Heather McNairn

13.1k total citations · 3 hit papers
203 papers, 7.7k citations indexed

About

Heather McNairn is a scholar working on Environmental Engineering, Aerospace Engineering and Ecology. According to data from OpenAlex, Heather McNairn has authored 203 papers receiving a total of 7.7k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Environmental Engineering, 90 papers in Aerospace Engineering and 83 papers in Ecology. Recurrent topics in Heather McNairn's work include Soil Moisture and Remote Sensing (131 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (90 papers) and Remote Sensing in Agriculture (80 papers). Heather McNairn is often cited by papers focused on Soil Moisture and Remote Sensing (131 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (90 papers) and Remote Sensing in Agriculture (80 papers). Heather McNairn collaborates with scholars based in Canada, United States and India. Heather McNairn's co-authors include Jiali Shang, Catherine Champagne, Brian Brisco, Anna Pacheco, Amine Merzouki, Mehdi Hosseini, Xianfeng Jiao, Saeid Homayouni, Aaron Berg and David R. Lapen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Geophysical Research Letters.

In The Last Decade

Heather McNairn

193 papers receiving 7.4k citations

Hit Papers

align trajectories sort by overperformance

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.

Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

2014 356 citations Heather McNairn, Catherine Champagne et al. profile →
Radar Remote Sensing of Agricultural Canopies: A Review

2017 274 citations Heather McNairn et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing profile →
Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

2020 269 citations Heather McNairn et al. Remote Sensing of Environment profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Heather McNairn Canada	46	4.8k	3.6k	2.4k	2.4k	1.4k	203	7.7k
Jiali Shang Canada	43	2.8k 0.6×	3.3k 0.9×	1.4k 0.6×	1.5k 0.6×	1.8k 1.3×	181	6.7k
Nicolas Baghdadi France	53	5.9k 1.2×	2.4k 0.7×	3.2k 1.3×	2.3k 1.0×	517 0.4×	268	8.1k
M. Susan Moran United States	61	5.6k 1.1×	5.3k 1.5×	3.5k 1.5×	1.4k 0.6×	2.4k 1.7×	161	12.8k
Guangjian Yan China	43	6.6k 1.4×	4.0k 1.1×	2.9k 1.2×	651 0.3×	1.1k 0.8×	238	9.8k
Olivier Hagolle France	39	2.1k 0.4×	3.0k 0.8×	1.8k 0.7×	614 0.3×	725 0.5×	116	5.3k
Michel M. Verstraete Italy	53	4.0k 0.8×	5.7k 1.6×	2.8k 1.1×	652 0.3×	1.1k 0.8×	136	9.8k
Jean‐Louis Roujean France	39	3.5k 0.7×	4.2k 1.2×	2.3k 1.0×	531 0.2×	1.1k 0.8×	142	7.2k
Qinhuo Liu China	41	3.8k 0.8×	3.2k 0.9×	2.8k 1.2×	475 0.2×	687 0.5×	488	7.4k
P. Lewis United Kingdom	43	3.9k 0.8×	5.4k 1.5×	1.3k 0.6×	362 0.2×	1.3k 0.9×	124	8.2k
Ferran Gascon Italy	24	2.0k 0.4×	3.2k 0.9×	1.0k 0.4×	453 0.2×	524 0.4×	88	5.3k

Countries citing papers authored by Heather McNairn

Since Specialization

Citations

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

Fields of papers citing papers by Heather McNairn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heather McNairn

This figure shows the co-authorship network connecting the top 25 collaborators of Heather McNairn. A scholar is included among the top collaborators of Heather McNairn 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 Heather McNairn. Heather McNairn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

McNairn, Heather, et al.. (2025). Automating sentinel-1 SLC product processing: Parallelization and optimization for efficient polarimetric parameter extraction. MethodsX. 14. 103253–103253.

McNairn, Heather, et al.. (2023). Reinforcing Our Commitment: Why DEI Matters for the IEEE GRSS [Technical Committees]. IEEE Geoscience and Remote Sensing Magazine. 11(3). 126–129.

