Matthew F. McCabe

20.2k total citations · 6 hit papers
225 papers, 13.0k citations indexed

About

Matthew F. McCabe is a scholar working on Global and Planetary Change, Environmental Engineering and Ecology. According to data from OpenAlex, Matthew F. McCabe has authored 225 papers receiving a total of 13.0k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Global and Planetary Change, 94 papers in Environmental Engineering and 71 papers in Ecology. Recurrent topics in Matthew F. McCabe's work include Remote Sensing in Agriculture (62 papers), Plant Water Relations and Carbon Dynamics (61 papers) and Climate variability and models (47 papers). Matthew F. McCabe is often cited by papers focused on Remote Sensing in Agriculture (62 papers), Plant Water Relations and Carbon Dynamics (61 papers) and Climate variability and models (47 papers). Matthew F. McCabe collaborates with scholars based in Saudi Arabia, United States and Australia. Matthew F. McCabe's co-authors include Jason P. Evans, Rasmus Houborg, Eric F. Wood, J. D. Kalma, Richard de Jeu, Albert I. J. M. van Dijk, Tim R. McVicar, A. Ershadi, Kasper Johansen and Yi Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and PLoS ONE.

In The Last Decade

Matthew F. McCabe

212 papers receiving 12.8k citations

Hit Papers

Estimating Land Surface E... 2008 2026 2014 2020 2008 2012 2011 2015 2017 250 500 750
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. Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data
    2008 930 citations Matthew F. McCabe et al. profile →
  2. Trend-preserving blending of passive and active microwave soil moisture retrievals
    2012 594 citations Matthew F. McCabe, Jason P. Evans et al. Remote Sensing of Environment profile →
  3. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals
    2011 543 citations Albert I. J. M. van Dijk, Matthew F. McCabe et al. Hydrology and earth system sciences profile →
  4. Recent reversal in loss of global terrestrial biomass
    2015 457 citations Albert I. J. M. van Dijk, Matthew F. McCabe et al. profile →
  5. The future of Earth observation in hydrology
    2017 321 citations Matthew F. McCabe, Diego G. Miralles et al. Hydrology and earth system sciences profile →
  6. Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future
    2021 201 citations Lixin Wang, Matthew F. McCabe et al. Remote Sensing of Environment profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matthew F. McCabe 7.4k 4.8k 3.9k 3.3k 3.0k 225 13.0k
Pierre Gentine 11.7k 1.6× 3.2k 0.7× 5.9k 1.5× 2.4k 0.7× 2.7k 0.9× 270 15.2k
John S. Kimball 8.6k 1.2× 4.1k 0.9× 7.0k 1.8× 4.2k 1.3× 2.8k 0.9× 309 16.0k
Zhongbo Su 8.1k 1.1× 5.9k 1.2× 5.6k 1.4× 2.5k 0.8× 3.1k 1.0× 428 13.7k
Martin Jung 10.6k 1.4× 2.8k 0.6× 3.9k 1.0× 4.5k 1.4× 2.3k 0.8× 102 14.7k
Massimo Menenti 6.8k 0.9× 4.4k 0.9× 2.7k 0.7× 3.4k 1.0× 2.1k 0.7× 318 10.7k
David R. Legates 6.2k 0.8× 2.8k 0.6× 4.0k 1.0× 1.5k 0.5× 3.2k 1.1× 77 11.1k
Christopher Hain 6.8k 0.9× 2.7k 0.6× 2.3k 0.6× 1.8k 0.6× 2.1k 0.7× 159 9.2k
Yongjiu Dai 6.1k 0.8× 2.7k 0.6× 4.3k 1.1× 1.7k 0.5× 1.9k 0.6× 177 9.9k
M. Susan Moran 6.6k 0.9× 5.6k 1.2× 3.5k 0.9× 5.3k 1.6× 1.5k 0.5× 161 12.8k
Diego G. Miralles 14.7k 2.0× 4.3k 0.9× 7.8k 2.0× 2.1k 0.6× 6.3k 2.1× 165 19.5k

Countries citing papers authored by Matthew F. McCabe

Since Specialization
Citations

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

Fields of papers citing papers by Matthew F. McCabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew F. McCabe. 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 Matthew F. McCabe. The network helps show where Matthew F. McCabe may publish in the future.

