What is she best known for?
The fields of study she is best known for:
- Ecology
- Statistics
- Artificial intelligence
Remote sensing, Vegetation, Canopy, Hyperspectral imaging and Hydrology are her primary areas of study.
She studies Endmember, a branch of Remote sensing.
Her Vegetation study incorporates themes from Shrub, Biomass, Chaparral and Wetland.
Susan L. Ustin interconnects Radiative transfer, Chlorophyll fluorescence, Leaf area index and Normalized Difference Vegetation Index in the investigation of issues within Canopy.
Her Hyperspectral imaging study combines topics in areas such as Remote sensing, Multispectral image and Reflectivity.
The various areas that she examines in her Hydrology study include Atmospheric sciences and Deciduous.
Her most cited work include:
- Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models (1000 citations)
- PROSPECT+SAIL models: A review of use for vegetation characterization (855 citations)
- Vegetation in deserts: I. A regional measure of abundance from multispectral images (645 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of study are Remote sensing, Vegetation, Canopy, Hyperspectral imaging and Hydrology.
The Remote sensing study combines topics in areas such as Pixel, Normalized Difference Vegetation Index, Water content and Imaging spectrometer.
Her Water content research includes themes of Soil science and Soil water.
Her study in Vegetation is interdisciplinary in nature, drawing from both Biomass, Endmember and Marsh, Wetland.
Her Canopy research incorporates themes from Radiative transfer, Atmospheric sciences, Leaf area index and Ecosystem.
The study incorporates disciplines such as Precision agriculture and Multispectral image in addition to Hyperspectral imaging.
She most often published in these fields:
- Remote sensing (52.97%)
- Vegetation (23.75%)
- Canopy (18.29%)
What were the highlights of her more recent work (between 2013-2021)?
- Remote sensing (52.97%)
- Hyperspectral imaging (17.58%)
- Ecosystem (13.06%)
In recent papers she was focusing on the following fields of study:
Susan L. Ustin mostly deals with Remote sensing, Hyperspectral imaging, Ecosystem, Canopy and Vegetation.
Particularly relevant to Imaging spectroscopy is her body of work in Remote sensing.
Her Hyperspectral imaging research integrates issues from Airborne visible/infrared imaging spectrometer, Precision agriculture, Woodland and Multispectral image.
Her Ecosystem research is multidisciplinary, incorporating elements of Remote sensing, Climate change, Physical geography and Environmental resource management.
Her Canopy research is multidisciplinary, incorporating perspectives in Agronomy, Leaf area index, Lidar and Atmospheric sciences.
Her research integrates issues of Marsh, Wetland, Bay and Satellite imagery in her study of Vegetation.
Between 2013 and 2021, her most popular works were:
- An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities (208 citations)
- Monitoring plant functional diversity from space (169 citations)
- Erratum: Monitoring plant functional diversity from space (139 citations)
In her most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Artificial intelligence
Susan L. Ustin mainly investigates Remote sensing, Vegetation, Canopy, Hyperspectral imaging and Lidar.
The concepts of her Remote sensing study are interwoven with issues in Image resolution, Ecology and Satellite.
She combines subjects such as Bay, Ecophysiology, Satellite imagery and Marsh, Wetland with her study of Vegetation.
Her Canopy research is multidisciplinary, relying on both Biomass, Agronomy, Growing season and Normalized Difference Vegetation Index.
Her research in Hyperspectral imaging intersects with topics in Airborne visible/infrared imaging spectrometer and Multispectral image.
Her Lidar study integrates concerns from other disciplines, such as Atmospheric sciences, Tree canopy, Carbon cycle, Greenhouse gas and Biomass.
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