Estimating aboveground forest carbon density using Landsat 8 and field-based data: a comparison of modelling approaches-Reference-Cited by-同舟云学术

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Estimating aboveground forest carbon density using Landsat 8 and field-based data: a comparison of modelling approaches

Published:2020-02-04 Issue:11 Volume:41 Page:4269-4292
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Li Chao¹²^ORCID,Li Mingyang¹²^ORCID,Li Yingchang¹²,Qian Pei³

Affiliation:

1. College of Forestry, Nanjing Forestry University, Nanjing, China

2. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China

3. Department of Natural Resources of Guangdong Province, Guangzhou, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2020.1714782

Reference70 articles.

1. A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methods

2. Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data

3. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors

4. Improved allometric models to estimate the aboveground biomass of tropical trees

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1. Mapping tree carbon density using sentinel 2A sensor on Google Earth Engine in Darjeeling Himalayas: Implication for tree carbon management and climate change mitigation;Physics and Chemistry of the Earth, Parts A/B/C;2024-06

2. AGB estimation using Sentinel-2 and Sentinel-1 datasets;Environmental Monitoring and Assessment;2024-02-24

3. A systematic review of remote sensing and machine learning approaches for accurate carbon storage estimation in natural forests;Southern Forests: a Journal of Forest Science;2023-10-02

4. A Categorical Modelling Approach to Site and Growth of Eucalyptus Stands in Brazilian Eastern Amazon;Revista de Gestão Social e Ambiental;2023-09-11

5. Forest Carbon Density Estimation Using Tree Species Diversity and Stand Spatial Structure Indices;Forests;2023-05-26

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