Liyong Fu

• Chinese Academy of Forestry

Key messageA climate-sensitive aboveground biomass (AGB) equation, in combination with nonlinear mixed-effects modeling and dummy variable approach, was developed to examine how climate change may affect the allometric relationships between tree diameter and biomass. We showed that such changes in allometry need to be taken into account for estimat...

Accurate estimates of forest site productivity are essential for environmental planning and forest management. In this study, we developed a new productivity index, hereafter termed basal area potential productivity index (BAPP), to estimate site productivity for irregular and complex forests characterized by multi-aged, multi-species, and multi-la...

The estimation of forest biomass for large spatial regions is key to national carbon stocks, but few models have been developed at the regional level. Based on mensuration data from large samples (755 trees for aboveground and 253 for belowground biomass) of four major pine species in China, we developed compatible individual tree models for above-...

Introduction Chinese fir (Cunninghamia lanceolata) is a crucial afforestation and timber species in southern China. Accurate estimation of its stand biomass is vital for forest resource assessment, ecological industry development, and ecosystem management. However, traditional biomass prediction methods often face limitations in terms of accuracy a...

Accurately assessing the quality of a forested site is essential for sustainable forest management. In forest practices, assessment methods primarily rely on ground meas-urements, but these approaches face challenges such as high costs, low efficiency, and spatial and temporal limitations in data collection. At present, a large number of studies ha...

As the cornerstone of terrestrial ecosystems, forests have faced mounting challenges due to escalating human activities, jeopardizing their vital ecological functions and even their existence. It has become an important issue to explore how to promote harmonious coexistence of man and nature, or even to improve the forest ecological function (FEF)...

With the rapid economic development and continuous expansion of human activities, forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threats to ecosystem stability. Understanding the current status of forest degradation and assessing potential carbon stocks in China are of...

This study focused on 16,101 Cunninghamia lanceolata trees across 133 plots in seven cities of Guangdong Province, China, to develop a comprehensive full growth cycle crown width (CW) model. We systematically analyzed the dynamic characteristics of CW and its multi-scale influencing mechanisms. A binary basic model, with the diameter at breast heig...

Forest aboveground biomass (AGB) is not only the basis for forest carbon stock research, but also an important parameter for assessing the forest carbon cycle and ecological functions of forests. However, there are various uncertainties in the estimation process, limiting the accuracy of AGB estimation. Therefore, we extracted the spectral features...

The processing of LiDAR point cloud data is of critical importance in the context of forest resource surveys, as well as representing a pivotal element in the realm of forest physiological and ecological studies.Nonetheless, conventional denoising algorithms frequently exhibit deficiencies with regard to adaptability and denoising efficacy, particu...

With the rapid development of Earth observation sensors, the fusion of remote sensing (RS) data in multi-modal semantic segmentation has garnered significant research focus in recent years. The fusion of multi-modal data presents challenges due to discrepancies in image acquisition mechanisms among different sensors, leading to misalignment issues....

Increasing evidence shows that biodiversity–ecosystem functioning relationships (BEFs) become stronger as forests develop, but much of the evidence is drawn from experiments (less than 30 years). How the biodiversity effects vary with stand development stages remains largely unexplored. Using a large temperate forest dataset with 2392 permanent plo...

Few-shot Action Recognition (FSAR) has been a heat topic in various areas, such as computer vision and forest ecosystem security. FSAR aims to recognize previously unseen classes using limited labeled video examples. A principal challenge in the FSAR task is to obtain more action semantics related to the category from a few samples for classificati...

Accurate information of the fine-scale spatial patterns of trees and their interactions within a stand is critical for explaining the competition, health and vigor status, and future development of a stand. There are a number of indices which can show such patterns, but the stand spatial structure index is the most important. This index can be quan...

1. Forest ecosystem is a basic component of terrestrial ecosystem that mitigates the impact of climate change through absorbing significant amount of carbon dioxide. Forest is crucial in maintaining ecological equilibrium, reducing greenhouse gas emission, and preserving biodiversity. Thus, standardised and precise methodologies for measuring fores...

