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Results 1-7 of 7 (Search time: 0.001 seconds).
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  • LT


  • Authors: de By, R.A.;  Advisor: -;  Participants: - (2015)

  • This lecture presents: Project synopsis; Project facts; Objectives; Main hypotheses; High dimensionality of problem space; Compared to high-income ag; STARS Data collection.

  • LT


  • Authors: de By, R.A.;  Advisor: -;  Participants: - (2015)

  • This lecture presents: Project synopsis; Project facts; Objectives; Main hypotheses; High dimensionality of problem space; Compared to high-income ag; STARS Data collection.

  • BB


  • Authors: Belgiu, M.;  Advisor: -;  Participants: - (2017)

  • Efficient methodologies for mapping croplands are an essential condition for the implementation of sustainable agricultural practices and for monitoring crops periodically. The increasing spatial and temporal resolution of globally available satellite images, such as those provided by Sentinel-2, creates new possibilities for generating accurate datasets on available crop types, in ready-to-use vector data format. Existing solutions dedicated to cropland mapping, based on high resolution remote sensing data, are mainly focused on pixel-based analysis of time series data. This paper evaluates how a time-weighted dynamic time warping (TWDTW) method that uses Sentinel-2 time series performs when applied to pixel-based and object-based classifications of various crop types in three diff...

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