A5036064800- Remote Sensing in Agriculture
- Leaf Properties and Growth Measurement
- Land Use and Ecosystem Services
- Plant Water Relations and Carbon Dynamics
- Remote Sensing and LiDAR Applications
- Remote Sensing and Land Use
- Water Quality Monitoring and Analysis
- Urban Heat Island Mitigation
- Species Distribution and Climate Change
- Forest Management and Policy
- Environmental Changes in China
- Conservation, Biodiversity, and Resource Management
- Spectroscopy and Chemometric Analyses
- Marine and coastal ecosystems
- Smart Agriculture and AI
- Remote-Sensing Image Classification
- Impact of Light on Environment and Health
- Atmospheric and Environmental Gas Dynamics
- Fire effects on ecosystems
- Plant responses to elevated CO2
- Forest ecology and management
- Oil Spill Detection and Mitigation
- Rangeland Management and Livestock Ecology
- Oceanographic and Atmospheric Processes
- Regional Development and Environment
Ministry of Ecology and Environment
2024-2025
Nanjing Institute of Environmental Sciences
2024-2025
Nanjing University
2015-2024
State Key Laboratory of Remote Sensing Science
2020
Beijing Normal University
2020
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
2015-2017
Wuhan University
2010
Deforestation-induced forest loss largely affects both the carbon budget and ecosystem services. Subsequent regrowth plays a crucial role in restoration replenishment. However, there is an absence of comprehensive datasets explicitly delineating following deforestation. Here we employed multiple remotely sensed to generate first dataset capturing structural regrowth, including height, aboveground biomass (AGB), leaf area index (LAI), fraction photosynthetically active radiation (FPAR),...
With the rapid advancement of unmanned aerial vehicles (UAVs) in recent years, UAV-based remote sensing has emerged as a highly efficient and practical tool for environmental monitoring. In vegetation sensing, UAVs equipped with hyperspectral sensors can capture detailed spectral information, enabling precise monitoring plant health retrieval physiological biochemical parameters. A critical aspect is accurate acquisition canopy reflectance. However, due to mobility variation flight altitude,...
The ratio of leaf carotenoid to chlorophyll (Car/Chl) is an indicator vegetation photosynthesis, development and responses stress. However, the correlation between Car Chl, their overlapping absorption in visible spectral domain pose a challenge for optical remote sensing ratio. This study aims investigate combinations indices (VIs) minimize influence Car-Chl correlation, thus being more sensitive variability across species sites. VIs Chl were combined into four candidates combinations,...
为了更好地了解中国定量遥感的发展态势和加强同行之间的信息交流,根据中国学者2019年发表的SCI检索论文和部分中文论文,对陆表定量遥感的核心进展进行了总结,涉及数据预处理(云及其阴影识别,大气与地形校正)、陆表辐射传输建模、不同变量的反演方法、产品生产评价与精度验证,以及相关应用等内容。陆表变量产品较多,本文概要介绍了反射率、下行太阳辐射、反照率、地表温度、长波辐射、总净辐射、荧光遥感、植被生化参数、叶面积指数、光合有效辐射比、植被覆盖度、森林高度、森林生物量、植被生产力、土壤水分、雪水当量、雪盖、蒸散发、地表与地下水量等最新进展,也一并介绍了2019年与定量遥感相关的科研项目、学术交流会与暑假培训班等内容。
Leaf reflectance is widely used to retrieve leaf chlorophyll content (Cab) and parameterize canopy radiative transfer models. Measurements of broadleaf are typically made by using integrating sphere devices, but the approach generally limited in conifer needle measurements due narrow coverage relative sample port sphere. In this study, we proposed a method measure bidirectional factor (BRF) needles hyperspectral imaging spectrometer an optical microscope. Pure pixels can be easily extracted...
Light use efficiency (LUE) models are widely used to estimate gross primary productivity (GPP), a dominant component of the terrestrial carbon cycle. Their outputs very sensitive LUE. Proper determination this parameter is prerequisite for LUE simulate GPP at regional and global scales. This study was devoted investigating ability photochemical reflectance index (PRI) track variations sub-tropical planted coniferous forest in southern China using tower-based PRI measurements over period from...
The PROSPECT model has been widely used to estimate leaf biochemical constituents, but retrieval of mass per area (LMA) in fresh leaves proved be difficult due the predominant water absorption infrared spectral region. At wavelengths where is low, both LMA and light scattering are relatively high. Therefore, uncertainty simulation at these will lead a large error estimation. In this paper, we introduce wavelength-independent factor represent first-order effect anisotropic elementary layer...
