Reprint

Recent Advances and Contribution of Synthetic Aperture Radar (SAR) Applications for Agricultural Monitoring

Edited by
April 2023
222 pages
  • ISBN978-3-0365-7358-8 (Hardback)
  • ISBN978-3-0365-7359-5 (PDF)

This book is a reprint of the Special Issue Recent Advances and Contribution of Synthetic Aperture Radar (SAR) Applications for Agricultural Monitoring that was published in

Engineering
Environmental & Earth Sciences
Summary

Following on from the Special Issue “Recent Advances and Contribution of Synthetic Aperture Radar (SAR) Applications for Agricultural Monitoring”, we concluded that SAR has now become a pivotal sensor for agricultural monitoring. In this Special Issue, you will find a variety of background material discussing SAR and its applications. Several papers focused on using machine learning approaches with SAR to monitor crop stages and classify crops, while others focused on the polarimetric mode to estimate crop height. Going forward, we hope that you will find this Special Issue to be a useful reference.

Format
  • Hardback
License
© by the authors
Keywords
monsoon cropland; Sentinel; smallholders; Google Earth Engine; SAR; India; tropical agricultural monitoring; canopy development analysis; phenology retrieval; Sentinel-1; multitemporal SAR; multi-task machine learning; Sentinel-1; crop development; remote sensing; productivity indicators; wheat; SAR; growth dynamics; synthetic aperture radar; Sentinel-1A; rice detection; time-series data; rice growth-related features; crop height; RADARSAT-2; corn; Synthetic Aperture Radar (SAR); PolSAR; machine learning; RFR; SVR; agriculture; Sentinel-1; temporal composite; object-oriented; crop classification; Google Earth Engine; agriculture; crop monitoring; Sentinel-1; polarimetry; decomposition; field variability; crop parameters; Sentinel-1; SAR; multitemporal analysis; crop identification; parcel-based classification; remote sensing; Common Agricultural Policy; Sentinel-1; polarimetry; dual-pol; crop characterization; phenology; unsupervised classification