Jenny Lovell

3.5k total citations
38 papers, 2.3k citations indexed

About

Jenny Lovell is a scholar working on Environmental Engineering, Ecology and Nature and Landscape Conservation. According to data from OpenAlex, Jenny Lovell has authored 38 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Environmental Engineering, 18 papers in Ecology and 17 papers in Nature and Landscape Conservation. Recurrent topics in Jenny Lovell's work include Remote Sensing and LiDAR Applications (19 papers), Forest ecology and management (17 papers) and Remote Sensing in Agriculture (16 papers). Jenny Lovell is often cited by papers focused on Remote Sensing and LiDAR Applications (19 papers), Forest ecology and management (17 papers) and Remote Sensing in Agriculture (16 papers). Jenny Lovell collaborates with scholars based in Australia, United States and United Kingdom. Jenny Lovell's co-authors include David L.B. Jupp, Darius Culvenor, Glenn Newnham, Nicholas C. Coops, Alan H. Strahler, Curtis E. Woodcock, Crystal Schaaf, RD Graetz, Xiaoyuan Yang and Tian Yao and has published in prestigious journals such as Remote Sensing of Environment, Journal of the Operational Research Society and International Journal of Remote Sensing.

In The Last Decade

Jenny Lovell

37 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jenny Lovell Australia 20 1.9k 1.3k 1.2k 585 543 38 2.3k
Mariano Garcı́a Spain 31 1.7k 0.9× 926 0.7× 1.6k 1.4× 303 0.5× 1.7k 3.1× 75 3.0k
Robert G. Knox United States 18 1.5k 0.8× 1.4k 1.1× 1.1k 0.9× 324 0.6× 999 1.8× 36 2.6k
Peter Krzystek Germany 23 1.8k 0.9× 879 0.7× 860 0.7× 733 1.3× 282 0.5× 53 2.1k
Steven A. Acker United States 22 1.5k 0.8× 1.6k 1.3× 1.1k 0.9× 787 1.3× 946 1.7× 42 2.6k
Mats Nilsson Sweden 21 2.4k 1.3× 1.8k 1.4× 1.3k 1.1× 912 1.6× 701 1.3× 45 2.9k
Atticus Stovall United States 20 992 0.5× 1.0k 0.8× 707 0.6× 310 0.5× 841 1.5× 45 1.8k
Håkan Olsson Sweden 32 3.2k 1.7× 2.2k 1.7× 1.7k 1.5× 1.2k 2.0× 906 1.7× 93 3.9k
J. Rosette United Kingdom 17 1.1k 0.6× 555 0.4× 871 0.7× 211 0.4× 564 1.0× 54 1.6k
Robert J. McGaughey United States 25 2.5k 1.3× 1.7k 1.3× 1.3k 1.1× 936 1.6× 1.2k 2.3× 47 3.2k

Countries citing papers authored by Jenny Lovell

Since Specialization
Citations

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

Fields of papers citing papers by Jenny Lovell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jenny Lovell

This figure shows the co-authorship network connecting the top 25 collaborators of Jenny Lovell. A scholar is included among the top collaborators of Jenny Lovell 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 Jenny Lovell. Jenny Lovell 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.
Schroeder, Thomas, M. Schaale, Jenny Lovell, & David Blondeau‐Patissier. (2021). An ensemble neural network atmospheric correction for Sentinel-3 OLCI over coastal waters providing inherent model uncertainty estimation and sensor noise propagation. Remote Sensing of Environment. 270. 112848–112848. 36 indexed citations
2.
3.
Jones, Emlyn, Mark E. Baird, Mathieu Mongin, et al.. (2016). Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef. Biogeosciences. 13(23). 6441–6469. 46 indexed citations
4.
Brando, Vittorio, et al.. (2016). The Potential of Autonomous Ship-Borne Hyperspectral Radiometers for the Validation of Ocean Color Radiometry Data. Remote Sensing. 8(2). 150–150. 45 indexed citations
5.
Newnham, Glenn, John Armston, Kim Calders, et al.. (2015). Terrestrial Laser Scanning for Plot-Scale Forest Measurement. Current Forestry Reports. 1(4). 239–251. 199 indexed citations
6.
Li, Zhan, Ewan S. Douglas, Alan H. Strahler, et al.. (2013). Separating leaves from trunks and branches with dual-wavelength terrestrial lidar scanning. 3383–3386. 22 indexed citations
7.
8.
Hopkinson, Chris, Jenny Lovell, L. Chasmer, et al.. (2013). Integrating terrestrial and airborne lidar to calibrate a 3D canopy model of effective leaf area index. Remote Sensing of Environment. 136. 301–314. 76 indexed citations
9.
Strahler, Alan H., Ewan S. Douglas, T. Cook, et al.. (2012). A Dual Wavelength Echidna® Lidar (DWEL) for Forest Structure Retrieval. AGUFM. 2012. 2 indexed citations
10.
Lovell, Jenny, Vanessa Haverd, David L.B. Jupp, & Glenn Newnham. (2012). The Canopy Semi-analytic Pgap And Radiative Transfer (CanSPART) model: Validation using ground based lidar. Agricultural and Forest Meteorology. 158-159. 1–12. 13 indexed citations
11.
Lovell, Jenny, et al.. (2011). Deconvolution of MODIS imagery using multiscale maximum entropy. Remote Sensing Letters. 2(3). 179–187. 7 indexed citations
12.
Zhao, Feng, Xiaoyuan Yang, Mitchell Schull, et al.. (2011). Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using a full-waveform ground-based lidar. Remote Sensing of Environment. 115(11). 2954–2964. 131 indexed citations
13.
Lovell, Jenny, David L.B. Jupp, Glenn Newnham, & Darius Culvenor. (2010). Measuring tree stem diameters using intensity profiles from ground-based scanning lidar from a fixed viewpoint. ISPRS Journal of Photogrammetry and Remote Sensing. 66(1). 46–55. 146 indexed citations
14.
Strahler, Alan H., David L.B. Jupp, Curtis E. Woodcock, et al.. (2008). Retrieval of forest structural parameters using a ground-based lidar instrument (Echidna®). Canadian Journal of Remote Sensing. 34(sup2). S426–S440. 176 indexed citations
15.
Jupp, David L.B., Darius Culvenor, Jenny Lovell, et al.. (2008). Estimating forest LAI profiles and structural parameters using a ground-based laser called 'Echidna(R). Tree Physiology. 29(2). 171–181. 209 indexed citations
16.
Lovell, Jenny, RD Graetz, & Edward King. (2003). Compositing AVHRR data for the Australian continent: seeking best practice. Canadian Journal of Remote Sensing. 29(6). 770–782. 6 indexed citations
17.
Barry, P.S., Peter J. Jarecke, Jay Pearlman, et al.. (2002). Use of the Lake Frome ground truth campaign as a cross-calibration of the Hyperion instrument. 6. 2538–2540. 5 indexed citations
18.
Barry, P.S., Peter J. Jarecke, Jay Pearlman, et al.. (2002). Radiometric calibration validation of the Hyperion instrument using ground truth at a site in Lake Frome, Australia. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4480. 242–242. 15 indexed citations
19.
Lovell, Jenny & RD Graetz. (2001). Filtering Pathfinder AVHRR Land NDVI data for Australia. International Journal of Remote Sensing. 22(13). 2649–2654. 61 indexed citations
20.
Hartley, David A., et al.. (1979). A Case Study on the Development of the Home Defence Training Game HOT SEAT. Journal of the Operational Research Society. 30(10). 861–871. 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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