Yanjun Su

Institute of Botany CAS · State Key Laboratory of Vegetation and Environmental Change

The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is one of the most complete and frequently used global-scale DEM products in various applications. However, previous studies have shown that the SRTM DEM is systematically higher than the actual land surface in vegetated mountain areas. The objective of this study is to propo...

Digital elevation models (DEMs) are essential to various applications in topography, geomorphology, hydrology, and ecology. The Shuttle Radar Topographic Mission (SRTM) DEM data set is one of the most complete and most widely used DEM data sets; it provides accurate information on elevations over bare land areas. However, the accuracy of SRTM data...

Accurate vegetation mapping is critical for natural resources management, ecological analysis, and hydrological modeling, among other tasks. Remotely sensed multispectral and hyperspectral imageries have proved to be valuable inputs to the vegetation mapping process, but they can provide limited vegetation structure characteristics, which are criti...

Treatments to reduce forest fuels are often performed in forests to enhance forest health, regulate stand density, and reduce the risk of wildfires. Although commonly employed, there are concerns that these forest fuel treatments (FTs) may have negative impacts on certain wildlife species. Often FTs are planned across large landscapes, but the actu...

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemica...

Guo QH (2022) The outlook and system construction for monitoring Essential Biodiversity Variables based on remote sensing: The case of China. ABSTRACT Background: Maintaining biodiversity is crucial to human beings. In recent years, the concept of Essential Biodiversity Variables (EBVs) has provided new insights into large-scale and long-time biodi...

Satellite radar backscatter contains unique information on land surface moisture, vegetation features, and surface roughness and has thus been used in a range of Earth science disciplines. However, there is no single global radar data set that has a relatively long wavelength and a decades-long time span. We here provide the first long-term (since...

Canopy height (CH) is an important trait for crop breeding and production. The rapid development of 3D sensing technologies shed new light on high-throughput height measurement. However, a systematic comparison of the accuracy and heritability of different 3D sensing technologies is seriously lacking. Moreover, it is questionable whether the field-...

Understanding how plants adapt to spatially heterogeneous phosphorus (P) supply is important to elucidate the effect of environmental changes on ecosystem productivity. Plant P supply is concurrently controlled by plant internal conservation and external acquisition. However, it's unclear how climate, soil, and microbes influence the contributions...

Forest canopy structural complexity (CSC) describes the three-dimensional (3D) arrangement of canopy elements, and has become an emergent forest attribute mediating forest ecosystem functioning along with species diversity. Light detection and ranging (lidar), especially the emerging near-surface lidar platforms (e.g., terrestrial laser scanning/TL...

Human-scale greenery has been heavily featured in the development of planning-related theories and research. Daily exposure to street greenery is proportionately greater than exposure to parks. Several case studies have estimated the green view index (GVI), which quantifies daily exposure to street-side greenery, at the city-scale. However, the str...

Grassland is one of the largest terrestrial biomes, providing critical ecosystem services such as food production, biodiversity conservation, and climate change mitigation. Global climate change and land-use intensification have been causing grassland degradation and desertification worldwide. As one of the primary medium for ecosystem energy flow...

Forest structural complexity can mediate the light and water distribution within forest canopies, and has a direct impact on forest biodiversity and carbon storage capability. It is believed that increases in forest structural complexity can enhance tree species diversity and forest productivity, but inconsistent relationships among them have been...

Grasslands are one of the largest coupled human-nature terrestrial ecosystems on Earth, and severe anthropogenic-induced grassland ecosystem function declines have been reported recently. Understanding factors influencing grassland ecosystem functions is critical for making sustainable management policies. Canopy structure is an important factor in...

Satellite radar backscatter contains unique information on land surface moisture, vegetation features, and surface roughness, and can be acquired in all weather conditions, thus has been used in a range of earth science disciplines. However, there is no single global radar data set that spans more than two decades. This has limited the use of radar...

The three-dimensional (3D) structure of forests has long been recognized to have profound effects on forest ecosystems. However, the use of spectral and radar remotely sensed data for forest structure quantification is insensitive to changes in forest vertical structure. LiDAR has emerged as a robust means to measure forest structures. Numerous stu...

Vegetation community complexity is a critical factor influencing terrestrial ecosystem stability. China, the country leading the world in vegetation greening resulting from human activities, has experienced dramatic changes in vegetation community composition during the past 30 years. However, how China's vegetation community complexity varies spat...

Accurate, efficient, and timely yield estimation is critical for crop variety breeding and management optimization. However, the contributions of proximal sensing data characteristics (spectral, temporal, and spatial) to yield estimation have not been systematically evaluated. We collected long-term, hyper-temporal, and large-volume light detection...