Leaf mass per area (LMA) and equivalent water thickness (EWT) are key indicators providing information on plant growth status agricultural management, their retrieval is commonly done through radiative transfer models (RTMs) such as the PROSPECT model. However, model frequently hampered by ill-posed problem a consequence of measurement uncertainties. Here, we propose wavelength selection method to improve inversion EWT LMA integrating with machine learning algorithm (Gaussian process...
Nitrogen is an essential nutrient in many terrestrial ecosystems because it affects vegetation’s primary production. Due to the variety of nitrogen-containing substances and differences their composition across species, statistical approaches are now dominant remote sensing retrieval leaf nitrogen content. Many studies remove spectral regions characterized by strong water absorptions before retrieving content, believed mask absorption features nitrogen. The objectives this study discuss...
Leaf chlorophyll content plays a vital role in plant photosynthesis. The PROSPECT model has been widely used for retrieving leaf from remote sensing data over various species. However, despite wide variations surface reflectance across different species and environmental conditions, is assumed to be the same leaves model. This work extends by taking into account variation of reflection. In modified named PROSPECT-Rsurf, an additional layer with variable refractive index bounded on N...
Leaf functional traits are key indicators of plant functions useful for inferring complex processes, including their responses to environmental changes. Vegetation indices (VIs) composed a few reflectance wavelengths hold the advantages being relatively simple and effective have been widely used within remote sensing estimate leaf traits. However, difference between from upper lower part suggests that mainly provides one-sided information, constraining its ability transmittance, on other...
Leaf carotenoids (Cxc) play a crucial role in vegetation as essential pigments responsible for capturing sunlight and protecting leaf tissues. They provide vital insights into plant physiological status serve sensitive indicators of stress. However, remote sensing Cxc at the level has been challenging due to low content weaker absorption features compared those chlorophylls visible domain. Existing indices have widely applied but often lack solid physical foundation, which limits their...
Abstract Solar‐induced chlorophyll fluorescence (SIF) provides remotely sensible signals for monitoring gross primary production (GPP). Ground‐based multiangle observations of both red and far‐red SIF above wheat maize canopies were conducted to examine angular effects on SIF. With these new measurements, we able the first time refine apply an algorithm developed normalization measurements. The improved correlation with GPP derived from eddy covariance measurements at instantaneous scale (1...
遥感综合试验对于遥感科学技术的发展起到重要作用,无论是基础研究还是遥感应用都需要试验提供支撑。从2018年开始,遥感科学国家重点实验室针对遥感自身发展和遥感面向地表圈层深化应用面临的科学问题,在滦河上游流域组织了小滦河流域复杂地表碳循环遥感综合观测试验,本文旨在介绍该试验的目标、区域、观测参数、观测方法以及对未来研究的展望,以期望为今后开展其他遥感试验及相关研究提供有益的参考和帮助。该试验采用星机地协同综合观测的方式,选择主要的在轨运行卫星数据及覆盖此流域的遥感产品作为主要数据;针对典型区域开展航空及无人机遥感试验,搭载光学传感器设备,获取典型区域水热循环、碳循环等关键参数;并同步开展地面观测试验,在典型实验区开展大气、植被和土壤关键参数的精细观测。目前已系统的开展了地面测量试验、无人机遥感试验及航空遥感试验,并同步收集了卫星遥感数据,形成了一套丰富的星—机—地配套遥感实测数据集。在试验的推动下,遥感科学国家重点实验室于2020年在试验区架设了多座综合观测塔,并配置了多种观测设备,开启了长时间序列观测任务,虚拟试验场的构建和机理生态模型的运行也在同步开展。小滦河流域复杂地表碳循环...
Comparison and validation of canopy reflectance (CR) models are two important steps to ensure their reliability. Pure forest plantations an ideal type for validating CR because simple background the low variance in crown structures which usually assumed be identical most models. A Geometric Optical Model Forest Plantations (GOFP) was compared using dataset radiation transfer model intercomparison exercise (RAMI) stands validated situ detailed optical structural data Saihanba Forestry Center,...
The accurate retrieval of forest functional and structural parameters is great significance in the scientific research ecosystem, global change, carbon nitrogen cycles. Recently, an unmanned aerial vehicle (UAV) hyperspectral imaging system provides a cost-effective way to capture imageries from any points hemisphere above canopy. However, compared with single-angle images, multiangle images provide more information about characteristics. We developed semiautomatic observation method using...
Proper determinations of light use efficiency (LUE) and absorbed photosynthetically active radiation (APAR) are essential for LUE models to simulate gross primary productivity (GPP). This study intended apply the photochemical reflectance index (PRI) track or APAR variations in a subtropical coniferous forest using tower-based PRI GPP measurements. To improve ability APAR, two-leaf approach differentiating sunlit shaded leaves was used process remote sensing flux data. However, penumbra...