shortwave and MISR and MODIS visible radiance measurements during the Terra satellite mission J. Corbett & N. Loeb https://doi.org/10.1002/2015JD023484
115. The retrieval of snow properties from SLSTR Sentinel-3 – Part 2: Results and validation L. Mei et al. https://doi.org/10.5194/tc-15-2781-2021
116. Advanced Libya-4 radiometric and atmospheric characterization utilizing moderate resolution imaging spectroradiometer and visible infrared imaging radiometer suite full-scan reflective solar band measurements D. Doelling et al. https://doi.org/10.1117/1.JRS.18.034511
117. A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations L. Mei et al. https://doi.org/10.1080/01431161.2019.1601279
118. A multidimensional comparison between MODIS and VIIRS AOD in estimating ground-level PM2.5 concentrations over a heavily polluted region in China F. Yao et al. https://doi.org/10.1016/j.scitotenv.2017.08.209
119. Variability in glacier albedo and links to annual mass balance for the gardens of Eden and Allah, Southern Alps, New Zealand A. Dowson et al. https://doi.org/10.5194/tc-14-3425-2020
120. Nearly Half of Global Vegetated Area Experienced Inconsistent Vegetation Growth in Terms of Greenness, Cover, and Productivity Z. Ding et al. https://doi.org/10.1029/2020EF001618
121. Late Summer Frazil Ice‐Associated Algal Blooms around Antarctica H. DeJong et al. https://doi.org/10.1002/2017GL075472
122. Estimating PM2.5 surface concentrations from AOD: A combination of SLSTR and MODIS J. Handschuh et al. https://doi.org/10.1016/j.rsase.2022.100716
123. Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land A. Sayer et al. https://doi.org/10.1029/2018JD029598
124. A sparse representation-based fusion model for improving daily MODIS C6.1 aerosol products on a 3 km grid Y. Zhao et al. https://doi.org/10.1080/01431161.2020.1823040
125. Quantifying Grass Coverage Trends to Identify the Hot Plots of Grassland Degradation in the Tibetan Plateau during 2000–2019 Y. Liu & C. Lu https://doi.org/10.3390/ijerph18020416
126. Dust interannual variability and trend in Central Asia from 2000 to 2014 and their climatic linkages X. Xi & I. Sokolik https://doi.org/10.1002/2015JD024092
127. Terra MODIS: 20 years of on-orbit calibration and performance X. Xiong et al. https://doi.org/10.1117/1.JRS.14.037501
128. Influence of recent warming and ice dynamics on glacier surface elevations in the Canadian High Arctic, 1995–2014 C. MORTIMER et al. https://doi.org/10.1017/jog.2018.37
129. Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations V. Martins et al. https://doi.org/10.1016/j.atmosres.2019.04.005
130. Calibration of the DSCOVR EPIC Visible and NIR Channels using Multiple LEO Radiometers I. Geogdzhayev et al. https://doi.org/10.3389/frsen.2021.671933
131. Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing T. Eck et al. https://doi.org/10.1029/2018JD028313
132. Quantifying spatiotemporal variability of glacier algal blooms and the impact on surface albedo in southwestern Greenland S. Wang et al. https://doi.org/10.5194/tc-14-2687-2020
133. Radiative forcing reduced by early twenty-first century increase in land albedo Z. Hou et al. https://doi.org/10.1038/s41586-025-08987-z
134. Comparing the accuracy of MODIS data products for vegetation detection between two environmentally dissimilar ecoregions: the Chocó-Darien of South America and the Great Basin of North America J. Fagua & R. Ramsey https://doi.org/10.1080/15481603.2019.1611024
135. Response Versus Scan-Angle Assessment of MODIS Reflective Solar Bands in Collection 6.1 Calibration R. Bhatt et al. https://doi.org/10.1109/TGRS.2019.2946963
136. A 38-year (1978–2015) Northern Hemisphere daily snow cover extent product derived using consistent objective criteria from satellite-borne optical sensors M. Hori et al. https://doi.org/10.1016/j.rse.2017.01.023
137. Long-term validation of MODIS C6 and C6.1 Dark Target aerosol products over China using CARSNET and AERONET H. Che et al. https://doi.org/10.1016/j.chemosphere.2019.06.238
138. SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe N. Ajtai et al. https://doi.org/10.3390/rs13050844
139. Improving MISR AOD Retrievals With Low-Light-Level Corrections for Veiling Light M. Witek et al. https://doi.org/10.1109/TGRS.2017.2727342
140. No Proportional Increase of Terrestrial Gross Carbon Sequestration From the Greening Earth Y. Zhang et al. https://doi.org/10.1029/2018JG004917
141. Spatio-Temporal Variation and Future Sustainability of Net Primary Productivity from 2001 to 2021 in Hetao Irrigation District, Inner Mongolia M. Peng et al. https://doi.org/10.3390/agriculture14040613
142. Spatio-temporal distribution of aerosol direct radiative forcing over mid-latitude regions in north hemisphere estimated from satellite observations A. Chen et al. https://doi.org/10.1016/j.atmosres.2021.105938
143. Aqua and Terra MODIS RSB Calibration Comparison Using BRDF Modeled Reflectance T. Chang et al. https://doi.org/10.1109/TGRS.2016.2641258
144. Assessment of Terra MODIS On-Orbit Polarization Sensitivity Using Pseudoinvariant Desert Sites A. Wu et al. https://doi.org/10.1109/TGRS.2017.2689719
145. A spatially structured adaptive two-stage model for retrieving ground-level PM2.5 concentrations from VIIRS AOD in China F. Yao et al. https://doi.org/10.1016/j.isprsjprs.2019.03.011
