Annika Kangas

1.6k total citations
64 papers, 1.3k citations indexed

About

Annika Kangas is a scholar working on Environmental Engineering, Nature and Landscape Conservation and Global and Planetary Change. According to data from OpenAlex, Annika Kangas has authored 64 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Environmental Engineering, 37 papers in Nature and Landscape Conservation and 34 papers in Global and Planetary Change. Recurrent topics in Annika Kangas's work include Remote Sensing and LiDAR Applications (39 papers), Forest ecology and management (35 papers) and Forest Management and Policy (24 papers). Annika Kangas is often cited by papers focused on Remote Sensing and LiDAR Applications (39 papers), Forest ecology and management (35 papers) and Forest Management and Policy (24 papers). Annika Kangas collaborates with scholars based in Finland, Norway and United States. Annika Kangas's co-authors include Matti Maltamo, Jyrki Kangas, Mikko Kurttila, Lauri Mehtätalo, Janne Uuttera, Jussi Saramäki, Minna Räty, Kari Korhonen, Susanna Sironen and Kyle Eyvindson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and International Journal of Remote Sensing.

In The Last Decade

Annika Kangas

61 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Annika Kangas Finland 21 828 785 527 285 216 64 1.3k
Daniel Mandallaz Switzerland 18 490 0.6× 597 0.8× 382 0.7× 154 0.5× 183 0.8× 42 1.0k
Zhongke Feng China 24 711 0.9× 433 0.6× 705 1.3× 125 0.4× 395 1.8× 142 1.5k
Brian F. Walters United States 23 463 0.6× 635 0.8× 862 1.6× 225 0.8× 522 2.4× 53 1.5k
Tero Heinonen Finland 17 426 0.5× 317 0.4× 579 1.1× 164 0.6× 108 0.5× 31 1.1k
Robert E. Froese United States 17 414 0.5× 533 0.7× 574 1.1× 170 0.6× 435 2.0× 44 1.2k
Marco A. Contreras United States 13 308 0.4× 301 0.4× 291 0.6× 121 0.4× 158 0.7× 29 646
Ninni Saarinen Finland 25 1.3k 1.5× 931 1.2× 462 0.9× 551 1.9× 540 2.5× 63 1.7k
Chris J. Cieszewski United States 22 719 0.9× 1.1k 1.5× 983 1.9× 100 0.4× 330 1.5× 87 1.8k
Hans T. Schreuder United States 15 561 0.7× 778 1.0× 482 0.9× 156 0.5× 262 1.2× 69 1.3k
Jari Vauhkonen Finland 25 1.9k 2.2× 1.5k 1.9× 469 0.9× 890 3.1× 754 3.5× 70 2.1k

Countries citing papers authored by Annika Kangas

Since Specialization
Citations

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

Fields of papers citing papers by Annika Kangas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Annika Kangas

