Leveraging Google Earth Engine for Drought Assessment using Global Soil Moisture Data [0.03%]
基于全球土壤水分数据的干旱评估中谷歌地球引擎的应用
Nazmus Sazib,Iliana Mladenova,John Bolten
Nazmus Sazib
Soil moisture is considered a key variable to assess crop and drought conditions. However, readily available soil moisture datasets developed for monitoring agricultural drought conditions are uncommon. The aim of this work is to examine tw...
First-Order Estimates of Coastal Bathymetry in Ilulissat and Naajarsuit Fjords, Greenland, from Remotely Sensed Iceberg Observations [0.03%]
基于遥感冰山观测的格陵兰伊卢利萨特和纳贾尔斯密特峡湾的第一秩序海岸地形估算
Jessica Scheick,Ellyn M Enderlin,Emily E Miller et al.
Jessica Scheick et al.
Warm water masses circulating at depth off the coast of Greenland play an important role in controlling rates of mass loss from the Greenland Ice Sheet through feedbacks associated with the melting of marine glacier termini. The ability of ...
Maximizing the Information Content of Ill-Posed Space-Based Measurements Using Deterministic Inverse Method [0.03%]
基于确定性反演法的最大信息量空间观测逆问题研究
Prabhat K Koner,Prasanjit Dash
Prabhat K Koner
For several decades, operational retrievals from spaceborne hyperspectral infrared sounders have been dominated by stochastic approaches where many ambiguities are pervasive. One major drawback of such methods is their reliance on treating ...
Weidong Yang,Alexander Marshak,Tamás Várnai et al.
Weidong Yang et al.
NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) satellite observes the entire sunlit Earth every 65 to 110 min from the Sun-Earth Lagrangian L1 point. This paper presents initial EPIC ...
Evaluation of the Uncertainty in Satellite-Based Crop State Variable Retrievals Due to Site and Growth Stage Specific Factors and Their Potential in Coupling with Crop Growth Models [0.03%]
基于卫星的作物状态变量反演结果因地点和生育期不同引起的不确定性评估及其在农学过程模型中的应用潜景
Nathaniel Levitan,Yanghui Kang,Mutlu Özdoğan et al.
Nathaniel Levitan et al.
Coupling crop growth models and remote sensing provides the potential to improve our understanding of the genotype x environment x management (G × E × M) variability of crop growth on a global scale. Unfortunately, the uncertainty in the ...
Bryan N Vu,Odón Sánchez,Jianzhao Bi et al.
Bryan N Vu et al.
It is well recognized that exposure to fine particulate matter (PM2.5) affects health adversely, yet few studies from South America have documented such associations due to the sparsity of PM2.5 measurements. Lima's topography and aging veh...
A method of retrieving BRDF from surface reflected radiance using decoupling of atmospheric radiative transfer and surface reflection [0.03%]
一种基于大气辐射传输与地表反射解耦的双向反射率分布函数反演方法研究
Alexander Radkevich
Alexander Radkevich
BRDF defines anisotropy of the surface reflection. It is required to specify the boundary condition for radiative transfer (RT) modeling used in aerosol retrievals, cloud retrievals, atmospheric modeling and other applications. Ground based...
RAVAN: CubeSat Demonstration for Multi-Point Earth Radiation Budget Measurements [0.03%]
辐射预算观测的立方星实验(RAVAN)
William H Swartz,Steven R Lorentz,Stergios J Papadakis et al.
William H Swartz et al.
The Radiometer Assessment using Vertically Aligned Nanotubes (RAVAN) 3U CubeSat mission is a pathfinder to demonstrate technologies for the measurement of Earth's radiation budget, the quantification of which is critical for predicting the ...
Radiative Transfer Modeling of Phytoplankton Fluorescence Quenching Processes [0.03%]
叶绿素a荧光淬灭过程的辐射传输模式研究进展
Peng-Wang Zhai,Emmanuel Boss,Bryan Franz et al.
Peng-Wang Zhai et al.
We report the first radiative transfer model that is able to simulate phytoplankton fluorescence with both photochemical and non-photochemical quenching included. The fluorescence source term in the inelastic radiative transfer equation is ...
Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA [0.03%]
基于机器学习的卫星气溶胶光学厚度遥感反演及其在美国东北地区PM2.5浓度估算中的应用研究
Allan C Just,Margherita M De Carli,Alexandra Shtein et al.
Allan C Just et al.
Satellite-derived estimates of aerosol optical depth (AOD) are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systemat...