Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements
Alexei Lyapustin,Yujie Wang,Xiaoxiong Xiong,G. Meister,Steven Platnick,Robert C. Levy,Bryan A. Franz,Sergey Korkin,Thomas Hilker,J. Tucker,Forrest G. Hall,Piers J. Sellers,A. Wu,Amit Angal +13 more
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In this article, an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra-Aqua cross-calibration over quasi-stable desert calibration sites.Abstract:
. The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Angstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra–Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1–B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.read more
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Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009
Maosheng Zhao,Steven W. Running +1 more
TL;DR: In this article, the authors suggest a reduction in the global NPP of 0.55 petagrams of carbon, which would not only weaken the terrestrial carbon sink, but would also intensify future competition between food demand and biofuel production.
Journal ArticleDOI
Characteristics, drivers and feedbacks of global greening
Shilong Piao,Shilong Piao,Xuhui Wang,Taejin Park,Taejin Park,Chi Chen,Xu Lian,Yue He,Jarle W. Bjerke,Anping Chen,Philippe Ciais,Philippe Ciais,Hans Tømmervik,Ramakrishna R. Nemani,Ranga B. Myneni +14 more
TL;DR: In this article, the authors examined the detection of the greening signal, its causes and its consequences, and showed that greening is pronounced over intensively farmed or afforested areas, such as in China and India, reflecting human activities.
Journal ArticleDOI
MODIS Collection 6 MAIAC Algorithm
TL;DR: In this paper, the authors describe the latest version of the algorithm MAIAC used for processing the MODIS Collection 6 data record, which has changed considerably to adapt to global processing and improve cloud/snow detection, aerosol retrievals and atmospheric correction of MODIS data.
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A global moderate resolution dataset of gross primary production of vegetation for 2000–2016
Yao Zhang,Xiangming Xiao,Xiangming Xiao,Xiaocui Wu,Sha Zhou,Geli Zhang,Yuanwei Qin,Jinwei Dong +7 more
TL;DR: This paper provides a new GPP dataset at moderate spatial and temporal resolutions over the entire globe for 2000–2016 and employs a state-of-the-art vegetation index (VI) gap-filling and smoothing algorithm and a separate treatment for C3/C4 photosynthesis pathways.
Journal ArticleDOI
Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?
TL;DR: In this article, the authors re-examined the global vegetation activity by comparing the recent MODIS Collection 6 (C6) and Collection 5 (C5) VIs including Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation index (EVI) from Terra (2001-2015) and Aqua Satellites (2003-2015).
References
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Red and photographic infrared linear combinations for monitoring vegetation
TL;DR: In this article, the relationship between various linear combinations of red and photographic infrared radiances and vegetation parameters is investigated, showing that red-IR combinations to be more significant than green-red combinations.
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AERONET-a federated instrument network and data archive for aerosol Characterization
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TL;DR: The operation and philosophy of the monitoring system, the precision and accuracy of the measuring radiometers, a brief description of the processing system, and access to the database are discussed.
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A Large and Persistent Carbon Sink in the World’s Forests
Yude Pan,Richard Birdsey,Jingyun Fang,Jingyun Fang,Richard A. Houghton,Pekka E. Kauppi,Werner A. Kurz,Oliver L. Phillips,Anatoly Shvidenko,Simon L. Lewis,Josep G. Canadell,Philippe Ciais,Robert B. Jackson,Stephen W. Pacala,A. David McGuire,Shilong Piao,Aapo Rautiainen,Stephen Sitch,Daniel J. Hayes +18 more
TL;DR: The total forest sink estimate is equivalent in magnitude to the terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks, with tropical estimates having the largest uncertainties.
Supporting Online Material for A Large and Persistent Carbon Sink in the World's Forests
Yude Pan,Richard A. Birdsey,Jingyun Fang,Richard A. Houghton,Pekka E. Kauppi,Werner A. Kurz,Oliver L. Phillips,Anatoly Shvidenko,Simon L. Lewis,Philippe Ciais,Robert B. Jackson,Stephen W. Pacala,A. David McGuire,Shilong Piao,Aapo Rautiainen,Stephen Sitch,Daniel J. Hayes +16 more
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First operational BRDF, albedo nadir reflectance products from MODIS
Crystal B. Schaaf,Feng Gao,Alan H. Strahler,Wolfgang Lucht,Xiaowen Li,Trevor Tsang,Nicholas C. Strugnell,Xiaoyang Zhang,Yufang Jin,Jan-Peter Muller,Philip Lewis,M. J. Barnsley,P. Hobson,Mathias Disney,Gareth Roberts,Michael Dunderdale,Christopher N.H. Doll,Robert P. d'Entremont,Baoxin Hu,Shunlin Liang,Jeffrey L. Privette,David P. Roy +21 more
TL;DR: The MODIS BRDF/Albedo algorithm makes use of a semi-empirical kernel-driven bidirectional reflectance model and multidate, multispectral data to provide global 1-km gridded and tiled products of the land surface every 16 days.