Patrick Schratz
Impact in
- Environmental Engineering top 5%
- Remote Sensing and LiDAR Applications
- Soil Geostatistics and Mapping
- Ecological Modeling top 10%
- Species Distribution and Climate Change
Papers in
- Ecology 6
- Remote Sensing in Agriculture 5
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- Remote Sensing and LiDAR Applications 4
- Soil Geostatistics and Mapping 2
- Co-authors
- Jakob Richter (2 shared papers)Alexander Brenning (8 shared papers)Jannes Muenchow (7 shared papers)Eugenia Iturritxa (3 shared papers)Bernd Bischl (3 shared papers)Michel Lang (3 shared papers)Stefan Coors (1 shared paper)Martin Binder (1 shared paper)
- Journals
- Remote Sensing (2 papers)The R Journal (1 paper)Ecological Modelling (1 paper)Journal of Statistical Software (1 paper)Ecography (1 paper)
- Partner nations
- GermanySpainUnited States
In The Last Decade
Patrick Schratz
13 papers receiving 802 citations
Patrick Schratz's Hit Papers
Peers
Comparison fields: 5 of 140
- Environmental Engineering 189
- Ecological Modeling 44
- Management, Monitoring, Policy and Law 97
- Global and Planetary Change 170
- Ecology 193
Countries citing papers authored by Patrick Schratz
This map shows the geographic impact of Patrick Schratz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Patrick Schratz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Schratz more than expected).
Fields of papers citing papers by Patrick Schratz
This network shows the impact of papers produced by Patrick Schratz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Patrick Schratz. The network helps show where Patrick Schratz may publish in the future.
Co-authors
The 25 scholars most cited alongside Patrick Schratz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data Hit paper breakdown → | 2019 | 392 |
| 2 | mlr3: A modern object-oriented machine learning framework in R Hit paper breakdown → | 2019 | 250 |
| 3 | 2020 | 60 | |
| 4 | 2020 | 54 | |
| 5 | 2021 | 19 | |
| 6 | 2017 | 19 | |
| 7 | 2020 | 16 | |
| 8 | 2024 | 5 | |
| 9 | 2020 | 4 | |
| 10 | Unified Interface to Parallelization Back-Ends [R package parallelMap version 1.5.0] | 2020 | 2 |
| 11 | 2018 | 1 | |
| 12 | 2020 | 1 | |
| 13 | Odds Ratio Calculation for GAM(M)s & GLM(M)s [R package oddsratio version 2.0.1] | 2020 | 1 |
| 14 | 2020 | 0 |
About Patrick Schratz
Patrick Schratz is a scholar working on Ecology, Environmental Engineering, Ecological Modeling, Nature and Landscape Conservation and Artificial Intelligence, having authored 14 papers that have together received 824 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (5 papers), Species Distribution and Climate Change (4 papers), Remote Sensing and LiDAR Applications (4 papers), Soil Geostatistics and Mapping (2 papers), Ecology and Vegetation Dynamics Studies (2 papers), Data Analysis with R (2 papers), Landslides and related hazards (2 papers) and Plant Pathogens and Fungal Diseases (1 paper). The work is most often cited by research in Environmental Engineering (189 citations), Ecological Modeling (44 citations), Management, Monitoring, Policy and Law (97 citations), Global and Planetary Change (170 citations) and Ecology (193 citations). Patrick Schratz has collaborated with scholars based in Germany, Spain and United States. Frequent co-authors include Jakob Richter, Alexander Brenning, Jannes Muenchow, Eugenia Iturritxa, Bernd Bischl, Michel Lang, Stefan Coors, Martin Binder, Florian Pfisterer and Lars Kotthoff. Their work appears in journals such as Remote Sensing, The R Journal, Ecological Modelling, Journal of Statistical Software and Ecography.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.