What is he best known for?
The fields of study he is best known for:
His scientific interests lie mostly in Remote sensing, Leaf area index, Canopy, Vegetation and Atmospheric sciences.
His study in Remote sensing is interdisciplinary in nature, drawing from both Black spruce, Pixel, Moderate-resolution imaging spectroradiometer, Radiative transfer and Normalized Difference Vegetation Index.
His study explores the link between Leaf area index and topics such as Land cover that cross with problems in Evapotranspiration.
His Canopy study integrates concerns from other disciplines, such as Shrub, Boreal, Radiance, Spatial distribution and Taiga.
His Vegetation research is multidisciplinary, incorporating elements of Photosynthetically active radiation, Multispectral Scanner, Satellite imagery and Deciduous.
The concepts of his Atmospheric sciences study are interwoven with issues in Ecology, Growing season, Ecosystem, Carbon cycle and Boreal ecosystem.
His most cited work include:
- Defining leaf area index for non‐flat leaves (865 citations)
- Leaf area index of boreal forests: theory, techniques, and measurements (783 citations)
- Retrieving Leaf Area Index of Boreal Conifer Forests Using Landsat TM Images (617 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Remote sensing, Atmospheric sciences, Leaf area index, Vegetation and Canopy.
Jing M. Chen interconnects Bidirectional reflectance distribution function, Pixel, Land cover, Moderate-resolution imaging spectroradiometer and Normalized Difference Vegetation Index in the investigation of issues within Remote sensing.
His Atmospheric sciences research includes themes of Eddy covariance, Ecosystem, Carbon cycle, Carbon sink and Terrestrial ecosystem.
His Ecosystem research integrates issues from Productivity, Climatology and Climate change.
Jing M. Chen usually deals with Terrestrial ecosystem and limits it to topics linked to Hydrology and Soil water.
His Leaf area index research includes elements of Primary production, Black spruce, Taiga and Deciduous.
He most often published in these fields:
- Remote sensing (37.26%)
- Atmospheric sciences (36.07%)
- Leaf area index (26.84%)
What were the highlights of his more recent work (between 2016-2021)?
- Atmospheric sciences (36.07%)
- Remote sensing (37.26%)
- Terrestrial ecosystem (13.85%)
In recent papers he was focusing on the following fields of study:
Jing M. Chen focuses on Atmospheric sciences, Remote sensing, Terrestrial ecosystem, Canopy and Photosynthesis.
He has included themes like Eddy covariance, Leaf area index, Carbon cycle, Vegetation and Carbon sink in his Atmospheric sciences study.
Jing M. Chen has researched Leaf area index in several fields, including Meteorology and Ecosystem model.
His Remote sensing study combines topics in areas such as Photochemical Reflectance Index and Chlorophyll fluorescence.
His Terrestrial ecosystem course of study focuses on Northern Hemisphere and Phenology.
His biological study spans a wide range of topics, including Hydrology, Chlorophyll and Deciduous.
Between 2016 and 2021, his most popular works were:
- Leaf chlorophyll content as a proxy for leaf photosynthetic capacity (148 citations)
- Nitrogen Availability Dampens the Positive Impacts of CO2 Fertilization on Terrestrial Ecosystem Carbon and Water Cycles (70 citations)
- Angular normalization of GOME-2 Sun-induced chlorophyll fluorescence observation as a better proxy of vegetation productivity (51 citations)
In his most recent research, the most cited papers focused on:
Jing M. Chen mainly focuses on Remote sensing, Atmospheric sciences, Canopy, Leaf area index and Climate change.
His Remote sensing research incorporates themes from Chlorophyll fluorescence and Chlorophyll content.
His research in Atmospheric sciences intersects with topics in Photosynthesis, Photosynthetic capacity, Deciduous, Carbon cycle and Evapotranspiration.
The Deciduous study combines topics in areas such as Eddy covariance and Evergreen.
His studies in Canopy integrate themes in fields like Primary production and Vegetation.
The study incorporates disciplines such as Projected area, Bidirectional reflectance distribution function, Meteorology and Ecosystem model in addition to Leaf area index.
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