S. M. Skirvin

446 total citations
11 papers, 347 citations indexed

About

S. M. Skirvin is a scholar working on Atmospheric Science, Environmental Engineering and Ecology. According to data from OpenAlex, S. M. Skirvin has authored 11 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Atmospheric Science, 5 papers in Environmental Engineering and 4 papers in Ecology. Recurrent topics in S. M. Skirvin's work include Soil Moisture and Remote Sensing (5 papers), Remote Sensing in Agriculture (3 papers) and Rangeland and Wildlife Management (3 papers). S. M. Skirvin is often cited by papers focused on Soil Moisture and Remote Sensing (5 papers), Remote Sensing in Agriculture (3 papers) and Rangeland and Wildlife Management (3 papers). S. M. Skirvin collaborates with scholars based in United States, Spain and Brazil. S. M. Skirvin's co-authors include M. Susan Moran, Ray B. Bryant, David Thoma, M. Rahman, Chandra D. Holifield Collins, Edson Eyji Sano, Sharon H. Biedenbender, Mark A. Weltz, María P. González-Dugo and Patrick J. Starks and has published in prestigious journals such as Water Resources Research, International Journal of Remote Sensing and Remote Sensing.

In The Last Decade

S. M. Skirvin

10 papers receiving 326 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. M. Skirvin United States 8 205 137 89 83 78 11 347
Martin Baur Germany 8 165 0.8× 129 0.9× 81 0.9× 97 1.2× 55 0.7× 28 330
Tara Bongiovanni United States 11 302 1.5× 219 1.6× 60 0.7× 71 0.9× 54 0.7× 19 390
Hammadi Achour Tunisia 10 125 0.6× 54 0.4× 92 1.0× 128 1.5× 50 0.6× 25 347
Xiaoji Shen China 11 263 1.3× 228 1.7× 97 1.1× 127 1.5× 31 0.4× 24 412
Raphael Quast Austria 9 191 0.9× 133 1.0× 36 0.4× 70 0.8× 35 0.4× 15 262
Isabella Pfeil Austria 9 313 1.5× 197 1.4× 221 2.5× 142 1.7× 86 1.1× 23 494
D. Troufleau France 10 306 1.5× 147 1.1× 199 2.2× 298 3.6× 67 0.9× 11 517
Chandra Holifield Collins United States 14 476 2.3× 387 2.8× 99 1.1× 134 1.6× 28 0.4× 24 660
B. J. Blanchard United States 11 391 1.9× 265 1.9× 85 1.0× 159 1.9× 89 1.1× 32 542
Safa Bousbih France 7 531 2.6× 294 2.1× 156 1.8× 99 1.2× 191 2.4× 12 629

Countries citing papers authored by S. M. Skirvin

Since Specialization
Citations

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

Fields of papers citing papers by S. M. Skirvin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. M. Skirvin. 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 S. M. Skirvin. The network helps show where S. M. Skirvin may publish in the future.

Co-authorship network of co-authors of S. M. Skirvin

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

All Works

11 of 11 papers shown
1.
Collins, Chandra Holifield, S. M. Skirvin, Mark A. Kautz, et al.. (2023). Rangeland Brush Estimation Tool (RaBET): An Operational Remote Sensing-Based Application for Quantifying Woody Cover on Western Rangelands. Remote Sensing. 15(21). 5102–5102. 3 indexed citations
3.
Skirvin, S. M., et al.. (2008). Vegetation data, Walnut Gulch Experimental Watershed, Arizona, United States. Water Resources Research. 44(5). 35 indexed citations
4.
Skirvin, S. M., et al.. (2008). Assessing vegetation change temporally and spatially in southeastern Arizona. Water Resources Research. 44(5). 38 indexed citations
5.
Bryant, Ray B., M. Susan Moran, David Thoma, et al.. (2007). Measuring Surface Roughness Height to Parameterize Radar Backscatter Models for Retrieval of Surface Soil Moisture. IEEE Geoscience and Remote Sensing Letters. 4(1). 137–141. 82 indexed citations
6.
Rahman, M., M. Susan Moran, David Thoma, et al.. (2007). A derivation of roughness correlation length for parameterizing radar backscatter models. International Journal of Remote Sensing. 28(18). 3995–4012. 41 indexed citations
7.
Thoma, David, M. Susan Moran, Ray B. Bryant, et al.. (2006). Comparison of four models to determine surface soil moisture from C‐band radar imagery in a sparsely vegetated semiarid landscape. Water Resources Research. 42(1). 74 indexed citations
8.
Thoma, David, M. Susan Moran, Ray B. Bryant, et al.. (2004). Comparison of two methods for extracting surface soil moisture from C-band radar imagery. 2. 827–830. 9 indexed citations
9.
Skirvin, S. M., Stuart E. Marsh, Mitchel P. McClaran, & David M. Meko. (2003). Climate spatial variability and data resolution in a semi-arid watershed, south-eastern Arizona. Journal of Arid Environments. 54(4). 667–686. 22 indexed citations
10.
Skirvin, S. M., et al.. (2003). Rangeland Ecological and Physical Modeling in a Spatial Context. 1 indexed citations
11.
Skirvin, S. M.. (1991). Use of processed LANDSAT thematic mapper data to detect surface soil moisture over mountain pediments, southeastern Arizona. UA Campus Repository (The University of Arizona). 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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