Accurate estimates of forest aboveground biomass (AGB) are essential for global carbon cycle studies and have widely relied on approaches using spectral and structural information of forest canopies extracted from various remote sensing datasets. However, combining the advantages of active and passive data sources to improve estimation accuracy rem...

Mangroves are essential coastal wetland vegetation and their extent and leaf area index (LAI) have been mapped using remotely sensed Earth Observation images. However, the physics-based relationship between biophysical properties of mangroves, tidal height, and their spectral values remains underexplored. In order to quantitatively evaluate the imp...

Regional landslide identification is important for the risk management of landslide hazards. The traditional methods of regional landslide identification were mainly conducted by a human being. In previous studies, automatic landslide recognition mainly focused on new landslides distinct from the environment induced by rainfall or earthquake, using...

Spatially continuous estimates of forest canopy height at national to global scales are critical for quantifying forest carbon storage, understanding forest ecosystem processes, and developing forest management and restoration policies to mitigate global climate change. Spaceborne light detection and ranging (lidar) platforms, especially the Global...

Accurate quantification of grassland structural and functional traits is the foundation for grassland management and restoration. Light detection and ranging (lidar), especially the unmanned aerial vehicle (UAV) lidar, has been recognized as an accurate and effective technique for local to regional-scale vegetation structural and functional traits...

Street trees are important components of an urban green space and understanding and measuring their ecological and cultural services is crucial for assessing the quality of streets and managing urban environments. Currently, most studies mainly focus on evaluating the ecological services of street trees by measuring the amount of greenness, but how...

Canopy structural complexity is a critical emergent forest attribute, and light detection and ranging (lidar)-based fractal dimension has been recognized as its powerful measure at the individual tree level. However, the current lidar-based estimation method is highly sensitive to data characteristics, and its scalability from individual trees to f...

High-throughput maize phenotyping at both organ and plant levels plays a key role in molecular breeding for increasing crop yields. Although the rapid development of light detection and ranging (LiDAR) provides a new way to characterize three-dimensional (3D) plant structure, there is a need to develop robust algorithms for extracting 3D phenotypic...

Positive relationships between structural diversity and forest productivity have been documented in controlled experiments and early secondary forests, however, negative relationships have also been observed in late successional forests. The mechanisms causing observed relationships between structural diversity and productivity are not well‐establi...

Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment. Terrestrial laser scanning (TLS) is a well-suited tool to study structural rhythm under field conditions. Recent studies have used TLS to describe the structural rhythm of trees, but no consistent patterns have been drawn....

In recent decades, a substantial increase in electricity demand has put pressure on powerline systems to ensure an uninterrupted power supply. In order to prevent power failures, timely and thorough powerline inspections are needed to detect possible anomalies in advance. In the past few years, the emerging unmanned aerial vehicle (UAV)-mounted sen...

Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity ( V c,max ), an important trait for modelling photosynthesis, can be inferred from other easier‐to‐measure traits. However, whether trait– V c,max relationships are robust across different fores...

In temperate forests, autumn leaf phenology signals the end of leaf growing season and shows large variability across tree-crowns, which importantly mediates photosynthetic seasonality, hydrological regulation, and nutrient cycling of forest ecosystems. However, critical challenges remain with the monitoring of autumn leaf phenology at the tree-cro...

Plant phenomics is a new avenue for linking plant genomics and environmental studies, thereby improving plant breeding and management. Remote sensing techniques have improved high-throughput plant phenotyping. However, the accuracy, efficiency, and applicability of three-dimensional (3D) phenotyping are still challenging, especially in field enviro...

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them f...

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 of 3D ecological observations. Developments in lidar hardware systems and data processing algorithms have greatly improved the accessibility and ease of use of lidar obser...

Vegetation maps serve as the key source information for ecological studies, biodiversity conservation, and vegetation management and restoration. The latest version of the Vegetation Map of China (1:1000000) was generated in the 1980s. Since then, the vegetation distribution pattern of China has changed dramatically during these 40 years. Classific...

Airborne laser scanning (ALS) data is one of the most commonly used data for terrain products generation. Filtering ground points is a prerequisite step for ALS data processing. Traditional filtering methods mainly use handcrafted features or predefined classification rules with pre-processing/post-processing operations to filter ground points iter...

Forest inventory holds an essential role in forest management and research, but the existing field inventory methods are highly time-consuming and labor-intensive. Here, we developed a simultaneous localization and mapping-based backpack light detection and ranging (LiDAR) system with dual orthogonal laser scanners and an open-source Python package...

Terrestrial laser scanning (TLS) has been recognized as an accurate means for non-destructively deriving three-dimensional (3D) forest structural attributes. These attributes include but are not limited to tree height, diameter at breast height, and leaf area density. As such, TLS has become an increasingly important technique in forest inventory p...

