Qinghua Guo

Qinghua Guo
Peking University | PKU · Institute of Remote Sensing & GIS

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190
Publications
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Publications

Publications (190)
Article
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Canopy height greatly affects the biomass stock, carbon dynamics, and maintenance of biodiversity in forests. Previous research reported that the maximum forest canopy height (Hmax) at global and regional scales could be explained by variations in water or energy availability, that is, the water- or energy-related hypothesis. However, fundamental g...
Article
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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...
Article
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无人机是低空领域准确、灵活、高效获取多种类型高分辨率遥感数据的重要载体,无人机遥感技术在行业应用创新和管理部门科学决策之间构筑起信息沟通的关键桥梁。随着科技的进步、大数据时代的来临,无人机遥感系统的硬件设备、信息提取方法都取得了飞速的发展;同时其在国民经济主要行业领域的应用也面临着前所未有的机遇和挑战。论文首先介绍了无人机遥感系统的硬件研发进展,并指出轻小型、高精度、标准化与集成化是未来无人机遥感系统发展的总体趋势。其次,详细介绍了目前轻小型无人机遥感应用在农业、林草业、电力、测绘、大气探测和地质灾害等行业的应用现状,指出实现无人机多源遥感数据获取、融合、分析和提取的综合平台是未来轻小型无人机在民用领域行业应用创新的关键所在。最后,针对载荷与飞行平台的一体化集成应用、无人机组网作业、海量数据...
Article
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...
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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...
Article
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...
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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...
Article
1. 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 esta...
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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....
Article
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...
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• The receiver operating characteristic (ROC) and precision–recall (PR) plots have been widely used to evaluate the performance of species distribution models. Plotting the ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting t...
Preprint
1. The receiver operating characteristic (ROC) and precision-recall (PR) plots have been widely used to evaluate the performances of species distribution models. Plotting ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting ROC...
Preprint
Full-text available
Abstract: The receiver operating characteristic (ROC) and precision-recall (PR) plots have been widely used to evaluate the performances of species distribution models. Plotting ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plott...
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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...
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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...
Article
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...
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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...
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Imbalanced learning is a common problem in remote sensing imagery-based land-use and land-cover classifications. Imbalanced learning can lead to a reduction in classification accuracy and even the omission of the minority class. In this paper, an impartial semi-supervised learning strategy based on extreme gradient boosting (ISS-XGB) is proposed to...
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Objectives: The knowledge of regional landslides detection plays a fundamental role in the landslide risk management. However, most of that recognition was taken manually in the past, which is rather time‑ and labor‑ consuming. As the development of technologies of remote sensing and artificial intelligence, the automatic detection of landslides be...
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Space-earth integrated stereoscopic mapping promotes the progress of earth observation technologies. The method which combined remote sensing images with zenith perspectives and ground-level landscape photos with slanted viewing angles improves the efficiency and accuracy of land surveys. Recently, numerous efforts have been devoted to combining de...
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One-class classification is a common situation in remote sensing, where researchers aim to extract a single land type from remotely sensed data. Learning a classifier from labeled positive and unlabeled background data, which is the case-control sampling scenario, is efficient for one-class remote sensing classification because labeled negative dat...
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Background: Identification and characterization of new traits with sound physiological foundation is essential for crop breeding and production management. Deep learning has been widely used in image data analysis to explore spatial and temporal information on crop growth and development, thus strengthening the power of identification of physiolog...
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Microfossils, tiny fossils whose study requires the use of a microscope, have been widely applied in many fields of earth, life, and environmental sciences. The abundance and high diversity of microfossils, as well as the need for rapid identification, call for automated methods to classify microfossils. In this study, we constructed an open datase...
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Tree allometry in semi-arid forests is characterized by short height but large canopy. This pattern may be important for maintaining water-use efficiency and carbon sequestration simultaneously, but still lacks quantification. Here we use terrestrial laser scanning to quantify allometry variations of Quercus mongolica in semi-arid forests. With tre...
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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...
Article
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...
Article
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...
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A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem prima...
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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...
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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...
Preprint
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Background: Identification and characterization of new traits with a sound physiological foundation for crop breeding and management is one of the primary objectives for crop physiology. New technological advances in high throughput phenotyping have strengthened the power of physiological breeding. Methods for data mining of the big data acquired b...
Preprint
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Background : Identification and characterization of new traits with a sound physiological foundation is essential for crop breeding and management. Deep learning has been widely used in image data analysis to explore spatial and temporal information on crop growth and development, thus strengthening the power of the identification of physiological...
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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...
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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...
Article
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...
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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...
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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...
Article
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The capacity of canopy light interception is a key functional trait to distinguish the phenotypic variation over genotypes. High-throughput phenotyping canopy light interception in the field, therefore, would be of high interests for breeders to increase the efficiency of crop improvement. In this research, the Digital Plant Phenotyping Platform(D3...
Article
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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...
Article
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...
Article
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...
Article
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...
Article
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...
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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...
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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...
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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...
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Imbalanced learning is a methodological challenge in remote sensing communities, especially in complex areas where the spectral similarity exists between land covers. Obtaining high-confidence classification results for imbalanced class issues is highly important in practice. In this paper, extreme gradient boosting (XGB), a novel tree-based ensemb...
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Background Maize (Zea mays L.) is the third most consumed grain in the world and improving maize yield is of great importance of the world food security, especially under global climate change and more frequent severe droughts. Due to the limitation of phenotyping methods, most current studies only focused on the responses of phenotypes on certain...
Article
This study proposes a new method (profile area change, PAC) to quantify fire-induced forest structural changes at the individual tree and clump of trees scales using pre-and post-fire LiDAR data. The PAC measures the difference in profile area summarized from pre-and post-fire LiDAR points. We applied the PAC method to assess the effects of the 201...
Article
Filtering of airborne light detection and ranging (LiDAR) data is a challenging task in vegetated mountain areas. Environmental features and LiDAR data characteristics have significant impacts on the performance of filtering algorithms. This study aims to determine the effects of topographic and environmental features such as slope, canopy cover, e...
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Long non-coding RNAs (lncRNAs) play crucial roles in regulating gene expression, and a growing number of researchers have focused on the identification of target genes of lncRNAs. However, no online repository is available to collect the information on target genes regulated by lncRNAs. To make it convenient for researchers to know what genes are r...
Article
Accurate and high throughput extraction of crop phenotypic traits, as a crucial step of molecular breeding, is of great importance for yield increasing. However, automatic stem-leaf segmentation as a prerequisite of many precise phenotypic trait extractions is still a big challenge. Current works focus on the study of the 2-D image-based segmentati...
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Mapping mangrove extent and species is important for understanding their response to environmental changes and for observing their integrity for providing goods and services. However, accurately mapping mangrove extent and species are ongoing challenges in remote sensing. The newly-launched and freely-available Sentinel-2 (S2) sensor offers a new o...
Article
Ecological niche modeling seeks to infer the relationship between occurrences of a species and environmental covariates and has been widely applied in biodiversity studies. Light detection and ranging (LiDAR) is a new active remote sensing technology that is being increasingly used for acquisition of 3D structural information of forests. However, i...