Some challenges in global land cover mapping : An assessment of agreement and accuracy in existing 1 km datasets

By Martin Herold, P. Mayaux, Curtis E. Woodcock, Alessandro Baccini, C. Schmullius. 2008

584 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/14db51c9e2fdbbb6f363c9bce4c1ca84dfea2d95

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Citations in the corpus

GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production (2013, unknown): “The use of global classification is likely to be insufficient because of its limited accuracy (Defourny et al. 2009; Herold et al. 2008; Yang et al. 2006a) and because the variability in canopy architecture and optical properties within a given class is probably as large as between classes when the…”
Global Land Cover Mapping: A Review and Uncertainty Analysis (2014, methodology): “However, the users of these maps have often found it difficult to effectively apply these products to their specific applications due to compelling amounts of uncertainty and inconsistency that occurred in these maps [16].”
Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions (2016, background): “Heterogeneity within land cover classes can be high, and the accuracy of land cover maps derived from satellite data can, correspondingly, be quite variable (see, e.g. Herold et al. 2008).”
Land cover 2.0 (2018, background): “…has logically led to some users comparing land cover maps as a means of better understanding their di ﬀ erences and strengths (Wulder et al. 2004; Herold et al. 2008) and to subsequently apply these combined products to meet science and application needs (Tuanmu and Jetz 2014; Jung et al. 2006).”
Automated cropland mapping of continental Africa using Google Earth Engine cloud computing (2017, background): “…Africa, amongst existing cropland products there has been large disagreement (Fritz and See, 2008; Giri et al., 2005; Hansen and Reed, 2010; Herold et al., 2008; McCallum et al., 2006) especially in the extent of the cultivated areas and their spatial distribution (Fritz et al., 2011a;…”
Geo-Wiki: An online platform for improving global land cover (2012, background): “Hybrid products will be available at spatial resolutions of 300 m, 500 m or 1 km2 in the simplified legend of Herold et al. (2008), which was developed for comparison of different land cover maps and for the recalculation of accuracies.”
Challenges in using land use and land cover data for global change studies (2011, unknown): “A similar conclusion was reached by an analysis of global land cover maps at 1 km spatial resolution by Herold et al. (2008).”
Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine (2017, background): “In addition, a primary requirement for agricultural cropland studies is a dependency on the availability of a precise map of cropland extent at high spatial resolution (30-m or better) as well as determining reliable and consistent cropland areas derived from these accurate maps [3].”
Scarcity amidst abundance? Reassessing the potential for cropland expansion in Africa (2014, background): “In acknowledgement of the continued uncertainty in satellite-based land cover classifications (Herold et al., 2008; Fritz and See, 2008; Fritz et al., 2010, 2011; Kaptué Tchuenté et al., 2011; PérezHoyos et al., 2012), we evaluated the degree of correspondence between these datasets (see Chamberlin,”