D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Environmental Sciences D-index 52 Citations 8,230 254 World Ranking 1819 National Ranking 40

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Ecology

His primary scientific interests are in Statistics, Hydrology, Spatial variability, Artificial intelligence and Geostatistics. His research integrates issues of Soil survey and Interpolation in his study of Statistics. Alfred Stein has researched Hydrology in several fields, including Soil science, Soil water, Fuzzy set, Fuzzy logic and Variogram.

His Spatial variability research is multidisciplinary, incorporating elements of Atmospheric sciences, Sampling, Peat, Soil physics and Field. The concepts of his Artificial intelligence study are interwoven with issues in Remote sensing, Computer vision and Pattern recognition. His Geostatistics research incorporates themes from Spatial ecology, Simulated annealing and Soil chemistry.

His most cited work include:

  • A generic framework for spatial prediction of soil variables based on regression-kriging (734 citations)
  • Model-based geostatistics. Discussion. Authors' reply (276 citations)
  • Propagation of errors in spatial modelling with GIS. (248 citations)

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

His primary areas of study are Remote sensing, Statistics, Artificial intelligence, Spatial analysis and Geostatistics. His Remote sensing study combines topics from a wide range of disciplines, such as Pixel, Normalized Difference Vegetation Index and Scale. The various areas that he examines in his Artificial intelligence study include Machine learning, Computer vision and Pattern recognition.

The subject of his Geostatistics research is within the realm of Spatial variability. His study looks at the relationship between Spatial variability and fields such as Hydrology, as well as how they intersect with chemical problems. He combines subjects such as Multivariate interpolation and Interpolation with his study of Kriging.

He most often published in these fields:

  • Remote sensing (18.49%)
  • Statistics (15.08%)
  • Artificial intelligence (13.46%)

What were the highlights of his more recent work (between 2015-2021)?

  • Remote sensing (18.49%)
  • Artificial intelligence (13.46%)
  • Statistics (15.08%)

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

His primary areas of investigation include Remote sensing, Artificial intelligence, Statistics, Pattern recognition and Spatial analysis. His Remote sensing research incorporates elements of Tree, Image segmentation and Land use. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning.

The Covariate, Bayesian probability, Spatial variability and Prior probability research Alfred Stein does as part of his general Statistics study is frequently linked to other disciplines of science, such as Air temperature, therefore creating a link between diverse domains of science. His study looks at the relationship between Pattern recognition and topics such as Multispectral image, which overlap with Upsampling. His Spatial analysis study incorporates themes from Sampling and Geostatistics.

Between 2015 and 2021, his most popular works were:

  • Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges (217 citations)
  • Deep Fully Convolutional Networks for the Detection of Informal Settlements in VHR Images (71 citations)
  • Automatic Detection of Individual Trees from VHR Satellite Images Using Scale-Space Methods (62 citations)

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

  • Statistics
  • Artificial intelligence
  • Ecology

Alfred Stein mostly deals with Remote sensing, Artificial intelligence, Statistics, Pattern recognition and Pixel. His work on Remote sensing as part of general Remote sensing research is often related to Wireless sensor network, thus linking different fields of science. In the subject of general Artificial intelligence, his work in Deep learning, Contextual image classification and Scale space is often linked to Maxima, thereby combining diverse domains of study.

Alfred Stein incorporates Statistics and Air temperature in his studies. His Pattern recognition study combines topics in areas such as Image resolution, Kernel, Computer vision and Maxima and minima. His work in Spatial variability addresses subjects such as Logistic regression, which are connected to disciplines such as Environmental health.

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.

Best Publications

A generic framework for spatial prediction of soil variables based on regression-kriging

Tomislav Hengl;Gerard B.M. Heuvelink;Alfred Stein.
Geoderma (2004)

1129 Citations

Model-based geostatistics. Discussion. Authors' reply

P. J. Diggle;J. A. Tawn;R. A. Moyeed;R. Webster.
Applied statistics (1998)

425 Citations

Propagation of errors in spatial modelling with GIS.

Gerard B. M. Heuvelink;Peter A. Burrough;Alfred Stein.
International Journal of Geographic Information Systems (1989)

396 Citations

Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges

Songnian Li;Suzana Dragicevic;Francesc Antón Castro;Monika Sester.
Isprs Journal of Photogrammetry and Remote Sensing (2016)

360 Citations

Constrained optimisation of soil sampling for minimisation of the kriging variance

J.W. van Groenigen;W. Siderius;A. Stein.
Geoderma (1999)

351 Citations

Interpolation techniques for climate variables

A.D. Hartkamp;K. De Beurs;A. Stein;J.W. White.
(1999)

327 Citations

Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India)

Iswar Das;Iswar Das;Sashikant Sahoo;Cees van Westen;Alfred Stein.
Geomorphology (2010)

272 Citations

A review of spatial sampling

Jin Feng Wang;A. Stein;Bin Bo Gao;Yong Ge.
spatial statistics (2012)

254 Citations

Constrained Optimization of Spatial Sampling using Continuous Simulated Annealing

J.W. van Groenigen;A. Stein.
Journal of Environmental Quality (1998)

253 Citations

Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges

S. Li;S. Dragicevic;F. Anton;M. Sester.
arXiv: Physics and Society (2015)

244 Citations

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