146. Variability and Uncertainty Challenges in Scaling Imaging Spectroscopy Retrievals and Validations from Leaves Up to Vegetation Canopies Z. Malenovský et al. https://doi.org/10.1007/s10712-019-09534-y
147. Observed decreasing trend in the upper-tropospheric cloud top temperature H. Liu et al. https://doi.org/10.1038/s41612-023-00465-5
148. Spatio-Temporal Analysis of Urban Heat Island Using Multisource Remote Sensing Data: A Case Study in Hangzhou, China Y. Zhang & J. Cheng https://doi.org/10.1109/JSTARS.2019.2926417
149. Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions P. Gupta et al. https://doi.org/10.5194/amt-11-3145-2018
150. Seasonal and long-term variations in leaf area of Congolese rainforest Y. Sun et al. https://doi.org/10.1016/j.rse.2021.112762
151. Incorporating long-term satellite-based aerosol optical depth, localized land use data, and meteorological variables to estimate ground-level PM2.5 concentrations in Taiwan from 2005 to 2015 C. Jung et al. https://doi.org/10.1016/j.envpol.2017.11.016
152. Estimating Live Fuel Moisture from MODIS Satellite Data for Wildfire Danger Assessment in Southern California USA B. Myoung et al. https://doi.org/10.3390/rs10010087
153. Mapping snow cover from daily Collection 6 MODIS products over Austria R. Tong et al. https://doi.org/10.1016/j.jhydrol.2020.125548
154. A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading Y. Shi et al. https://doi.org/10.5194/amt-14-3449-2021
155. Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications Z. Li et al. https://doi.org/10.1029/2022RG000777
156. Calibration of Maxar Constellation Over Libya-4 Site Using MAIAC Technique M. Choi et al. https://doi.org/10.1109/JSTARS.2024.3367250
157. TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation C. Zou et al. https://doi.org/10.5194/essd-16-2789-2024
158. A Multiscale Land Use Regression Approach for Estimating Intraurban Spatial Variability of PM2.5 Concentration by Integrating Multisource Datasets Y. Shi et al. https://doi.org/10.3390/ijerph19010321
159. On the potential of an RST-based analysis of the MODIS-derived chl-a product over Condor seamount and surrounding areas (Azores, NE Atlantic) E. Ciancia et al. https://doi.org/10.1007/s10236-016-0972-9
160. A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors S. Smith et al. https://doi.org/10.3390/s25041028
161. Snow cover and snow albedo changes in the central Andes of Chile and Argentina from daily MODIS observations (2000–2016) J. Malmros et al. https://doi.org/10.1016/j.rse.2018.02.072
162. A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China T. Chen et al. https://doi.org/10.1007/s11629-018-4982-6
163. Large discrepancies among remote sensing indices for characterizing vegetation growth dynamics in Nepal D. Zhou et al. https://doi.org/10.1016/j.agrformet.2023.109546
164. Mapping gains and losses in woody vegetation across global tropical drylands F. Tian et al. https://doi.org/10.1111/gcb.13464
165. Optical vegetation indices for monitoring terrestrial ecosystems globally Y. Zeng et al. https://doi.org/10.1038/s43017-022-00298-5
166. Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product S. Go et al. https://doi.org/10.3390/rs12233987
167. Understanding MODIS dark-target collection 5 and 6 aerosol data over China: Effect of surface type, aerosol loading and aerosol absorption L. Mei et al. https://doi.org/10.1016/j.atmosres.2019.05.023
168. A fast and accurate radiative transfer model for aerosol remote sensing L. Mei et al. https://doi.org/10.1016/j.jqsrt.2020.107270
169. On the response of MODIS cloud coverage to global mean surface air temperature Q. Yue et al. https://doi.org/10.1002/2016JD025174
170. Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle J. Jian et al. https://doi.org/10.1038/s41467-022-29391-5
171. Calibration of the SNPP and NOAA 20 VIIRS sensors for continuity of the MODIS climate data records A. Lyapustin et al. https://doi.org/10.1016/j.rse.2023.113717
172. Impact of MODIS sensor calibration updates on Greenland Ice Sheet surface reflectance and albedo trends K. Casey et al. https://doi.org/10.5194/tc-11-1781-2017
173. Harmonization of GEOV2 fAPAR time series through MODIS data for global drought monitoring C. Cammalleri et al. https://doi.org/10.1016/j.jag.2019.03.017
174. Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM N. Ma et al. https://doi.org/10.1016/j.jhydrol.2020.125221
175. Characteristics, drivers and feedbacks of global greening S. Piao et al. https://doi.org/10.1038/s43017-019-0001-x
176. How should we aggregate data? Methods accounting for the numerical distributions, with an assessment of aerosol optical depth A. Sayer & K. Knobelspiesse https://doi.org/10.5194/acp-19-15023-2019
177. Calibration‐Free Complementary Relationship Estimates Terrestrial Evapotranspiration Globally N. Ma et al. https://doi.org/10.1029/2021WR029691
178. Monitoring cyanobacterial harmful algal blooms at high spatiotemporal resolution by fusing Landsat and MODIS imagery Y. Zhao et al. https://doi.org/10.1016/j.envadv.2020.100008
179. Evaluation and analysis of long-term MODIS MAIAC aerosol products in China G. Huang et al. https://doi.org/10.1016/j.scitotenv.2024.174983
180. Record-breaking aerosol levels explained by smoke injection into the stratosphere E. Hirsch & I. Koren https://doi.org/10.1126/science.abe1415
181. Biases and Abrupt Shifts of Monthly Precipitable Water from Terra MODIS N. Lu https://doi.org/10.3390/rs11111315