Outputs (98)

Optimal endmember-based super-resolution land cover mapping (2019)
Journal Article
Li, X., Li, X., Foody, G., Yang, X., Zhang, Y., Du, Y., & Ling, F. (2019). Optimal endmember-based super-resolution land cover mapping. IEEE Geoscience and Remote Sensing Letters, 16(8), 1279-1283. https://doi.org/10.1109/lgrs.2019.2894805

Super-resolution mapping (SRM) aims to determine the spatial distribution of the land cover classes contained in the area represented by mixed pixels to obtain a more appropriate and accurate map at a finer spatial resolution than the input remotely... Read More about Optimal endmember-based super-resolution land cover mapping.

Reducing the impacts of intra-class spectral variability on the accuracy of soft classification and super-resolution mapping of shoreline (2018)
Journal Article
Doan, H. T., Foody, G. M., & Bui, D. T. (2019). Reducing the impacts of intra-class spectral variability on the accuracy of soft classification and super-resolution mapping of shoreline. International Journal of Remote Sensing, 40(9), 3384-3400. https://doi.org/10.1080/01431161.2018.1545099

The main objective of this research is to assess the impact of intra-class spectral variation on the accuracy of soft classification and super-resolution mapping. The accuracy of both analyses was negatively related to the degree of intra-class spect... Read More about Reducing the impacts of intra-class spectral variability on the accuracy of soft classification and super-resolution mapping of shoreline.

Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring (2018)
Journal Article
Rocchini, D., Luque, S., Pettorelli, N., Bastin, L., Doktor, D., Faedi, N., Feilhauer, H., Feret, J.-B., Foody, G. M., Gavish, Y., Godinho, S., Kunin, W. E., Lausch, A., Leitao, P. J., Marcantonio, M., Neteler, M., Ricotta, C., Schmidtlein, S., Vihervaara, P., Wegmann, M., & Nagendra, H. (2018). Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring. Methods in Ecology and Evolution, 9(8), 1787-1798. https://doi.org/10.1111/2041-210X.12941

Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches... Read More about Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring.

Spatial-temporal fraction map fusion with multi-scale remotely sensed images (2018)
Journal Article
Zhang, Y., Foody, G. M., Ling, F., Li, X., Ge, Y., Du, Y., & Atkinson, P. M. (2018). Spatial-temporal fraction map fusion with multi-scale remotely sensed images. Remote Sensing of Environment, 213, https://doi.org/10.1016/j.rse.2018.05.010

Given the common trade-off between the spatial and temporal resolutions of current satellite sensors, spatial-temporal data fusion methods could be applied to produce fused remotely sensed data with synthetic fine spatial resolution (FR) and high rep... Read More about Spatial-temporal fraction map fusion with multi-scale remotely sensed images.

Using volunteered geographic information (VGI) in design-based statistical inference for area estimation and accuracy assessment of land cover (2018)
Journal Article
Stehman, S. V., Fonte, C. C., Foody, G. M., & 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, https://doi.org/10.1016/j.rse.2018.04.014

Volunteered Geographic Information (VGI) offers a potentially inexpensive source of reference data for estimating area and assessing map accuracy in the context of remote-sensing based land-cover monitoring. The quality of observations from VGI and t... Read More about Using volunteered geographic information (VGI) in design-based statistical inference for area estimation and accuracy assessment of land cover.

Slavery from Space: Demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8 (2018)
Journal Article
Boyd, D. S., Jackson, B., Wardlaw, J., Foody, G. M., Marsh, S., & Bales, K. (2018). Slavery from Space: Demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8. ISPRS Journal of Photogrammetry and Remote Sensing, 142, 380-388. https://doi.org/10.1016/j.isprsjprs.2018.02.012

The most recent Global Slavery Index estimates that there are 40.3 million people enslaved globally. The UN’s Agenda 2030 for Sustainable Development Goal number 8, section 8.7 specifically refers to the issue of forced labour: ending modern slavery... Read More about Slavery from Space: Demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8.

Increasing the accuracy of crowdsourced information on land cover via a voting procedure weighted by information inferred from the contributed data (2018)
Journal Article
Foody, G., See, L., Fritz, S., Moorthy, I., Perger, C., Schill, C., & Boyd, D. (2018). Increasing the accuracy of crowdsourced information on land cover via a voting procedure weighted by information inferred from the contributed data. ISPRS International Journal of Geo-Information, 7(3), https://doi.org/10.3390/ijgi7030080

Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the c... Read More about Increasing the accuracy of crowdsourced information on land cover via a voting procedure weighted by information inferred from the contributed data.

Supervised methods of image segmentation accuracy assessment in land cover mapping (2017)
Journal Article
Costa, H., Foody, G. M., & Boyd, D. S. (2018). Supervised methods of image segmentation accuracy assessment in land cover mapping. Remote Sensing of Environment, 205, https://doi.org/10.1016/j.rse.2017.11.024

Land cover mapping via image classification is sometimes realized through object-based image analysis. Objects are typically constructed by partitioning imagery into spatially contiguous groups of pixels through image segmentation and used as the bas... Read More about Supervised methods of image segmentation accuracy assessment in land cover mapping.

Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study (2017)
Journal Article
Rocchini, D., Bacaro, G., Chirici, G., Da Re, D., Feilhauer, H., Foody, G. M., Galluzzi, M., Garzon-Lopez, C. X., Gillespie, T. W., He, K. S., Lenoir, J., Marcantonio, M., Nagendra, H., Ricotta, C., Rommel, E., Schmidtlein, S., Skidmore, A. K., Van de Kerchove, R., Wegmann, M., & Rugani, B. (in press). Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study. Ecological Indicators, 85, https://doi.org/10.1016/j.ecolind.2017.09.055

Assessing biodiversity from field-based data is difficult for a number of practical reasons: (i) establishing the total number of sampling units to be investigated and the sampling design (e.g. systematic, random, stratified) can be difficult; (ii) t... Read More about Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study.

Monitoring thermal pollution in rivers downstream of dams with Landsat ETM+ thermal infrared images (2017)
Journal Article
Ling, F., Foody, G., Du, H., Ban, X., Li, X., Zhang, Y., & Du, Y. (2017). Monitoring thermal pollution in rivers downstream of dams with Landsat ETM+ thermal infrared images. Remote Sensing, 9(11), Article 1175. https://doi.org/10.3390/rs9111175

Dams play a significant role in altering the spatial pattern of temperature in rivers and contribute to thermal pollution, which greatly affects the river aquatic ecosystems. Understanding the temporal and spatial variation of thermal pollution cause... Read More about Monitoring thermal pollution in rivers downstream of dams with Landsat ETM+ thermal infrared images.