Paul Treitz

6.2k total citations · 1 hit paper
92 papers, 4.9k citations indexed

About

Paul Treitz is a scholar working on Environmental Engineering, Ecology and Atmospheric Science. According to data from OpenAlex, Paul Treitz has authored 92 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Environmental Engineering, 37 papers in Ecology and 33 papers in Atmospheric Science. Recurrent topics in Paul Treitz's work include Remote Sensing and LiDAR Applications (45 papers), Forest ecology and management (31 papers) and Remote Sensing in Agriculture (30 papers). Paul Treitz is often cited by papers focused on Remote Sensing and LiDAR Applications (45 papers), Forest ecology and management (31 papers) and Remote Sensing in Agriculture (30 papers). Paul Treitz collaborates with scholars based in Canada, United States and United Kingdom. Paul Treitz's co-authors include Kevin Lim, Chris Hopkinson, L. Chasmer, Michael A. Wulder, Martin Flood, Benoît St-Onge, Philip J. Howarth, I. K. Morrison, Valerie A. Thomas and Murray Woods and has published in prestigious journals such as Remote Sensing of Environment, International Journal of Remote Sensing and Agricultural and Forest Meteorology.

In The Last Decade

Paul Treitz

92 papers receiving 4.5k citations

Hit Papers

LiDAR remote sensing of f... 2003 2026 2010 2018 2003 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. LiDAR remote sensing of forest structure
    2003 853 citations Kevin Lim, Paul Treitz et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Paul Treitz 3.4k 2.3k 2.0k 1.4k 1.2k 92 4.9k
Randolph H. Wynne 3.0k 0.9× 2.6k 1.1× 2.1k 1.0× 1.8k 1.3× 944 0.8× 125 6.0k
Glenn Newnham 3.4k 1.0× 2.5k 1.1× 2.3k 1.1× 1.8k 1.3× 1.1k 0.9× 63 5.1k
Darius Culvenor 3.7k 1.1× 3.3k 1.4× 2.4k 1.2× 2.1k 1.6× 1.0k 0.9× 54 5.8k
Guoqing Sun 4.0k 1.2× 2.8k 1.2× 1.6k 0.8× 1.5k 1.1× 384 0.3× 180 5.5k
Felix Morsdorf 3.5k 1.0× 2.5k 1.1× 2.1k 1.1× 1.3k 1.0× 991 0.9× 96 4.7k
Ross Nelson 4.6k 1.4× 2.6k 1.1× 3.3k 1.6× 1.3k 1.0× 1.6k 1.3× 62 5.4k
John Armston 5.5k 1.6× 4.0k 1.8× 3.1k 1.5× 2.8k 2.1× 821 0.7× 132 7.5k
Bruce D. Cook 2.6k 0.8× 2.8k 1.2× 1.4k 0.7× 2.9k 2.1× 522 0.5× 117 5.5k
Håkan Olsson 3.2k 1.0× 1.7k 0.8× 2.2k 1.1× 906 0.7× 1.2k 1.0× 93 3.9k
Thomas Hilker 3.9k 1.2× 4.5k 2.0× 1.9k 1.0× 3.6k 2.6× 891 0.8× 83 7.4k

Countries citing papers authored by Paul Treitz

Since Specialization
Citations

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

Fields of papers citing papers by Paul Treitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Treitz

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Treitz. A scholar is included among the top collaborators of Paul Treitz 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 Paul Treitz. Paul Treitz 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.
Scott, Neal A., et al.. (2023). Investigating ten years of warming and enhanced snow depth on nutrient availability and greenhouse gas fluxes in a High Arctic ecosystem. Arctic Antarctic and Alpine Research. 55(1). 1 indexed citations
2.
3.
Scott, Neal A., et al.. (2021). Interannual Variability of Summer Net Ecosystem CO2 Exchange in High Arctic Tundra. Journal of Geophysical Research Biogeosciences. 126(8). 4 indexed citations
4.
Wright, Claire, et al.. (2021). Spatial variability in carbon dioxide exchange processes within wet sedge meadows in the Canadian High Arctic. ADVANCES IN POLAR SCIENCE. 1–19. 2 indexed citations
5.
Freemantle, Jim, et al.. (2020). A High Spatial Resolution Satellite Remote Sensing Time Series Analysis of Cape Bounty, Melville Island, Nunavut (2004–2018). Canadian Journal of Remote Sensing. 46(6). 733–752. 8 indexed citations
6.
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Danby, Ryan K., et al.. (2018). Landscape variability of vegetation change across the forest to tundra transition of central Canada. Remote Sensing of Environment. 217. 18–29. 36 indexed citations
8.
9.
Treitz, Paul, et al.. (2012). Can Landsat data detect variations in snow cover within habitats of arctic ungulates?. Wildlife Biology. 18(1). 75–87. 12 indexed citations
10.
Ewijk, Karin Y. van, Paul Treitz, & Neal A. Scott. (2011). Characterizing Forest Succession in Central Ontario using Lidar-derived Indices. Photogrammetric Engineering & Remote Sensing. 77(3). 261–269. 116 indexed citations
11.
Woods, Murray, et al.. (2011). Operational implementation of a LiDAR inventory in Boreal Ontario. The Forestry Chronicle. 87(4). 512–528. 122 indexed citations
12.
Lim, Kevin, Chris Hopkinson, & Paul Treitz. (2008). Examining the effects of sampling point densities on laser canopy height and density metrics at the forest plot level. The Forestry Chronicle. 84. 6 indexed citations
13.
Chasmer, L., Harry McCaughey, Alan Barr, et al.. (2008). Investigating light-use efficiency across a jack pine chronosequence during dry and wet years. Tree Physiology. 28(9). 1395–1406. 25 indexed citations
14.
Thomas, Valerie A., et al.. (2008). Spatial modelling of photosynthesis for a boreal mixedwood forest by integrating micrometeorological, lidar and hyperspectral remote sensing data. Agricultural and Forest Meteorology. 149(3-4). 639–654. 15 indexed citations
15.
Thomas, Valerie A., et al.. (2007). Canopy chlorophyll concentration estimation using hyperspectral and lidar data for a boreal mixedwood forest in northern Ontario, Canada. International Journal of Remote Sensing. 29(4). 1029–1052. 44 indexed citations
16.
Treitz, Paul, et al.. (2005). Comparison of function‐ and structure‐based schemes for classification of remotely sensed data. International Journal of Remote Sensing. 26(3). 543–561. 9 indexed citations
17.
Treitz, Paul & John Rogan. (2004). Remote sensing for mapping and monitoring land-cover and land-use change—an introduction. Progress in Planning. 61(4). 269–279. 118 indexed citations
18.
Treitz, Paul & Peter Howarth. (2000). Integrating spectral, spatial, and terrain variables for forest ecosystem classification. Photogrammetric Engineering & Remote Sensing. 66(3). 305–317. 64 indexed citations
19.
Sampson, P. H., Gina H. Mohammed, Thomas L. Noland, et al.. (2000). The Bioindicators of Forest Condition Project: A physiological, remote sensing approach. The Forestry Chronicle. 76(6). 941–952. 23 indexed citations
20.
Treitz, Paul, Philip J. Howarth, & Peng Gong. (1992). Application of satellite and GIS technologies for land-cover and land-use mapping at the rural-urban fringe : A case study. Photogrammetric Engineering & Remote Sensing. 58(4). 439–448. 137 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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