Geoffrey J. Hay

7.6k total citations · 3 hit papers
53 papers, 5.5k citations indexed

About

Geoffrey J. Hay is a scholar working on Ecology, Environmental Engineering and Media Technology. According to data from OpenAlex, Geoffrey J. Hay has authored 53 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Ecology, 22 papers in Environmental Engineering and 19 papers in Media Technology. Recurrent topics in Geoffrey J. Hay's work include Remote Sensing in Agriculture (23 papers), Remote-Sensing Image Classification (19 papers) and Land Use and Ecosystem Services (16 papers). Geoffrey J. Hay is often cited by papers focused on Remote Sensing in Agriculture (23 papers), Remote-Sensing Image Classification (19 papers) and Land Use and Ecosystem Services (16 papers). Geoffrey J. Hay collaborates with scholars based in Canada, United States and Austria. Geoffrey J. Hay's co-authors include Thomas Blaschke, Gang Chen, Danielle J. Marceau, Stefan Lang, Michael A. Wulder, Guillermo Castilla, Dirk Tiede, Maggi Kelly, Elisabeth A. Addink and H.M.A. van der Werff and has published in prestigious journals such as Remote Sensing of Environment, Journal of Hydrology and International Journal of Remote Sensing.

In The Last Decade

Geoffrey J. Hay

53 papers receiving 5.1k citations

Hit Papers

Geographic Object-Based Image Analysis – Towards a new pa... 2008 2026 2014 2020 2013 2008 2012 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Geoffrey J. Hay Canada 32 2.5k 2.3k 2.0k 1.7k 1.4k 53 5.5k
Giorgos Mountrakis United States 26 2.6k 1.0× 1.6k 0.7× 1.9k 0.9× 1.4k 0.8× 1.2k 0.8× 68 5.1k
Dirk Tiede Austria 33 2.2k 0.9× 2.2k 1.0× 2.1k 1.0× 1.6k 0.9× 1.3k 0.9× 165 6.3k
John Nicol United Kingdom 15 2.1k 0.8× 969 0.4× 2.7k 1.3× 1.6k 0.9× 1.5k 1.1× 27 5.7k
Timothy A. Warner United States 35 2.2k 0.9× 1.3k 0.6× 1.7k 0.8× 1.4k 0.8× 892 0.6× 110 4.9k
Feng Ling China 38 1.9k 0.7× 1.6k 0.7× 2.0k 1.0× 1.4k 0.8× 1.0k 0.8× 179 4.9k
Xuehong Chen China 32 2.8k 1.1× 1.6k 0.7× 2.5k 1.2× 1.7k 1.0× 1.6k 1.2× 115 5.6k
Pat S. Chavez United States 19 2.4k 1.0× 2.6k 1.1× 1.9k 0.9× 1.4k 0.8× 1.1k 0.8× 49 6.3k
Daniel L. Civco United States 29 1.3k 0.5× 1.4k 0.6× 2.3k 1.1× 1.2k 0.7× 776 0.6× 80 4.8k
Xiaolin Zhu China 45 5.0k 2.0× 2.3k 1.0× 3.9k 1.9× 3.0k 1.8× 2.0k 1.5× 160 9.5k
Masoud Mahdianpari Canada 34 2.5k 1.0× 1.0k 0.4× 2.5k 1.2× 1.9k 1.1× 902 0.7× 134 5.6k

Countries citing papers authored by Geoffrey J. Hay

Since Specialization
Citations

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

Fields of papers citing papers by Geoffrey J. Hay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geoffrey J. Hay. 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 Geoffrey J. Hay. The network helps show where Geoffrey J. Hay may publish in the future.

