Author

Chenkai Teng

Observed name: Teng, Chenkai

Institution: Southwest Forestry University

Observed institution: Southwest Forestry University

ORCID: 0009-0001-8336-5907

Observed ORCID: 0009-0001-8336-5907

OpenAlex ID: A5112989790

Estimation of Above-Ground Biomass for Pinus densata Using Multi-Source Time Series in Shangri-La Considering Seasonal Effects

2023 · Chaoqing Chen, Yunrun He, et al. · Forests · 12

Developing a Method to Estimate Above-Ground Carbon Stock of Forest Tree Species Pinus densata Using Remote Sensing and Climatic Data

2024 · Kai Luo, Yafei Feng, et al. · Forests · 7

Mapping forest aboveground carbon stock of combined stratified sampling and RFRK model with mean annual temperature and precipitation

2025 · Min Peng, Mingrui Xu, et al. · Scientific Reports · 5

A New Spatiotemporal Filtering Method to Reconstruct Landsat Time-Series for Improving Estimation Accuracy of Forest Aboveground Carbon Stock

2025 · Kai Huang, Chenkai Teng, et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 5

A Forest Fire Risk Prediction Framework Based on Machine Learning Models in the Greater Khingan

2026 · Heng Li, Jialong Zhang, et al. · Fire · 1

Physics-constrained deep learning for joint estimation of terrestrial CO2 fluxes and differentiated climatic sensitivities across China (2002–2022)

2026 · Leyan Xia, Chenkai Teng, et al. · Agricultural and Forest Meteorology

2026 · Chenkai Teng · Figshare

A deep learning-based spatio-temporal reconstruction framework for Landsat time series: Improving mountain forest carbon stock estimation accuracy

2026 · Chenkai Teng, Kai Huang, et al. · Remote Sensing Applications Society and Environment

1987-2017 Pinus densata Aboveground Carbon Stock(Shangri_La)

2026 · Teng, Chenkai · Figshare

An RF-Guided Dual-Strategy Feature-Selection Framework for Multi-Source Remote-Sensing-Based Estimation of Forest Aboveground Carbon Stock in Mountainous Terrain

2026 · Yong Jiang, Jialong Zhang, et al. · Remote Sensing

Works count: 10

Citation count: 30

H-index: 4

I10-index: 1