Crop biomass estimation using multi regression analysis and neural networks from multitemporal L-band polarimetric synthetic aperture radar data-Reference-Cited by-同舟云学术

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Crop biomass estimation using multi regression analysis and neural networks from multitemporal L-band polarimetric synthetic aperture radar data

Published:2019-03-26 Issue:17 Volume:40 Page:6822-6840
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Reisi-Gahrouei Omid¹^ORCID,Homayouni Saeid²^ORCID,McNairn Heather³,Hosseini Mehdi⁴^ORCID,Safari Abdolreza¹^ORCID

Affiliation:

1. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2. Centre Eau Terre Environnement, Institut National de la Recherche Scientifique, Quebec, Canada

3. Ottawa Center of Research & Development, Agriculture & Agri-Food Canada, Ottawa, Canada

4. Department of Geography and Environmental Studies, Carleton University, Ottawa, Canada

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1594436

Reference41 articles.

1. Modeling Managed Grassland Biomass Estimation by Using Multitemporal Remote Sensing Data—A Machine Learning Approach

2. Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island

3. Crop scattering analysis of L-band PolSAR data for vegetation and soil monitoring

4. Artificial neural networks: fundamentals, computing, design, and application

5. Remote sensing for irrigated agriculture: examples from research and possible applications

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