What is he best known for?
The fields of study he is best known for:
- Statistics
- Ecology
- Regression analysis
His primary areas of investigation include Forest inventory, Remote sensing, Estimator, Satellite imagery and Statistics.
His Forest inventory study integrates concerns from other disciplines, such as Regression analysis, Ancillary data, Thematic Mapper and Categorical variable.
His studies deal with areas such as Small area estimation, National forest and Plot as well as Remote sensing.
Ronald E. McRoberts undertakes multidisciplinary investigations into Estimator and Inference in his work.
His Satellite imagery study combines topics in areas such as Stratification, Land cover and Simple random sample.
In Statistics, Ronald E. McRoberts works on issues like Econometrics, which are connected to Monte Carlo method, Sensitivity analysis and Residual.
His most cited work include:
- Remote sensing support for national forest inventories (273 citations)
- Stratified estimation of forest area using satellite imagery, inventory data, and the k-Nearest Neighbors technique (183 citations)
- Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery (145 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Forest inventory, Statistics, Remote sensing, Estimator and Environmental resource management.
He combines subjects such as Thematic Mapper, Satellite imagery, Basal area and Plot with his study of Forest inventory.
His work on Sampling, Monte Carlo method and Simple random sample as part of his general Statistics study is frequently connected to Inference, thereby bridging the divide between different branches of science.
His work investigates the relationship between Remote sensing and topics such as Small area estimation that intersect with problems in Ancillary data.
His work deals with themes such as Variables, Mean squared error, Standard error, Resampling and Regression analysis, which intersect with Estimator.
His Environmental resource management research includes themes of Biodiversity, National forest inventory, Sustainability and National forest.
He most often published in these fields:
- Forest inventory (49.45%)
- Statistics (37.36%)
- Remote sensing (26.92%)
What were the highlights of his more recent work (between 2015-2021)?
- Statistics (37.36%)
- Remote sensing (26.92%)
- Estimator (23.63%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Statistics, Remote sensing, Estimator, Forest inventory and Sampling.
His work in the fields of Statistics, such as Plot, overlaps with other areas such as Inference, Volume and Stock.
His Remote sensing study combines topics from a wide range of disciplines, such as Forest management, Natural resource and Small area estimation.
His work carried out in the field of Estimator brings together such families of science as Covariance, Mean squared error, Standard error, Residual and Regression analysis.
His Forest inventory research includes elements of Parametric statistics, Regression, Confidence interval, Simple random sample and Aerial photography.
His Sampling study incorporates themes from Data mining, Bootstrapping, Forestry, Greenhouse gas and Sample.
Between 2015 and 2021, his most popular works were:
- Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation (74 citations)
- A questionnaire-based review of the operational use of remotely sensed data by national forest inventories (56 citations)
- Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass (43 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Ecology
- Regression analysis
His main research concerns Estimator, Statistics, Remote sensing, Forest inventory and Mean squared error.
His work in the fields of Estimator, such as Bias of an estimator, intersects with other areas such as Inference.
Many of his research projects under Statistics are closely connected to Random forest and Feature selection with Random forest and Feature selection, tying the diverse disciplines of science together.
His Remote sensing research is multidisciplinary, incorporating elements of Biomass, Sample and Small area estimation.
His work focuses on many connections between Small area estimation and other disciplines, such as National forest, that overlap with his field of interest in Remote sensing and Satellite imagery.
His study in Forest inventory is interdisciplinary in nature, drawing from both Plot, Land cover, Simple random sample, Standard error and Regression analysis.
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