What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Ecosystem
His scientific interests lie mostly in Remote sensing, Ecology, Geographic information system, Pixel and Lidar.
His biological study spans a wide range of topics, including Segmentation, Prediction interval and Canopy.
As a member of one scientific family, Maggi Kelly mostly works in the field of Ecology, focusing on Hydrology and, on occasion, Flux footprint, Methane and Biogeochemical cycle.
His study in Geographic information system is interdisciplinary in nature, drawing from both Abundance and Statistics, Logistic regression.
His work carried out in the field of Pixel brings together such families of science as Image resolution, Vegetation classification, k-nearest neighbors algorithm, Object and Dais.
His Lidar study integrates concerns from other disciplines, such as Linear regression, Accuracy and precision, Pulse, Scale and Crown.
His most cited work include:
- Geographic Object-Based Image Analysis - Towards a new paradigm. (840 citations)
- Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery (613 citations)
- Isolating individual trees in a savanna woodland using small footprint lidar data (354 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Remote sensing, Vegetation, Ecology, Lidar and Canopy.
Maggi Kelly has included themes like Normalized Difference Vegetation Index and Wetland in his Remote sensing study.
His Vegetation research is multidisciplinary, incorporating perspectives in Ecosystem, Physical geography, Habitat and Scale.
His Ecology research is multidisciplinary, incorporating elements of Bay and Plot.
As part of one scientific family, Maggi Kelly deals mainly with the area of Lidar, narrowing it down to issues related to the Basal area, and often Diameter at breast height.
The concepts of his Canopy study are interwoven with issues in Forest restoration, Atmospheric sciences and Crown.
He most often published in these fields:
- Remote sensing (25.47%)
- Vegetation (21.74%)
- Ecology (17.39%)
What were the highlights of his more recent work (between 2016-2021)?
- Vegetation (21.74%)
- Habitat (13.66%)
- Remote sensing (25.47%)
In recent papers he was focusing on the following fields of study:
Maggi Kelly mainly focuses on Vegetation, Habitat, Remote sensing, Lidar and Physical geography.
Vegetation is a subfield of Ecology that he studies.
His work on Segmentation expands to the thematically related Remote sensing.
His work deals with themes such as Perspective, Canopy, Optical reflection and Atmospheric sciences, which intersect with Lidar.
Maggi Kelly has researched Canopy in several fields, including Forest restoration and Basal area.
Maggi Kelly interconnects Shrub, Range, Karst and China in the investigation of issues within Physical geography.
Between 2016 and 2021, his most popular works were:
- Identification of Citrus Trees from Unmanned Aerial Vehicle Imagery Using Convolutional Neural Networks (61 citations)
- UAVs in Support of Algal Bloom Research: A Review of Current Applications and Future Opportunities (32 citations)
- Vegetation change during 40 years of repeated managed wildfires in the Sierra Nevada, California. (24 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Ecosystem
Maggi Kelly mostly deals with Remote sensing, Lidar, Vegetation, Canopy and Workflow.
The study incorporates disciplines such as Understory, Coefficient of determination, Mean squared error, Scale and Wildfire modeling in addition to Remote sensing.
Maggi Kelly integrates Lidar and Simulation modeling in his studies.
His Vegetation research is multidisciplinary, incorporating perspectives in Satellite Image Time Series, Euclidean distance, Pattern recognition and Object based.
His work carried out in the field of Canopy brings together such families of science as Atmospheric sciences and Crown.
His study looks at the relationship between Spatial analysis and topics such as Geospatial analysis, which overlap with Key and Natural resource.
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