Co-authorship network of co-authors of Geoffrey J. Hay

This figure shows the co-authorship network connecting the top 25 collaborators of Geoffrey J. Hay. A scholar is included among the top collaborators of Geoffrey J. Hay 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 Geoffrey J. Hay. Geoffrey J. Hay 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.
Lang, Stefan, Geoffrey J. Hay, Andrea Baraldi, Dirk Tiede, & Thomas Blaschke. (2019). GEOBIA Achievements and Spatial Opportunities in the Era of Big Earth Observation Data. ISPRS International Journal of Geo-Information. 8(11). 474–474. 36 indexed citations
2.
Griffith, David & Geoffrey J. Hay. (2018). Integrating GEOBIA, Machine Learning, and Volunteered Geographic Information to Map Vegetation over Rooftops. ISPRS International Journal of Geo-Information. 7(12). 462–462. 11 indexed citations
4.
Hay, Geoffrey J., et al.. (2014). Supporting Urban Energy Efficiency with Volunteered Roof Information and the Google Maps API. Remote Sensing. 6(10). 9691–9711. 8 indexed citations
5.
Blaschke, Thomas, Geoffrey J. Hay, Maggi Kelly, et al.. (2013). Geographic Object-Based Image Analysis – Towards a new paradigm. ISPRS Journal of Photogrammetry and Remote Sensing. 87(100). 180–191. 1315 indexed citations breakdown →
6.
Rahman, Mir Mustafizur, et al.. (2013). Geographic Object-Based Mosaicing (OBM) of High-Resolution Thermal Airborne Imagery (TABI-1800) to Improve the Interpretation of Urban Image Objects. IEEE Geoscience and Remote Sensing Letters. 10(4). 918–922. 9 indexed citations
7.
Powers, Ryan, Geoffrey J. Hay, & Gang Chen. (2011). How wetland type and area differ through scale: A GEOBIA case study in Alberta's Boreal Plains. Remote Sensing of Environment. 117. 135–145. 53 indexed citations
8.
Chen, Gang, Kaiguang Zhao, Gregory J. McDermid, & Geoffrey J. Hay. (2011). The influence of sampling density on geographically weighted regression: a case study using forest canopy height and optical data. International Journal of Remote Sensing. 33(9). 2909–2924. 28 indexed citations
9.
Hay, Geoffrey J. & Thomas Blaschke. (2010). Special Issue on Geographic Object-Based Image Analysis (GEOBIA).. 76(2). 121–122. 40 indexed citations
10.
Blaschke, Thomas, Stefan Lang, & Geoffrey J. Hay. (2008). Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Medical Entomology and Zoology. 324 indexed citations
11.
Hay, Geoffrey J., et al.. (2008). Object-Based Image Analysis. DIAL (Catholic University of Leuven). 498 indexed citations breakdown →
12.
Castilla, Guillermo, et al.. (2008). The impact of thematic resolution on the patch-mosaic model of natural landscapes. Landscape Ecology. 24(1). 15–23. 56 indexed citations
13.
Castilla, Guillermo & Geoffrey J. Hay. (2007). Uncertainties in land use data. Hydrology and earth system sciences. 11(6). 1857–1868. 40 indexed citations
14.
Hay, Geoffrey J., et al.. (2005). An automated object-based approach for the multiscale image segmentation of forest scenes. International Journal of Applied Earth Observation and Geoinformation. 7(4). 339–359. 253 indexed citations
15.
Hay, Geoffrey J.. (2005). Bridging scales and epistemologies: An introduction. International Journal of Applied Earth Observation and Geoinformation. 7(4). 249–252. 5 indexed citations
16.
Hay, Geoffrey J., Thomas Blaschke, Danielle J. Marceau, & André Bouchard. (2003). A comparison of three image-object methods for the multiscale analysis of landscape structure. ISPRS Journal of Photogrammetry and Remote Sensing. 57(5-6). 327–345. 304 indexed citations
17.
Hay, Geoffrey J., et al.. (2002). A scale-space primer for exploring and quantifying complex landscapes. Ecological Modelling. 153(1-2). 27–49. 73 indexed citations
18.
Blaschke, Thomas & Geoffrey J. Hay. (2001). Object-oriented image analysis and scale-space: Theory and methods for modeling and evaluating multi-scale landscape structure. 22–29. 103 indexed citations
19.
Hay, Geoffrey J., et al.. (1997). A survey of the fishes of the Kunene River, Namibia. 1997. 129–141. 6 indexed citations
20.
Hay, Geoffrey J.. (1994). Visualizing 3-D texture: a three dimensional structural approach to model forest texture. 20 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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