Johannes Uhl

2.0k total citations
56 papers, 961 citations indexed

About

Johannes Uhl is a scholar working on Global and Planetary Change, Ecology and Environmental Engineering. According to data from OpenAlex, Johannes Uhl has authored 56 papers receiving a total of 961 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Global and Planetary Change, 14 papers in Ecology and 12 papers in Environmental Engineering. Recurrent topics in Johannes Uhl's work include Land Use and Ecosystem Services (23 papers), Remote Sensing in Agriculture (14 papers) and Remote Sensing and LiDAR Applications (12 papers). Johannes Uhl is often cited by papers focused on Land Use and Ecosystem Services (23 papers), Remote Sensing in Agriculture (14 papers) and Remote Sensing and LiDAR Applications (12 papers). Johannes Uhl collaborates with scholars based in United States, Italy and Poland. Johannes Uhl's co-authors include Stefan Leyk, Yao‐Yi Chiang, Craig A. Knoblock, Weiwei Duan, Dylan S. Connor, Deborah Balk, Peter Reinartz, Sahil Suri, Anna Braswell and Peter Schwind and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Johannes Uhl

52 papers receiving 938 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Johannes Uhl United States 19 416 197 168 158 116 56 961
Vasileios Syrris Italy 20 1.0k 2.4× 371 1.9× 90 0.5× 386 2.4× 71 0.6× 43 1.8k
Christian Geiß Germany 23 449 1.1× 252 1.3× 97 0.6× 236 1.5× 41 0.4× 69 1.3k
Jingxiong Zhang China 12 245 0.6× 209 1.1× 60 0.4× 182 1.2× 172 1.5× 57 787
Guonian Lv China 16 177 0.4× 183 0.9× 72 0.4× 71 0.4× 87 0.8× 78 773
Mingyi Du China 19 374 0.9× 294 1.5× 58 0.3× 95 0.6× 24 0.2× 71 896
Kang‐Tsung Chang Taiwan 19 458 1.1× 181 0.9× 55 0.3× 154 1.0× 104 0.9× 48 1.2k
Andreas Felbier Germany 11 692 1.7× 276 1.4× 29 0.2× 197 1.2× 37 0.3× 22 1.1k
E. Lynn Usery United States 19 211 0.5× 158 0.8× 96 0.6× 129 0.8× 321 2.8× 66 1.1k
P.F. Fisher United Kingdom 14 469 1.1× 267 1.4× 84 0.5× 404 2.6× 193 1.7× 41 1.3k
Dongyang Hou China 17 208 0.5× 95 0.5× 133 0.8× 143 0.9× 69 0.6× 54 621

Countries citing papers authored by Johannes Uhl

Since Specialization
Citations

This map shows the geographic impact of Johannes Uhl'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 Johannes Uhl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Uhl more than expected).

Fields of papers citing papers by Johannes Uhl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johannes Uhl. 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 Johannes Uhl. The network helps show where Johannes Uhl may publish in the future.

Co-authorship network of co-authors of Johannes Uhl

This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Uhl. A scholar is included among the top collaborators of Johannes Uhl based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Johannes Uhl. Johannes Uhl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Florio, Pietro, Panagiotis Politis, Johannes Uhl, et al.. (2025). GHS-OBAT: Global, open building attribute data reporting age, function, height and compactness at footprint level. Data in Brief. 61. 111751–111751.
2.
Uhl, Johannes, et al.. (2024). A fragment-based approach for computing the long-term visual evolution of historical maps. Humanities and Social Sciences Communications. 11(1). 1 indexed citations
3.
Pesaresi, Martino, Marcello Schiavina, Panagiotis Politis, et al.. (2024). Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data. International Journal of Digital Earth. 17(1). 44 indexed citations
4.
Connor, Dylan S., Johannes Uhl, Catherine V. Talbot, et al.. (2024). Spatial poverty dynamics and social mobility in rural America. Population Space and Place. 30(8). 3 indexed citations
5.
Leyk, Stefan, et al.. (2024). An Integrated Multi-Source Dataset for Measuring Settlement Evolution in the United States from 1810 to 2020. Scientific Data. 11(1). 275–275. 4 indexed citations
6.
Uhl, Johannes, Lori M. Hunter, Stefan Leyk, et al.. (2023). Place-level urban–rural indices for the United States from 1930 to 2018. Landscape and Urban Planning. 236. 104762–104762. 20 indexed citations
7.
Uhl, Johannes, et al.. (2023). HISDAC-ES: historical settlement data compilation for Spain (1900–2020). Earth system science data. 15(10). 4713–4747. 6 indexed citations
8.
Uhl, Johannes & Stefan Leyk. (2023). Spatially explicit accuracy assessment of deep learning-based, fine-resolution built-up land data in the United States. International Journal of Applied Earth Observation and Geoinformation. 123. 103469–103469. 6 indexed citations
9.
Uhl, Johannes & Stefan Leyk. (2022). MTBF-33: A multi-temporal building footprint dataset for 33 counties in the United States (1900 – 2015). arXiv (Cornell University). 12 indexed citations
10.
Knoblock, Craig A., et al.. (2022). Building spatio-temporal knowledge graphs from vectorized topographic historical maps. Semantic Web. 14(3). 527–549. 8 indexed citations
11.
Uhl, Johannes, et al.. (2022). Gridded land use data for the conterminous United States 1940–2015. Scientific Data. 9(1). 493–493. 9 indexed citations
12.
Dimov, Dimo, et al.. (2022). Sugarcane Yield Estimation Through Remote Sensing Time Series and Phenology Metrics. SSRN Electronic Journal. 2 indexed citations
13.
Connor, Dylan S., Johannes Uhl, Catherine V. Talbot, et al.. (2022). Rising community poverty reduces social mobility for rural children. SSRN Electronic Journal. 5 indexed citations
14.
Uhl, Johannes, Stefan Leyk, Weiwei Duan, et al.. (2021). Towards the large-scale extraction of historical land cover information from historical maps. Abstracts of the ICA. 3. 1–2. 1 indexed citations
15.
Braswell, Anna, Stefan Leyk, Dylan S. Connor, & Johannes Uhl. (2021). Creeping disaster along the U.S. coastline: Understanding exposure to sea level rise and hurricanes through historical development. SHILAP Revista de lepidopterología. 1 indexed citations
16.
Hunter, Lori M., et al.. (2020). Change in U.S. Small Town Community Capitals, 1980–2010. Population Research and Policy Review. 39(5). 913–940. 8 indexed citations
17.
Li, Zekun, Yao‐Yi Chiang, Sasan Tavakkol, et al.. (2020). An Automatic Approach for Generating Rich, Linked Geo-Metadata from Historical Map Images. 3290–3298. 13 indexed citations
18.
Duan, Weiwei, Yao‐Yi Chiang, Stefan Leyk, Johannes Uhl, & Craig A. Knoblock. (2019). Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning. International Journal of Geographical Information Systems. 34(4). 824–849. 26 indexed citations
19.
Uhl, Johannes. (2019). Spatio-Temporal Information Extraction Under Uncertainty Using Multi-Source Data Integration and Machine Learning: Applications to Human Settlement Modelling. CU Scholar (University of Colorado Boulder). 1 indexed citations
20.
Uhl, Johannes, Stefan Leyk, Yao‐Yi Chiang, Weiwei Duan, & Craig A. Knoblock. (2017). Extracting Human Settlement Footprint from Historical Topographic Map Series Using Context-Based Machine Learning. 15 (6 .)–15 (6 .). 29 indexed citations

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.

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