Co-authorship network of co-authors of Matthew F. McCabe

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew F. McCabe. A scholar is included among the top collaborators of Matthew F. McCabe 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 Matthew F. McCabe. Matthew F. McCabe 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.
Wang, Xuetong, Oscar M. Baez‐Villanueva, Amy Green, et al.. (2025). Saudi Rainfall (SaRa): hourly 0.1° gridded rainfall (1979–present) for Saudi Arabia via machine learning fusion of satellite and model data. Hydrology and earth system sciences. 29(19). 4983–5003. 1 indexed citations
2.
Courault, Dominique, Claude Doussan, Mohammad El Hajj, et al.. (2025). Integration of sentinel-2 data into the SIMETAW model for assessing irrigation water requirements and evapotranspiration. Agricultural Water Management. 317. 109637–109637.
3.
Johansen, Kasper, et al.. (2024). Quantifying mangrove carbon assimilation rates using UAV imagery. Scientific Reports. 14(1). 4648–4648. 3 indexed citations
4.
Song, Yang, Josep Peñuelas, Philippe Ciais, et al.. (2024). Recent Water Constraints Mediate the Dominance of Climate and Atmospheric CO2 on Vegetation Growth Across China. Earth s Future. 12(6). 12 indexed citations
5.
Courault, Dominique, et al.. (2024). High-resolution satellite imagery to assess orchard characteristics impacting water use. Agricultural Water Management. 295. 108763–108763. 6 indexed citations
6.
Kim, Youngwook, Hotaek Park, John S. Kimball, Andreas Colliander, & Matthew F. McCabe. (2023). Global estimates of daily evapotranspiration using SMAP surface and root-zone soil moisture. Remote Sensing of Environment. 298. 113803–113803. 21 indexed citations
7.
Hong, Pei‐Ying, Himanshu Mishra, Daniele Daffonchio, & Matthew F. McCabe. (2023). Greening initiatives in the Middle East can leverage urban infrastructure to enhance sustainable water use. Nature Water. 1(12). 996–999. 3 indexed citations
8.
Rouault, Pascale, Dominique Courault, Raúl López‐Lozano, et al.. (2023). GRASS COVER, TREE DENSITY, AND LEAF DEVELOPMENT OF MEDITERRANEAN ORCHARDS FROM HIGH RESOLUTION DATA. SHILAP Revista de lepidopterología. XLVIII-1/W2-2023. 1531–1536.
9.
Kenawy, Ahmed El, Juan Ignacio López‐Moreno, Matthew F. McCabe, et al.. (2021). The impact of COVID-19 lockdowns on surface urban heat island changes and air-quality improvements across 21 major cities in the Middle East. Environmental Pollution. 288. 117802–117802. 61 indexed citations
10.
Manfreda, Salvatore, Helge Aasen, M. R. James, et al.. (2020). Current Practices in UAS-based Environmental Monitoring. Remote Sensing. 12(6). 1001–1001. 169 indexed citations
11.
Angel, Yoseline, et al.. (2019). A Random Forest Machine Learning Approach for the Retrieval of Leaf Chlorophyll Content in Wheat. Remote Sensing. 11(8). 920–920. 168 indexed citations
12.
Ziliani, Matteo G., Stephen Parkes, Ibrahim Hoteit, & Matthew F. McCabe. (2018). Intra-Season Crop Height Variability at Commercial Farm Scales Using a Fixed-Wing UAV. Remote Sensing. 10(12). 2007–2007. 67 indexed citations
13.
Kenawy, Ahmed El, Matthew F. McCabe, Juan Ignacio López‐Moreno, et al.. (2018). Spatial assessment of the performance of multiple high‐resolution satellite‐based precipitation data sets over the Middle East. International Journal of Climatology. 39(5). 2522–2543. 13 indexed citations
14.
Michel, D., Carlos Jiménez, Diego G. Miralles, et al.. (2016). The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms. Hydrology and earth system sciences. 20(2). 803–822. 177 indexed citations
15.
16.
López, Oliver, Matthew F. McCabe, & Rasmus Houborg. (2015). Evaluation of multiple satellite evaporation products in two dryland regions using GRACE. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 1 indexed citations
17.
Mariethoz, Grégoire, et al.. (2015). A Multiple-point Geostatistics Method for filling gaps in Landsat ETM+ SLC-off images. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 1 indexed citations
18.
Griffiths, Alan D., Stephen Parkes, Scott Chambers, Matthew F. McCabe, & Alastair G. Williams. (2013). Improved mixing height monitoring through a combination of lidar and radon measurements. Atmospheric measurement techniques. 6(2). 207–218. 44 indexed citations
19.
Mueller, Brigitte, Martin Hirschi, Carlos Jiménez, et al.. (2013). Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis. Hydrology and earth system sciences. 17(10). 3707–3720. 298 indexed citations
20.
Hughes, Catherine E., et al.. (2011). A comparison between direct and pan-derived measurements of the isotopic composition of atmospheric waters. Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation.. 2 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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