Leah Wasser

561 total citations
10 papers, 200 citations indexed

About

Leah Wasser is a scholar working on Environmental Engineering, Artificial Intelligence and Information Systems. According to data from OpenAlex, Leah Wasser has authored 10 papers receiving a total of 200 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Environmental Engineering, 4 papers in Artificial Intelligence and 2 papers in Information Systems. Recurrent topics in Leah Wasser's work include Remote Sensing and LiDAR Applications (4 papers), Research Data Management Practices (2 papers) and Soil erosion and sediment transport (2 papers). Leah Wasser is often cited by papers focused on Remote Sensing and LiDAR Applications (4 papers), Research Data Management Practices (2 papers) and Soil erosion and sediment transport (2 papers). Leah Wasser collaborates with scholars based in United States, Canada and France. Leah Wasser's co-authors include L. Chasmer, R. L. Day, Alan H. Taylor, A. W. Taylor, Sarah R. Supp, Juliann E. Aukema, Amber E Budden, Julien Brun, Ethan P. White and Stephanie Labou and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and BioScience.

In The Last Decade

Leah Wasser

7 papers receiving 193 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leah Wasser United States	4	110	90	58	46	40	10	200
Hannes Taubenboeck Germany	2	52 0.5×	170 1.9×	42 0.7×	77 1.7×	126 3.1×	4	271
Erika Gonzalez‐Akre United States	11	31 0.3×	74 0.8×	247 4.3×	29 0.6×	272 6.8×	15	403
Phillip Papastefanou Germany	9	24 0.2×	45 0.5×	39 0.7×	16 0.3×	148 3.7×	16	223
Ulrike Stahl Germany	5	40 0.4×	217 2.4×	229 3.9×	194 4.2×	191 4.8×	8	436
Sagar Mysorekar United States	5	17 0.2×	260 2.9×	109 1.9×	31 0.7×	45 1.1×	6	365
James Toledano United States	5	18 0.2×	72 0.8×	31 0.5×	35 0.8×	111 2.8×	7	208
Sisira Ediriweera Sri Lanka	10	70 0.6×	79 0.9×	114 2.0×	16 0.3×	91 2.3×	24	204
Glenda M. Yenni United States	5	10 0.1×	85 0.9×	105 1.8×	97 2.1×	47 1.2×	11	220
K. L. Castro Canada	5	82 0.7×	198 2.2×	73 1.3×	70 1.5×	92 2.3×	5	284
Aji John United States	7	19 0.2×	55 0.6×	25 0.4×	47 1.0×	33 0.8×	15	156

Countries citing papers authored by Leah Wasser

Since Specialization

Citations

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

Fields of papers citing papers by Leah Wasser

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leah Wasser

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

All Works

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10 of 10 papers shown

Mahood, Adam L., Maxwell B. Joseph, Michael J. Koontz, et al.. (2023). Ten simple rules for working with high resolution remote sensing data. SHILAP Revista de lepidopterología. 3.

Palomino, Jenny, et al.. (2021). earthlab/earth-analytics-intro-to-earth-data-science-textbook: Earth Analytics Updated Version of the Intro Textbook. Zenodo (CERN European Organization for Nuclear Research).

Wasser, Leah, et al.. (2019). Democratizing Access to Earth data Science Skills Using Blended Online and In-Person Approaches and Open Education. AGUFM. 2019. 1 indexed citations

Wasser, Leah, Maxwell B. Joseph, Joseph McGlinchy, et al.. (2019). EarthPy: A Python package that makes it easier to explore and plot raster and vector data using open source Python tools.. The Journal of Open Source Software. 4(43). 1886–1886. 9 indexed citations

Wasser, Leah. (2018). earthlab/earth-analytics-r-course: Earth Analytics Course in the R Programming Language. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

Budden, Amber E, D. M. Bloom, Amy Hodge, et al.. (2017). Using Peer Review to Support Development of Community Resources for Research Data Management. SHILAP Revista de lepidopterología. 6(2). e1114–e1114. 3 indexed citations

Hampton, Stephanie E., Matthew B. Jones, Leah Wasser, et al.. (2017). Skills and Knowledge for Data-Intensive Environmental Research. BioScience. 67(6). 546–557. 57 indexed citations

Wasser, Leah, L. Chasmer, R. L. Day, & A. W. Taylor. (2015). Quantifying land use effects on forested riparian buffer vegetation structure using LiDAR data. Ecosphere. 6(1). 1–17. 29 indexed citations

Wasser, Leah, R. L. Day, L. Chasmer, & Alan H. Taylor. (2013). Influence of Vegetation Structure on Lidar-derived Canopy Height and Fractional Cover in Forested Riparian Buffers During Leaf-Off and Leaf-On Conditions. PLoS ONE. 8(1). e54776–e54776. 99 indexed citations

10.

Wasser, Leah, L. Chasmer, A. W. Taylor, & R. L. Day. (2010). Validating LiDAR Derived Estimates of Canopy Height, Structure and Fractional Cover in Riparian Areas: A Comparison of Leaf-on and Leaf-off LiDAR Data. AGUFM. 2010. 1 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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