Estimation of Maize Biomass Components from Sentinel-1 SAR Data Using Multi-Target Regressors-Reference-Cited by-同舟云学术

Estimation of Maize Biomass Components from Sentinel-1 SAR Data Using Multi-Target Regressors

Published:2022-07-17 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
language:
Short-container-title:

Author:

Xu Chi¹,Ding Yanling¹,Dai Zewen¹

Affiliation:

1. School of Geographical Sciences, Northeast Normal University,Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education,Changchun,China,130024

Funder

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9883023/9883024/09884054.pdf?arnumber=9884054

Reference14 articles.

1. Above-ground biomass mapping in West African dryland forest using Sentinel-1 and 2 datasets - A case study

2. Combining spectral and textural information in UAV hyperspectral images to estimate rice grain yield

3. Combining texture, color, and vegetation indices from fixed-wing UAS imagery to estimate wheat growth parameters using multivariate regression methods

4. Estimating tree aboveground biomass using multispectral satellite-based data in Mediterranean agroforestry system using random forest algorithm

5. Improved estimation of rice aboveground biomass combining textural and spectral analysis of UAV imagery

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel neural network model to achieve generality for diverse morphologies and crop science interpretability in rice biomass estimation;Computers and Electronics in Agriculture;2024-03

2. Above Ground Biomass Estimation By Multi-Source Data Based On Interpretable DNN Model;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16