Chaoyang Wu mostly deals with Remote sensing, Vegetation, Normalized Difference Vegetation Index, Moderate-resolution imaging spectroradiometer and Phenology. His Remote sensing study integrates concerns from other disciplines, such as Enhanced vegetation index, Primary production and Eddy covariance. His Normalized Difference Vegetation Index study combines topics in areas such as Canopy, Chlorophyll and Meteorology.
His Phenology research is multidisciplinary, incorporating perspectives in Productivity, Ecosystem and Growing season. The study incorporates disciplines such as Climatology, Climate change, Atmospheric sciences and Precipitation in addition to Ecosystem. His Growing season research includes themes of Deciduous, Terrestrial ecosystem and Evergreen.
Chaoyang Wu mostly deals with Remote sensing, Phenology, Climate change, Vegetation and Ecosystem. The Remote sensing study combines topics in areas such as Enhanced vegetation index, Primary production, Leaf area index, Moderate-resolution imaging spectroradiometer and Normalized Difference Vegetation Index. His work deals with themes such as Advanced very-high-resolution radiometer and Vegetation Index, which intersect with Moderate-resolution imaging spectroradiometer.
His Phenology study integrates concerns from other disciplines, such as Growing season, Northern Hemisphere, Atmospheric sciences, Deciduous and Evergreen. The various areas that Chaoyang Wu examines in his Climate change study include Spring, FluxNet, Physical geography and Precipitation. His research integrates issues of Productivity and Climatology in his study of Ecosystem.
His primary areas of investigation include Phenology, Climate change, Atmospheric sciences, Ecosystem and Normalized Difference Vegetation Index. His work carried out in the field of Phenology brings together such families of science as photoperiodism, Terrestrial ecosystem, Radiative forcing and Evergreen. His study in Terrestrial ecosystem is interdisciplinary in nature, drawing from both Physical geography, Spatial heterogeneity and Vegetation.
The study incorporates disciplines such as Temperate climate, Northern Hemisphere, Spring and Precipitation in addition to Climate change. His work in Ecosystem tackles topics such as Remote sensing which are related to areas like Chlorophyll content. His Normalized Difference Vegetation Index study combines topics from a wide range of disciplines, such as Growing season and Biome.
Chaoyang Wu spends much of his time researching Phenology, Climate change, Ecosystem, Normalized Difference Vegetation Index and Ecology. His Climate change research is multidisciplinary, incorporating elements of Precipitation, Daytime, Northern Hemisphere and Biome. His biological study spans a wide range of topics, including Spatial heterogeneity, Atmospheric sciences and Advanced very-high-resolution radiometer.
In Atmospheric sciences, Chaoyang Wu works on issues like Photosynthesis, which are connected to Vegetation Index. His Vegetation Index research includes elements of Remote sensing and Chlorophyll content. As part of his studies on Normalized Difference Vegetation Index, Chaoyang Wu often connects relevant subjects like Terrestrial ecosystem.
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Estimating chlorophyll content from hyperspectral vegetation indices : Modeling and validation
Chaoyang Wu;Zheng Niu;Quan Tang;Wenjiang Huang.
Agricultural and Forest Meteorology (2008)
An underestimated role of precipitation frequency in regulating summer soil moisture
Chaoyang Wu;Jing M. Chen;Jukka Pumpanen;Alessandro Cescatti.
Environmental Research Letters (2012)
Increased atmospheric vapor pressure deficit reduces global vegetation growth
Wenping Yuan;Yi Zheng;Shilong Piao;Philippe Ciais.
Science Advances (2019)
Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices
Chaoyang Wu;Zheng Niu;Quan Tang;Wenjiang Huang;Wenjiang Huang.
Agricultural and Forest Meteorology (2009)
Use of MODIS and Landsat time series data to generate high-resolution temporal synthetic Landsat data using a spatial and temporal reflectance fusion model
Mingquan Wu;Zheng Niu;Changyao Wang;Chaoyang Wu;Chaoyang Wu.
Journal of Applied Remote Sensing (2012)
Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest
Chaoyang Wu;J. William Munger;Zheng Niu;Da Kuang.
Remote Sensing of Environment (2010)
Land surface phenology from optical satellite measurement and CO2 eddy covariance technique
Alemu Gonsamo;Jing M. Chen;David T. Price;Werner A. Kurz.
Journal of Geophysical Research (2012)
Land surface phenology derived from normalized difference vegetation index (NDVI) at global FLUXNET sites
Chaoyang Wu;Dailiang Peng;Kamel Soudani;Lukas Siebicke.
Agricultural and Forest Meteorology (2017)
Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn
Chaoyang Wu;Jing M. Chen;T. Andrew Black;David T. Price.
Global Ecology and Biogeography (2013)
Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration
Chaoyang Wu;Chaoyang Wu;Jing M. Chen;Ni Huang.
Remote Sensing of Environment (2011)
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