John Hogland

454 total citations
23 papers, 317 citations indexed

About

John Hogland is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, John Hogland has authored 23 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ecology, 13 papers in Environmental Engineering and 11 papers in Global and Planetary Change. Recurrent topics in John Hogland's work include Remote Sensing and LiDAR Applications (13 papers), Remote Sensing in Agriculture (11 papers) and Forest ecology and management (7 papers). John Hogland is often cited by papers focused on Remote Sensing and LiDAR Applications (13 papers), Remote Sensing in Agriculture (11 papers) and Forest ecology and management (7 papers). John Hogland collaborates with scholars based in United States and Greece. John Hogland's co-authors include Nathaniel Anderson, Nedret Billor, James B. Armstrong, Anwar Hussain, Woodam Chung, David L.R. Affleck, Christopher J. Dunn, Christopher D. O’Connor, Yu Wei and Matthew P. Thompson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Remote Sensing.

In The Last Decade

John Hogland

22 papers receiving 298 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Hogland United States 11 176 152 104 51 31 23 317
Juan Picos Spain 13 257 1.5× 187 1.2× 169 1.6× 104 2.0× 13 0.4× 45 482
Pawan Datta Germany 10 128 0.7× 127 0.8× 153 1.5× 70 1.4× 23 0.7× 19 330
Kathy Gray United States 9 151 0.9× 287 1.9× 86 0.8× 155 3.0× 24 0.8× 15 379
Luigi Saulino Italy 13 130 0.7× 231 1.5× 61 0.6× 134 2.6× 23 0.7× 23 403
T. Vilén Finland 5 83 0.5× 326 2.1× 54 0.5× 179 3.5× 36 1.2× 9 398
Walter Mattioli Italy 13 229 1.3× 280 1.8× 223 2.1× 199 3.9× 27 0.9× 37 585
Matthias Dees Germany 13 216 1.2× 193 1.3× 261 2.5× 141 2.8× 34 1.1× 26 475
Shukui Niu China 10 123 0.7× 249 1.6× 34 0.3× 129 2.5× 16 0.5× 33 403
Dominique Blain Canada 8 154 0.9× 383 2.5× 156 1.5× 168 3.3× 46 1.5× 9 585
Brian P. Oswald United States 12 195 1.1× 267 1.8× 47 0.5× 248 4.9× 17 0.5× 61 458

Countries citing papers authored by John Hogland

Since Specialization
Citations

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

Fields of papers citing papers by John Hogland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Hogland

This figure shows the co-authorship network connecting the top 25 collaborators of John Hogland. A scholar is included among the top collaborators of John Hogland 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 John Hogland. John Hogland 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.
Reynolds‐Hogland, Melissa J., et al.. (2023). Long-term video and genetic data yield insights into complex sociality of a solitary large carnivore. Behavioural Processes. 214. 104972–104972.
2.
Hogland, John, Christopher J. Dunn, & James D. Johnston. (2021). 21st Century Planning Techniques for Creating Fire-Resilient Forests in the American West. Forests. 12(8). 1084–1084. 6 indexed citations
3.
Palaiologou, Palaiologos, et al.. (2020). Locating Forest Management Units Using Remote Sensing and Geostatistical Tools in North-Central Washington, USA. Sensors. 20(9). 2454–2454. 6 indexed citations
4.
Hogland, John, David L.R. Affleck, Nathaniel Anderson, et al.. (2020). Estimating Forest Characteristics for Longleaf Pine Restoration Using Normalized Remotely Sensed Imagery in Florida USA. Forests. 11(4). 426–426. 5 indexed citations
5.
Hogland, John, et al.. (2019). Using Forest Inventory Data with Landsat 8 Imagery to Map Longleaf Pine Forest Characteristics in Georgia, USA. Remote Sensing. 11(15). 1803–1803. 11 indexed citations
6.
Thompson, Matthew P., Yu Wei, David E. Calkin, et al.. (2019). Risk Management and Analytics in Wildfire Response. Current Forestry Reports. 5(4). 226–239. 41 indexed citations
7.
8.
Hogland, John, et al.. (2018). Mapping Forest Characteristics at Fine Resolution across Large Landscapes of the Southeastern United States Using NAIP Imagery and FIA Field Plot Data. ISPRS International Journal of Geo-Information. 7(4). 140–140. 21 indexed citations
9.
Hogland, John, Nathaniel Anderson, & Woodam Chung. (2018). New Geospatial Approaches for Efficiently Mapping Forest Biomass Logistics at High Resolution over Large Areas. ISPRS International Journal of Geo-Information. 7(4). 156–156. 11 indexed citations
10.
Hogland, John, et al.. (2018). Linking Phenological Indices from Digital Cameras in Idaho and Montana to MODIS NDVI. Remote Sensing. 10(10). 1612–1612. 18 indexed citations
11.
Hogland, John, et al.. (2018). Fine Resolution Probabilistic Land Cover Classification of Landscapes in the Southeastern United States. ISPRS International Journal of Geo-Information. 7(3). 107–107. 9 indexed citations
12.
Hogland, John & Nathaniel Anderson. (2017). Function Modeling Improves the Efficiency of Spatial Modeling Using Big Data from Remote Sensing. Big Data and Cognitive Computing. 1(1). 3–3. 21 indexed citations
13.
Chung, Woodam, et al.. (2016). Spatial and temporal quantification of forest residue volumes and delivered costs. Canadian Journal of Forest Research. 46(6). 832–843. 15 indexed citations
14.
Hogland, John & Nathaniel Anderson. (2015). Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS raster utility coding library. 931. 340–344. 2 indexed citations
15.
Hogland, John, et al.. (2014). Estimating forest characteristics using NAIP imagery and ArcObjects. 155–181. 11 indexed citations
16.
Keefe, Robert, et al.. (2014). Woody biomass logistics [Chapter 14]. 251–279. 4 indexed citations
17.
Hogland, John, Nedret Billor, & Nathaniel Anderson. (2013). Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing. European Journal of Remote Sensing. 46(1). 623–640. 54 indexed citations
18.
Hogland, John, et al.. (2013). Function modeling: improved raster analysis through delayed reading and function raster datasets. 1 indexed citations
19.
Reynolds‐Hogland, Melissa J., John Hogland, & Michael S. Mitchell. (2007). Evaluating intercepts from demographic models to understand resource limitation and resource thresholds. Ecological Modelling. 211(3-4). 424–432. 6 indexed citations
20.
Hussain, Anwar, et al.. (2007). Land-Use Pattern, Urbanization, and Deer–Vehicle Collisions in Alabama. SHILAP Revista de lepidopterología. 50 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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