This figure shows the co-authorship network connecting the top 25 collaborators of Annika Kangas. A scholar is included among the top collaborators of Annika Kangas 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 Annika Kangas. Annika Kangas 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.
Rajala, Tuomas, Annika Kangas, & Mari Myllymäki. (2025). Computing maps of forest structural diversity: Aggregate late. Ecological Indicators. 178. 114046–114046.
2.
Hou, Zhengyang, Göran Ståhl, Ronald E. McRoberts, et al.. (2023). Conjugating remotely sensed data assimilation and model-assisted estimation for efficient multivariate forest inventory. Remote Sensing of Environment. 299. 113854–113854. 6 indexed citations
3.
Hou, Zhengyang, Svetlana Saarela, Ronald E. McRoberts, et al.. (2023). Leveraging remotely sensed non-wall-to-wall data for wall-to-wall upscaling in forest inventory. International Journal of Applied Earth Observation and Geoinformation. 119. 103314–103314. 3 indexed citations
4.
Kangas, Annika, et al.. (2023). Assessing biodiversity using forest structure indicators based on airborne laser scanning data. Forest Ecology and Management. 546. 121376–121376. 22 indexed citations
5.
Liski, Eero, et al.. (2022). Comparison of neural networks and k-nearest neighbors methods in forest stand variable estimation using airborne laser data. SHILAP Revista de lepidopterología. 4. 100012–100012. 10 indexed citations
6.
Hansen, Endre, Terje Gobakken, Svein Solberg, et al.. (2015). Relative Efficiency of ALS and InSAR for Biomass Estimation in a Tanzanian Rainforest. Remote Sensing. 7(8). 9865–9885. 24 indexed citations
7.
Kangas, Annika & Kari Korhonen. (2015). Application of non-parametric kernel regression and nearest-neighbor regression for generalizing sample tree information. Jukuri (Natural Resources Institute Finland (Luke)).
8.
Eyvindson, Kyle & Annika Kangas. (2014). Using a Compromise Programming Framework to Integrating Spatially Specific Preference Information for Forest Management Problems. Journal of Multi-Criteria Decision Analysis. 22(1-2). 3–15. 10 indexed citations
9.
Korpela, Ilkka, et al.. (2014). Tree species identification in aerial image data using directional reflectance signatures. Silva Fennica. 48(3). 32 indexed citations
10.
11.
Leskinen, Pekka, Teppo Hujala, Jukka Tikkanen, et al.. (2009). Adaptive Decision Analysis in Forest Management Planning. Forest Science. 55(2). 95–108. 17 indexed citations
12.
Tokola, Timo, et al.. (2009). A GIS-based stand management system for estimating local energy wood supplies. Biomass and Bioenergy. 33(9). 1278–1288. 17 indexed citations
13.
Næsset, Erik, Terje Gobakken, Annika Kangas, et al.. (2006). Extending and improving methods for operational stand-wise forest inventories utilizing multi-resolution airborne laser scanner data. 75–79. 7 indexed citations
14.
Mehtätalo, Lauri & Annika Kangas. (2005). An approach to optimizing field data collection in an inventory by compartments. Canadian Journal of Forest Research. 35(1). 100–112. 11 indexed citations
15.
Kangas, Annika, et al.. (2004). Accuracy of partially visually assessed stand characteristics: a case study of Finnish forest inventory by compartments. Canadian Journal of Forest Research. 34(4). 916–930. 42 indexed citations
16.
Sironen, Susanna, Annika Kangas, Matti Maltamo, & Jyrki Kangas. (2003). Estimating individual tree growth with nonparametric methods. Canadian Journal of Forest Research. 33(3). 444–449. 22 indexed citations
17.
Kangas, Annika, et al.. (2000). Calibrating Predicted Diameter Distribution with Additional Information. Forest Science. 46(3). 390–396. 52 indexed citations
18.
Kangas, Annika & Matti Maltamo. (2000). Performance of percentile based diameter distribution prediction and Weibull method in independent data sets. Silva Fennica. 34(4). 53 indexed citations
19.
Kangas, Annika & Jyrki Kangas. (1999). Optimization bias in forest management planning solutions due to errors in forest variables. Silva Fennica. 33(4). 35 indexed citations
20.
Korhonen, Kari & Annika Kangas. (1997). Application of nearest‐neighbour regression for generalizing sample tree information. Scandinavian Journal of Forest Research. 12(1). 97–101. 39 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Daniel Mandallaz Breakdown of academic impact, for papers by Zhongke Feng Breakdown of academic impact, for papers by Brian F. Walters Breakdown of academic impact, for papers by Tero Heinonen Breakdown of academic impact, for papers by Robert E. Froese Breakdown of academic impact, for papers by Marco A. Contreras Breakdown of academic impact, for papers by Ninni Saarinen Breakdown of academic impact, for papers by Chris J. Cieszewski Breakdown of academic impact, for papers by Hans T. Schreuder Breakdown of academic impact, for papers by Jari Vauhkonen
Rankless by CCL
2026