D. S. Kimes

5.2k total citations
76 papers, 4.2k citations indexed

About

D. S. Kimes is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, D. S. Kimes has authored 76 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Ecology, 40 papers in Environmental Engineering and 25 papers in Global and Planetary Change. Recurrent topics in D. S. Kimes's work include Remote Sensing in Agriculture (53 papers), Remote Sensing and LiDAR Applications (24 papers) and Plant Water Relations and Carbon Dynamics (13 papers). D. S. Kimes is often cited by papers focused on Remote Sensing in Agriculture (53 papers), Remote Sensing and LiDAR Applications (24 papers) and Plant Water Relations and Carbon Dynamics (13 papers). D. S. Kimes collaborates with scholars based in United States, Barbados and Russia. D. S. Kimes's co-authors include J. A. Kirchner, K.J. Ranson, Guoqing Sun, P. J. Sellers, W. W. Newcomb, R. Nelson, Ross Nelson, J. L. Privette, J. B. Blair and William A. Salas and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

D. S. Kimes

75 papers receiving 3.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. S. Kimes United States 36 2.8k 2.5k 1.8k 725 618 76 4.2k
K.I. Itten Switzerland 27 2.0k 0.7× 1.8k 0.7× 1.1k 0.6× 646 0.9× 230 0.4× 127 3.4k
Stephen Plummer United Kingdom 33 3.1k 1.1× 1.9k 0.7× 2.7k 1.5× 419 0.6× 1.1k 1.8× 60 5.0k
Forrest G. Hall United States 35 4.0k 1.4× 2.6k 1.0× 4.2k 2.3× 958 1.3× 787 1.3× 65 6.5k
Donald W. Deering United States 22 3.5k 1.2× 2.1k 0.8× 2.3k 1.3× 370 0.5× 992 1.6× 62 4.7k
Douglas J. King Canada 30 2.1k 0.7× 1.7k 0.7× 1.2k 0.6× 871 1.2× 447 0.7× 80 3.4k
Peter North United Kingdom 38 3.0k 1.1× 1.9k 0.8× 3.0k 1.6× 511 0.7× 1.2k 1.9× 96 5.0k
Renaud Mathieu South Africa 38 2.9k 1.0× 1.8k 0.7× 1.7k 0.9× 603 0.8× 613 1.0× 113 4.7k
Jean‐Philippe Gastellu‐Etchegorry France 43 4.4k 1.6× 3.9k 1.5× 3.1k 1.7× 585 0.8× 1.3k 2.1× 218 6.6k
Miina Rautiainen Finland 38 3.7k 1.3× 2.6k 1.0× 2.5k 1.4× 975 1.3× 1.0k 1.7× 145 5.0k
David Riaño Spain 39 3.4k 1.2× 2.7k 1.1× 3.4k 1.8× 1.0k 1.4× 624 1.0× 80 5.3k

Countries citing papers authored by D. S. Kimes

Since Specialization
Citations

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

Fields of papers citing papers by D. S. Kimes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. S. Kimes

