D. Muchoney

3.7k total citations · 1 hit paper
19 papers, 2.7k citations indexed

About

D. Muchoney is a scholar working on Ecology, Ecological Modeling and Artificial Intelligence. According to data from OpenAlex, D. Muchoney has authored 19 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Ecology, 8 papers in Ecological Modeling and 6 papers in Artificial Intelligence. Recurrent topics in D. Muchoney's work include Remote Sensing in Agriculture (13 papers), Species Distribution and Climate Change (8 papers) and Geochemistry and Geologic Mapping (4 papers). D. Muchoney is often cited by papers focused on Remote Sensing in Agriculture (13 papers), Species Distribution and Climate Change (8 papers) and Geochemistry and Geologic Mapping (4 papers). D. Muchoney collaborates with scholars based in United States, Italy and Canada. D. Muchoney's co-authors include Alan H. Strahler, M. A. Friedl, Sucharita Gopal, J.C.F. Hodges, Crystal Schaaf, Curtis E. Woodcock, Feng Gao, D.K. McIver, Alessandro Baccini and Alan Cooper and has published in prestigious journals such as Science, Remote Sensing of Environment and Geophysical Research Letters.

In The Last Decade

D. Muchoney

17 papers receiving 2.6k citations

Hit Papers

Global land cover mapping from MODIS: algorithms and earl... 2002 2026 2010 2018 2002 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Muchoney United States 10 1.7k 1.6k 884 797 318 19 2.7k
Olivier Arinò Italy 24 2.0k 1.1× 1.5k 0.9× 860 1.0× 723 0.9× 277 0.9× 77 3.0k
Étienne Bartholomé Italy 16 1.9k 1.1× 1.4k 0.9× 709 0.8× 556 0.7× 284 0.9× 32 2.8k
D.K. McIver United States 6 1.8k 1.0× 1.5k 0.9× 906 1.0× 787 1.0× 199 0.6× 11 2.6k
R. Latifovic Canada 33 1.3k 0.8× 1.8k 1.1× 814 0.9× 860 1.1× 323 1.0× 69 2.8k
C. Dimiceli United States 12 2.0k 1.2× 1.9k 1.2× 782 0.9× 1.0k 1.3× 402 1.3× 19 3.4k
V. Kovalskyy United States 13 1.4k 0.8× 1.7k 1.1× 471 0.5× 857 1.1× 225 0.7× 23 2.4k
Sophie Bontemps Belgium 21 1.7k 1.0× 1.5k 0.9× 786 0.9× 681 0.9× 239 0.8× 43 2.8k
Ian Olthof Canada 31 988 0.6× 1.1k 0.7× 1.3k 1.5× 549 0.7× 267 0.8× 62 2.6k
John G. Lyon United States 19 1.1k 0.6× 1.7k 1.1× 570 0.6× 674 0.8× 187 0.6× 39 2.3k
Stephen L. Egbert United States 20 1.2k 0.7× 1.7k 1.1× 585 0.7× 608 0.8× 271 0.9× 48 2.4k

Countries citing papers authored by D. Muchoney

Since Specialization
Citations

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

Fields of papers citing papers by D. Muchoney

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Muchoney

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

All Works

19 of 19 papers shown
1.
Henry, Matieu, Antonio Di Gregorio, J. Latham, et al.. (2022). An International Library for Land Cover Legends: The Land Cover Legend Registry. Land. 11(7). 1083–1083. 12 indexed citations
2.
Dwyer, John L., et al.. (2011). Developing climate data records and essential climate variables from landsat data. 4 indexed citations
3.
Muchoney, D. & Mark V. Williams. (2010). Building a 2010 biodiversity conservation data baseline: contributions of the Group on Earth Observations. Ecological Research. 25(5). 937–946. 9 indexed citations
4.
Scholes, Robert J., Georgina M. Mace, Woody Turner, et al.. (2008). Toward a Global Biodiversity Observing System. Science. 321(5892). 1044–1045. 181 indexed citations
5.
Muchoney, D.. (2008). Earth observations for terrestrial biodiversity and ecosystems. Remote Sensing of Environment. 112(5). 1909–1911. 21 indexed citations
6.
Andréfouët, Serge, Mark J. Costello, Daniel P. Faith, et al.. (2008). The GEO Biodiversity Observation Network. GEO BON Concept document. NERC Open Research Archive (Natural Environment Research Council). 2 indexed citations
8.
Muchoney, D. & Alan H. Strahler. (2002). Pixel- and site-based calibration and validation methods for evaluating supervised classification of remotely sensed data. Remote Sensing of Environment. 81(2-3). 290–299. 41 indexed citations
9.
Friedl, M. A., D.K. McIver, J.C.F. Hodges, et al.. (2002). Global land cover mapping from MODIS: algorithms and early results. Remote Sensing of Environment. 83(1-2). 287–302. 2178 indexed citations breakdown →
10.
Muchoney, D. & Alan H. Strahler. (2002). Regional vegetation mapping and direct land surface parameterization from remotely sensed and site data. International Journal of Remote Sensing. 23(6). 1125–1142. 18 indexed citations
11.
Muchoney, D., Jordan S. Borak, & Alan H. Strahler. (2002). Global landcover classification validation issues and requirements. 1. 233–235. 1 indexed citations
12.
Friedl, M. A., Sucharita Gopal, D. Muchoney, & Alan H. Strahler. (2002). Global land cover mapping from MODIS: algorithm design and preliminary results. 2. 527–529. 2 indexed citations
13.
Muchoney, D. & James R. Williamson. (2001). A Gaussian adaptive resonance theory neural network classification algorithm applied to supervised land cover mapping using multitemporal vegetation index data. IEEE Transactions on Geoscience and Remote Sensing. 39(9). 1969–1977. 26 indexed citations
14.
Muchoney, D., Jordan S. Borak, M. A. Friedl, et al.. (2000). Application of the MODIS global supervised classification model to vegetation and land cover mapping of Central America. International Journal of Remote Sensing. 21(6-7). 1115–1138. 101 indexed citations
15.
Friedl, M. A., D. Muchoney, D.K. McIver, et al.. (2000). Characterization of North American land cover from NOAA‐AVHRR data using the EOS MODIS Land Cover Classification Algorithm. Geophysical Research Letters. 27(7). 977–980. 45 indexed citations
16.
Friedl, M. A., Curtis E. Woodcock, Sucharita Gopal, et al.. (2000). A note on procedures used for accuracy assessment in land cover maps derived from AVHRR data. International Journal of Remote Sensing. 21(5). 1073–1077. 88 indexed citations
17.
Muchoney, D. & Alan H. Strahler. (1998). Developing vegetation and land surface parameters using classification approaches. 49. 2112–2114 vol.4. 2 indexed citations
18.
Muchoney, D.. (1994). Relationships and Divergence of Vegetation and Mapping Classifications. 5(1). 121–128. 4 indexed citations
19.
Iremonger, Susan, et al.. (1992). A rapid ecological assessment of Jamaica - phase 1 : An island-wide characterisation and mapping of natural communities and modified vegetation types. 3 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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