!!Giles Foody - Publications
\\
Citations in Google Scholar, July 2022 – total >35,000, h-index = 92 (of these sole or first author of 56).
\\ \\
Ranked 2nd in world for citations within field (out of 44,176) over career – see Ioannidis JPA, Boyack KW, Baas J (2020) Updated science-wide author databases of standardized citation indicators. ''PLoS Biol'' 18(10): e3000918.\\
\\

__10 key recent publications:__\\
\\
1.  Boyd, D., Perrat, B., Li, X., Jackson, B., Landman, T., Ling, F., Bales, K., Fitzpatrick, A., Goulding, J., Marsh, S. and Foody, G., 2021. Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space, ''Humanities and Social Sciences Communications'', 8, 111, [https://doi.org/10.1057/s41599-021-00792-z].\\
\\
2.  Foody, G. M., 2021. Impacts of ignorance on the accuracy of image classification and thematic mapping, ''Remote Sensing of Environment'', 259, p112367, [https://doi.org/10.1016/j.rse.2021.112367].\\
\\
3.  Philipson, C., Cutler, M., Brodrick, P. G., Asner, G. P., Boyd, D. S., Costa, P. M., Fiddes, J., Foody, G. M., van der Heijden, G. M. F., Ledo, A., Lincoln, P. R., Margrove, J. A., Martin, R. E., Milne, S., Pinard, M. A., Reynolds, G., Snoep, M., Tangki, H., Wai, Y. S., Wheeler, C. E. and Burslem, D. F. R. P., 2020. Active restoration accelerates the carbon recovery of human modified-tropical forests, ''Science'', 369 (6505), 838-841. [https://doi.org/10.1126/science.aay4490].\\
\\
4.  Foody, G.M., 2020. Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification, ''Remote Sensing of Environment'', 239, p.111630.\\
\\
5.  Foody, G. M., Ling, F., Boyd, D. S., Li, X., and Wardlaw, J., 2019. Earth observation and machine learning to meet sustainable development goal 8.7: mapping sites associated with slavery from space, ''Remote Sensing'', 11 (3), 266 (12pp).\\
\\
6.  Stehman, S.V., Fonte, C.C., Foody, G.M. and See, L., 2018. Using volunteered geographic information (VGI) in design-based statistical inference for area estimation and accuracy assessment of land cover, ''Remote Sensing of Environment'', 212, 47-59.\\
\\
7. Li, X, Ling, F., Foody, G. M., Ge, Y., Zhang, Y. and Du, Y., 2017. Generating a series of fine spatial and temporal resolution land cover maps by fusing coarse spatial resolution remotely sensed imagery and fine spatial resolution land cover maps, ''Remote Sensing of Environment'', 196, 293–311.\\
\\
8.  Foody, G., See, L., Fritz, S, Mooney, P., Fonte, C, Olteanu-Raimond, A-M., and Antoniou, V. (editors), 2017, ''Mapping and the Citizen Sensor'', Ubiquity Press, London, 398pp; open access – available at: [https://doi.org/10.5334/bbf].\\
\\
9. Olteanu-Raimond, A-M., Hart, G., Touya, G., Foody, G. Kellenberger, T. and Demetriou, D., 2017. The scale of VGI in map production: a perspective of European National Mapping Agencies, ''Transactions in GIS'', 21, 74-90.\\
\\
10.  See, L., Mooney, P., Foody, G., Bastin, L., Comber, A., Estima, J., Fritz, S., Kerle, N., Jiang, B., Laakso, M., Liu, H-Y., Milčinski, G., Nikšič, M., Painho, M., Pődör, A., Olteanu-Raimond, A-M., and Rutzinger, M., 2016. Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information, ''ISPRS International Journal of Geoinformation'', 5 (5), 55.