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Optical and radar Earth observation data for upscaling methane emissions linked to permafrost degradation in sub-Arctic peatlands in northern Sweden (2023)
Journal Article
Sjögersten, S., Ledger, M., Siewert, M., de la Barreda-Bautista, B., Sowter, A., Gee, D., Foody, G., & Boyd, D. S. (2023). Optical and radar Earth observation data for upscaling methane emissions linked to permafrost degradation in sub-Arctic peatlands in northern Sweden. Biogeosciences, 20(20), 4221-4239. https://doi.org/10.5194/bg-20-4221-2023

Permafrost thaw in Arctic regions is increasing methane (CH4) emissions into the atmosphere, but quantification of such emissions is difficult given the large and remote areas impacted. Hence, Earth observation (EO) data are critical for assessing pe... Read More about Optical and radar Earth observation data for upscaling methane emissions linked to permafrost degradation in sub-Arctic peatlands in northern Sweden.

Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient (2023)
Journal Article
Foody, G. M. (2023). Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient. PLoS ONE, 18(10), Article e0291908. https://doi.org/10.1371/journal.pone.0291908

The accuracy of a classification is fundamental to its interpretation, use and ultimately decision making. Unfortunately, the apparent accuracy assessed can differ greatly from the true accuracy. Mis-estimation of classification accuracy metrics and... Read More about Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient.

Spectral Characteristics of Beached Sargassum in Response to Drying and Decay over Time (2023)
Journal Article
Chandler, C. J., Ávila-Mosqueda, S. V., Salas-Acosta, E. R., Magaña-Gallegos, E., Escalante Mancera, E., Gómez Reali, M. A., de la Barreda-Bautista, B., Boyd, D. S., Metcalfe, S. E., Sjogersten, S., van Tussenbroek, B., Silva, R., & Foody, G. M. (2023). Spectral Characteristics of Beached Sargassum in Response to Drying and Decay over Time. Remote Sensing, 15(17), Article 4336. https://doi.org/10.3390/rs15174336

The bloom of pelagic Sargassum in the Atlantic Ocean has become increasingly problematic, especially when the algae have beached. A build-up of decaying beached material has damaging effects on coastal ecosystems and tourism industries. While remote... Read More about Spectral Characteristics of Beached Sargassum in Response to Drying and Decay over Time.

Unmixing-based Spatiotemporal Image Fusion Based on the Self-trained Random Forest Regression and Residual Compensation (2023)
Journal Article
Li, X., Wang, Y., Zhang, Y., Hou, S., Zhou, P., Wang, X., Du, Y., & Foody, G. (2023). Unmixing-based Spatiotemporal Image Fusion Based on the Self-trained Random Forest Regression and Residual Compensation. IEEE Transactions on Geoscience and Remote Sensing, 61, Article 5406319. https://doi.org/10.1109/tgrs.2023.3308902

Spatiotemporal satellite image fusion (STIF) has been widely applied in land surface monitoring to generate high spatial and high temporal reflectance images from satellite sensors. This paper proposed a new unmixing-based spatiotemporal fusion metho... Read More about Unmixing-based Spatiotemporal Image Fusion Based on the Self-trained Random Forest Regression and Residual Compensation.

Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies (2023)
Journal Article
Wang, Y., Foody, G., Li, X., Zhang, Y., Zhou, P., & Du, Y. (2023). Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies. GIScience and Remote Sensing, 60(1), Article 2217573. https://doi.org/10.1080/15481603.2023.2217573

Small water bodies (SWBs), such as ponds and on-farm reservoirs, are a key part of the hydrological system and play important roles in diverse domains from agriculture to conservation. The monitoring of SWBs has been greatly facilitated by medium-spa... Read More about Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies.

Monitoring holopelagic Sargassum spp. along the Mexican Caribbean coast: understanding and addressing user requirements for satellite remote sensing (2023)
Journal Article
de la Barreda-Bautista, B., Metcalfe, S. E., Smith, G., Sjögersten, S., Boyd, D. S., Cerdeira-Estrada, S., López-Ramírez, P., Magaldi, A., Ressl, R., Perera-Valderrama, S., Caballero-Aragon, H., Siordia, O. S., Couldridge, J., Gray, P., Silva, R., Van Tussenbroek, B. I., Escalante‐Mancera, E., & Foody, G. (2023). Monitoring holopelagic Sargassum spp. along the Mexican Caribbean coast: understanding and addressing user requirements for satellite remote sensing. Frontiers in Marine Science, 10, Article 1166000. https://doi.org/10.3389/fmars.2023.1166000

Massive influxes of holopelagic Sargassum spp. (Sargassum natans and S. fluitans) have been causing major economic, environmental and ecological problems along the Caribbean coast of Mexico. Predicting the arrival of the sargassum as an aid to addres... Read More about Monitoring holopelagic Sargassum spp. along the Mexican Caribbean coast: understanding and addressing user requirements for satellite remote sensing.

A quixotic view of spatial bias in modelling the distribution of species and their diversity (2023)
Journal Article
Rocchini, D., Tordoni, E., Marchetto, E., Marcantonio, M., Barbosa, A. M., Bazzichetto, M., Beierkuhnlein, C., Castelnuovo, E., Gatti, R. C., Chiarucci, A., Chieffallo, L., Da Re, D., Di Musciano, M., Foody, G. M., Gabor, L., Garzon-Lopez, C. X., Guisan, A., Hattab, T., Hortal, J., Kunin, W. E., …Malavasi, M. (2023). A quixotic view of spatial bias in modelling the distribution of species and their diversity. npj Biodiversity, 2(1), Article 10. https://doi.org/10.1038/s44185-023-00014-6

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect th... Read More about A quixotic view of spatial bias in modelling the distribution of species and their diversity.

Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns (2023)
Journal Article
Rocchini, D., Nowosad, J., D'Introno, R., Chieffallo, L., Bacaro, G., Gatti, R. C., Foody, G. M., Furrer, R., Gábor, L., Malavasi, M., Marcantonio, M., Marchetto, E., Moudrý, V., Ricotta, C., Šímová, P., Torresani, M., & Thouverai, E. (2023). Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns. Ecological Informatics, 76, Article 102045. https://doi.org/10.1016/j.ecoinf.2023.102045

Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is lin... Read More about Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns.

Deep Feature and Domain Knowledge Fusion Network for Mapping Surface Water Bodies by Fusing Google Earth RGB and Sentinel-2 images (2023)
Journal Article
Zhou, P., Li, X., Foody, G. M., Boyd, D. S., Wang, X., Ling, F., Zhang, Y., Wang, Y., & Du, Y. (2023). Deep Feature and Domain Knowledge Fusion Network for Mapping Surface Water Bodies by Fusing Google Earth RGB and Sentinel-2 images. IEEE Geoscience and Remote Sensing Letters, 1-1. https://doi.org/10.1109/LGRS.2023.3234306

Mapping surface water bodies from fine spatial resolution optical remote sensing imagery is essential for the understanding of the global hydrologic cycle. Although satellite data are useful for mapping, the limited spectral information captured by s... Read More about Deep Feature and Domain Knowledge Fusion Network for Mapping Surface Water Bodies by Fusing Google Earth RGB and Sentinel-2 images.