His main research concerns Dry season, Ecology, Ecosystem, Phenology and Tropical ecology. Kaiyu Guan usually deals with Ecosystem and limits it to topics linked to Vegetation and Growing season, Woodland, Wet season, Physical geography and Deciduous. Kaiyu Guan combines subjects such as Tropical savanna climate, Precipitation and Amazon rainforest with his study of Tropical ecology.
The study incorporates disciplines such as Tropical and subtropical dry broadleaf forests and Tropical vegetation in addition to Tropical savanna climate. He has researched Plant litter in several fields, including Seasonality, Canopy, Evapotranspiration and Evergreen. The Canopy study combines topics in areas such as Photosynthetic capacity, Productivity, Carbon cycle and Terrestrial ecosystem.
His scientific interests lie mostly in Remote sensing, Atmospheric sciences, Vegetation, Climate change and Canopy. His biological study spans a wide range of topics, including Photosynthesis, Chlorophyll fluorescence, Photosynthetically active radiation, Eddy covariance and Spatial ecology. Kaiyu Guan has included themes like Deciduous, Ecosystem and Growing season in his Vegetation study.
His Ecosystem study incorporates themes from Dry season, Seasonality and Wet season. While the research belongs to areas of Climate change, he spends his time largely on the problem of Yield, intersecting his research to questions surrounding Crop yield. His Canopy research includes elements of Photosynthetic capacity and Phenology.
Kaiyu Guan mainly investigates Atmospheric sciences, Remote sensing, Chlorophyll fluorescence, Photosynthesis and Vegetation. His Atmospheric sciences research is multidisciplinary, relying on both Primary production, Canopy, Normalized Difference Vegetation Index and Photosynthetically active radiation. His Remote sensing study combines topics from a wide range of disciplines, such as Mean squared error, Range, Precision agriculture and Sensor fusion.
His study in Photosynthesis is interdisciplinary in nature, drawing from both Partial least squares regression and Growing season. His study ties his expertise on Crop yield together with the subject of Vegetation. His work in Crop yield addresses issues such as Field, which are connected to fields such as Yield.
The scientist’s investigation covers issues in Atmospheric sciences, Remote sensing, Enhanced vegetation index, Troposphere and Primary production. His studies in Atmospheric sciences integrate themes in fields like Dry season and Vegetation. His Vegetation research is multidisciplinary, incorporating perspectives in Ecosystem, Biogeochemical cycle and Amazon rainforest.
His study on Remote sensing also encompasses disciplines like
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.
A Drought Monitoring and Forecasting System for Sub-Sahara African Water Resources and Food Security
Justin Sheffield;Eric F. Wood;Nathaniel Chaney;Kaiyu Guan.
Bulletin of the American Meteorological Society (2014)
Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests.
Jin Wu;Loren P. Albert;Aline P. Lopes;Natalia Restrepo-Coupe;Natalia Restrepo-Coupe.
Photosynthetic seasonality of global tropical forests constrained by hydroclimate
Kaiyu Guan;Kaiyu Guan;Ming Pan;Haibin Li;Adam Wolf.
Nature Geoscience (2015)
A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach
Yaping Cai;Kaiyu Guan;Jian Peng;Shaowen Wang.
Remote Sensing of Environment (2018)
Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence
Kaiyu Guan;Joseph A. Berry;Yongguang Zhang;Joanna Joiner.
Global Change Biology (2016)
Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests
Xiangtao Xu;David Medvigy;Jennifer S. Powers;Justin M. Becknell.
New Phytologist (2016)
Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches
Yaping Cai;Kaiyu Guan;David Lobell;Andries B. Potgieter.
Agricultural and Forest Meteorology (2019)
Interactions between urban heat islands and heat waves
Lei Zhao;Michael Oppenheimer;Qing Zhu;Jane W. Baldwin.
Environmental Research Letters (2018)
Temperature impacts on the water year 2014 drought in California
Shraddhanand Shukla;Mohammad Safeeq;Mohammad Safeeq;Amir AghaKouchak;Kaiyu Guan.
Geophysical Research Letters (2015)
Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States
Yan Li;Yan Li;Kaiyu Guan;Gary D Schnitkey;Evan H Delucia.
Global Change Biology (2019)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: