What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Artificial intelligence
His main research concerns Remote sensing, Hyperspectral imaging, Land cover, Leaf area index and Vegetation.
In general Remote sensing, his work in Radiometer is often linked to Imaging spectrometer linking many areas of study.
His work deals with themes such as In situ, Abundance, Weed, Multivariate statistics and Principal component analysis, which intersect with Hyperspectral imaging.
His Land cover research incorporates themes from Subpixel rendering, Downscaling and Multi resolution.
He interconnects Atmospheric correction, Linear regression and Radiance in the investigation of issues within Leaf area index.
He has included themes like Analytical chemistry and Water content in his Vegetation study.
His most cited work include:
- A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species (249 citations)
- Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data (245 citations)
- Land-use/land-cover change detection using improved change-vector analysis (208 citations)
What are the main themes of his work throughout his whole career to date?
Ruiliang Pu mainly focuses on Remote sensing, Hyperspectral imaging, Vegetation, Satellite imagery and Leaf area index.
His Remote sensing research is multidisciplinary, incorporating perspectives in Land cover, Pixel and Normalized Difference Vegetation Index.
The study incorporates disciplines such as Impervious surface, VNIR, Radiometer and Aster in addition to Land cover.
His Hyperspectral imaging research integrates issues from In situ, Multivariate statistics, Linear discriminant analysis and Principal component analysis.
His research investigates the link between Vegetation and topics such as Cartography that cross with problems in Random forest.
Ruiliang Pu combines subjects such as Crown closure, Atmospheric correction and Linear regression with his study of Leaf area index.
He most often published in these fields:
- Remote sensing (62.91%)
- Hyperspectral imaging (30.46%)
- Vegetation (18.54%)
What were the highlights of his more recent work (between 2017-2021)?
- Physical geography (7.28%)
- Remote sensing (10.60%)
- Remote sensing (62.91%)
In recent papers he was focusing on the following fields of study:
Ruiliang Pu mainly investigates Physical geography, Remote sensing, Remote sensing, Satellite imagery and Random forest.
Ruiliang Pu has researched Physical geography in several fields, including Urban heat island, Thematic Mapper and Land use.
His study in Remote sensing is interdisciplinary in nature, drawing from both Feature extraction, Shallow lake and Underwater.
His specific area of interest is Remote sensing, where Ruiliang Pu studies Hyperspectral imaging.
His research in Satellite imagery intersects with topics in Cartography, Urban forest and Tree canopy.
His Random forest study integrates concerns from other disciplines, such as Forestry, Vegetation and Robinia.
Between 2017 and 2021, his most popular works were:
- Monitoring Plant Diseases and Pests through Remote Sensing Technology: A Review (43 citations)
- Assessing the potential of multi-seasonal high resolution Pléiades satellite imagery for mapping urban tree species. (33 citations)
- Spatiotemporal pattern of urban forest leaf area index in response to rapid urbanization and urban greening (18 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Artificial intelligence
His primary scientific interests are in Land use, Ecosystem, Physical geography, Urbanization and Remote sensing.
His work carried out in the field of Ecosystem brings together such families of science as Drainage basin, Land resources, Resource and Spatial variability.
His Urbanization research is multidisciplinary, relying on both Ecosystem services, Greening, Urban greening, Leaf area index and Environmental monitoring.
His Remote sensing research incorporates themes from Synthetic aperture radar, Relation and Light detection.
His Automation investigation overlaps with Lidar and Remote sensing.
His study brings together the fields of Seawater and Remote sensing.
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