Trajectory-based change detection for automated characterization of forest disturbance dynamics

By Robert E. Kennedy, Warren B. Cohen, Todd A. Schroeder. 2007

467 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Media Technology

View Paper: https://www.semanticscholar.org/paper/523ec4ff8d5516f1b280d4f40d4300cfaa72591e

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In Ecology

In Global and Planetary Change

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Citations in the corpus

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync — Tools for calibration and validation (2010, methodology): “Third, advanced automated algorithms capable of processing annual LTS are currently being developed, tested, and operationalized (Kennedy et al., 2007 and 2010; Huang et al., 2010).”
Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach (2012, unknown): “These studies, aswell as those using dense time stacks to monitor forest and cropland change (Kennedy et al., 2007; Kuemmerle et al., 2009) serve as a point of departure for the new work described in this research.”
Continuous change detection and classification of land cover using all available Landsat data (2014, methodology): “Moreover, the CCDC algorithm does not need to perform relative normalization for each image like manymethods (Huang et al., 2010; Kennedy et al., 2007), as the time series model already includes the effects of phenology and sun angle differences.”
Automated mapping of tropical deforestation and forest degradation: CLASlite (2009, background): “Several other higher resolution, regional mapping approaches have also been developed [8-10], but to our knowledge, none have been designed for and widely distributed to non-experts outside of the remote sensing community.”
Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs (2013, methodology): “To move towards threshold-independent change detection, trajectory-based change detection methods have been proposed taking implicitly the temporal signature into account [136–139].”
A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies (2018, background): “The paradigm promotes a new approach to land change monitoring by extending from simple change detection at a bi-temporal scale to a multi-temporal scale (Jin and Sader, 2005; Latifovic and Pouliot, 2005; Kennedy et al., 2007; Huang et al., 2010; Zhu et al., 2012; Sexton et al., 2013b; Franklin et a”
Assessing Land Degradation and Desertification Using Vegetation Index Data: Current Frameworks and Future Directions (2014, unknown): “spatial and temporal resolution [134–137].”
Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications (2017, methodology): “Moreover, the hypothesized trajectory method favors univariate time series (Ahmed et al., 2014; Gillanders et al., 2008; Kennedy et al., 2007), while the multi-date classiﬁcation method favors multivariate time series (Boucher et al., 2006; Coops et al., 2010; Gavier-Pizarro et al., 2012; Hansen et…”