Mila Koeva

1.8k total citations · 1 hit paper
95 papers, 1.3k citations indexed

About

Mila Koeva is a scholar working on Environmental Engineering, Building and Construction and Geology. According to data from OpenAlex, Mila Koeva has authored 95 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Environmental Engineering, 50 papers in Building and Construction and 34 papers in Geology. Recurrent topics in Mila Koeva's work include Remote Sensing and LiDAR Applications (53 papers), 3D Modeling in Geospatial Applications (48 papers) and 3D Surveying and Cultural Heritage (34 papers). Mila Koeva is often cited by papers focused on Remote Sensing and LiDAR Applications (53 papers), 3D Modeling in Geospatial Applications (48 papers) and 3D Surveying and Cultural Heritage (34 papers). Mila Koeva collaborates with scholars based in Netherlands, Australia and Germany. Mila Koeva's co-authors include Rohan Bennett, M. Gerke, Francesco Nex, C. Lemmen, Claudia Stöcker, Claudio Persello, J.A. Zevenbergen, Sander Oude Elberink, Sophie Crommelinck and George Vosselman and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Remote Sensing.

In The Last Decade

Mila Koeva

89 papers receiving 1.2k citations

Hit Papers

Digital twin of a city: Review of technology serving city... 2022 2026 2023 2024 2022 40 80 120
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. Digital twin of a city: Review of technology serving city needs
    2022 123 citations Mila Koeva, Sander Oude Elberink et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mila Koeva Netherlands 20 554 442 375 220 143 95 1.3k
Joon Heo South Korea 26 726 1.3× 454 1.0× 711 1.9× 246 1.1× 143 1.0× 150 2.2k
Renzhong Guo China 19 285 0.5× 354 0.8× 173 0.5× 469 2.1× 85 0.6× 108 1.4k
Alias Abdul Rahman Malaysia 16 313 0.6× 617 1.4× 273 0.7× 131 0.6× 66 0.5× 133 1.2k
Charalabos Ioannidis Greece 18 335 0.6× 208 0.5× 473 1.3× 88 0.4× 144 1.0× 84 1.0k
Haihong Zhu China 20 445 0.8× 250 0.6× 378 1.0× 163 0.7× 135 0.9× 79 1.3k
Francisco Javier Ariza López Spain 16 300 0.5× 132 0.3× 168 0.4× 65 0.3× 204 1.4× 111 1.0k
Peter van Oosterom Netherlands 28 480 0.9× 1.7k 3.9× 634 1.7× 160 0.7× 218 1.5× 158 2.7k
Jianhua Gong China 21 330 0.6× 230 0.5× 94 0.3× 344 1.6× 335 2.3× 88 1.2k
Lars Harrie Sweden 23 258 0.5× 677 1.5× 335 0.9× 157 0.7× 123 0.9× 115 1.7k
Miro Govedarica Serbia 16 191 0.3× 245 0.6× 131 0.3× 96 0.4× 189 1.3× 76 798

Countries citing papers authored by Mila Koeva

Since Specialization
Citations

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

Fields of papers citing papers by Mila Koeva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mila Koeva

This figure shows the co-authorship network connecting the top 25 collaborators of Mila Koeva. A scholar is included among the top collaborators of Mila Koeva 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 Mila Koeva. Mila Koeva 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.
Dai, Shaoqing, et al.. (2025). Toward 3D hedonic price model for vertically developed cities using street view images and machine learning methods. Habitat International. 156. 103288–103288. 1 indexed citations
2.
Persello, Claudio, et al.. (2024). CadastreVision: A benchmark dataset for cadastral boundary delineation from multi-resolution earth observation images. ISPRS Journal of Photogrammetry and Remote Sensing. 217. 91–100. 1 indexed citations
3.
Koeva, Mila, et al.. (2024). Urban digital twin-based solution using geospatial information for solid waste management. Sustainable Cities and Society. 115. 105798–105798. 10 indexed citations
4.
Hussain, Ejaz, C. Lemmen, J.A. Zevenbergen, et al.. (2024). Deriving requirements for integrated and standardised cadastre profile from the legacy Board of Revenue and the contemporary land administration systems. Survey Review. 57(401). 99–119. 1 indexed citations
5.
6.
Koeva, Mila, et al.. (2023). Analysis of Potential Disruptions From Earthquakes in Istanbul and 3D Model Based Risk Communication. University of Twente Research Information. 13(2). 1 indexed citations
7.
Bennett, Rohan, et al.. (2023). Furthering Automatic Feature Extraction for Fit-for-Purpose Cadastral Updating: Cases from Peri-Urban Addis Ababa, Ethiopia. Remote Sensing. 15(17). 4155–4155. 3 indexed citations
8.
Koeva, Mila, et al.. (2023). Towards Digital Twinning on the Web: Heterogeneous 3D Data Fusion Based on Open-Source Structure. Remote Sensing. 15(3). 721–721. 15 indexed citations
9.
Koeva, Mila, et al.. (2023). Planning Walkable Cities: Generative Design Approach towards Digital Twin Implementation. Remote Sensing. 15(4). 1088–1088. 11 indexed citations
10.
Koeva, Mila, Rohan Bennett, & Claudio Persello. (2022). Remote Sensing for Land Administration 2.0. 3 indexed citations
11.
12.
Koeva, Mila, et al.. (2021). Geospatial Tool and Geocloud Platform Innovations: A Fit-for-Purpose Land Administration Assessment. Land. 10(6). 557–557. 16 indexed citations
13.
Koeva, Mila, Claudia Stöcker, Sophie Crommelinck, et al.. (2020). Innovative Remote Sensing Methodologies for Kenyan Land Tenure Mapping. Remote Sensing. 12(2). 273–273. 43 indexed citations
14.
Brito, Patricia, et al.. (2020). The Spatial Dimension of COVID-19: The Potential of Earth Observation Data in Support of Slum Communities with Evidence from Brazil. ISPRS International Journal of Geo-Information. 9(9). 557–557. 25 indexed citations
15.
Koeva, Mila, et al.. (2019). Towards 3D Indoor Cadastre Based on Change Detection from Point Clouds. Remote Sensing. 11(17). 1972–1972. 20 indexed citations
16.
Crommelinck, Sophie, Mila Koeva, Michael Ying Yang, & George Vosselman. (2019). Application of Deep Learning for Delineation of Visible Cadastral Boundaries from Remote Sensing Imagery. Remote Sensing. 11(21). 2505–2505. 40 indexed citations
17.
Koeva, Mila, et al.. (2017). Public participation using 3D city models. Data Archiving and Networked Services (DANS). 2 indexed citations
18.
Bennett, Rohan, et al.. (2016). Cadastral boundaries from point clouds? : Towards semi-automated cadastral boundary extraction from ALS data. Swinburne Research Bank (Swinburne University of Technology). 30(12). 16–17. 6 indexed citations
19.
Koeva, Mila, et al.. (2016). Towards automated detection of visual cadastral boundaries : initial investigation of imagery, algorithms and perceptions.. Swinburne Research Bank (Swinburne University of Technology). 30(8). 23–25. 2 indexed citations
20.
Koeva, Mila & Sander Oude Elberink. (2016). Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds. University of Twente Research Information. 169–182. 5 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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