What is he best known for?
The fields of study he is best known for:
- Ecology
- Remote sensing
- Statistics
Steven E. Franklin spends much of his time researching Remote sensing, Pixel, Land cover, Cartography and Remote sensing.
Remote sensing is often connected to Vegetation in his work.
The study incorporates disciplines such as Image resolution, Elevation and Image segmentation in addition to Pixel.
His Land cover research incorporates themes from Decision tree, Random forest, Artificial intelligence, Earth observation and Pattern recognition.
His Decision tree study combines topics from a wide range of disciplines, such as Object, Algorithm, Statistical classification and Support vector machine.
His Remote sensing research integrates issues from Ecology, Ecology, Field and Geographic information system.
His most cited work include:
- Refugia: identifying and understanding safe havens for biodiversity under climate change (585 citations)
- A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery (521 citations)
- A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery (521 citations)
What are the main themes of his work throughout his whole career to date?
Steven E. Franklin mostly deals with Remote sensing, Cartography, Land cover, Remote sensing and Forestry.
Image segmentation is closely connected to Pixel in his research, which is encompassed under the umbrella topic of Remote sensing.
His work in Cartography tackles topics such as Change detection which are related to areas like Time series.
Steven E. Franklin combines subjects such as Decision tree, Random forest, Earth observation and Pattern recognition with his study of Land cover.
His Remote sensing research is multidisciplinary, incorporating elements of Synthetic aperture radar, Ecology and Habitat.
In his research, Leaf area index is intimately related to Vegetation, which falls under the overarching field of Forestry.
He most often published in these fields:
- Remote sensing (61.18%)
- Cartography (31.76%)
- Land cover (21.18%)
What were the highlights of his more recent work (between 2011-2020)?
- Remote sensing (61.18%)
- Random forest (7.06%)
- Land cover (21.18%)
In recent papers he was focusing on the following fields of study:
His main research concerns Remote sensing, Random forest, Land cover, Time series and Lidar.
Steven E. Franklin has included themes like Pixel and Linear regression in his Remote sensing study.
Steven E. Franklin interconnects Mean annual increment, Forestry, Site index, Geomorphometrics and Climatic variables in the investigation of issues within Random forest.
His study in Land cover is interdisciplinary in nature, drawing from both Cartography, Leaf area index, Snow, Artificial intelligence and Pattern recognition.
His work carried out in the field of Artificial intelligence brings together such families of science as Algorithm and Computer vision.
The Pattern recognition study combines topics in areas such as Decision tree, Machine learning and Image resolution.
Between 2011 and 2020, his most popular works were:
- Refugia: identifying and understanding safe havens for biodiversity under climate change (585 citations)
- A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery (521 citations)
- A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery (521 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Artificial intelligence
Remote sensing, Random forest, Land cover, Pattern recognition and Artificial intelligence are his primary areas of study.
His biological study focuses on Multispectral image.
Steven E. Franklin has included themes like Data mining, Time series, Transect, Lidar and Object based in his Random forest study.
His Land cover study combines topics in areas such as Classifier, Earth observation, Vegetation, Digital camera and Multi sensor.
His biological study spans a wide range of topics, including Image resolution, Pixel and Decision tree, Machine learning.
His Artificial intelligence study incorporates themes from Algorithm and Computer vision.
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