Climate change is exacerbating the vulnerability of temperate forests to severe disturbances, potentially increasing tree mortality rates. Despite the significance of this issue, there has been a lack of comprehensive research on tree survival across extensive forest areas under the background of global climate change. To fill this gap, we conducte...

Airborne laser scanning technique (ALS) is the most appealing remote sensing technique for the precise estimation of forest above-ground biomass (AGB). Significantly strong correlations (collinearity) among the independent variables derived from ALS data decrease the accuracy of developed AGB models. To address this issue, we propose a novel variab...

Canopy volume is a crucial biological parameter for assessing tree growth, accurately estimating forest Above-Ground Biomass (AGB), and evaluating ecosystem stability. Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS) are advanced precision mapping technologies that capture highly accurate point clouds for forest digitization studi...

Significant influences on tree growth and forest functionality are attributed to nitrogen (N) addition. However, limited research has been conducted on the effects of N addition on forest spatial structure. In this study, we examined the effects of different N addition methods and concentrations on the stand spatial structure of a deciduous broad-l...

K-proximal plane clustering (kPPC) cluster data points to the center points and local k-proximal plane clustering (LkPPC) uses the combination of hyperplane and points as the cluster center to localize the hyperplane. However, the l2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \u...

Linear discriminant analysis (LDA) may yield an inexact solution by transforming a trace ratio problem into a corresponding ratio trace problem. Most recently, optimal dimensionality LDA (ODLDA) and trace ratio LDA (TRLDA) have been developed to overcome this problem. As one of the greatest contributions, the two methods design efficient iterative...

The effective combination of hyperspectral image (HSI) and light detection and ranging (LiDAR) data can be used for land cover classification. Recently, deep-learning-based classification methods, especially those using transformer networks, have achieved remarkable success. However, deep learning classification methods for multisource data still e...

Smart satellites and unmanned aerial vehicles (UAVs) are typically equipped with visible light and infrared (IR) spectrum sensors. However, achieving real-time object detection utilizing these multimodal data on such resource-limited devices is a challenging task. This paper proposes HyperYOLO, a real-time lightweight object detection framework for...

General-purpose foundation models have led to recent breakthroughs in artificial intelligence. In remote sensing, self-supervised learning (SSL) and Masked Image Modeling (MIM) have been adopted to build foundation models. However, these models primarily learn low-level features and require annotated data for fine-tuning. Moreover, they are inappli...

The spatial resolution of hyperspectral images (HSI) is usually limited due to internal imaging mechanisms. To obtain imagery with high spectral and high spatial resolutions, which is essential for subsequent HSI processing tasks, a cost-effective approach is to fuse HSI with multispectral images (MSI). One highly effective fusion method is the con...

Biomass productivity is of great significance for the evaluation of forest quality, which is important for the improvement of forest management. We propose the computational methods of biomass potential productivity (BPP) and biomass realistic productivity (BRP), both of which provide reliable practical guides for predicting forest growth under mul...

Amidst the compounded challenges posed by global climate change and urbanization on forest ecosystems, the integration of urbanization control measures within a climate-focused framework may offer an avenue for breakthroughs. This study delves into the impact of climate, specifically hydrothermal conditions, on the complex interplay between urbaniz...

Interest object (IO) extraction, or called region of interest (ROI) selection, is a fundamental task in remote sensing (RS), computer vision, and machine learning. Due to the non-rigidity, e.g., shapelessness and color-uncertainty, of interest objects like fires, smokes, clouds, or top-view tree canopies in a RS image, an unideal results usually oc...

This study presents auxiliary support techniques for tree selection strategies based on the spatial structure indices and three competition indices in secondary forests, and discusses the importance of tree competition in forest management. The spatial structure parameter in the structured management is used as a quantitative index—the uniform angl...

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and...

Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) are two ways to obtain forest three-dimensional (3D) spatial information. Due to canopy occlusion and the features of different scanning methods, some of the forest point clouds acquired by a single scanning platform may be missing, resulting in an inaccurate estimation of forest st...

In recent years, the development of instance segmentation has garnered significant attention in a wide range of applications. However, the training of a fully-supervised instance segmentation model requires costly both instance-level and pixel-level annotations. In contrast, weakly-supervised instance segmentation methods (i.e., with image-level cl...

Research on the inversion of forest aboveground biomass based on airborne light detection and ranging (LiDAR) data focuses on finding the relationship between the two, such as established linear or nonlinear models. However, these models may have poorer estimation accuracy for tree-components biomass and cannot guarantee the additivity of each comp...

Aboveground biomass (AGB) of shrub communities in the desert is a basic quantitative characteristic of the desert ecosystem and an important index to measure ecosystem productivity and monitor desertification. An accurate and efficient method of predicting the AGB of a shrub community is essential for studying the spatial patterns and ecological fu...

Drill feed speed significantly affects the measurement accuracy and efficiency of the micro drill resistance instrument. Generally, different speeds are set according to the density of the wood to be drilled. It is necessary to convert the resistance data measured at different drill feed speeds into resistance data at a uniform speed to properly an...

Drill feed speed significantly affects the measurement accuracy and efficiency of the micro drill resistance instrument. Generally, different speeds are set according to the density of the wood to be drilled. It is necessary to convert the resistance data measured at different drill feed speeds into resistance data at a uniform speed to properly an...

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. A number of hot issues can be investigated in desert ecosystems , including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence in...

Despite the remarkable progress made by the salient object detection of natural sensing images (NSI-SOD), the complex background and scale diversity issues of remote sensing images (RSIs) still pose a substantial obstacle. In this study, we build an end-to-end channel-enhanced remodeling-based network (CRNet) for optical RSIs (ORSIs) to highlight s...

Video moment retrieval (VMR) aims to localize the target moment in an untrimmed video according to the given nature language query. The existing algorithms typically rely on clean annotations to train their models. However, making annotations by human labors may introduce much noise. Thus, the video moment retrieval models will not be well trained...

Natural forests have the most complex structure and richest biodiversity among terrestrial ecosystems and are essential for maintaining the carbon balance and stability of the biosphere. Aboveground biomass (AGB) is a primary indicator used to evaluate forests and can directly measure forest growth and the quality of natural forests. Accurate and r...

Proximal support vector machine via generalized eigenvalues (GEPSVM) is one of the most successful methods for classification problems. However, GEPSVM is vulnerable to outliers since it learns classifiers based on the squared L2-norm distance without a specific strategy to deal with the outliers. Motivated by existing studies that improve the robu...

Background Fast and accurate forest aboveground biomass (AGB) estimation and mapping is the basic work of forest management and ecosystem dynamic investigation, which is of great significance to evaluate forest quality, resource assessment, and carbon cycle and management. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), as one of the lat...

Semi-supervised multi-view learning has been an important research topic due to its capability to exploit complementary information from unlabeled multi-view data. This work proposes MMatch, a new semi-supervised discriminative representation learning method for multi-view classification. Unlike existing multi-view representation learning methods t...

Fractional vegetation cover (FVC) is an important indicator of ecosystem changes. Both satellite remote sensing and ground measurements are common methods for estimating FVC. However, desert vegetation grows sparsely and scantly and spreads widely in desert regions, making it challenging to accurately estimate its vegetation cover using satellite d...

Robust principal component analysis (PCA) for feature extraction, which takes various robust norms as the distance metric, has been shown to be valid in data reconstruction and recognition tasks. However, some existing approaches do not achieve satisfactory performance and robustness owing to the imperfection of norms used for measuring the distanc...

region) were used as fixed effects variables. Tree morality variations caused by forest blocks were accounted for using forest blocks as a random effect in selected models. Results showed that tree mortality significantly positively correlated with stand basal area and dominant height, but negatively correlated with stand mean diameter. Incorporati...