Homayouni, Saeid, et al.. (2022). Regional Crop Characterization Using Multi-Temporal Optical and Synthetic Aperture Radar Earth Observations Data. Canadian Journal of Remote Sensing. 48(2). 258–277. 10 indexed citations

McNairn, Heather, et al.. (2022). A Meta-Analysis of Remote Sensing Technologies and Methodologies for Crop Characterization. Remote Sensing. 14(22). 5633–5633. 15 indexed citations

Hosseini, Mehdi, et al.. (2022). SOYBEAN YIELD FORECAST USING DUAL-POLARIMETRIC C-BAND SYNTHETIC APERTURE RADAR. SHILAP Revista de lepidopterología. V-3-2022. 405–410. 5 indexed citations

Kraatz, Simon, Nathan Torbick, Xianfeng Jiao, et al.. (2021). Comparison between Dense L-Band and C-Band Synthetic Aperture Radar (SAR) Time Series for Crop Area Mapping over a NISAR Calibration-Validation Site. Agronomy. 11(2). 273–273. 16 indexed citations

Huang, Xiaodong, et al.. (2021). Rice Inundation Assessment Using Polarimetric UAVSAR Data. Earth and Space Science. 8(3). e2020EA001554–e2020EA001554. 11 indexed citations

Robertson, Laura Dingle, Andrew Davidson, Heather McNairn, et al.. (2020). Synthetic Aperture Radar (SAR) image processing for operational space-based agriculture mapping. International Journal of Remote Sensing. 41(18). 7112–7144. 33 indexed citations

Dong, Taifeng, Jiangui Liu, Budong Qian, et al.. (2020). Estimating crop biomass using leaf area index derived from Landsat 8 and Sentinel-2 data. ISPRS Journal of Photogrammetry and Remote Sensing. 168. 236–250. 105 indexed citations

10.

McNairn, Heather, et al.. (2020). Estimation of Crop Biomass and Leaf Area Index from Multitemporal and Multispectral Imagery Using Machine Learning Approaches. Canadian Journal of Remote Sensing. 46(1). 84–99. 31 indexed citations

11.

Robertson, Laura Dingle, Andrew Davidson, Heather McNairn, et al.. (2020). C-band synthetic aperture radar (SAR) imagery for the classification of diverse cropping systems. International Journal of Remote Sensing. 41(24). 9628–9649. 19 indexed citations

12.

Homayouni, Saeid, et al.. (2019). Crop biomass estimation using multi regression analysis and neural networks from multitemporal L-band polarimetric synthetic aperture radar data. International Journal of Remote Sensing. 40(17). 6822–6840. 22 indexed citations

13.

Djamai, Najib, Richard Fernandes, Marie Weiss, Heather McNairn, & Kalifa Goı̈ta. (2019). Validation of the Sentinel Simplified Level 2 Product Prototype Processor (SL2P) for mapping cropland biophysical variables using Sentinel-2/MSI and Landsat-8/OLI data. Remote Sensing of Environment. 225. 416–430. 83 indexed citations

14.

Mahdianpari, Masoud, Fariba Mohammadimanesh, Heather McNairn, et al.. (2019). Mid-season Crop Classification Using Dual-, Compact-, and Full-Polarization in Preparation for the Radarsat Constellation Mission (RCM). Remote Sensing. 11(13). 1582–1582. 31 indexed citations

15.

Zwieback, Simon, Andreas Colliander, Michael H. Cosh, et al.. (2018). Estimating time-dependent vegetation biases in the SMAP soil moisture product. Hydrology and earth system sciences. 22(8). 4473–4489. 38 indexed citations

16.

Li, Qiangzi, Jiangui Liu, Jiali Shang, et al.. (2018). Corrections to “Image Classification Using RapidEye Data: Integration of Spectral and Textual Features in a Random Forest Classifier” [Dec 17 5334-5349]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(7). 2571–2571. 1 indexed citations

17.

McNairn, Heather, et al.. (2017). Application of HEC-HMS in a Cold Region Watershed and Use of RADARSAT-2 Soil Moisture in Initializing the Model. Hydrology. 4(1). 9–9. 56 indexed citations

18.

Li, Qiangzi, Jiangui Liu, Jiali Shang, et al.. (2017). Image Classification Using RapidEye Data: Integration of Spectral and Textual Features in a Random Forest Classifier. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 10(12). 5334–5349. 52 indexed citations

19.

Kim, Seung Bum, Huan Huang, Leung Tsang, et al.. (2014). Soil moisture retrieval using L-band time-series SAR data from the SMAPVEX12 experiment. 1–4. 5 indexed citations

20.

Wang, Chen, Jiali Shang, P.W. Vachon, & Heather McNairn. (2011). Crop Change Assessment Using Polarimetric RADARSAT-2 Data. ESASP. 695. 43. 1 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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