What is he best known for?
The fields of study he is best known for:
- Agriculture
- Climate change
- Ecology
His primary areas of investigation include Climate change, Agriculture, Global warming, Natural resource economics and Precipitation.
His Climate change research incorporates elements of Development economics, Growing season and Environmental protection.
Marshall Burke is interested in Agricultural productivity, which is a field of Agriculture.
His work carried out in the field of Global warming brings together such families of science as Range and Physical geography.
His Natural resource economics research incorporates themes from Agroforestry, Food security and Land reform.
His research in Precipitation intersects with topics in Spatial ecology and Contrast.
His most cited work include:
- Prioritizing Climate Change Adaptation Needs for Food Security in 2030 (2012 citations)
- Quantifying the influence of climate on human conflict (793 citations)
- Global non-linear effect of temperature on economic production (567 citations)
What are the main themes of his work throughout his whole career to date?
Marshall Burke mainly focuses on Climate change, Agriculture, Natural resource economics, Satellite imagery and Developing country.
The study incorporates disciplines such as Development economics and Precipitation in addition to Climate change.
Marshall Burke combines subjects such as Productivity, Crop yield and Environmental resource management with his study of Agriculture.
In his research, Environmental planning is intimately related to Food security, which falls under the overarching field of Natural resource economics.
His Satellite imagery study combines topics from a wide range of disciplines, such as Training set, Convolutional neural network, Artificial intelligence and Sustainable development.
His work focuses on many connections between Developing country and other disciplines, such as Poverty, that overlap with his field of interest in Machine learning, Livelihood and Socioeconomic status.
He most often published in these fields:
- Climate change (43.82%)
- Agriculture (25.28%)
- Natural resource economics (21.35%)
What were the highlights of his more recent work (between 2019-2021)?
- Climate change (43.82%)
- Satellite imagery (20.22%)
- Key (6.74%)
In recent papers he was focusing on the following fields of study:
Marshall Burke mainly investigates Climate change, Satellite imagery, Key, Data science and Flood myth.
His research integrates issues of Regional science and Cadastre in his study of Climate change.
His Satellite imagery study frequently draws connections between adjacent fields such as Artificial intelligence.
His study looks at the relationship between Key and topics such as Sustainable development, which overlap with Training set.
He has included themes like Natural resource economics, Floodplain, Climate risk and Precipitation in his Flood myth study.
His studies in Natural resource economics integrate themes in fields like Smoke and Pollution monitoring.
Between 2019 and 2021, his most popular works were:
- The COVID-19 lockdowns: a window into the Earth System (40 citations)
- Using publicly available satellite imagery and deep learning to understand economic well-being in Africa (27 citations)
- Generating Interpretable Poverty Maps using Object Detection in Satellite Images (14 citations)
In his most recent research, the most cited papers focused on:
- Agriculture
- Ecology
- Climate change
The scientist’s investigation covers issues in Artificial intelligence, Psychological intervention, Armed conflict, Climate change and Regional science.
The Artificial intelligence study combines topics in areas such as Machine learning and Satellite imagery.
His work deals with themes such as Object and Poverty, which intersect with Machine learning.
His Satellite imagery research integrates issues from Variation, Deep learning, Econometrics and Scale.
Marshall Burke conducts interdisciplinary study in the fields of Psychological intervention and Scientific domain through his works.
His Object detection study integrates concerns from other disciplines, such as Self supervised learning, Unsupervised learning and Leverage.
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