What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
The scientist’s investigation covers issues in Soil science, Soil map, Digital soil mapping, Soil survey and Soil classification.
His work on Soil management as part of his general Soil science study is frequently connected to Jargon, thereby bridging the divide between different branches of science.
His Soil map study incorporates themes from Mediterranean climate, Available water capacity, Crop yield and Atmospheric sciences.
His studies deal with areas such as HyMap, Hyperspectral imaging, Silt and Spatial data infrastructure as well as Digital soil mapping.
His work in Soil survey covers topics such as Civil engineering which are related to areas like Perspective, State, Soil horizon and Environmental data.
His Soil classification research integrates issues from Geographic information system, Land management, Environmental resource management and Ecosystem services.
His most cited work include:
- Digital Soil Map of the World (414 citations)
- Digital soil mapping : an introductory perspective (202 citations)
- Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements (200 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Digital soil mapping, Soil science, Soil map, Soil water and Remote sensing.
The concepts of his Digital soil mapping study are interwoven with issues in Silt, Sampling, Vegetation, Propagation of uncertainty and Soil horizon.
His Soil science study combines topics in areas such as Normalized Difference Vegetation Index and Water content.
His Soil map study combines topics from a wide range of disciplines, such as Soil classification, Environmental resource management, Statistics, Scale and Civil engineering.
His research integrates issues of Hydrology, Mediterranean climate and Tillage in his study of Soil water.
His Remote sensing research incorporates elements of Image resolution, Pixel and Random forest.
He most often published in these fields:
- Digital soil mapping (33.33%)
- Soil science (30.83%)
- Soil map (26.67%)
What were the highlights of his more recent work (between 2018-2021)?
- Digital soil mapping (33.33%)
- Soil science (30.83%)
- Soil water (23.33%)
In recent papers he was focusing on the following fields of study:
Philippe Lagacherie mainly investigates Digital soil mapping, Soil science, Soil water, Available water capacity and Water content.
His Digital soil mapping research includes elements of Sample, Quantile, Hyperspectral imaging and Stratified sampling.
The Soil science study combines topics in areas such as Sampling and Normalized Difference Vegetation Index.
His study in Soil water focuses on Soil map in particular.
His Soil map research is multidisciplinary, incorporating elements of Calibration and Covariate.
The various areas that Philippe Lagacherie examines in his Water content study include Soil classification, Watershed and Soil fertility.
Between 2018 and 2021, his most popular works were:
- Sentinel-2 image capacities to predict common topsoil properties of temperate and Mediterranean agroecosystems (47 citations)
- Satellite data integration for soil clay content modelling at a national scale (29 citations)
- Use of sentinel-2 time-series images for classification and uncertainty analysis of inherent biophysical property: Case of soil texture mapping (17 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
Philippe Lagacherie mainly focuses on Digital soil mapping, Soil science, Normalized Difference Vegetation Index, Topsoil and Vegetation.
Many of his studies on Digital soil mapping apply to Silt as well.
Philippe Lagacherie works mostly in the field of Silt, limiting it down to topics relating to Colluvium and, in certain cases, Remote sensing, as a part of the same area of interest.
He works mostly in the field of Normalized Difference Vegetation Index, limiting it down to concerns involving Water content and, occasionally, Partial least squares regression, Total organic carbon, Plough, Ancillary data and Moderate-resolution imaging spectroradiometer.
Topsoil is closely attributed to Soil carbon in his research.
His Vegetation research is multidisciplinary, incorporating perspectives in Permanent wilting point, Field capacity, Scale, Topographic Wetness Index and Soil horizon.
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