Greg S. Biging

2.2k citations
21 papers · 1.8k · 1 hit paper · h-index 16

Impact in

Papers in

Greg S. Biging

21 papers receiving 1.6k citations

Greg S. Biging's Hit Papers

Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery 2006 · 622 citations
6220+6+13Years since publication200400600

Peers

Greg S. Biging
Comparison fields: 5 of 99
  • Nature and Landscape Conservation 749
  • Environmental Engineering 753
  • Media Technology 364
  • Global and Planetary Change 710
  • Ecology 818
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Countries citing papers authored by Greg S. Biging

Since Specialization
Citations

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

Fields of papers citing papers by Greg S. Biging

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Greg S. Biging, 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 Greg S. Biging Line = papers co-authored together Greg S. Biging links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery
Hit paper breakdown →
2006622
2 1992296
3 2007213
4 2011106
5 198478
6 198559
7 201258
8 201151
9 198750
10 199047
11 200433
12 198832
13 199929
14
A comparison of photointerpretation and ground measurements of forest structure
199124
15 200022
16 200016
17 200614
18 198810
19
Impacts of Predicted Sea-Level Rise and Extreme Storm Events on the Transportation Infrastructure in the San Francisco Bay Region
20129
20 19948

About Greg S. Biging

Greg S. Biging is a scholar working on Global and Planetary Change, Nature and Landscape Conservation, Environmental Engineering, Ecology and Mechanics of Materials, having authored 21 papers that have together received 1.8k indexed citations. Recurring topics across this work include Forest ecology and management (10 papers), Remote Sensing and LiDAR Applications (9 papers), Plant Water Relations and Carbon Dynamics (7 papers), Remote Sensing in Agriculture (6 papers), Species Distribution and Climate Change (3 papers), Forest Biomass Utilization and Management (3 papers), Forest Management and Policy (3 papers) and Land Use and Ecosystem Services (3 papers). The work is most often cited by research in Nature and Landscape Conservation (749 citations), Environmental Engineering (753 citations), Media Technology (364 citations), Global and Planetary Change (710 citations) and Ecology (818 citations). Greg S. Biging has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Peng Gong, Matthias Dobbertin, Maggi Kelly, Qian Yu, Nick Clinton, Lee C. Wensel, Woo‐Kyun Lee, Doo-Ahn Kwak, Jun‐Hak Lee and Liheng Zhong. Their work appears in journals such as Forest Science, Photogrammetric Engineering & Remote Sensing, Canadian Journal of Forest Research, International Journal of Remote Sensing and International Journal of General Systems.

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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