Mait Lang
Impact in
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- Forest ecology and management
- Ecology and Vegetation Dynamics Studies
- Environmental Engineering top 1%
- Remote Sensing and LiDAR Applications
Papers in
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- Remote Sensing and LiDAR Applications 60
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- Forest ecology and management 45
- Co-authors
- Andres Kuusk (27 shared papers)Tiit Nilson (20 shared papers)Joel Kuusk (14 shared papers)Jan Písek (13 shared papers)Matti Mõttus (3 shared papers)Miina Rautiainen (4 shared papers)Mathias Neumann (6 shared papers)Lauri Korhonen (4 shared papers)
In The Last Decade
Mait Lang
94 papers receiving 2.4k citations
Mait Lang's Hit Papers
Peers
Comparison fields: 5 of 108
- Nature and Landscape Conservation 881
- Environmental Engineering 951
- Global and Planetary Change 1.2k
- Ecological Modeling 239
- Ecology 1.1k
Countries citing papers authored by Mait Lang
This map shows the geographic impact of Mait Lang'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 Mait Lang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mait Lang more than expected).
Fields of papers citing papers by Mait Lang
This network shows the impact of papers produced by Mait Lang. 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 Mait Lang. The network helps show where Mait Lang may publish in the future.
Co-authors
The 25 scholars most cited alongside Mait Lang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Integrated global assessment of the natural forest carbon potential Hit paper breakdown → | 2023 | 273 |
| 2 | 2015 | 216 | |
| 3 | 2020 | 206 | |
| 4 | The number of tree species on Earth Hit paper breakdown → | 2022 | 163 |
| 5 | 2015 | 109 | |
| 6 | 2022 | 78 | |
| 7 | 2010 | 71 | |
| 8 | 2023 | 67 | |
| 9 | 2022 | 56 | |
| 10 | 2009 | 55 | |
| 11 | 2009 | 54 | |
| 12 | 2008 | 54 | |
| 13 | 2021 | 52 | |
| 14 | 2016 | 51 | |
| 15 | 2019 | 51 | |
| 16 | 2023 | 42 | |
| 17 | 2017 | 41 | |
| 18 | 2004 | 40 | |
| 19 | 2012 | 37 | |
| 20 | 2024 | 37 |
About Mait Lang
Mait Lang is a scholar working on Environmental Engineering, Nature and Landscape Conservation, Ecology, Global and Planetary Change and Ecological Modeling, having authored 97 papers that have together received 2.5k indexed citations. Recurring topics across this work include Remote Sensing and LiDAR Applications (60 papers), Remote Sensing in Agriculture (46 papers), Forest ecology and management (45 papers), Plant Water Relations and Carbon Dynamics (17 papers), Forest Ecology and Biodiversity Studies (16 papers), Species Distribution and Climate Change (13 papers), Land Use and Ecosystem Services (12 papers) and Forest Management and Policy (11 papers). The work is most often cited by research in Nature and Landscape Conservation (881 citations), Environmental Engineering (951 citations), Global and Planetary Change (1.2k citations), Ecological Modeling (239 citations) and Ecology (1.1k citations). Mait Lang has collaborated with scholars based in Estonia, Finland and Austria. Frequent co-authors include Andres Kuusk, Tiit Nilson, Joel Kuusk, Jan Písek, Matti Mõttus, Miina Rautiainen, Mathias Neumann, Lauri Korhonen, Tanja Sanders and Karol Bronisz. Their work appears in journals such as Remote Sensing of Environment, Remote Sensing, Agricultural and Forest Meteorology, Forestry Studies / Metsanduslikud Uurimused and European Journal of Remote Sensing.
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.