Bi-LSTM Model for Time Series Leaf Area Index Estimation Using Multiple Satellite Products-Reference-Cited by-同舟云学术

Bi-LSTM Model for Time Series Leaf Area Index Estimation Using Multiple Satellite Products

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Liu Tian¹,Jin Huaan¹^ORCID,Xie Xinyao¹,Fang Hongliang²^ORCID,Wei Dandan³,Li Ainong¹^ORCID

Affiliation:

1. Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China

2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China

3. Land Satellite Remote Sensing Application Center, MNR, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Chinese Academy of Sciences “Light of West China” Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09864199.pdf?arnumber=9864199

Reference20 articles.

1. Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery

2. Long Short-Term Memory

3. Rice Crop Detection Using LSTM, Bi-LSTM, and Machine Learning Models from Sentinel-1 Time Series

4. Long Time Series Land Cover Classification in China from 1982 to 2015 Based on Bi-LSTM Deep Learning

5. Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model

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. Quantifying nonlinear responses of vegetation to hydro-climatic changes in mountainous Southwest China;Frontiers in Forests and Global Change;2024-06-27

2. Crop Yield Prediction Using Satellite Imagery;2023 7th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS);2023-11-02