Object detection in aerial images is a fundamental research topic in the domain of geoscience and remote sensing. However, advanced progresses on this topic are mainly focused on the designment of backbone networks or header networks, but surprisingly ignored the neck ones. In this letter, we first analyse the importance of the neck network in obje...

Accurate and real-time prediction of short-term traffic flow plays an increasingly vital role in the successful deployment of Intelligent Transportation Systems. Although existing studies have been done for traffic flow prediction problem, their efficacy relies heavily on traffic data. However, collected traffic data are usually affected by various...

Knowledge on the potential suitability of tree species to the site is very important for forest management planning. Natural forest distribution provides a good reference for afforestation and forest restoration. In this study, we developed species distribution model (SDM) for 16 major tree species with 2,825 permanent sample plots with natural ori...

Accurate and real-time prediction of short-term traffic states is a crucial research topic in modern intelligent transportation systems. However, effectively modeling traffic state predictions is difficult due to the complicated characteristics of stochastic and dynamic traffic processes. In addition, collected traffic data are typically influenced...

Distance Metric Learning for Large Margin Nearest Neighbor (LMNN), as a classic distance metric learning (DML) method, has attracted much attention among researchers. However, it, like most of the existing DML methods, cannot be guaranteed to achieve independent and shared feature subspaces from multiple sources or different feature subsets, such t...

Clothing parsing has made tremendous progress in the domain of computer vision recently. Most state-of-the-art methods are based on the encoder-decoder architecture. However, the existing methods mainly neglect problems of feature uncalibration within blocks and semantics dilution between blocks. In this work, we propose an unabridged adjacent modu...

Oil tea (Camellia oleifera) is one of the world’s major woody edible oil plants and is vital in providing food and raw materials and ensuring water conservation. The yield of oil tea can directly reflect the growth condition of oil tea forests, and rapid and accurate yield measurement is directly beneficial to efficient oil tea forest management. L...

Individual trees are characterized by various sizes and forms, such as diameter at breast height, total height (H), height to crown base (HCB), crown length (CL), crown width, and crown and stem forms. Tree characteristics are strongly related to each other, and studying their relationships is very important. The knowledge of the compatibility and...

Using unmanned aerial vehicles (UAV) as platforms for light detection and ranging (LiDAR) sensors offers the efficient operation and advantages of active remote sensing; hence, UAV-LiDAR plays an important role in forest resource investigations. However, high-precision individual tree segmentation, in which the most appropriate individual tree segm...

Since remote sensing images of post-fire vegetation are characterized by high resolution, multiple interferences, and high similarities between the background and the target area, it is difficult for existing methods to detect and segment the burned area in these images with sufficient speed and accuracy. In this article, we apply salient object de...

Zero-Shot Learning (ZSL) aims to employ seen images and their related semantics to identify unseen images through knowledge transfer. Among past numerous methods, the generative methods are more prominent and achieve better results than other methods. However, we find the input for generating samples is too monotonous, there are only semantics of e...

Tree height is a basic input variable in various forest models, such as growth and yield models, biomass models, and carbon budget models, which serve as very important tools for the informed decision-making in forestry. The height-diameter model is the most important component of the growth and yield models and forest simulators. We developed the...

The survival rate of seedlings is a decisive factor of afforestation assessment. Generally, ground checking is more accurate than any other methods. However, the survival rate of seedlings can be higher in the growing season, and this can be estimated in a larger area at a relatively lower cost by extracting the tree crown from the unmanned aerial...

Tropical forest degradation makes a major contribution to greenhouse gas emission. Crown width (CW) is one of the important predictors in forest growth and yield models that provide basic data for assessment of forest degradation. Precise method of estimating tree crown for two tropical tree species (Dacrydium pierrei Hickel and Podocarpus imbricat...

