M. R. Davis

794 total citations
49 papers, 601 citations indexed

About

M. R. Davis is a scholar working on Ecology, Environmental Engineering and Plant Science. According to data from OpenAlex, M. R. Davis has authored 49 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Ecology, 11 papers in Environmental Engineering and 10 papers in Plant Science. Recurrent topics in M. R. Davis's work include Remote Sensing in Agriculture (19 papers), Remote Sensing and LiDAR Applications (9 papers) and Species Distribution and Climate Change (9 papers). M. R. Davis is often cited by papers focused on Remote Sensing in Agriculture (19 papers), Remote Sensing and LiDAR Applications (9 papers) and Species Distribution and Climate Change (9 papers). M. R. Davis collaborates with scholars based in United States and Russia. M. R. Davis's co-authors include J. H. Everitt, D. E. Escobar, Chenghai Yang, Frank W. Judd, Robert I. Lonard, K. R. Summy, David N. Appel, Mohammad Shekaramiz, W. G. Hart and Carlton M. Britton and has published in prestigious journals such as Remote Sensing of Environment, International Journal of Remote Sensing and Forest Ecology and Management.

In The Last Decade

M. R. Davis

46 papers receiving 478 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. R. Davis United States	15	410	177	139	104	81	49	601
Lawrence W. Lass United States	12	505 1.2×	173 1.0×	85 0.6×	116 1.1×	74 0.9×	20	687
Reginald S. Fletcher United States	15	420 1.0×	263 1.5×	153 1.1×	154 1.5×	29 0.4×	62	674
Gabriela Takahashi Miyoshi Brazil	10	341 0.8×	83 0.5×	322 2.3×	85 0.8×	39 0.5×	20	550
Stefanie Holzwarth Germany	13	324 0.8×	75 0.4×	259 1.9×	223 2.1×	56 0.7×	46	600
Marcos Benedito Schimalski Brazil	10	353 0.9×	66 0.4×	289 2.1×	126 1.2×	36 0.4×	36	555
Raquel Alves de Oliveira Finland	14	302 0.7×	131 0.7×	225 1.6×	87 0.8×	34 0.4×	40	549
András Jung Hungary	13	347 0.8×	205 1.2×	257 1.8×	202 1.9×	20 0.2×	42	786
Yuanyong Dian China	15	357 0.9×	102 0.6×	268 1.9×	170 1.6×	29 0.4×	43	594
Pablo Rosso Germany	14	521 1.3×	269 1.5×	173 1.2×	265 2.5×	104 1.3×	23	1.1k
Yuri Shendryk Australia	15	467 1.1×	172 1.0×	456 3.3×	227 2.2×	58 0.7×	22	820

Countries citing papers authored by M. R. Davis

Since Specialization

Citations

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

Fields of papers citing papers by M. R. Davis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. R. Davis

This figure shows the co-authorship network connecting the top 25 collaborators of M. R. Davis. A scholar is included among the top collaborators of M. R. Davis 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 M. R. Davis. M. R. Davis 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

Davis, M. R., et al.. (2024). Anomaly Detection on Small Wind Turbine Blades Using Deep Learning Algorithms. Energies. 17(5). 982–982. 22 indexed citations

Davis, M. R., et al.. (2024). Deep Learning for Indoor Pedestal Fan Blade Inspection: Utilizing Low-Cost Autonomous Drones in an Educational Setting. Drones. 8(7). 298–298. 2 indexed citations

Pine, William E., J. Brucker, M. R. Davis, et al.. (2023). Collapsed oyster populations in large Florida estuaries appear resistant to restoration using traditional cultching methods—Insights from ongoing efforts in multiple systems. Marine and Coastal Fisheries. 15(5). 6 indexed citations

Davis, M. R. & Mohammad Shekaramiz. (2023). Desert/Forest Fire Detection Using Machine/Deep Learning Techniques. Fire. 6(11). 418–418. 5 indexed citations

Kahn, Ralph A., et al.. (2009). Detecting thin cirrus in MISR aerosol retrievals. EGUGA. 2009. 13737. 1 indexed citations

Everitt, J. H., et al.. (2007). Using spatial information technologies for detecting and mapping Eurasian watermilfoil. Geocarto International. 22(1). 49–61. 3 indexed citations

Everitt, J. H., Chenghai Yang, Reginald S. Fletcher, C. J. Deloach, & M. R. Davis. (2007). Using Remote Sensing to Assess Biological Control of Saltcedar. Southwestern Entomologist. 32(2). 93–103. 12 indexed citations

Everitt, J. H., Chenghai Yang, & M. R. Davis. (2004). Evaluating Airborne Hyperspectral Imagery for Rangeland Assessment in South Texas. Geocarto International. 19(3). 23–31. 3 indexed citations

Everitt, J. H., Chenghai Yang, Reginald S. Fletcher, M. R. Davis, & D. Lynn Drawe. (2004). Using Aerial Color‐infrared Photography and QuickBird Satellite Imagery for Mapping Wetland Vegetation. Geocarto International. 19(4). 15–22. 16 indexed citations

10.

Summy, K. R., Christopher R. Little, J. H. Everitt, et al.. (2003). Detecting Stress in Glasshouse Plants Using Color Infrared Imagery: A Potential New Application for Remote Sensing. ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley). 55. 51. 10 indexed citations

11.

Everitt, J. H., K. R. Summy, D. E. Escobar, & M. R. Davis. (2003). An Overview of Aircraft Remote Sensing in Integrated Pest Management. ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley). 55. 59. 3 indexed citations

12.

Everitt, J. H., et al.. (2003). Aerial detection of waste disposal sites near Donna Reservoir in south Texas.. ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley). 55(3). 247–254.

13.

Everitt, J. H., Chenghai Yang, D. E. Escobar, & M. R. Davis. (2000). Distinguishing Ecological Ground Conditions in a Rangeland Area Using a Video System with Visible/Near‐infrared/Mid‐infrared Sensitivity. Geocarto International. 15(3). 39–44. 4 indexed citations

14.

Everitt, J. H., et al.. (1999). Using remote sensing and spatial information technologies to detect and map two aquatic macrophytes.. Journal of Aquatic Plant Management. 71–80. 51 indexed citations

15.

Lonard, Robert I., et al.. (1999). Vegetative Change on South Padre Island, Texas, over Twenty Years and Evaluation of Multispectral Videography in Determining Vegetative Cover and Species Identity. ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley). 3 indexed citations

16.

Everitt, J. H., et al.. (1999). Distinguishing Ecological Parameters in a Coastal Area Using a Video System with Visible/Near-infrared/ Mid-infrared Sensitivity. Journal of Coastal Research. 15(4). 1145–1150. 4 indexed citations

17.

Davis, M. R., E.R. Langer, & C. W. Ross. (1997). Rehabilitation of native forest species after mining in Westland.. New Zealand journal of forestry science. 27(1). 51–68. 7 indexed citations

18.

Everitt, J. H., et al.. (1997). Detecting and mapping western pine beetle infestations with airborne videography, global positioning system and geographic information system technologies. 5 indexed citations

19.

Everitt, J. H., Frank W. Judd, D. E. Escobar, & M. R. Davis. (1996). Integration of Remote Sensing and Spatial Information Technologies for Mapping Black Mangrove on the Texas Gulf Coast. Journal of Coastal Research. 12(1). 64–69. 32 indexed citations

20.

Everitt, J. H., D. E. Escobar, K. R. Summy, & M. R. Davis. (1994). Using airborne video, global positioning system, and geographical information system technologies for detecting and mapping citrus blackfly infestations.. Southwestern Entomologist. 19(2). 129–138. 31 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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