Sherrie Wang

1.7k total citations · 1 hit paper
31 papers, 1.1k citations indexed

About

Sherrie Wang is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Sherrie Wang has authored 31 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ecology, 8 papers in Environmental Engineering and 8 papers in Global and Planetary Change. Recurrent topics in Sherrie Wang's work include Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (7 papers) and Smart Agriculture and AI (5 papers). Sherrie Wang is often cited by papers focused on Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (7 papers) and Smart Agriculture and AI (5 papers). Sherrie Wang collaborates with scholars based in United States, Switzerland and Germany. Sherrie Wang's co-authors include David B. Lobell, George Azzari, Jillian M. Deines, Sang Michael Xie, William Chen, Stefania Di Tommaso, Marco Körner, Minghao Qiu, Anne Driscoll and Jennifer Burney and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Environmental Science & Technology.

In The Last Decade

Sherrie Wang

29 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques

2019 305 citations Sherrie Wang, George Azzari et al. Remote Sensing of Environment profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sherrie Wang United States	13	538	317	265	259	218	31	1.1k
Yonglin Shen China	17	369 0.7×	191 0.6×	372 1.4×	294 1.1×	178 0.8×	51	1.0k
Zhongyi Sun China	16	382 0.7×	708 2.2×	149 0.6×	194 0.7×	243 1.1×	76	1.4k
Bogdan Zagajewski Poland	20	810 1.5×	317 1.0×	229 0.9×	396 1.5×	212 1.0×	75	1.4k
Ling Wu China	21	650 1.2×	416 1.3×	248 0.9×	251 1.0×	168 0.8×	86	1.2k
Qiong Hu China	19	743 1.4×	577 1.8×	257 1.0×	290 1.1×	383 1.8×	50	1.3k
Pieter Kempeneers Belgium	21	743 1.4×	420 1.3×	176 0.7×	392 1.5×	250 1.1×	60	1.3k
Jianyu Yang China	18	534 1.0×	670 2.1×	128 0.5×	265 1.0×	278 1.3×	50	1.3k
Raphaël d’Andrimont Italy	15	683 1.3×	414 1.3×	276 1.0×	340 1.3×	222 1.0×	38	1.2k
Masahiko Nagai Japan	17	345 0.6×	390 1.2×	134 0.5×	303 1.2×	167 0.8×	91	1.2k

Countries citing papers authored by Sherrie Wang

Since Specialization

Citations

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

Fields of papers citing papers by Sherrie Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sherrie Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Sherrie Wang. A scholar is included among the top collaborators of Sherrie Wang 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 Sherrie Wang. Sherrie Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bates, Stephen, et al.. (2025). Regression coefficient estimation from remote sensing maps. Remote Sensing of Environment. 330. 114949–114949. 1 indexed citations

Jakubik, Johannes, Jeremy Vila, Detlef Hohl, et al.. (2025). Local Off‐Grid Weather Forecasting With Multi‐Modal Earth Observation Data. Journal of Advances in Modeling Earth Systems. 17(12).

Rufin, Philippe, Patrick Meyfroidt, Felicia O. Akinyemi, et al.. (2025). To enhance sustainable development goal research, open up commercial satellite image archives. Proceedings of the National Academy of Sciences. 122(7). e2410246122–e2410246122. 4 indexed citations

Sapkota, Sujata, et al.. (2025). Impact of wildfire smoke on air pollution-related premature mortality in rapidly growing Kathmandu Valley. Atmospheric Environment X. 26. 100334–100334. 1 indexed citations

Rufin, Philippe, Sherrie Wang, Sá Nogueira Lisboa, et al.. (2024). Taking it further: Leveraging pseudo-labels for field delineation across label-scarce smallholder regions. International Journal of Applied Earth Observation and Geoinformation. 134. 104149–104149. 4 indexed citations

Tommaso, Stefania Di, et al.. (2024). Mapping sugarcane globally at 10 m resolution using Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2. Earth system science data. 16(10). 4931–4947. 2 indexed citations

Rußwurm, Marc, Sherrie Wang, Benjamin Kellenberger, Ribana Roscher, & Devis Tuia. (2024). Meta-learning to address diverse Earth observation problems across resolutions. Communications Earth & Environment. 5(1). 3 indexed citations

Wang, Sherrie, et al.. (2024). Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates. Science. 383(6681). 406–412. 18 indexed citations

Zhang, Chenhui & Sherrie Wang. (2024). Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data. 7839–7849. 12 indexed citations

10.

Wang, Sherrie, et al.. (2024). Combining Deep Learning and Street View Imagery to Map Smallholder Crop Types. Proceedings of the AAAI Conference on Artificial Intelligence. 38(20). 22202–22212. 4 indexed citations

11.

Tommaso, Stefania Di, et al.. (2023). Annual Field-Scale Maps of Tall and Short Crops at the Global Scale Using GEDI and Sentinel-2. Remote Sensing. 15(17). 4123–4123. 17 indexed citations

12.

Childs, Marissa L., Jeff Wen, Sam Heft‐Neal, et al.. (2022). Daily Local-Level Estimates of Ambient Wildfire Smoke PM_2.5 for the Contiguous US. Environmental Science & Technology. 56(19). 13607–13621. 119 indexed citations

13.

Wang, Sherrie, et al.. (2022). Outcomes of hip fracture surgery during the COVID-19 pandemic. European Journal of Orthopaedic Surgery & Traumatology. 33(6). 2453–2458. 1 indexed citations

14.

Wang, Sherrie, et al.. (2022). Current Benefits of Wildfire Smoke for Yields in the US Midwest May Dissipate by 2050. World Bank policy research working paper. 4 indexed citations

15.

Wang, Sherrie, François Waldner, & David B. Lobell. (2022). Unlocking Large-Scale Crop Field Delineation in Smallholder Farming Systems with Transfer Learning and Weak Supervision. Remote Sensing. 14(22). 5738–5738. 35 indexed citations

16.

Wang, Sherrie, Stefania Di Tommaso, Jillian M. Deines, & David B. Lobell. (2020). Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive. Scientific Data. 7(1). 307–307. 82 indexed citations

17.

Wang, Sherrie, et al.. (2020). Meta-Learning for Few-Shot Land Cover Classification. 788–796. 64 indexed citations

18.

Wang, Sherrie, et al.. (2020). Mapping Crop Types in Southeast India with Smartphone Crowdsourcing and Deep Learning. Remote Sensing. 12(18). 2957–2957. 73 indexed citations

19.

Wang, Sherrie & Ryan R. Brinkman. (2019). Data-Driven Flow Cytometry Analysis. Methods in molecular biology. 1989. 245–265. 8 indexed citations

20.

Jean, Neal, Sherrie Wang, George Azzari, David B. Lobell, & Stefano Ermon. (2018). Tile2Vec: Unsupervised representation learning for remote sensing data. arXiv (Cornell University). 2 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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