Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis
University of Twente · University of Salzburg · +2 more institutions
Abstract
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…
Citation impact
- FWCI
- 57.56
- Percentile
- 100%
- References
- 79
Authors
2Topics & keywords
- Pixel
- Computer science
- Remote sensing
- Dynamic time warping
- Image resolution
- Object (grammar)
- Artificial intelligence
- Data mining
- Zero hunger