Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects

S **, X Sun, F Wu, Y Su, Y Li, S Song, K Xu… - ISPRS Journal of …, 2021 - Elsevier
Plant phenomics is a new avenue for linking plant genomics and environmental studies,
thereby improving plant breeding and management. Remote sensing techniques have …

[HTML][HTML] Remote sensing image fusion on 3D scenarios: A review of applications for agriculture and forestry

JM Jurado, A López, L Pádua, JJ Sousa - International journal of applied …, 2022 - Elsevier
Abstract Three-dimensional (3D) image map** of real-world scenarios has a great
potential to provide the user with a more accurate scene understanding. This will enable …

Performance evaluation of GEDI and ICESat-2 laser altimeter data for terrain and canopy height retrievals

A Liu, X Cheng, Z Chen - Remote Sensing of Environment, 2021 - Elsevier
With the advent of the next generation of space-based laser altimeters, ICESat-2 and GEDI,
we are entering an exciting era of active remote sensing of forests that offers unprecedented …

Neural network guided interpolation for map** canopy height of China's forests by integrating GEDI and ICESat-2 data

X Liu, Y Su, T Hu, Q Yang, B Liu, Y Deng… - Remote Sensing of …, 2022 - Elsevier
Spatially continuous estimates of forest canopy height at national to global scales are critical
for quantifying forest carbon storage, understanding forest ecosystem processes, and …

Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm

K Zhao, MA Wulder, T Hu, R Bright, Q Wu, H Qin… - Remote sensing of …, 2019 - Elsevier
Satellite time-series data are bolstering global change research, but their use to elucidate
land changes and vegetation dynamics is sensitive to algorithmic choices. Different …

[HTML][HTML] High-resolution map** of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data

W Li, Z Niu, R Shang, Y Qin, L Wang, H Chen - International Journal of …, 2020 - Elsevier
Forest canopy height is an important indicator of forest carbon storage, productivity, and
biodiversity. The present study showed the first attempt to develop a machine-learning …

Combination of feature selection and catboost for prediction: The first application to the estimation of aboveground biomass

M Luo, Y Wang, Y **e, L Zhou, J Qiao, S Qiu, Y Sun - Forests, 2021 - mdpi.com
Increasing numbers of explanatory variables tend to result in information redundancy and
“dimensional disaster” in the quantitative remote sensing of forest aboveground biomass …

Lidar boosts 3D ecological observations and modelings: A review and perspective

Q Guo, Y Su, T Hu, H Guan, S **… - … and Remote Sensing …, 2020 - ieeexplore.ieee.org
The advent of lidar has revolutionized the way we observe and measure vegetation structure
from the ground and from above and represents a major advance toward the quantification …

[HTML][HTML] Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data …

D Wang, B Wan, J Liu, Y Su, Q Guo, P Qiu… - International Journal of …, 2020 - Elsevier
The mangrove forests of northeast Hainan Island are the most species diverse forests in
China and consist of the Dongzhai National Nature Reserve and the Qinglan Provincial …

Aboveground biomass estimation using multi-sensor data synergy and machine learning algorithms in a dense tropical forest

SM Ghosh, MD Behera - Applied Geography, 2018 - Elsevier
Forest aboveground biomass (AGB) is an important factor for tracking global carbon cycle to
tackle the impact of climate change. Among all available remote sensing data and methods …