Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas

By S. Franklin, M. Wulder. 2002

359 citations recorded by the source corpus.

Subfields: Atmospheric Science, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/a574480880ecc448b7027c37b143a263621d9bbb

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Citations in the corpus

Measuring and modelling biodiversity from space (2008, background): “Franklin and Wulder (2002) undertook an excellent review of large-scale land-cover classifi cations, such as CORINE and GAP, that generally seek to attain 85% accuracy across all mapping classes using a variety of passive sensors (TM, SPOT, AVHRR, MODIS) and to a lesser extent active sensors…”
Remote Sensing of Coral Reefs for Monitoring and Management: A Review (2016, background): “Land cover mapping is one of the earliest applications of remote sensing technology, and can be achieved using optical instruments across the range of available spatial resolutions, from detailed airborne imagery to low resolution data, according to the required area of observation and the purposes ”
A survey of image classification methods and techniques for improving classification performance (2007, neutral): “Franklin and Wulder ( 2002 ) assessed land‐cover classification approaches with medium spatial resolution remotely sensed data.”
Operational mapping of the land cover of the forested area of Canada with Landsat data: EOSD land cover program (2003, methodology): “While a multitude of methods for mapping land cover over large areas have been reported, unsupervised classification approaches are most commonly employed (Franklin and Wulder 2002).”
Landsat continuity: Issues and opportunities for land cover monitoring (2008, background): “The observation data alone represent a distinctive combination of spatial, spectral, and temporal resolutions, over a large image extent, resulting in information that can support management, monitoring, and scientific activities (Franklin & Wulder, 2002).”
A new approach for rescaling land cover data (2008, background): “…when images are acquired; and the timing of acquisition necessary for mapping pertinent landscape features all affect the accuracy of land cover classification and subsequent interpretation (Cihlar 2000; Song et al. 2001; Franklin and Wulder 2002; Kerr and Ostrovsky 2003; Lu and Weng 2007).”
Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content (2012, background): “Ghose et al. (2007) estimate the impact of buyer textual feedback on price premiums charged by sellers in online second-hand markets.”
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): “Cihlar (2000) and Franklin and Wulder (2002) investigated mapping strategies used in large area land-cover classi ﬁ cation and related issues such as multi-time/angle and multiple sensors, geometric processing, and radiometric scaling.”
Land cover 2.0 (2018, methodology): “Land cover informs the functional relationship between terrain, climate and soils, providing biophysical insights into the environment and drivers of change (DeFries et al. 2002; Townshend et al. 2012; Franklin and Wulder 2002; Andrew, Wulder, and Nelson 2014).”
A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS (2009, background): “…land cover classification product is based upon unsupervised classification, hyperclustering, and manual labelling of Landsat TM and ETM+ data, thereby facilitating the classification of land cover types over larger areas (Franklin and Wulder, 2002; Slaymaker et al., 1996; Wulder et al., 2003).”