Mangrove forest ecosystems are distributed at the land–sea interface in tropical and subtropical regions and play an important role in carbon cycles and biodiversity. Accurately mapping global mangrove aboveground biomass (AGB) will help us understand how mangrove ecosystems are affected by the impacts of climatic change and human activities. Light...

Background: Precision agriculture is an emerging research field that relies on monitoring and managing field variability in phenotypic traits. An important phenotypic trait is biomass, a comprehensive indicator that can reflect crop yields. However, non-destructive biomass estimation at fine levels is unknown and challenging due to the lack of acc...

生态资源是人类生存发展和自我实现的重要物质基础, 对其进行深入全面的研究和理解关系到人类社会的可持续发展. 随着观测技术的进步, 长时间、 跨尺度、 海量异构多源数据的获取能力得到了显著提升, 生态资源研究进入了数据驱动的新时代. 传统的统计学习和机器学习算法在海量数据面前存在饱和问题. 深度学习作为高维非线性复杂特征自动提取的新手段, 对海量数据具有不饱和性, 正成为学界和工业界数据处理的新引擎. 为推动深度学习在生态资源领域的应用, 文章首先介绍了深度学习的理论与生态资源研究的联系, 以及常用工具和 数据集. 其次, 通过物种识别、 作物育种和植被制图三个案例介绍了深度学习在分类识别、 检测定位、 语义分割和实例分割任务中的具体实践, 以及图神经网络在生态资源领域中典型的空间离散点数据上...

Vegetation maps are important sources of information for biodiversity conservation, ecological studies, vegetation management and restoration, and national strategic decision making. The current Vegetation Map of China (1:1000000) was generated by a team of more than 250 scientists in an effort that lasted over 20 years starting in the 1980s. Howev...

Rainfall interception (RI) by forest canopies is an important process in hydrological cycling in forest ecosystems. However, accurately predicting RI is a challenging topic. In this study, a dimensionless descriptor, canopy interception index (CII), for predicting RI was defined. The terrestrial laser scanning was used to estimate CII in four tempe...

Ecological resources are an important material foundation for the survival, development, and self-realization of human beings. In-depth and comprehensive research and understanding of ecological resources are beneficial for the sustainable development of human society. Advances in observation technology have improved the ability to acquire long-ter...

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 Nature Reserve. The former reserve is the first Chinese national nature reserve for mangroves and the latter has the most abundant mangrove species in China. However, to date th...

Crown architecture is a critical component for a tree to interact with the ambient environment and to compete with neighbors. However, little is known regarding how climate variability may shape crown architecture traits across large geographical extents and whether crown architecture traits have coordinated variations with trunk and leaf traits to...

Tree architecture, defined as the three-dimensional arrangement of tree above-ground elements, directly influences the biological and physical processes of vegetation such as photosynthesis and evapotranspiration. Accurate description of tree architecture is of central importance to understand the above biophysical processes. Terrestrial laser scan...

Aboveground biomass (AGB) is an important indicator for grassland ecosystem assessment, management and utilization. Remote sensing technologies have driven the development of grassland AGB estimation from labor-intensive to highly-efficient. However, optical image-based remote sensing methods are fraught with uncertainty issues due to the saturatio...

Separating structural components is important but also challenging for plant phenotyping and precision agriculture. Light detection and ranging (LiDAR) technology can potentially overcome these difficulties by providing high quality data. However, there are difficulties in automatically classifying and segmenting components of interest. Deep learni...

The emerging near-surface light detection and ranging (LiDAR) platforms [e.g., terrestrial, backpack, mobile, and unmanned aerial vehicle (UAV)] have shown great potential for forest inventory. However, different LiDAR platforms have limitations either in data coverage or in capturing undercanopy information. The fusion of multiplatform LiDAR data...

Spatiotemporal data fusion is a key technique for generating unified time-series images from various satellite platforms to support the mapping and monitoring of vegetation. However, the high similarity in the reflectance spectrum of different vegetation types brings an enormous challenge in the similar pixel selection procedure of spatiotemporal d...

This study investigated the effects of forest type, leaf area index (LAI), canopy cover (CC), tree density (TD), and the coefficient of variation of tree height (CVTH) on the accuracy of different individual tree segmentation methods (i.e., canopy height model, pit-free canopy height model (PFCHM), point cloud, and layer stacking seed point) with L...

Airborne light detection and ranging is an emerging measurement tool for snowpack estimation, and data are now emerging to better assess multiscale snow depth patterns. We used airborne light detection and ranging measurements from four sites in the southern Sierra Nevada to determine how snow depth varies with canopy structure and the interactions...