D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Environmental Sciences D-index 36 Citations 5,377 95 World Ranking 5356 National Ranking 381

Overview

What is he best known for?

The fields of study he is best known for:

  • Ecology
  • Ecosystem
  • Climate change

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.

His most cited work include:

  • An underestimated role of precipitation frequency in regulating summer soil moisture (408 citations)
  • Estimating chlorophyll content from hyperspectral vegetation indices : Modeling and validation (388 citations)
  • Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices (124 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Remote sensing (56.36%)
  • Phenology (41.82%)
  • Climate change (43.64%)

What were the highlights of his more recent work (between 2017-2021)?

  • Phenology (41.82%)
  • Climate change (43.64%)
  • Atmospheric sciences (39.09%)

In recent papers he was focusing on the following fields of study:

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.

Between 2017 and 2021, his most popular works were:

  • Increased atmospheric vapor pressure deficit reduces global vegetation growth. (111 citations)
  • Contrasting responses of autumn-leaf senescence to daytime and night-time warming (50 citations)
  • Snow cover phenology affects alpine vegetation growth dynamics on the Tibetan Plateau: Satellite observed evidence, impacts of different biomes, and climate drivers (31 citations)

In his most recent research, the most cited papers focused on:

  • Ecology
  • Ecosystem
  • Climate change

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Estimating chlorophyll content from hyperspectral vegetation indices : Modeling and validation

Chaoyang Wu;Zheng Niu;Quan Tang;Wenjiang Huang.
Agricultural and Forest Meteorology (2008)

678 Citations

An underestimated role of precipitation frequency in regulating summer soil moisture

Chaoyang Wu;Jing M. Chen;Jukka Pumpanen;Alessandro Cescatti.
Environmental Research Letters (2012)

428 Citations

Increased atmospheric vapor pressure deficit reduces global vegetation growth

Wenping Yuan;Yi Zheng;Shilong Piao;Philippe Ciais.
Science Advances (2019)

408 Citations

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)

197 Citations

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)

187 Citations

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)

164 Citations

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)

146 Citations

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)

136 Citations

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)

136 Citations

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)

130 Citations

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