Korean larch (Larix olgensis), Korean pine (Pinus koraiensis), and Mongolian pine (Pinus sylvestris) are important coniferous species in the northeastern area of the P.R. China; hence, accurate biomass estimates of these species are meaningful for evaluating forest health and calculating carbon storage. Based on the tree variables of diameter at br...

Multiview learning (MVL), which enhances the learners' performance by coordinating complementarity and consistency among different views, has attracted much attention. The multiview generalized eigenvalue proximal support vector machine (MvGSVM) is a recently proposed effective binary classification method, which introduces the concept of MVL into...

Forest mortality is an important variable commonly included as one of the predictors in the growth and yield models that are the fundamental decision-making tools in forest management. The existing forest mortality models for Larch (Larix gmelinii var. principis-rupprechtii) forest, which plays key roles in maintaining forest ecosystem functions an...

Forest mortality is an important variable commonly included as one of the predictors in the growth and yield models that are the fundamental decision-making tools in forest management. The existing forest mortality models for Larch (Larix gmelinii var. principis-rupprechtii) forest, which plays key roles in maintaining forest ecosystem functions an...

Desert vegetation is an important part of arid and semi-arid areas, which plays an important role in preventing wind and fixing sand, conserving water and soil, maintaining the balanced ecosystem. Therefore, mapping the vegetation accurately is necessary to conserve rare desert plants in the fragile ecosystems that are easily damaged and slow to re...

Tree mortality models play an important role in predicting tree growth and yield, but existing mortality models for Larix gmelinii subsp. principis-rupprechtii, an important species used for regeneration and afforestation in northern China, have overlooked potential regional influences on tree mortality. This study used data acquired from 102 tempo...

The self-attention mechanism has been empirically shown its effectiveness in a wide range of computer vision applications. However, it is usually criticized for the expensive computation cost. Although some revised methods are proposed in the recent past, they are not maturely applicable to remote sensing scene (RSS) images. To address this problem...

Recently, there are many works on discriminant analysis, which promote the robustness of models against outliers by using L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> - or L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2,1</sub> -norm as th...

Height to crown base (hcb) is an important tree-level characteristic used for determination of crown size and for prediction of the initiation and propagation potential of crown fires. Crown size variables are often used as input variables for forest growth and yield models. In this study, a nonlinear mixed-effects hcb model was developed using mea...

Dominant trees compose the upper story of forest canopies, and are one of the key factors that affect the light redistribution for forest ecosystem. UAV lidar and photogrammetry can be used to measure spatial variation of upper crowns of dominant trees with details. How about the differences of tree crowns using lidar and photogrammetry with very d...

Multiview Generalized Eigenvalue Proximal Support Vector Machines (MvGSVMs) is an effective multi-view classification algorithm, which effectively combines multi-view learning and classification. Then it was found that in the classification learning task, the classifier combined with multi-view learning has a better classification effect than consi...

Forest canopy height is one of the most important spatial characteristics for forest resource inventories and forest ecosystem modeling. Light detection and ranging (LiDAR) can be used to accurately detect canopy surface and terrain information from the backscattering signals of laser pulses, while photogrammetry tends to accurately depict the cano...

Forest degradation has been considered as one of the main causes of climate change in recent years. The knowledge of estimating degraded forest areas without the application of remote sensing tools can be useful in finding solutions to resolve degradation problems through appropriate restoration methods. Using the existing knowledge through literat...

The forest growth and yield models, which are used as important decision-support tools in forest management, are commonly based on the individual tree characteristics, such as diameter at breast height (DBH), crown ratio, and height to crown base (HCB). Taking direct measurements for DBH and HCB through the ground-based methods is cumbersome and co...

Discriminative Feature Selection (DFS) is an algorithm, proposed recently for effective feature selection by considering both joint linear discriminant analysis and row sparsity regularization. However, this method is not robust enough to protect the data from outliers, because it utilizes the squared L2-norm distance metric. To overcome this probl...