Journal ArticleDOI
Opening the archive: How free data has enabled the science and monitoring promise of Landsat
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The new data policy is revolutionizing the use of Landsat data, spurring the creation of robust standard products and new science and applications approaches, and promoting increased international collaboration to meet the Earth observing needs of the 21st century.About:
This article is published in Remote Sensing of Environment.The article was published on 2012-07-01. It has received 976 citations till now.read more
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High-resolution mapping of global surface water and its long-term changes
TL;DR: Using three million Landsat satellite images, this globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities.
Journal ArticleDOI
Good practices for estimating area and assessing accuracy of land change
Pontus Olofsson,Giles M. Foody,Martin Herold,Stephen V. Stehman,Curtis E. Woodcock,Michael A. Wulder +5 more
TL;DR: This work provides practitioners with a set of “good practice” recommendations for designing and implementing an accuracy assessment of a change map and estimating area based on the reference sample data.
Journal ArticleDOI
Landsat-8: Science and Product Vision for Terrestrial Global Change Research
David P. Roy,Michael A. Wulder,Thomas R. Loveland,Curtis E. Woodcock,Richard G. Allen,Martha C. Anderson,Dennis L. Helder,James R. Irons,Daniel M. Johnson,Robert E. Kennedy,Ted Scambos,Crystal B. Schaaf,John R. Schott,Yongwei Sheng,Eric Vermote,Alan Belward,Robert Bindschadler,Warren B. Cohen,Feng Gao,James D. Hipple,Patrick Hostert,Justin L. Huntington,Christopher O. Justice,Ayse Kilic,V. Kovalskyy,Zhongping Lee,Leo Lymburner,Jeffrey G. Masek,Joel McCorkel,Yanmin Shuai,Ricardo Trezza,James E. Vogelmann,Randolph H. Wynne,Zhe Zhu +33 more
TL;DR: Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared as mentioned in this paper.
Journal ArticleDOI
The Randolph Glacier inventory: a globally complete inventory of glaciers
W. Tad Pfeffer,Anthony Arendt,Andrew Bliss,Tobias Bolch,Tobias Bolch,J. Graham Cogley,Alex S. Gardner,Jon Ove Hagen,Regine Hock,Regine Hock,Georg Kaser,C. Kienholz,Evan S. Miles,Geir Moholdt,Nico Mölg,Frank Paul,Valentina Radić,Philipp Rastner,Bruce Raup,J. Rich,Martin Sharp +20 more
TL;DR: The Randolph Glacier Inventory (RGI) as discussed by the authors is a collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance.
References
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Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988
David L. Skole,Compton J. Tucker +1 more
TL;DR: Although this rate of deforestation is lower than previous estimates, the effect on biological diversity is greater and tropical forest habitat, severely affected with respect to biological diversity, increased.
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A Landsat surface reflectance dataset for North America, 1990-2000
Jeffrey G. Masek,Eric Vermote,Nazmi Saleous,Robert E. Wolfe,Forrest G. Hall,Karl F. Huemmrich,Feng Gao,J. Kutler,Teng-Kui Lim +8 more
TL;DR: Initial comparisons with ground-based optical thickness measurements and simultaneously acquired MODIS imagery indicate comparable uncertainty in Landsat surface reflectance compared to the standard MODIS reflectance product.
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On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance
TL;DR: A new spatial and temporal adaptive reflectance fusion model (STARFM) algorithm is presented to blend Landsat and MODIS surface reflectance so that high-frequency temporal information from MODIS and high-resolution spatial information from Landsat can be blended for applications that require high resolution in both time and space.
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Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms
TL;DR: LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks, appears to be a feasible and robust means of increasing information extraction from the Landsat archive.