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The Effects of Extreme Heat on Human Health in Tropical Africa (2024)
Journal Article
Kunda, J. J., Gosling, S. N., & Foody, G. M. (in press). The Effects of Extreme Heat on Human Health in Tropical Africa. International Journal of Biometeorology,

This review examines high-quality research evidence that synthesises the effects of extreme heat on human health in tropical Africa. Web of Science (WoS) was used to identify research articles on the effects extreme heat, humidity, Wet-bulb Globe Tem... Read More about The Effects of Extreme Heat on Human Health in Tropical Africa.

Ground Truth in Classification Accuracy Assessment: Myth and Reality (2024)
Journal Article
Foody, G. M. (2024). Ground Truth in Classification Accuracy Assessment: Myth and Reality. Geomatics, 4(1), 81-90. https://doi.org/10.3390/geomatics4010005

The ground reference dataset used in the assessment of classification accuracy is typically assumed implicitly to be perfect (i.e., 100% correct and representing ground truth). Rarely is this assumption valid, and errors in the ground dataset can cau... Read More about Ground Truth in Classification Accuracy Assessment: Myth and Reality.

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., …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., …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., …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., …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., …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., …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., …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.

Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data (2022)
Journal Article
Foody, G. M. (2022). Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data. Remote Sensing, 14(21), Article 5380. https://doi.org/10.3390/rs14215380

Ground reference data are typically required to evaluate the quality of a supervised image classification analysis used to produce a thematic map from remotely sensed data. Acquiring a suitable ground data set for a rigorous assessment of classificat... Read More about Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data.

Double down on remote sensing for biodiversity estimation: a biological mindset (2022)
Journal Article
Rocchini, D., Torresani, M., Beierkuhnlein, C., Feoli, E., Foody, G. M., Lenoir, J., …Ricotta, C. (2022). Double down on remote sensing for biodiversity estimation: a biological mindset. Community Ecology, https://doi.org/10.1007/s42974-022-00113-7

In the light of unprecedented planetary changes in biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential for informing policy and sustainable development. Biodiversity monitoring is a challeng... Read More about Double down on remote sensing for biodiversity estimation: a biological mindset.

The spectral species concept in living color (2022)
Journal Article
Rocchini, D., Santos, M. J., Ustin, S. L., Féret, J. B., Asner, G. P., Beierkuhnlein, C., …Lenoir, J. (2022). The spectral species concept in living color. Journal of Geophysical Research: Biogeosciences, 127(9), Article e2022JG007026. https://doi.org/10.1029/2022JG007026

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at... Read More about The spectral species concept in living color.

Assuring the quality of VGI on land use and land cover: experiences and learnings from the LandSense project (2022)
Journal Article
Foody, G., Long, G., Schultz, M., & Olteanu-Raimond, A. (2022). Assuring the quality of VGI on land use and land cover: experiences and learnings from the LandSense project. Geo-Spatial Information Scienc, https://doi.org/10.1080/10095020.2022.2100285

The potential of citizens as a source of geographical information has been recognized for many years. Such activity has grown recently due to the proliferation of inexpensive location aware devices and an ability to share data over the internet. Rece... Read More about Assuring the quality of VGI on land use and land cover: experiences and learnings from the LandSense project.

Citizen science for Earth Observation (Citzens4EO): understanding current use in the UK (2022)
Journal Article
Boyd, D. S., Foody, G. M., Brown, C., Mazumdar, S., Marshall, H., & Wardlaw, J. (2022). Citizen science for Earth Observation (Citzens4EO): understanding current use in the UK. International Journal of Remote Sensing, 43(8), 2965-2985. https://doi.org/10.1080/01431161.2022.2076574

The role of Earth observation (EO) data in addressing societal problems from environmental through to humanitarian should not be understated. Recent innovation in EO means provision of analysis ready data and data cubes, which allows for rapid use of... Read More about Citizen science for Earth Observation (Citzens4EO): understanding current use in the UK.

Making (remote) sense of lianas (2022)
Journal Article
van der Heijden, G. M., Proctor, A. D., Calders, K., Chandler, C., Field, R., Foody, G. M., …Boyd, D. S. (2022). Making (remote) sense of lianas. Journal of Ecology, 110(3), 498-513. https://doi.org/10.1111/1365-2745.13844

Lianas (woody vines) are abundant and diverse, particularly in tropical ecosystems. Lianas use trees for structural support to reach the forest canopy, often putting leaves above their host tree. Thus they are major parts of many forest canopies. Yet... Read More about Making (remote) sense of lianas.

Monitoring high spatiotemporal water dynamics by fusing MODIS, Landsat, water occurrence data and DEM (2021)
Journal Article
Li, X., Ling, F., Foody, G. M., Boyd, D. S., Jiang, L., Zhang, Y., …Du, Y. (2021). Monitoring high spatiotemporal water dynamics by fusing MODIS, Landsat, water occurrence data and DEM. Remote Sensing of Environment, 265, Article 112680. https://doi.org/10.1016/j.rse.2021.112680

Monitoring the spatiotemporal dynamics of surface water from remote sensing imagery is essential for understanding water's impact on the global ecosystem and climate change. There is often a tradeoff between the spatial and temporal resolutions of im... Read More about Monitoring high spatiotemporal water dynamics by fusing MODIS, Landsat, water occurrence data and DEM.

Detection of spatial and temporal patterns of liana infestation using satellite-derived imagery (2021)
Journal Article
Chandler, C. J., van der Heijden, G. M., Boyd, D. S., & Foody, G. M. (2021). Detection of spatial and temporal patterns of liana infestation using satellite-derived imagery. Remote Sensing, 13(14), 1-15. https://doi.org/10.3390/rs13142774

Lianas (woody vines) play a key role in tropical forest dynamics because of their strong influence on tree growth, mortality and regeneration. Assessing liana infestation over large areas is critical to understand the factors that drive their spatial... Read More about Detection of spatial and temporal patterns of liana infestation using satellite-derived imagery.