This figure shows the co-authorship network connecting the top 25 collaborators of D. S. Kimes. A scholar is included among the top collaborators of D. S. Kimes 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 D. S. Kimes. D. S. Kimes 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.
Ranson, K.J., et al.. (2006). Merging IceSAT GLAS and Terra MODIS Data in Order to Derive Forest Type Specific Tree Heights in the Central Siberian Boreal Forest. 1 indexed citations
2.
Amr, Sania, Mary E. Bollinger, Monica F. Myers, et al.. (2003). Environmental allergens and asthma in urban elementary schools. Annals of Allergy Asthma & Immunology. 90(1). 34–40. 73 indexed citations
3.
Kimes, D. S., et al.. (2003). Temporal dynamics of emergency department and hospital admissions of pediatric asthmatics. Environmental Research. 94(1). 7–17. 40 indexed citations
4.
Kimes, D. S., Asad Ullah, Elissa R. Levine, et al.. (2003). Relationships between pediatric asthma and socioeconomic/urban variables in Baltimore, Maryland. Health & Place. 10(2). 141–152. 18 indexed citations
5.
Blaisdell, Carol J., Sheila R. Weiss, D. S. Kimes, et al.. (2002). Using Seasonal Variations in Asthma Hospitalizations in Children to Predict Hospitalization Frequency. Journal of Asthma. 39(7). 567–575. 38 indexed citations
6.
Kimes, D. S., R. Nelson, M.T. Manry, & A.K. Fung. (1998). Review article: Attributes of neural networks for extracting continuous vegetation variables from optical and radar measurements. International Journal of Remote Sensing. 19(14). 2639–2663. 135 indexed citations
7.
Toll, D. L., et al.. (1997). NOAA AVHRR land surface albedo algorithm development. International Journal of Remote Sensing. 18(18). 3761–3796. 9 indexed citations
8.
Harrison, Patrick R., et al.. (1995). VEG: Intelligent workbench for studying earth's vegetation. Expert Systems with Applications. 9(2). 135–151.
9.
Otterman, J., et al.. (1995). Inferring the thermal-infrared hemispheric emission from a sparsely-vegetated surface by directional measurements. Boundary-Layer Meteorology. 74(1-2). 163–180. 21 indexed citations
10.
Kimes, D. S., James A. Smith, P. A. Harrison, & Patrick R. Harrison. (1994). Application of AI techniques to infer vegetation characteristics from directional reflectance(s). Frontiers in Plant Science. 12. 628328–628328. 1 indexed citations
11.
Kimes, D. S., P. A. Harrison, & Patrick R. Harrison. (1994). Extension of off-nadir view angles for directional sensor systems. Remote Sensing of Environment. 50(3). 201–211. 9 indexed citations
12.
Schutt, J. B., et al.. (1985). Diurnal movements of cotton leaves expressed as thermodynamic work and entropy changes. Photogrammetric Engineering & Remote Sensing. 51(6). 697–702. 1 indexed citations
13.
Kimes, D. S., W. W. Newcomb, Compton J. Tucker, et al.. (1985). Directional reflectance factor distributions for cover types of Northern Africa. Remote Sensing of Environment. 18(1). 1–19. 115 indexed citations
14.
Kimes, D. S., W. W. Newcomb, J. B. Schutt, Paul J. Pinter, & Ray D. Jackson. (1984). Directional reflectance factor distributions of a cotton row crop. International Journal of Remote Sensing. 5(2). 263–277. 30 indexed citations
15.
Kimes, D. S. & J. A. Kirchner. (1982). Radiative transfer model for heterogeneous 3-D scenes. Applied Optics. 21(22). 4119–4119. 128 indexed citations
16.
Kirchner, J. A., D. S. Kimes, & J. E. McMurtrey. (1982). Variation of directional reflectance factors with structural changes of a developing alfalfa canopy. Applied Optics. 21(20). 3766–3766. 48 indexed citations
17.
Markham, Brian L., D. S. Kimes, Compton J. Tucker, & J. E. McMurtrey. (1981). Temporal spectral response of a corn canopy. Photogrammetric Engineering & Remote Sensing. 47. 12 indexed citations
18.
Kimes, D. S.. (1981). Azimuthal radiometric temperature measurements of wheat canopies. Applied Optics. 20(7). 1119–1119. 17 indexed citations
19.
Kimes, D. S., K.J. Ranson, & J. A. Smith. (1980). A Monte Carlo calculation of the effects of canopy geometry on PhAR absorption.. Photosynthetica. 14(1). 55–64. 14 indexed citations
20.
Kimes, D. S., James A. Smith, & K.J. Ranson. (1980). Vegetation reflectance measurements as a function of solar zenith angle. Photogrammetric Engineering & Remote Sensing. 46. 50 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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