High-Resolution Global Maps of 21st-Century Forest Cover Change

By Matthew C. Hansen, Peter V. Potapov, R. Moore, Matt Hancher, Svetlana Turubanova, Alexandra Tyukavina, D. Thau, Stephen V. Stehman, Scott J. Goetz, Thomas R. Loveland and 5 more. Science, 2013

10,692 citations recorded by the source corpus.

Subfields: Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/467f0fdc420f5cd8996c0b2b1eb33a3dcda93c5e

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In Global and Planetary Change

Citations in the corpus

Forest Types Classification Based on Multi-Source Data Fusion (2017, background): “[26] analyzed global 21st-Century forest covers’ change based on Landsat data.”
Hotspots of land use change in Europe (2016, background): “…system science has so far predominantly focused on conversions among board land-use classes, such as deforestation (e.g., Geist and Lambin 2002, Hansen et al 2013, Graesser et al 2015), urbanization (e.g., Deng et al 2008, Taubenböck et al 2012), or forest expansion (e.g., Rudel et al 2005,…”
A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems (2016, methodology): “Other GLAS waveform metrics used for biomass estimation include the slope of the leading extent (e.g. Boudreau et al. 2008; Hansen et al. 2013) and various waveform statistics such as maximum, variance, and skewness (e.g. Duncanson et al. 2010).”
Effects of Payment for Environmental Services (PES) on Deforestation and Poverty in Low and Middle Income Countries: A Systematic Review (2014, methodology): “…used for deforestation impacts, including differences in operational definitions for deforestation or degradation and different types of data sources---for example, onthe-ground point samples or remote sensing samples from satellite or fly-over imagery (West, 2009; Achard and Hansen et al., 2013).”
GEDI launches a new era of biomass inference from space (2022, background): “Maps of localized biomass estimates, when combined with spatial records of recent land use change [9, 10], support policy-critical decisions about the role of ecosystem dynamics in the climate system.”
Correlates of extinction risk in squamate reptiles: the relative importance of biology, geography, threat and range size (2016, neutral): “435 Because threats are not evenly distributed across space [e.g. habitat loss/exploitation 436 in reptiles, Böhm et al. (2013); forest loss, Hansen et al. (2013)], where a species occurs 437 geographically may be as relevant to determining extinction risk as its specific biological…”
CTFS‐ForestGEO: a worldwide network monitoring forests in an era of global change (2015, neutral): “5; data from Hansen et al., 2013; see Appendix S1 for details).”
A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: General guidelines for practitioners and future research (2016, neutral): “…(Birdsey et al., 2013; DeFries et al., 2002; Myneni et al., 2001; Schwalm et al., 2012), forest monitoring (Asner et al., 2006; Gong et al., 2013; Hansen et al., 2008, 2013; Myneni et al., 2007; Potapov et al., 2015; Townshend et al., 2012), medical science and epidemiology studies (Evans et…”
Continuous change detection and classification of land cover using all available Landsat data (2014, methodology): “Following free access to the Landsat archive, studies using lots of Landsat images are appearing (Brooks, Thomas, Wynne, & Coulston, 2012; Goodwin et al., 2008; Hansen et al., 2013; Huang et al., 2010; Kennedy, Yang, & Cohen, 2010; Melaas, Friedl, & Zhu, 2013; Vogelmann et al., 2009; Zhu, Woodcock, ”
Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review (2020, methodology): “Hansen et al. [8] analyzed forest cover changes at the global scale between 2000 and 2012 using Landsat time-series images within GEE.”
Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications (2017, methodology): “…et al., 2010; Gavier-Pizarro et al., 2012; Hayes and Sader, 2001; Sader et al., 2003; Sader and Legaard, 2008; Wilson and Sader, 2002) and high (Hansen et al., 2016, 2014, 2013; Hansen and Loveland, 2012; Potapov et al., 2011, 2015, 2012) frequencies of Landsat time series, while only a few…”
What we (don’t) know about global plant diversity (2018, neutral): “…and data availability; this diversity, while valid within each effort, creates global-scale biases in terms of which species feature in a particular database and which do not, which in turn effects the usability of data (Beck et al. , 2014, 2013; Hinchliff & Smith, 2014; Gratton et al. , in press).”
Remote sensing of forest pest damage: a review and lessons learned from a Canadian perspective* (2016, background): “More recently, Hansen et al. (2013) produced globalmaps of forest depletions from2000 to 2012 that further demonstrate the potential for automated processing of large volumes of Landsat 30-m satellite imagery.”