Sherrie Wang

32 papers receiving 1.2k citations

Sherrie Wang's Hit Papers

Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US 2022 · 140 citations
1400+2+4Years since publication100200300

Peers

Sherrie Wang
Comparison fields: 5 of 106
  • Media Technology 234
  • Ecology 564
  • Environmental Engineering 267
  • Global and Planetary Change 344
  • Atmospheric Science 235
Replace Jiantao Liu with:
Jiantao Liu China
Jianyu Yang China
Qiong Hu China
Lei Deng China
Yonglin Shen China
Giovanni Laneve Italy
Masahiko Nagai Japan
Emma Izquierdo‐Verdiguier Spain
Jianhao Gao China
W. Bijker Netherlands
Sherrie Wang relative to Jiantao Liu China Jiantao Liu's profile →
Citations per field
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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-authors

The 25 scholars most cited alongside Sherrie Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sherrie Wang Line = papers co-authored together Sherrie Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques
Hit paper breakdown →
2019316
2 2020179
3
Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US
Hit paper breakdown →
2022140
4 201994
5 202083
6 202073
7 202067
8 201963
9 202146
10 202240
11 201521
12 202420
13 202317
14 202216
15 202412
16 202010
17 20199
18 20246
19 20256
20 20245

About Sherrie Wang

Sherrie Wang is a scholar working on Ecology, Environmental Engineering, Global and Planetary Change, Plant Science and Artificial Intelligence, having authored 33 papers that have together received 1.3k indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (14 papers), Remote Sensing and LiDAR Applications (8 papers), Domain Adaptation and Few-Shot Learning (6 papers), Smart Agriculture and AI (5 papers), Remote-Sensing Image Classification (4 papers), Remote Sensing and Land Use (3 papers), Fire effects on ecosystems (3 papers) and Flood Risk Assessment and Management (2 papers). The work is most often cited by research in Media Technology (234 citations), Ecology (564 citations), Environmental Engineering (267 citations), Global and Planetary Change (344 citations) and Atmospheric Science (235 citations). Sherrie Wang has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include David B. Lobell, George Azzari, Jillian M. Deines, Sang Michael Xie, William Chen, Stefania Di Tommaso, Marco Körner, Stefano Ermon, Neal Jean and Carlos Gould. Their work appears in journals such as Remote Sensing, Remote Sensing of Environment, Environmental Research Letters, Earth system science data and Atmospheric Environment X.

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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