Outputs (90)

Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record (2021)
Journal Article
Zhang, Y., Ling, F., Wang, X., Foody, G. M., Boyd, D. S., Li, X., …Atkinson, P. M. (2021). Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record. Remote Sensing of Environment, 261, Article 112470. https://doi.org/10.1016/j.rse.2021.112470

Information on forest disturbance is crucial for tropical forest management and global carbon cycle analysis. The long-term collection of data from the Landsat missions provides some of the most valuable information for understanding the processes of... Read More about Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record.

rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back (2021)
Journal Article
Rocchini, D., Thouverai, E., Marcantonio, M., Iannacito, M., Da Re, D., Torresani, M., …Wegmann, M. (2021). rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back. Methods in Ecology and Evolution, 12(6), 1093-1102. https://doi.org/10.1111/2041-210X.13583

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—... Read More about rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back.

Impacts of ignorance on the accuracy of image classification and thematic mapping (2021)
Journal Article
Foody, G. M. (2021). Impacts of ignorance on the accuracy of image classification and thematic mapping. Remote Sensing of Environment, 259, Article 112367. https://doi.org/10.1016/j.rse.2021.112367

Thematic maps are often derived from remotely sensed imagery via a supervised image classification analysis. The training and testing stages of a supervised image classification may proceed ignorant of the presence of some classes in the region to be... Read More about Impacts of ignorance on the accuracy of image classification and thematic mapping.

Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability (2021)
Journal Article
Xing, D., Stehman, S. V., Foody, G. M., & Pengra, B. W. (2021). Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability. Land, 10(1), Article 35. https://doi.org/10.3390/land10010035

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite image... Read More about Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability.

Object-Based Area-to-Point Regression Kriging for Pansharpening (2020)
Journal Article
Zhang, Y., Atkinson, P. M., Ling, F., Foody, G. M., Wang, Q., Ge, Y., …Du, Y. (2021). Object-Based Area-to-Point Regression Kriging for Pansharpening. IEEE Transactions on Geoscience and Remote Sensing, 59(10), 8599-8614. https://doi.org/10.1109/TGRS.2020.3041724

IEEE Optical earth observation satellite sensors often provide a coarse spatial resolution (CR) multispectral (MS) image together with a fine spatial resolution (FR) panchromatic (PAN) image. Pansharpening is a technique applied to such satellite sen... Read More about Object-Based Area-to-Point Regression Kriging for Pansharpening.

Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation (2020)
Journal Article
Feilhauer, H., Zlinszky, A., Kania, A., Foody, G. M., Doktor, D., Lausch, A., & Schmidtlein, S. (2020). Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation. Remote Sensing in Ecology and Conservation, https://doi.org/10.1002/rse2.188

© 2020 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Mapping vegetation as hard classes based on remote sensing data is a frequently applied approach, even thou... Read More about Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation.

Cloud detection in Landsat-8 imagery in Google Earth Engine based on a deep convolutional neural network (2020)
Journal Article
Yin, Z., Ling, F., Foody, G. M., Li, X., & Du, Y. (2020). Cloud detection in Landsat-8 imagery in Google Earth Engine based on a deep convolutional neural network. Remote Sensing Letters, 11(12), 1181-1190. https://doi.org/10.1080/2150704X.2020.1833096

© 2020 Informa UK Limited, trading as Taylor & Francis Group. Google Earth Engine (GEE) provides a convenient platform for applications based on optical satellite imagery of large areas. With such data sets, the detection of cloud is often a necess... Read More about Cloud detection in Landsat-8 imagery in Google Earth Engine based on a deep convolutional neural network.

Remote sensing of fish-processing in the Sundarbans Reserve Forest, Bangladesh: an insight into the modern slavery-environment nexus in the coastal fringe (2020)
Journal Article
Jackson, B., Boyd, D. S., Ives, C. D., Decker Sparks, J. L., Foody, G. M., Marsh, S., & Bales, K. (2020). Remote sensing of fish-processing in the Sundarbans Reserve Forest, Bangladesh: an insight into the modern slavery-environment nexus in the coastal fringe. Maritime Studies, 19(4), 429–444. https://doi.org/10.1007/s40152-020-00199-7

© 2020, The Author(s). Land-based fish-processing activities in coastal fringe areas and their social-ecological impacts have often been overlooked by marine scientists and antislavery groups. Using remote sensing methods, the location and impacts of... Read More about Remote sensing of fish-processing in the Sundarbans Reserve Forest, Bangladesh: an insight into the modern slavery-environment nexus in the coastal fringe.

Superresolution Land Cover Mapping Using a Generative Adversarial Network (2020)
Journal Article
Shang, C., Li, X., Foody, G. M., Du, Y., & Ling, F. (2022). Superresolution Land Cover Mapping Using a Generative Adversarial Network. IEEE Geoscience and Remote Sensing Letters, 19, Article 6000105. https://doi.org/10.1109/LGRS.2020.3020395

Superresolution mapping (SRM) is a commonly used method to cope with the problem of mixed pixels when predicting the spatial distribution within low-resolution pixels. Central to the popular SRM method is the spatial pattern model, which is utilized... Read More about Superresolution Land Cover Mapping Using a Generative Adversarial Network.

Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information (2020)
Journal Article
Ling, F., Li, X., Foody, G. M., Boyd, D., Ge, Y., Li, X., & Du, Y. (2020). Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information. ISPRS Journal of Photogrammetry and Remote Sensing, 168, 141-152. https://doi.org/10.1016/j.isprsjprs.2020.08.008

© 2020 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Information on the temporal variation of surface water area of reservoirs is fundamental for water resource management and is often monitored by satellite remote sensing... Read More about Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information.