What is she best known for?
The fields of study she is best known for:
- Ecology
- Meteorology
- Remote sensing
The scientist’s investigation covers issues in Remote sensing, Meteorology, Image resolution, Urban heat island and Aerosol.
Her studies in Remote sensing integrate themes in fields like Biomass, Pixel, Vegetation and Scale.
Her studies deal with areas such as Image processing, Entropy, Wavelet and Image fusion as well as Image resolution.
The concepts of her Urban heat island study are interwoven with issues in Urban area, Environmental quality, Thematic Mapper, Daytime and Urban climatology.
In her study, Particulates, Atmospheric model, Spatial distribution and AOD products is inextricably linked to Atmospheric sciences, which falls within the broad field of Aerosol.
Janet Elizabeth Nichol has included themes like Retrieval algorithm and Moderate-resolution imaging spectroradiometer in her AERONET study.
Her most cited work include:
- Satellite remote sensing for detailed landslide inventories using change detection and image fusion (190 citations)
- High-Resolution Surface Temperature Patterns Related to Urban Morphology in a Tropical City: A Satellite-Based Study. (190 citations)
- Wavelet-based image fusion and quality assessment (176 citations)
What are the main themes of her work throughout her whole career to date?
Janet Elizabeth Nichol focuses on Remote sensing, Aerosol, Meteorology, AERONET and Image resolution.
Her research in Remote sensing intersects with topics in Vegetation and Scale.
Her study looks at the relationship between Aerosol and topics such as Moderate-resolution imaging spectroradiometer, which overlap with Particulates.
Her studies in Meteorology integrate themes in fields like Advanced Spaceborne Thermal Emission and Reflection Radiometer and Climatology.
As part of the same scientific family, Janet Elizabeth Nichol usually focuses on AERONET, concentrating on Air quality index and intersecting with Visibility and Pollution.
Janet Elizabeth Nichol studied Urban heat island and Urban area that intersect with Geographic information system.
She most often published in these fields:
- Remote sensing (53.59%)
- Aerosol (22.88%)
- Meteorology (20.92%)
What were the highlights of her more recent work (between 2017-2021)?
- Vegetation (15.69%)
- Secondary forest (11.76%)
- Ecological succession (7.84%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Vegetation, Secondary forest, Ecological succession, Species richness and Aerosol.
Her study in the field of Normalized Difference Vegetation Index is also linked to topics like Dryness.
Janet Elizabeth Nichol focuses mostly in the field of Normalized Difference Vegetation Index, narrowing it down to topics relating to Seasonality and, in certain cases, Atmospheric sciences.
Her studies deal with areas such as Shrubland, Ecosystem, Biodiversity, Seed dispersal and Forestry as well as Ecological succession.
She studies Aerosol, namely AERONET.
Her study explores the link between Arid and topics such as Productivity that cross with problems in Precipitation, Growing season and Biomass.
Between 2017 and 2021, her most popular works were:
- Air pollution scenario over China during COVID-19 (19 citations)
- Evaluation of Terra Modis C6 and C6.1 Aerosol Products Against Beijing, Xianghe, and Xinglong Aeronet Sites in China During 2004 2014 (16 citations)
- A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use over Diverse Land Surfaces Using Multi-Sensor Data (14 citations)
In her most recent research, the most cited papers focused on:
- Ecology
- Artificial intelligence
- Meteorology
Janet Elizabeth Nichol mainly investigates Remote sensing, Pollution, Deep blue, AERONET and Aerosol.
Her research ties Normalized Difference Vegetation Index and Remote sensing together.
Her Pollution study combines topics from a wide range of disciplines, such as Ozone Monitoring Instrument, Ozone, Particulates, Air pollution and Haze.
Her study in Deep blue intersects with areas of studies such as Meteorology, High resolution and Beijing.
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.
