H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Environmental Sciences H-index 89 Citations 32,543 422 World Ranking 188 National Ranking 7

Overview

What is he best known for?

The fields of study he is best known for:

  • Ecology
  • Statistics
  • Ecosystem

His primary scientific interests are in Remote sensing, Hyperspectral imaging, Vegetation, Ecology and Red edge. He interconnects Regression analysis, Canopy, Linear regression and Leaf area index in the investigation of issues within Remote sensing. The various areas that Andrew K. Skidmore examines in his Hyperspectral imaging study include Coefficient of determination and Rangeland.

In his work, Cartography is strongly intertwined with Remote sensing, which is a subfield of Vegetation. His Ecology study frequently involves adjacent topics like Spatial variability. His Red edge research includes themes of Absorption and Least squares.

His most cited work include:

  • Collinearity: a review of methods to deal with it and a simulation study evaluating their performance (3544 citations)
  • EFFECTS OF FIRE AND HERBIVORY ON THE STABILITY OF SAVANNA ECOSYSTEMS (566 citations)
  • Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI (556 citations)

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

Andrew K. Skidmore focuses on Remote sensing, Ecology, Vegetation, Hyperspectral imaging and Canopy. As a part of the same scientific study, Andrew K. Skidmore usually deals with the Remote sensing, concentrating on Normalized Difference Vegetation Index and frequently concerns with Physical geography. His studies in Habitat, Biodiversity, Ecosystem, Herbivore and Species richness are all subfields of Ecology research.

Many of his studies involve connections with topics such as Environmental resource management and Biodiversity. The study of Hyperspectral imaging is intertwined with the study of Partial least squares regression in a number of ways. The Canopy study combines topics in areas such as Atmospheric radiative transfer codes, Spectroradiometer and Atmospheric sciences.

He most often published in these fields:

  • Remote sensing (45.35%)
  • Ecology (22.05%)
  • Vegetation (16.78%)

What were the highlights of his more recent work (between 2018-2021)?

  • Remote sensing (45.35%)
  • Vegetation (16.78%)
  • Canopy (12.90%)

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

The scientist’s investigation covers issues in Remote sensing, Vegetation, Canopy, Biodiversity and Remote sensing. His Remote sensing study combines topics in areas such as Mean squared error, Atmospheric radiative transfer codes and Leaf area index. His biological study spans a wide range of topics, including Disturbance, Temperate forest, Partial least squares regression, Forest ecology and Scale.

His Canopy research is multidisciplinary, incorporating elements of Infestation, Bark beetle, Atmospheric sciences, Phenology and Chlorophyll content. To a larger extent, Andrew K. Skidmore studies Ecology with the aim of understanding Biodiversity. In his study, Information theory, Wetland, Environmental resource management and Satellite imagery is strongly linked to Ecosystem, which falls under the umbrella field of Remote sensing.

Between 2018 and 2021, his most popular works were:

  • Analysis of Sentinel-2 and RapidEye for Retrieval of Leaf Area Index in a Saltmarsh Using a Radiative Transfer Model (74 citations)
  • Linking the remote sensing of geodiversity and traits relevant to biodiversity—Part II : Geomorphology, terrain and surfaces (44 citations)
  • Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model (30 citations)

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

  • Ecology
  • Statistics
  • Artificial intelligence

Andrew K. Skidmore spends much of his time researching Remote sensing, Vegetation, Canopy, Spectral bands and Leaf area index. His Remote sensing research includes elements of Mean squared error and Random forest. His research in Vegetation intersects with topics in Bark beetle, Temperate forest and Infestation.

Andrew K. Skidmore has researched Canopy in several fields, including Partial least squares regression, Atmospheric sciences and Remote sensing application. As a part of the same scientific family, Andrew K. Skidmore mostly works in the field of Leaf area index, focusing on Ecosystem and, on occasion, Yield, Photosynthetically active radiation, Growing season and Satellite imagery. His work in Normalized Difference Vegetation Index addresses issues such as Word error rate, which are connected to fields such as Statistics.

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.

Top Publications

Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

Carsten F. Dormann;Jane Elith;Sven Bacher;Carsten Buchmann.
Ecography (2013)

4698 Citations

Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI

Pieter S.A. Beck;Clement Atzberger;Kjell Arild Høgda;Bernt Johansen.
Remote Sensing of Environment (2006)

806 Citations

EFFECTS OF FIRE AND HERBIVORY ON THE STABILITY OF SAVANNA ECOSYSTEMS

Frank van Langevelde;Claudius A.D.M. van de Vijver;Claudius A.D.M. van de Vijver;Lalit Kumar;Lalit Kumar;Johan van de Koppel.
Ecology (2003)

766 Citations

Spectral discrimination of vegetation types in a coastal wetland

K.S. Schmidt;A.K. Skidmore.
Remote Sensing of Environment (2003)

711 Citations

Narrow band vegetation indices overcome the saturation problem in biomass estimation

Onisimo Mutanga;A. K. Skidmore.
International Journal of Remote Sensing (2004)

647 Citations

Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests

T.M. Basuki;P.E. van Laake;A.K. Skidmore;Y.A. Hussin.
Forest Ecology and Management (2009)

646 Citations

Modelling topographic variation in solar radiation in a GIS environment

Lalit Kumar;Andrew K. Skidmore;Edmund Knowles.
International Journal of Geographical Information Science (1997)

627 Citations

A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method

Moses Azong Cho;Andrew K. Skidmore.
Remote Sensing of Environment (2006)

580 Citations

Where is positional uncertainty a problem for species distribution modelling

Babak Naimi;Nicholas A. S. Hamm;Thomas A. Groen;Andrew K. Skidmore.
Ecography (2014)

536 Citations

Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland

Roshanak Darvishzadeh;Andrew Skidmore;Martin Schlerf;Clement Atzberger.
Remote Sensing of Environment (2008)

450 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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