CLASlite unmixing of Landsat images to estimate REDD+ activity data for deforestation in a Bangladesh forest-Reference-Cited by-同舟云学术

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CLASlite unmixing of Landsat images to estimate REDD+ activity data for deforestation in a Bangladesh forest

Published:2020-04-08 Issue:02 Volume:14 Page:1
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Redowan Mohammad¹,Phinn Stuart¹,Roelfsema Chris¹,Aziz Ammar Abdul²

Affiliation:

1. University of Queensland, School of Earth and Environmental Science, Remote Sensing Research Centre,

2. University of Queensland, School of Agriculture and Food Sciences, Gatton, Queensland

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Cited by 6 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. Spatial Validation of Spectral Unmixing Results: A Systematic Review;Remote Sensing;2023-05-29

2. A google earth engine approach for anthropogenic forest fire assessment with remote sensing data in Rema-Kalenga wildlife sanctuary, Bangladesh;Geology, Ecology, and Landscapes;2023-01-10

3. Post-typhoon forest damage estimation using multiple vegetation indices and machine learning models;Weather and Climate Extremes;2022-12

4. Modeling forest cover dynamics in Bangladesh using multilayer perceptron neural network with Markov chain;Journal of Applied Remote Sensing;2022-07-04

5. Advances of Forensic Remote Sensing Applications in the Face of Transnational Organized Crime and Terrorism;Technologies to Advance Automation in Forensic Science and Criminal Investigation;2022

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