Tim Whiteside

23 papers receiving 613 citations

Peers

Tim Whiteside
Comparison fields: 5 of 66
  • Environmental Engineering 289
  • Media Technology 145
  • Ecology 366
  • Global and Planetary Change 255
  • Ecological Modeling 42
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Kotaro Iizuka Japan
Jason McVay United States
Zuyuan Wang Switzerland
Oumer S. Ahmed Canada
Nick Clinton United States
Renée E. Bartolo Australia
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Countries citing papers authored by Tim Whiteside

Since Specialization
Citations

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

Fields of papers citing papers by Tim Whiteside

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tim Whiteside, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tim Whiteside Line = papers co-authored together Tim Whiteside links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011265
2 202289
3 201352
4 201546
5 202141
6 201819
7 201518
8 202115
9 201915
10 201110
11 20259
12 20209
13 20189
14 20217
15
Area-based validity assessment of single- and multi-class object-based image analysis
20107
16 20206
17 20226
18 20165
19 20213
20
A multi-scale object-oriented approach to the classification of multi-sensor imagery for mapping land cover in the Top End
20053

About Tim Whiteside

Tim Whiteside is a scholar working on Ecology, Environmental Engineering, Global and Planetary Change, Nature and Landscape Conservation and Artificial Intelligence, having authored 24 papers that have together received 638 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (9 papers), Land Use and Ecosystem Services (7 papers), Geochemistry and Geologic Mapping (6 papers), Species Distribution and Climate Change (4 papers), Remote-Sensing Image Classification (4 papers), Ecology and Vegetation Dynamics Studies (4 papers) and Forest ecology and management (3 papers). The work is most often cited by research in Environmental Engineering (289 citations), Media Technology (145 citations), Ecology (366 citations), Global and Planetary Change (255 citations) and Ecological Modeling (42 citations). Tim Whiteside has collaborated with scholars based in Australia, Belgium and Netherlands. Frequent co-authors include Stefan Maier, Guy Boggs, Renée E. Bartolo, Shaun R. Levick, Harm Bartholomeus, Louise Terryn, Sruthi M. Krishna Moorthy, Hans Verbeeck, Kim Calders and Nicolas Barbier. Their work appears in journals such as Remote Sensing, International Journal of Applied Earth Observation and Geoinformation, Restoration Ecology, The Science of The Total Environment and Photogrammetric Engineering & Remote Sensing.

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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